Dissertations / Theses: 'Joint species distribution models'

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Valiquette, Samuel. "Sur les données de comptage dans le cadre des valeurs extrêmes et la modélisation multivariée." Electronic Thesis or Diss., Université de Montpellier (2022-....), 2024. http://www.theses.fr/2024UMONS028.

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Cette thèse s’intéresse à certains aspects théoriques de la modélisation des données de comptage. Deux cadres distincts sont abordés : celui des valeurs extrêmes et celui de la modélisation multivariée. Notre première contribution explore, en termes des comportements extrêmes, les liens existants entre le mélange Poisson et sa loi de mélange. Ce travail permet de caractériser et séparer plusieurs familles de lois de mélanges Poisson selon leur comportement en queue. Bien que ce travail soit théorique, nous discutons de son utilité d’un point de vue pratique, notamment pour le choix de la loi de mélange. Notre deuxième contribution porte sur une nouvelle classe de modèles multivariés dénommée Tree Pólya Splitting. Celle-ci repose sur une modélisation hiérarchique et suppose qu’une quantité aléatoire est répartie successivement selon une loi de Pólya à travers une structure d’arbre de partition. Dans ce travail, nous caractérisons les lois marginales univariées et multivariées, les moments factoriels, ainsi que les structures de dépendance (covariance/corrélation) qui en découlent. Nous mettons en évidence, à l’aide d’un jeu de données correspondant à l’abondance de trichoptères, l’intérêt de cette classe de modèles en comparant nos résultats à ceux obtenus, par exemple, avec des modèles de type Poisson log-normale multivariée. Nous concluons cette thèse en présentant diverses perspectives de recherche
This thesis focuses on certain theoretical aspects of counting data modeling. Two distinct frameworks are addressed: extreme values and multivariate modeling. Our first contribution explores, in terms of extreme behaviors, the existing connections between the Poisson mixture and its mixing distribution. This work allows us to characterize and discriminate several families of Poisson mixture according to their tail behavior. Although this work is theoretical, we discuss its practical utility, particularly regarding the choice of the mixing distribution. Our second contribution focuses on a new class of multivariate models called Tree Pólya Splitting. This class is based on hierarchical modeling and assumes that a random quantity is successively divided according to a Pólya distribution through a partition tree structure. In this work, we characterize univariate and multivariate marginal distributions, factorial moments, as well as the resulting dependency structures (covariance/correlation). Using a dataset corresponding to the abundance of Trichoptera, we highlight the interest of this class of models by comparing our results to those obtained, for example, with multivariate Poisson-lognormal models. We conclude this thesis by presenting various perspectives

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Venne, Simon. "Can Species Distribution Models Predict Colonizations and Extinctions?" Thesis, Université d'Ottawa / University of Ottawa, 2018. http://hdl.handle.net/10393/38465.

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Aim MaxEnt, a very popular species distribution modelling technique, has been used extensively to relate species’ geographic distributions to environmental variables and to predict changes in species’ distributions in response to environmental change. Here, we test its predictive ability through time (rather than through space, as is commonly done) by modeling colonizations and extinctions. Location Continental U.S. and southern Canada. Time period 1979-2009 Major taxa studied Twenty-one species of passerine birds. Methods We used MaxEnt to relate species’ geographic distributions to the variation in environmental conditions across North America. We then modelled site-specific colonizations and extinctions between 1979 and 2009 as functions of MaxEnt-estimated previous habitat suitability and inter- annual change in habitat suitability and neighborhood occupancy. We evaluated whether the effects were in the expected direction, we partitioned model’s explained deviance, and we compared colonization and extinction model’s accuracy to MaxEnt’s AUC. Results IV Colonization and extinction probabilities both varied as functions of previous habitat suitability, change in habitat suitability, and neighborhood occupancy, in the expected direction. Change in habitat suitability explained very little deviance compared to other predictors. Neighborhood occupancy accounted for more explained deviance in colonization models than in extinction models. MaxEnt AUC correlates with extinction models’ predictive ability, but not with that of colonization models. Main conclusions MaxEnt appears to sometime capture a real effect of the environment on species’ distributions since a statistical effect of habitat suitability is detected through both time and space. However, change in habitat suitability (which is much smaller through time than through space) is a poor predictor of change in occupancy. Over short time scales, proximity of sites occupied by conspecifics predicts changes in occupancy just as well as MaxEnt. The ability of MaxEnt models to predict spatial variation in occupancy (as measured by AUC) gives little indication of transferability through time. Thus, the predictive value of species distribution models may be overestimated when evaluated through space only. Future prediction of species’ responses to climate change should make a distinction between colonization and extinction, recognizing that the two processes are not equally well predicted by SDMs.

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Mugodo, James, and n/a. "Plant species rarity and data restriction influence the prediction success of species distribution models." University of Canberra. Resource, Environmental & Heritage Sciences, 2002. http://erl.canberra.edu.au./public/adt-AUC20050530.112801.

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There is a growing need for accurate distribution data for both common and rare plant species for conservation planning and ecological research purposes. A database of more than 500 observations for nine tree species with different ecological and geographical distributions and a range of frequencies of occurrence in south-eastern New South Wales (Australia) was used to compare the predictive performance of logistic regression models, generalised additive models (GAMs) and classification tree models (CTMs) using different data restriction regimes and several model-building strategies. Environmental variables (mean annual rainfall, mean summer rainfall, mean winter rainfall, mean annual temperature, mean maximum summer temperature, mean minimum winter temperature, mean daily radiation, mean daily summer radiation, mean daily June radiation, lithology and topography) were used to model the distribution of each of the plant species in the study area. Model predictive performance was measured as the area under the curve of a receiver operating characteristic (ROC) plot. The initial predictive performance of logistic regression models and generalised additive models (GAMs) using unrestricted, temperature restricted, major gradient restricted and climatic domain restricted data gave results that were contrary to current practice in species distribution modelling. Although climatic domain restriction has been used in other studies, it was found to produce models that had the lowest predictive performance. The performance of domain restricted models was significantly (p = 0.007) inferior to the performance of major gradient restricted models when the predictions of the models were confined to the climatic domain of the species. Furthermore, the effect of data restriction on model predictive performance was found to depend on the species as shown by a significant interaction between species and data restriction treatment (p = 0.013). As found in other studies however, the predictive performance of GAM was significantly (p = 0.003) better than that of logistic regression. The superiority of GAM over logistic regression was unaffected by different data restriction regimes and was not significantly different within species. The logistic regression models used in the initial performance comparisons were based on models developed using the forward selection procedure in a rigorous-fitting model-building framework that was designed to produce parsimonious models. The rigorous-fitting modelbuilding framework involved testing for the significant reduction in model deviance (p = 0.05) and significance of the parameter estimates (p = 0.05). The size of the parameter estimates and their standard errors were inspected because large estimates and/or standard errors are an indication of model degradation from overfilling or effecls such as mullicollinearily. For additional variables to be included in a model, they had to contribule significantly (p = 0.025) to the model prediclive performance. An attempt to improve the performance of species distribution models using logistic regression models in a rigorousfitting model-building framework, the backward elimination procedure was employed for model selection, bul it yielded models with reduced performance. A liberal-filling model-building framework that used significant model deviance reduction at p = 0.05 (low significance models) and 0.00001 (high significance models) levels as the major criterion for variable selection was employed for the development of logistic regression models using the forward selection and backward elimination procedures. Liberal filling yielded models that had a significantly greater predictive performance than the rigorous-fitting logistic regression models (p = 0.0006). The predictive performance of the former models was comparable to that of GAM and classification tree models (CTMs). The low significance liberal-filling models had a much larger number of variables than the high significance liberal-fitting models, but with no significant increase in predictive performance. To develop liberal-filling CTMs, the tree shrinking program in S-PLUS was used to produce a number of trees of differenl sizes (subtrees) by optimally reducing the size of a full CTM for a given species. The 10-fold cross-validated model deviance for the subtrees was plotted against the size of the subtree as a means of selecting an appropriate tree size. In contrast to liberal-fitting logistic regression, liberal-fitting CTMs had poor predictive performance. Species geographical range and species prevalence within the study area were used to categorise the tree species into different distributional forms. These were then used, to compare the effect of plant species rarity on the predictive performance of logistic regression models, GAMs and CTMs. The distributional forms included restricted and rare (RR) species (Eucalyptus paliformis and Eucalyptus kybeanensis), restricted and common (RC) species (Eucalyptus delegatensis, Eucryphia moorei and Eucalyptus fraxinoides), widespread and rare (WR) species (Eucalyptus data) and widespread and common (WC) species (Eucalyptus sieberi, Eucalyptus pauciflora and Eucalyptus fastigata). There were significant differences (p = 0.076) in predictive performance among the distributional forms for the logistic regression and GAM. The predictive performance for the WR distributional form was significantly lower than the performance for the other plant species distributional forms. The predictive performance for the RC and RR distributional forms was significantly greater than the performance for the WC distributional form. The trend in model predictive performance among plant species distributional forms was similar for CTMs except that the CTMs had poor predictive performance for the RR distributional form. This study shows the importance of data restriction to model predictive performance with major gradient data restriction being recommended for consistently high performance. Given the appropriate model selection strategy, logistic regression, GAM and CTM have similar predictive performance. Logistic regression requires a high significance liberal-fitting strategy to both maximise its predictive performance and to select a relatively small model that could be useful for framing future ecological hypotheses about the distribution of individual plant species. The results for the modelling of plant species for conservation purposes were encouraging since logistic regression and GAM performed well for the restricted and rare species, which are usually of greater conservation concern.

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Rapacciuolo, Giovanni. "Predicting species' range shifts under global change : when can species distribution models be useful?" Thesis, Imperial College London, 2013. http://hdl.handle.net/10044/1/18025.

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Predicting how species’ distributions will change in response to environmental changes is fundamental for many aspects of agriculture, ecosystem service provision, human and animal health, and wildlife conservation. Correlative species distribution models (SDMs) are the primary tool for making such predictions; however, assessing their predictive accuracy is notoriously difficult, since predicted events are yet to occur. In this thesis, I tested the temporal transferability of widely-used SDMs based on coarse climate and land cover variables by validating these against records of recently-observed distribution changes in British vascular plants, birds, and butterflies. When transferred to a new time period, SDMs were generally accurate at discriminating between presence and absence across large portions of species’ ranges that had remained unchanged through time; however, their discrimination ability over portions of species ranges which had been observed to change occupancy status in time was no better than random. When considering the probabilistic nature of predictions, this lack of discrimination ability over dynamic portions of species’ ranges translated into significant deviations between values of predicted and observed probabilities of species’ gain and loss at given sites. Nonetheless, species’ gains and losses were more likely to be observed at sites with higher predicted probabilities of gain and loss, respectively. In addition, there was considerable variation in the temporal transferability of models with some models being more transferable than others. Differences amongst species were a major determinant of this variation. In particular, models of species found across a distinct and narrow range of environments, which also occurred across most geographical sites satisfying these requirements, were more transferable over time than others. Other factors leading to significant variation in temporal transferability were the choice of modelling framework and the geographical area over which a model was projected. My findings suggest that SDMs are unlikely to generate projections of single species’ range shifts that are accurate enough to provide a solid basis for local-scale conservation and management. However, they may be useful in pinpointing species and areas that are particularly vulnerable to environmental change and should thus be monitored closely. Clearly, more processes will need to be explicitly accounted for in our predictive models if we want to significantly increase their biological realism in the face of environmental change.

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Marshall, Charlotte Emily. "Species distribution modelling to support marine conservation planning." Thesis, University of Plymouth, 2012. http://hdl.handle.net/10026.1/1176.

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This thesis explores some important practical considerations concerning the use of species distribution models in marine conservation planning. Using geo-referenced gorgonian distribution data, together with explanatory environmental variables, predictive models have been used to map the spatial distribution of suitable gorgonian (sea fan) habitat in two study sites; Hatton Bank, in the Northeast Atlantic, and Lyme Bay on the south coast of Devon. Generalized Linear Models (GLMs), Generalized Additive Models (GAMs) and a Maximum Entropy (Maxent) model have been used to support critical investigation into important model considerations that have received inadequate attention in the marine environment. The influence of environmental data resolution on model performance has been explored with specific reference to available datasets in the nearshore and offshore environments. The transferability of deep-sea models has been similarly appraised, with recommendations as to the appropriate use of transferred models. Investigating these practical issues will allow managers to make informed decisions with respect to the best and most appropriate use of existing data. This study has also used novel approaches and investigated their suitability for marine conservation planning, including the use of model classification error in the spatial prioritisation of monitoring sites, and the adaptation of an existing presence-only modelling method to include absence data. Together, these studies contribute both practical recommendations for marine conservation planning and novel applications within the wider species distribution modelling discipline, and consider the implications of these developments for managers, to ensure the ongoing improvement and development of models to support conservation planning.

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ONGARO, SILVIA. "Ecology of Mediterranean lichens and plants: application of species distribution models." Doctoral thesis, Università degli Studi di Trieste, 2019. http://hdl.handle.net/11368/2962383.

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Many studies include Species Distribution Modelling (SDM) techniques to define spatial biogeographic patterns of species and to explore ecological variability. As first, a study on the ecology of infrageneric taxa of genus Solenopsora is presented. The genus includes 25 species of foliose, rupicolous lichens, mostly occurring in temperate and subtropical regions. In Europe, only some taxa range from central Europe (with continental/Atlantic climate) to the Mediterranean, while others are restricted to Mediterranean area. The aim was to explore ecological variability of infrageneric taxa (with diverse distributions), for understanding whether the responses to environmental factors are species-specific. SDMs is used to predict taxa distributions using future climatic scenarios, which take in account climate change effects. It is a fact that climate trends nowadays are anomalous if compared with previous climatic oscillations of the Earth. Climate change already generated distributional range shifts for several species, and increased risk of extinction, or of invasion, disrupting ecosystem dynamics and services. Policy and decision-making can be supported by SDMs, thus improving the effectiveness of global change mitigation strategies. Since conservation efforts can be expensive, and time consuming, SDMs provide a way for optimizing and better addressing resources. The second section host a study on current and future (2070) distribution models of some Sardinian orchids. The Mediterranean is one of the most important biodiversity hot-spots in the world, labelled also as a climate change hot-spot. Plants distribution in the Mediterranean area was strongly influenced by its ecological complexity. In this area, climate changes could heavily impact communities, and the most relevant effect could be an increased occurrence of taxa adapted to dry and hot conditions, leading extinction of endemic taxa. In Europe, Sardinia is one of orchids major biodiversity hotspot (60 taxa). Sardinian ecosystems are changing in consequence of climate change, and while some species are reducing their habitat, others are widening their distribution. Future climate change scenarios for Sardinia depict a situation in which the average monthly temperatures increase, and precipitations increase by 20–50% in the cold season, and decrease of 20–50% in the rest of the year. The third study is on SDMs used for investigating taxonomic questions. The case of Pterygiopsis affinis, a rare crustose cyanolichen, adapted to the Mediterranean climate, is investigated. P. affinis is known to reproduce by apothecia. But, a sorediate morphotype was discovered in S Italy: its identity was never deeply investigated before. SDMs, together with morphological analysis, are used here to understand if this morphotype is an ecological variation of the species, or a new taxonomic entity. Most primitive lichens had a crustose, unorganized thallus, without an actual stratification, with blue algae as photobiont. These primitive lichens, still occurring in many environments, are normally crustose pioneer cyanolichens. They have an extreme phenotypic plasticity, ranging from “typical” to very uncommon forms, such as chimeras. This variability can also affect the reproductive strategies: some lichens can switch to asexual reproductive strategies, if driven by a limited availability of free-living algae. Taxonomy of lichens is traditionally based on anatomy and morphology of the fruiting bodies. Taxa which reproduce by vegetative structures only are normally treated separately from sexually reproducing ones. But, according to the hypothesis of species pairs, the same taxon can adopt different reproductive strategies in different ecological conditions. For all these reasons, the collocation of some taxa of cyanolichens is difficult, and species distribution modelling can be helpful in depicting the niche, and supporting taxonomical delimitation in complex situations.

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Wong, Po-shing, and 黃寶誠. "Some mixture models for the joint distribution of stock's return and trading volume." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1991. http://hub.hku.hk/bib/B31210065.

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Wong, Po-shing. "Some mixture models for the joint distribution of stock's return and trading volume /." [Hong Kong] : University of Hong Kong, 1991. http://sunzi.lib.hku.hk/hkuto/record.jsp?B13009485.

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Scott-Hayward, Lindesay Alexandra Sarah. "Novel methods for species distribution mapping including spatial models in complex regions." Thesis, University of St Andrews, 2013. http://hdl.handle.net/10023/4514.

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Species Distribution Modelling (SDM) plays a key role in a number of biological applications: assessment of temporal trends in distribution, environmental impact assessment and spatial conservation planning. From a statistical perspective, this thesis develops two methods for increasing the accuracy and reliability of maps of density surfaces and provides a solution to the problem of how to collate multiple density maps of the same region, obtained from differing sources. From a biological perspective, these statistical methods are used to analyse two marine mammal datasets to produce accurate maps for use in spatial conservation planning and temporal trend assessment. The first new method, Complex Region Spatial Smoother [CReSS; Scott-Hayward et al., 2013], improves smoothing in areas where the real distance an animal must travel (`as the animal swims') between two points may be greater than the straight line distance between them, a problem that occurs in complex domains with coastline or islands. CReSS uses estimates of the geodesic distance between points, model averaging and local radial smoothing. Simulation is used to compare its performance with other traditional and recently-developed smoothing techniques: Thin Plate Splines (TPS, Harder and Desmarais [1972]), Geodesic Low rank TPS (GLTPS; Wang and Ranalli [2007]) and the Soap lm smoother (SOAP; Wood et al. [2008]). GLTPS cannot be used in areas with islands and SOAP can be very hard to parametrise. CReSS outperforms all of the other methods on a range of simulations, based on their fit to the underlying function as measured by mean squared error, particularly for sparse data sets. Smoothing functions need to be flexible when they are used to model density surfaces that are highly heterogeneous, in order to avoid biases due to under- or over-fitting. This issue was addressed using an adaptation of a Spatially Adaptive Local Smoothing Algorithm (SALSA, Walker et al. [2010]) in combination with the CReSS method (CReSS-SALSA2D). Unlike traditional methods, such as Generalised Additive Modelling, the adaptive knot selection approach used in SALSA2D naturally accommodates local changes in the smoothness of the density surface that is being modelled. At the time of writing, there are no other methods available to deal with this issue in topographically complex regions. Simulation results show that CReSS-SALSA2D performs better than CReSS (based on MSE scores), except at very high noise levels where there is an issue with over-fitting. There is an increasing need for a facility to combine multiple density surface maps of individual species in order to make best use of meta-databases, to maintain existing maps, and to extend their geographical coverage. This thesis develops a framework and methods for combining species distribution maps as new information becomes available. The methods use Bayes Theorem to combine density surfaces, taking account of the levels of precision associated with the different sets of estimates, and kernel smoothing to alleviate artefacts that may be created where pairs of surfaces join. The methods were used as part of an algorithm (the Dynamic Cetacean Abundance Predictor) designed for BAE Systems to aid in risk mitigation for naval exercises. Two case studies show the capabilities of CReSS and CReSS-SALSA2D when applied to real ecological data. In the first case study, CReSS was used in a Generalised Estimating Equation framework to identify a candidate Marine Protected Area for the Southern Resident Killer Whale population to the south of San Juan Island, off the Pacific coast of the United States. In the second case study, changes in the spatial and temporal distribution of harbour porpoise and minke whale in north-western European waters over a period of 17 years (1994-2010) were modelled. CReSS and CReSS-SALSA2D performed well in a large, topographically complex study area. Based on simulation results, maps produced using these methods are more accurate than if a traditional GAM-based method is used. The resulting maps identified particularly high densities of both harbour porpoise and minke whale in an area off the west coast of Scotland in 2010, that might be a candidate for inclusion into the Scottish network of Nature Conservation Marine Protected Areas.

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Galaiduk, Ronen. "Spatial ecology and ontogeny: incorporating fish size-classes into species distribution models." Thesis, Curtin University, 2016. http://hdl.handle.net/20.500.11937/51887.

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I use spatial modelling to investigate how relative abundance and body-length can be used to identify niche requirements and habitat partitioning between conspecific fishes. The models identified specific areas associated with juveniles and adults of same or multiple fish species. I investigate the performance of models using data collected from towed and baited video systems. The towed video models detected fine-scale environmental niche associations of fish, which could be missed by commonly used baited systems.

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Aizpurua, San Roman Olatz. "Species distribution models for birds: How useful are their outcomes for conservation applications?" Doctoral thesis, Universitat de Lleida, 2018. http://hdl.handle.net/10803/667947.

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Els models de distribució d'espècies s'utilitzen cada vegada més per orientar les accions de conservació de la biodiversitat. Aquests models prediuen la probabilitat d'aparició d'espècies en llocs on la seva presència es desconeix i són funció del vincle conegut entre la presència de l’espècie i les condicions ambientals. La probabilitat d'aparició d'espècies sovint es considera com un indicador de la qualitat de l'hàbitat. La interpretació correcta dels resultats d'aquesta tècnica de modelatge és de primordial importància abans d'utilitzar els models en aplicacions de conservació. L'objectiu principal d'aquesta tesi és contribuir a evidenciar la utilitat i aplicabilitat dels models de distribució d'espècies en la conservació i gestió de la biodiversitat. Amb aquesta tesi, es pretén fomentar l'ús de models de distribució d'espècies entre els professionals com a eina acceptada per donar suport a la conservació i gestió de la biodiversitat. Tanmateix, cal tenir precaució a l'hora d'interpretar els resultats dels models, especialment en aquelles zones on una espècie ocupa diversos tipus d'hàbitats i quan sorgeixen noves condicions com a conseqüència dels canvis ambientals ràpids induïts per l'humà.
Los modelos de distribución de especies se utilizan cada vez más para guiar las acciones de conservación de la biodiversidad. Estos modelos predicen la probabilidad de ocurrencia de especies en lugares donde se desconoce, basándose en la relación conocida entre la presencia de la especie y las condiciones ambientales. La probabilidad de ocurrencia de especies a menudo se considera como un indicador de la calidad del hábitat. Interpretar correctamente los resultados de esta técnica de modelización es de suma importancia antes de utilizar los modelos en aplicaciones de conservación. El objetivo principal de esta tesis es contribuir a proporcionar evidencia de la utilidad y aplicabilidad de los modelos de distribución de especies en la conservación y gestión de la biodiversidad. Los resultados de esta tesis ayudan a fomentar el uso de modelos de distribución de especies entre los profesionales como una herramienta aceptada para apoyar la conservación y gestión de la biodiversidad. Sin embargo, se debe tener precaución al interpretar los resultados del modelo, especialmente en las áreas donde una especie ocupa varios tipos de hábitat y cuando surgen condiciones nuevas como resultado de cambios ambientales rápidos inducidos por el humano.
Species distribution models are increasingly used to guide biodiversity conservation actions. These models predict the probability of species occurrence in locations where the species presence is unknown based on the link between species presence and environmental conditions. Probability of species occurrence is often considered as indicator of habitat quality. Correctly interpreting the outcomes of this modelling technique is of paramount importance before using the models in conservation applications. The main objective of this thesis is to contribute to providing evidence of the usefulness and applicability of species distribution models for some conservation and management applications. With this thesis, we encourage the use of species distribution models among practitioners as an accepted tool to support biodiversity conservation and management. However, caution is needed when interpreting model outcomes, especially in the areas where a species occupies several habitat types and when novel conditions are emerging as a result of human-induced rapid environmental changes.

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Vaughan, Ian P. "Development of species distribution models and their application to birds in river habitats." Thesis, Cardiff University, 2004. http://orca.cf.ac.uk/55925/.

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1. Distribution models are used as management tools to predict species' distributions and quantify their habitat preferences. Numerous methodological issues require further development, which are explored using the distribution of birds along rivers as a model system in which there is a need to i) develop the quantification and analysis of variation in river habitat features and ii) better quantify species' habitat preferences for conservation and prediction. These themes were linked using a combination of the British Trust for Ornithology's Waterways Breeding Bird Survey (WBBS) and the Environment Agency's River Habitat Survey (RHS), along with similar data from upland Wales and the Himalayan mountains. 2. Training data are the starting point for distribution models and their properties can have profound effects. These issues were investigated via a literature review, which identified key factors including the type of predictors chosen, the approach to environmental sampling and spatial autocorrelation in distribution patterns. Recommendations are made that should optimise model quality, whilst making the most efficient use of available resources. 3. Testing the performance of distribution models is vital. Using a review of the available literature, highlighting weaknesses in current practice, and a case study using a Himalayan river bird, recommendations are made for improved practice. Bootstrapping and independent data should be used to assess overfitting and transportability, respectively. Accuracy statistics should facilitate inter-model comparisons, examining both discrimination and calibration. Nominal presence/absence predictions are problematic: information-theoretic methods may be the most useful approach. 4. Complex habitat data, such as RHS, may create a range of problems during statistical analyses unless the sample size is large. Data reduction, using methods such as principal components analysis (PCA), is an effective solution, but the resulting axes may be difficult to interpret. Using models built with Welsh river bird-RHS data, I compared the interpretability and predictive efficacy of PCA used in its conventional form against PCA preceded by the clustering of RHS variables that referred to the same ecological factors. The two approaches produced similar predictive performance but habitat indices produced by the latter were easier to interpret. A variant of PCA devised for qualitative data was also examined, and benefited RHS analyses involving ordinal variables. 5. Predictive models for 28 river birds, built with the WBBS, represent the first quantitative study linking detailed river habitat data with river bird distributions across the UK. Accuracy varied widely, with better performance for species associated with the river channel, rather than floodplain habitats, reflecting the relative coverage of these river features in RHS. By using variable clustering, the likelihood of species occurrences could be easily related to the observed habitat. 6. By utilising important methodological developments, this project provides important evidence that RHS forms an effective basis for relating many river birds to their habitats, and that when used in conjunction with the WBBS, could bring valuable benefits to river bird conservation. More generally, the work illustrates how RHS can describe variations in river structure and anthropogenic modification in a manner that is relevant to riverine organisms, along with transferable methods for describing and modelling the resulting relationships.

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Sokolovska, Iva. "Are Experimentally Derived Estimates of Thermal Tolerance Useful in Interpreting Species Distribution Models." DigitalCommons@USU, 2014. https://digitalcommons.usu.edu/etd/3695.

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Species distribution models are frequently used in ecology to predict the spatial and temporal occurrence of organisms. Direct interpretation of these models assumes that the relationships between the organisms and their environment are manifestations of causal mechanisms. However, in general, the mechanisms producing these associations have not been experimentally validated, which questions our confidence in their interpretation and application. Temperature is one of the most important factors influencing the fitness and distribution of aquatic organisms, and studying the thermal physiology of aquatic invertebrates could provide a useful approach for validating predictions of the species distribution models. Experimental thermal tolerance studies, which assess the physiological limits to temperature, should be useful in interpreting the causal basis for species distribution model predictions. Critical Thermal Maxima experiments are frequently used to measure the thermal tolerance of ectothermic organisms. They represent the temperature at which organisms exhibit disorganized locomotor activity to the point that they lose their ability to escape conditions that will promptly lead to death. Critical Thermal Maxima experiments could, therefore, provide a useful test of the inferred mechanisms of species distribution models. The objective of my study was to determine if Critical Thermal Maxima experiments are associated with the thermal limits inferred from species distribution models. If the models accurately describe causal relationships between predicted distributions of organisms and environmental temperatures, and if the thermal maxima are associated with the limits to organism fitness, I expected to see a strong correspondence between model-derived and experimentally-derived thermal limits. A strong correspondence between model predictions and experimentally obtained thermal maxima would both validate a physiological interpretation of the species distribution models and justify the use of Critical Thermal Maxima experiments alone in predicting species distributions and responses to climate change.

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Robertson, Mark Peter. "Predictive modelling of species' potential geographical distributions." Thesis, Rhodes University, 2003. http://hdl.handle.net/10962/d1007189.

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Models that are used for predicting species' potential distributions are important tools that have found applications in a number of areas of applied ecology. The majority of these models can be classified as correlative, as they rely on strong, often indirect, links between species distribution records and environmental predictor variables to make predictions. Correlative models are an alternative to more complex mechanistic models that attempt to simulate the mechanisms considered to underlie the observed correlations with environmental attributes. This study explores the influence of the type and quality of the data used to calibrate correlative models. In terms of data type, the most popular techniques in use are group discrimination techniques, those that use both presence and absence locality data to make predictions. However, for many organisms absence data are either not available or are considered to be unreliable. As the available range of profile techniques (those using presence only data) appeared to be limited, new profile techniques were investigated and evaluated. A new profile modelling technique based on fuzzy classification (the Fuzzy Envelope Model) was developed and implemented. A second profile technique based on Principal Components Analysis was implemented and evaluated. Based on quantitative model evaluation tests, both of these techniques performed well and show considerable promise. In terms of data quality, the effects on model performance of false absence records, the number of locality records (sample size) and the proportion of localities representing species presence (prevalence) in samples were investigated for logistic regression distribution models. Sample size and prevalence both had a significant effect on model performance. False absence records had a significant influence on model performance, which was affected by sample size. A quantitative comparison of the performance of selected profile models and group discrimination modelling techniques suggests that different techniques may be more successful for predicting distributions for particular species or types of organism than others. The results also suggest that several different model design! sample size combinations are capable of making predictions that will on average not differ significantly in performance for a particular species. A further quantitative comparison among modelling techniques suggests that correlative techniques can perform as well as simple mechanistic techniques for predicting potential distributions.

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Villero, Pi Daniel. "Applying species distribution models in conservation biology = Aplicacions dels models de distribució d'espècies en biologia de la conservació." Doctoral thesis, Universitat de Barcelona, 2016. http://hdl.handle.net/10803/398994.

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This work is at the crossroads where conservation problems, arising from the biodiversity loss and environmental crisis, meet the difficulties of applying research outcomes in conservation practice, framed in a sustained decline of resources for biodiversity conservation due to an entrenched economic and social crisis. The overall aim of the thesis is to deepen the use of species distribution models (SDM) to improve decision-making processes in biodiversity conservation. With the ambition to build bridges between research and conservation practice, the thesis proposes to go closer to real contexts of decision making and contribute to boost effective species conservation strategies. Concerning methodological issues, the thesis emphasizes the importance of information sources of species distribution, since it is a key aspect of the quality of SDM results and also one of the most controversial sections of conservation budgets. To meet these objectives, the thesis include six chapters organised in three thematic blocks. The first block include various examples of SDM application in different conservation backgrounds (Chapters I, II, III, IV and V). Complementarily, the second block explore how to boost SDM outcomes to inform conservation practice (Chapter IV and V). Finally, the third block examines uncertainties of different information sources of species distribution to develop SDM (Chapter VI). The thesis highlight SDM as key tools to improve decision-making in different conservation backgrounds, playing critical roles in almost all steps of the decision-making processes, especially in dealing with decision uncertainties. It also emphasize that an effective implementation of SDM to solve conservation problems has to match SDM goals to specific questions arising from the decision-making process, and also to promote utilisation of SDM outcomes through active communication and clear, valuable and useful spatial products. These two conditions are also sufficient for an effective knowledge-transfer from other scientific developments to inform and improve conservation practice.
Aquest treball se situa en la cruïlla on conflueixen els problemes de conservació, derivats de la pèrdua de biodiversitat i la crisi ambiental, amb els problemes d’implementació de solucions efectives, relacionats amb les dificultats d’aplicar els resultats de la recerca en la pràctica de la conservació, tot plegat emmarcat dins un context més general de crisi econòmica i social que es tradueix en una reducció progressiva dels recursos destinats a la conservació de la biodiversitat. L’objectiu general de la tesi es aprofundir en la utilització de SDM (models de distribució d’espècies) per millorar els processos de decisió en conservació de la biodiversitat. Amb l’ambició de bastir ponts entre la recerca ecològica i la conservació sobre el terreny, la tesi es planteja anar una mica més enllà dels exercicis teòrics i apropar-se a contextos reals de presa de decisions per fer contribucions més efectives a la conservació de les espècies. Pel que fa als aspectes metodològics, la tesi posa l’accent en la importància de les fonts d’informació sobre distribució d’espècies, atès que es un aspecte clau de la qualitat dels resultats dels SDM i alhora un dels apartats més controvertits en els pressupostos públics destinats a la conservació. Per donar resposta a aquests objectius, la tesi consta de sis capítols estructurats en tres blocs temàtics. En el primer bloc es desenvolupen exemples d’aplicació de SDM en diferents contextos de conservació (Capítols I, II, III, IV i V). De forma complementària, el segon bloc explora com potenciar els resultats derivats dels SDM per informar la pràctica real de la conservació (Capítol IV i V). Finalment, el tercer bloc examina la incertesa de diferents fonts de dades biològiques per desenvolupar SDM, tenint en comte diferents àmbits d’aplicació (Capítol VI). Al llarg dels diferents capítols s’ha posat de manifest que els SDM son eines clau en la millora de les decisions de problemes de conservació diversos, i amb implicacions en quasi totes les etapes dels processos de decisió, i especialment en la quantificació de la incertesa relacionada amb cadascuna de les etapes. També s’ha posat de relleu que l’aplicació efectiva de SDM en processos de decisió passa per ajustar els objectius dels SDM a les preguntes plantejades en el context particular del problema de conservació, i també per promoure la utilització dels resultats obtinguts amb SDM a traves d’una comunicació activa i de productes espacials clars, útils, accessibles i ben ajustats al problema de conservació. Aquestes dues condicions son igualment vàlides per la transferència efectiva d’altres desenvolupaments científics per la millora de la pràctica de la conservació de la biodivesitat.

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Maggini, Ramona. "Species distribution models for conservation-oriented studies in Switzerland: filling data and tool gaps." Thesis, University of Lausanne, Switzerland, 2011. https://serval.unil.ch/notice/serval:BIB_16EF29C539B2.

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Species distribution models (SDMs) represent nowadays an essential tool in the research fields of ecology and conservation biology. By combining observations of species occurrence or abundance with information on the environmental characteristic of the observation sites, they can provide information on the ecology of species, predict their distributions across the landscape or extrapolate them to other spatial or time frames. The advent of SDMs, supported by geographic information systems (GIS), new developments in statistical models and constantly increasing computational capacities, has revolutionized the way ecologists can comprehend species distributions in their environment. SDMs have brought the tool that allows describing species realized niches across a multivariate environmental space and predict their spatial distribution. Predictions, in the form of probabilistic maps showing the potential distribution of the species, are an irreplaceable mean to inform every single unit of a territory about its biodiversity potential. SDMs and the corresponding spatial predictions can be used to plan conservation actions for particular species, to design field surveys, to assess the risks related to the spread of invasive species, to select reserve locations and design reserve networks, and ultimately, to forecast distributional changes according to scenarios of climate and/or land use change. By assessing the effect of several factors on model performance and on the accuracy of spatial predictions, this thesis aims at improving techniques and data available for distribution modelling and at providing the best possible information to conservation managers to support their decisions and action plans for the conservation of biodiversity in Switzerland and beyond. Several monitoring programs have been put in place from the national to the global scale, and different sources of data now exist and start to be available to researchers who want to model species distribution. However, because of the lack of means, data are often not gathered at an appropriate resolution, are sampled only over limited areas, are not spatially explicit or do not provide a sound biological information. A typical example of this is data on ‘habitat’ (sensu biota). Even though this is essential information for an effective conservation planning, it often has to be approximated from land use, the closest available information. Moreover, data are often not sampled according to an established sampling design, which can lead to biased samples and consequently to spurious modelling results. Understanding the sources of variability linked to the different phases of the modelling process and their importance is crucial in order to evaluate the final distribution maps that are to be used for conservation purposes. The research presented in this thesis was essentially conducted within the framework of the Landspot Project, a project supported by the Swiss National Science Foundation. The main goal of the project was to assess the possible contribution of pre-modelled ‘habitat’ units to model the distribution of animal species, in particular butterfly species, across Switzerland. While pursuing this goal, different aspects of data quality, sampling design and modelling process were addressed and improved, and implications for conservation discussed. The main ‘habitat’ units considered in this thesis are grassland and forest communities of natural and anthropogenic origin as defined in the typology of habitats for Switzerland. These communities are mainly defined at the phytosociological level of the alliance. For the time being, no comprehensive map of such communities is available at the national scale and at fine resolution. As a first step, it was therefore necessary to create distribution models and maps for these communities across Switzerland and thus to gather and collect the necessary data. In order to reach this first objective, several new developments were necessary such as the definition of expert models, the classification of the Swiss t rritory in environmental domains, the design of an environmentally stratified sampling of the target vegetation units across Switzerland, the development of a database integrating a decision-support system assisting in the classification of the relevés, and the downscaling of the land use/cover data from 100 m to 25 m resolution. The main contributions of this thesis to the discipline of species distribution modelling (SDM) are assembled in four main scientific papers. In the first, published in Journal of Biogeography different issues related to the modelling process itself are investigated. First is assessed the effect of five different stepwise selection methods on model performance, stability and parsimony, using data of the forest inventory of State of Vaud. In the same paper are also assessed: the effect of weighting absences to ensure a prevalence of 0.5 prior to model calibration; the effect of limiting absences beyond the environmental envelope defined by presences; four different methods for incorporating spatial autocorrelation; and finally, the effect of integrating predictor interactions. Results allowed to specifically enhance the GRASP tool (Generalized Regression Analysis and Spatial Predictions) that now incorporates new selection methods and the possibility of dealing with interactions among predictors as well as spatial autocorrelation. The contribution of different sources of remotely sensed information to species distribution models was also assessed. The second paper (to be submitted) explores the combined effects of sample size and data post-stratification on the accuracy of models using data on grassland distribution across Switzerland collected within the framework of the Landspot project and supplemented with other important vegetation databases. For the stratification of the data, different spatial frameworks were compared. In particular, environmental stratification by Swiss Environmental Domains was compared to geographical stratification either by biogeographic regions or political states (cantons). The third paper (to be submitted) assesses the contribution of premodelled vegetation communities to the modelling of fauna. It is a two-steps approach that combines the disciplines of community ecology and spatial ecology and integrates their corresponding concepts of habitat. First are modelled vegetation communities per se and then these ‘habitat’ units are used in order to model animal species habitat. A case study is presented with grassland communities and butterfly species. Different ways of integrating vegetation information in the models of butterfly distribution were also evaluated. Finally, a glimpse to climate change is given in the fourth paper, recently published in Ecological Modelling. This paper proposes a conceptual framework for analysing range shifts, namely a catalogue of the possible patterns of change in the distribution of a species along elevational or other environmental gradients and an improved quantitative methodology to identify and objectively describe these patterns. The methodology was developed using data from the Swiss national common breeding bird survey and the article presents results concerning the observed shifts in the elevational distribution of breeding birds in Switzerland. The overall objective of this thesis is to improve species distribution models as potential inputs for different conservation tools (e.g. red lists, ecological networks, risk assessment of the spread of invasive species, vulnerability assessment in the context of climate change). While no conservation issues or tools are directly tested in this thesis, the importance of the proposed improvements made in species distribution modelling is discussed in the context of the selection of reserve networks.

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Crego, Ramiro Daniel. "Modeling the distribution of meadows in arid and semi-arid Patagonia, Argentina: assessing current distribution and predicting response to climate change." OpenSIUC, 2012. https://opensiuc.lib.siu.edu/theses/1001.

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Meadows are critical in arid and semi-arid Argentinean Patagonia because of their importance for regional biodiversity. Despite this, little information on the spatial distribution of meadows is available and no analysis of the potential effect of climate change on meadows has been performed, which hampers conservation planning. In this study, I modeled the spatial distribution of meadows and investigated how climate change may affect the current distribution of meadows in arid and semiarid Patagonia by 2050. In addition, I investigated conservation status and areas of desertification vulnerability of those areas predicted to contain meadows. I used high-resolution imagery available in Google Earth software to visually estimate presence and absence of meadows. To model current and future distribution of meadows I used these observations and different socio-environmental predictor variables. I implemented generalized linear, additive, boosting, and random forest models, as the basis for a mean ensemble technique. I predicted future distribution of meadows using four different general circulation models and the A2 SERES scenario. The final ensemble model was an accurate representation of the current distribution of meadows in Patagonia and indicates they are severely under-represented within protected areas. I determined that overall meadow abundance is going to decrease by 2050 given the changes in climate. However, there were two contrasting trends: severe reduction of meadows in northwest Patagonia and Tierra del Fuego Island, and an expansion of suitable areas for meadows in the south and a small section in the northwest. This first regional map of meadow distribution across Argentinean Patagonia and information on meadows vulnerability to climate change represent key information for planning actions to conserve this critical habitat.

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Beton, Damla. "Effects Of Climate Change On Biodiversity: A Case Study On Four Plant Species Using Distribution Models." Phd thesis, METU, 2011. http://etd.lib.metu.edu.tr/upload/12613538/index.pdf.

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Conservation strategies are mainly focused on species existing in an environment shaped by natural and anthropogenic pressures. Yet, evidence shows that climate is changing faster than ever and expected to continue to change in the near future, which can be devastating for plants with restricted ranges. Turkey harbors many endemic species that might be affected from these changes. However, available data is scarce and biased, complicating the anticipation of future changes. Aim of this study is to improve our understanding of endemic species distributions and forecasting effects of climate change via species distribution modelling (SDM). The study is based on two Anatolian (Crocus ancyrensis and Crataegus tanacetifolia) and two Ankara (Salvia aytachii and Centaurea tchihatcheffii) endemics. Independent presence and absence data (ranging between 19-68 and 38-61, respectively) for each species was collected through fieldwork in and around the Upper Sakarya Basin in 2008 and 2009. With the software Maxent, SDMs were performed by using 8 least correlated environmental features and random presence records (of which 25% were used for confusion matrix). SDMs for current distributions of C. ancyrensis, C. tchihatcheffii and C. tanacetifolia were reliable enough for future extrapolations despite errors originating from scale, non-equilibrium status and biotic interactions, respectively. The model for S. aytachii failed due to absence of limiting factor (soil type) in the model. Future projections of those three species modelled using CCCMA-CGCM2 and HADCM3 climate models indicated three possible responses to climate change: (1) Extinction, especially for habitat specialists
(2) Range expansion, especially for generalist species
and (3) Range contradiction, especially for Euro-Siberian mountainous species. Species modelling can be used to understand possible responses of plant species to climate change in Turkey. Modelling techniques should to be improved, however, especially by integrating other parameters such as biotic interactions and through a better understanding of uncertainties.

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Leitão, Pedro Jorge Paixão. "Improving species distribution models to describe steppe bird occurrence patterns and habitat selection in Southern Portugal." Thesis, University of Southampton, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.505778.

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The birds of the steppe environments face a number of different threats relating to habitat degradation (such as agricultural intensification, land abandonment afforestation), and the vast majority of species have unfavourable conservation status. Conservation measures require an understanding of species habitat preferences and their occurrence patterns and must be applied at the relevant spatial scales. This study, investigated the habitat selection and resulting distributions of the steppe bird community in southern Portugal, one its strongholds.

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Huang, Jian. "Assessing predictive performance and transferability of species distribution models for freshwater fish in the United States." Diss., Virginia Tech, 2015. http://hdl.handle.net/10919/73477.

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Rigorous modeling of the spatial species distributions is critical in biogeography, conservation, resource management, and assessment of climate change. The goal of chapter 2 of this dissertation was to evaluate the potential of using historical samples to develop high-resolution species distribution models (SDMs) of stream fishes of the United States. I explored the spatial transferability and temporal transferability of stream–fish distribution models in chapter 3 and chapter 4 respectively. Chapter 2 showed that the discrimination power of SDMs for 76 non-game fish species depended on data quality, species' rarity, statistical modeling technique, and incorporation of spatial autocorrelation. The area under the Receiver-Operating-Characteristic curve (AUC) in the cross validation tended to be higher in the logistic regression and boosted regression trees (BRT) than the presence-only MaxEnt models. AUC in the cross validation was also higher for species with large geographic ranges and small local populations. Species prevalence affected discrimination power in the model training but not in the validation. In chapter 3, spatial transferability of SDMs was low for over 70% of the 21 species examined. Only 24% of logistic regression, 12% of BRT, and 16% of MaxEnt had AUC > 0.6 in the spatial transfers. Friedman's rank sum test showed that there was no significant difference in the performance of the three modeling techniques. Spatial transferability could be improved by using spatial logistic regression under Lasso regularization in the training of SDMs and by matching the range and location of predictor variables between training and transfer regions. In chapter 4, testing of temporal SDM transfer on independent samples resulted in discrimination power of the moderate to good range, with AUC > 0.6 for 80% of species in all three types of models. Most cool water species had good temporal transferability. However, biases and misspecified spread occurred frequently in the temporal model transfers. To reduce under- or over-estimation bias, I suggest rescaling the predicted probability of species presence to ordinal ranks. To mitigate inappropriate spread of predictions in the climate change scenarios, I recommended to use large training datasets with good coverage of environmental gradients, and fine-tune predictor variables with regularization and cross validation.
Ph. D.

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Emery, Nathan. "Enhanced species distribution models: a case study using essential population data from Actinotus helianthi (flannel flower)." Thesis, The University of Sydney, 2014. http://hdl.handle.net/2123/13322.

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Species distribution models (SDMs) quantify the spatial configuration or change of suitable habitat for species. This makes SDMs indispensable for conservation planning and climate adaptation management. It is timely, therefore, to examine the underlying model assumptions more carefully. These models typically use known localities of individuals of the species as an indication of what environmental conditions the species will persist under. Each confirmed record is treated equally as an indication of suitability, thus assuming that all populations are equal. However, populations vary considerably in the number of individuals, ranging from a few individuals to many thousands with implications for how they might persist. The number of individuals may also indicate another dimension to how suitable the environment is to the growth, survival and reproductive success of that species. A second assumption is that within each population all individuals are equivalent in their requirements from the environment. My thesis focused on testing these assumptions by performing field and laboratory experiments, which incorporated population level data, collected from Actinotus helianthi plants, to determine whether populations are equivalent in their response to current or future environments. Specifically, I report on the variation in plant trait values associated with the reproductive niche of the species. I then incorporated some of the limiting soil environment factors identified in my experiments to produce a new and more accurate SDM prediction than an SDM built on climate alone. The choice of predictors in SDMs is crucial to their success, as the model assumes that all relevant factors are included. My thesis is an important foundation for experimentally testing the assumptions inherent in most SDMs, while at the same time, illustrating how these factors can be added to, or combined with, the initial model.

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Foster, Sharla. "Quantifying the Expansion of an Invasive Plant Species, Dog-strangling Vine (Vincetoxicum rossicum), in Environmental and Geographic Space Over the Past 130 Years." Thesis, Université d'Ottawa / University of Ottawa, 2021. http://hdl.handle.net/10393/42478.

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Invasive plant species are an increasing global threat to native biodiversity. Effective management depends on accurate predictions of their spread. However, modelling the geographic distribution of invasive species, particularly with methods like correlative species distribution models (SDMs), is challenging. SDMs operate under the assumption that species are in equilibrium with their environment (i.e., they occur in all suitable environments); this assumption is more likely to be violated for a species that is still in the process of colonizing suitable environments. SDMs also assume that environmental constraints are the most important factors determining a species' distribution. However, these assumptions are not commonly assessed, and when violated can have consequences for model reliability. I investigated SDM performance and equilibrium in the invasive Vincetoxicum rossicum vine in northeastern North America. Vincetoxicum rossicum has a long, detailed history of occurrence records in its invaded range, which enabled me to observe trends in equilibrium and model performance over a relatively long time scale. I tested the hypotheses that: 1) invasive species approach equilibrium in environmental and geographic space over time; 2) SDM performance will increase as V. rossicum approaches environmental equilibrium; and 3) range expansion in the early stages of an invasion is primarily a function of dispersal rather than environmental constraints, while the reverse is true in later stages. I found that V. rossicum has reached equilibrium in environmental space, but is still expanding its geographic range. SDM performance was poor in the first 30 years following introduction, but then improved as V. rossicum approached environmental equilibrium. SDMs were outperformed by spatial dispersal models in the earliest time period, however, the reverse was true for all subsequent time periods. Overall, these results suggest that V. rossicum’s distribution is becoming more stable and more predictable over time and that models built using the most recent data for this species, will be the most transferable across time and space. Additionally, my findings highlight the need for researchers modelling invasive species’ distributions to consider the inherent assumptions, biases, and unique features related to SDMs and SDMs of invasive species.

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Motloung, Rethabile Frangenie. "Understanding current and potential distribution of Australian acacia species in southern Africa." Diss., University of Pretoria, 2014. http://hdl.handle.net/2263/79720.

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This dissertation presents research on the value of using different sources of data to explore the factors determining invasiveness of introduced species. The research draws upon the availability of data on the historical trial plantings of alien species and other sources. The focus of the study is on Australian Acacia species as a taxon introduced into southern Africa (Lesotho, South Africa and Swaziland). The first component of the study focused on understanding the factors determining introduction outcome of species in historical trial plantings and invasion success of Australian Acacia species using Species Distribution Models (SDMs) and classification tree techniques. SDMs were calibrated using the native range occurrence records (Australia) and were validated using results of 150 years of South African government forestry trial planting records and invaded range data from the Southern African Plant Invaders Atlas. To understand factors associated with survival (‘trial success’) or failure to survive (‘trial failure’) of species in historical trial plantings, classification and regression tree analysis was used. The results indicate climate as one of the factors that explains introduction and/or invasion success of Australian Acacia species in southern Africa. However, the results also indicate that for ‘trial failures’ there are factors other than climate that could have influenced the trial outcome. This study emphasizes the need to integrate data on whether the species has been recorded to be invasive elsewhere with climate matching for invasion risk assessment. The second component of the study focused on understanding the distribution patterns of Australian Acacia species that are not known as invasive in southern Africa. The specific aims were to determine which species still exist at previously recorded sites and determine the current invasion status. This was done by collating data from different sources that list species introduced into southern Africa and then conducting revisits. For the purpose of this study, revisits means conducting field surveys based on recorded occurrences of introduced species. The known occurrence data for species on the list were obtained from different data sources and various invasion biology experts. As it was not practical to do revisits for all species on the list, three ornamental species (Acacia floribunda, A. pendula and A. retinodes) were selected as part of the pilot study for the conducted revisits in this study. Acacia retinodes trees were not found during the revisits. The results provided data that could be used to characterize species based on the Blackburn et al., (2011) scheme. However, it is not clear whether observed Acacia pendula or A. floribunda trees will spread away from the sites hence the need to continuously monitor sites for spread. The methods used in this research establish a protocol for future work on conducting revisits at known localities of introduced species to determine their population dynamics and thereby characterize the species according to the scheme for management purposes.
Dissertation (MSc)--University of Pretoria, 2014.
National Research Foundation (NRF)
Zoology and Entomology
MSc (Zoology)
Unrestricted

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Sampson, Mark Robert. "Modelling the distribution and abundance of several demersal fish species on the Agulhas Bank, South Africa." Thesis, Rhodes University, 2002. http://hdl.handle.net/10962/d1006207.

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The Agulhas Bank supports a speciose fish community, many of which are commercially important. Despite substantial research being conducted on aspects of their biology spatial aspects of their distribution and abundance in relation to environment parameters has been ignored. This study, therefore, addressed aspects related to the distribution and abundance of representative species on the Agulhas Bank within a Geographic Information System (GIS). Four candidate species were chosen due to their importance either in numbers or unit mass to the South African demersal trawl fishery. The species also shared morphological and taxonomic similarities. The candidate species chosen were the two Cape hake species, shallow-water hake Meluccius capensis, and deep-water hake Merluccius paradoxus, and the two pleuronectiform species being Agulhas sole Austroglossus pectoralis and redspotted tonguesole Cynoglossus zanzibarensis. The use of a GIS was appropriate and allowed for hidden spatial patterns be exposed and illustrated visually, while also facilitating the quantification of the relationships between distribution/abundance and certain environmental predictors using statistical methods The Department of Marine and Coastal Management, Cape Town, supplied biological data in the form of length frequency and biomass information from spring (AprillMay) and autumn (September/October) cruises conducted between 1986 and 1993 on the R. V. Africana. The Council for National Geoscience, Cape Town, supplied sediment data for the entire southern African coastline. Initial exploratory data analysis highlighted potential relationships between environmental variables and abundance for each specie's life-history stanzas. Variations in spatial distribution were found to be significantly different between each life-history stanzas within species. Fish density as a function of the additive effects of the various environmental parameters, including temperature, depth and sediment type, was assessed using a Poisson Generalized Additive Model (GAM), while distribution was analysed with a logistic GAM. A predictive logistic model was then created, taking into consideration the importance of the predictor variables for each species, allowing for predictive estimates to be made for each species by inputting environmental information within the study area. The importance of certain environmental variables influencing distribution and abundance were noted. General patterns indicated that sediment was the most important to both the distribution and abundance of the two pleuronectiform species and juvenile life-history stanzas, while the adult gadoids' distribution and abundance appeared to be depth dependent.

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Li, Yuming. "Univariate and multivariate measures of risk aversion and risk premiums with joint normal distribution and applications in portfolio selection models." Thesis, University of British Columbia, 1987. http://hdl.handle.net/2429/26110.

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This thesis gives the formal derivations of the so-called Rubinstein's measures of risk aversion and their multivariate generalizations. The applications of these measures in portfolio selection models are also presented. Assuming that a decision maker's preferences can be represented by a unidimensional von Neumann and Morgenstern utility function, we consider a model with an uninsurable initial random wealth and an insurable risk. Under the assumption that the two random variables have a bivariate normal distribution, the second-order co-variance operator is developed from Stein/Rubinstein first-order covariance operator and is used to derive Rubinstein's measures of risk aversion from the approximations of risk premiums. Rubinstein's measures of risk aversion are proved to be the appropriate generalizations of the Arrow-Pratt measures of risk aversion. In a portfolio selection model with two risky investments having a bivariate normal distribution, we show that Rubinstein's measures of risk aversion can yield the desirable characterizations of risk aversion and wealth effects on the optimal portfolio. These properties of Rubinstein's measures of risk aversion are analogous to those of the Arrow-Pratt measures of risk aversion in the portfolio selection model with one riskless and one risky investment. In multi-dimensional decision problems, we assume that a decision maker's preferences can be represented by a multivariate utility function. From the model with an uninsurable initial wealth vector and insurable risk vector having a joint normal distribution in the wealth space, we derived the matrix measures of risk aversion which are the multivariate extension of Rubinstein's measures of risk aversion. The derivations are based on the multivariate version of Stein/Rubinstein covariance operator developed by Gassmann and its second-order generalization to be developed in this thesis. We finally present an application of the matrix measures of risk aversion in a portfolio selection model with a multivariate utility function and two risky investments. In this model, if we assume that the random returns on the two investments and other random variables have a joint normal distribution, the optimal portfolio can be characterized by the matrix measures of risk aversion.
Business, Sauder School of
Graduate

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Eddings, James B. "The Utility of Environmental DNA and Species Distribution Models in Assessing the Habitat Requirements of Twelve Fish Species in Alaskan North Slope Rivers." DigitalCommons@USU, 2020. https://digitalcommons.usu.edu/etd/7708.

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Subsistence fishing is a vital component of Alaska’s North Slope borough economy and culture that is being threatened by human disturbance. These threats mean the fish must be protected, but the size of the region makes conservation planning difficult. Fortunately, advances in species distribution models (SDMs), environmental DNA (eDNA), and remote sensing technologies provide potential to better understand species’ needs and guide management. The objectives of my study were to: (1) map the current habitat suitability for twelve fish species, occurring in Alaska’s North Slope,(2) determine if SDMs based on eDNA data performed similarly to, or improved, models based on traditional sampling data, and (3) predict how species distributions will shift in the future in response to climate change. I was able to produce robust models for 8 of 12 species that relate environmental characteristics to a species’ presence or absence and identify stream reaches where species are likely to occur. Unfortunately, the use of eDNA data did not produce useful models in Northern Alaskan rivers. However, I was able to generate predictions of species distributions into the future that should help inform management for years to come.

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Newbold, Tim. "The value of species distribution models as a tool for conservation and ecology in Egypt and Britain." Thesis, University of Nottingham, 2010. http://eprints.nottingham.ac.uk/11405/.

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Knowledge about the distribution of species is limited, with extensive gaps in our knowledge, particularly in tropical areas and in arid environments. Species distribution models offer a potentially very powerful tool for filling these gaps in our knowledge. They relate a set of recorded occurrences of a species to environmental variables thought to be important in determining the distributions of species, in order to predict where species will be found throughout an area of interest. In this thesis, I explore the development, potential applications and possible limitations of distribution models using species from various taxonomic groups in two regions of the world: butterflies, mammals, reptiles and amphibians in Egypt, and butterflies, hoverflies and birds in Great Britain. Specifically I test: 1) which modelling methods produce the best models; 2) which variables correlate best with the distributions of species, and in particular whether interactions among species can explain observed distributions; 3) whether the distributions of some species correlate better with environmental variables than others and whether this variation can be explained by ecological characteristics of the species; 4) whether the same environmental variables that explain species’ occurrence can also explain species richness, and whether distribution models can be combined to produce an accurate model of species richness; 5) whether the apparent accuracy of distribution models is supported by ground-truthing; and 6) whether the models can predict the impact of climate change on the distribution of species. Overall the use of distribution models is supported; my models for species in both Egypt and Britain explained observed occurrence very well. My results shed some light on factors that may be important in determining the distributions of species, particularly on the importance of interactions among species. As they currently stand, distribution models appear unable to predict accurately the impacts of climate change.

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Laferriere, Alison Beth. "K-distribution fading models for Bayesian estimation of an underwater acoustic channel." Thesis, Massachusetts Institute of Technology, 2011. http://hdl.handle.net/1721.1/63080.

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Thesis (S.M. in Electrical Engineering and Computer Science)--Joint Program in Applied Ocean Science and Engineering (Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science; and the Woods Hole Oceanographic Institution), 2011.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 113-114).
Current underwater acoustic channel estimation techniques generally apply linear MMSE estimation. This approach is optimal in a mean square error sense under the assumption that the impulse response fluctuations are well characterized by Gaussian statistics, leading to a Rayleigh distributed envelope. However, the envelope statistics of the underwater acoustic communication channel are often better modeled by the K-distribution. In this thesis, by presenting and analyzing field data to support this claim, I demonstrate the need to investigate channel estimation algorithms that exploit K-distributed fading statistics. The impact that environmental conditions and system parameters have on the resulting distribution are analyzed. In doing so, the shape parameter of the K-distribution is found to be correlated with the source-to-receiver distance, bandwidth, and wave height. Next, simulations of the scattering behavior are carried out in order to gain insight into the physical mechanism that cause these statistics to arise. Finally, MAP and MMSE based algorithms are derived assuming K-distributed fading models. The implementation of these estimation algorithms on simulated data demonstrates an improvement in performance over linear MMSE estimation.
by Alison Beth Laferriere.
S.M.in Electrical Engineering and Computer Science

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Sirois-Delisle, Catherine. "Modeling Future Climate Change Impacts on North American Bumblebee Distributions." Thesis, Université d'Ottawa / University of Ottawa, 2017. http://hdl.handle.net/10393/37028.

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Climate change is an important contributor to the modification of many bumblebee species’ range boundaries. It was linked to widespread decline at the southern edge of their distribution and to their inability to colonize new areas at the northern edge. Additionally, bumblebee decline is aggravated by other anthropogenic threats like land use change, agricultural practices and pathogen spillover. Predicted consequences are numerous, and could lead to severe economic and ecological impacts on human populations. A species-specific assessment of potential climate change impacts on North American bumblebees, based on the most recent global change scenarios as used in the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC), was done for the first time. Using a massive dataset of georeferenced bumblebee observations and general circulation models, a series of species distribution models explore the impact of different climate change scenarios on climatically suitable areas of 30 bumblebee species. Northward range shifts occur in most bumblebee species’ projected climatic niches, revealing potential hotspots – places projected to be climatically suitable to multiple species – under future climate scenarios. Areas where species are likely to be lost in the absence of intervention are substantial, particularly in eastern parts of the continent. Models showed significant contractions of current ranges even under the very optimistic scenario in which all species disperse at 10 km/year. Results indicate that managed relocation as well as habitat management should be considered as a conservation strategy for some species. This research serves as a foundation for broader discussion and research in a nascent research area. It may assist in establishing localities where first conservation efforts could be directed for vulnerable bumblebee species.

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Bieleveld, Michel Jan Marinus. "Improving species distribution model quality with a parallel linear genetic programming-fuzzy algorithm." Universidade de São Paulo, 2016. http://www.teses.usp.br/teses/disponiveis/3/3141/tde-26012017-113329/.

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Biodiversity, the variety of life on the planet, is declining due to climate change, population and species interactions and as the result f demographic and landscape dynamics. Integrated model-based assessments play a key role in understanding and exploring these complex dynamics and have proven use in conservation planning. Model-based assessments using Species Distribution Models constitute an efficient means of translating limited point data to distribution probability maps for current and future scenarios in support of conservation decision making. The aims of this doctoral study were to investigate; (1) the use of a hybrid genetic programming to build high quality models that handle noisy real-world presence and absence data, (2) the extension of this solution to exploit the parallelism inherent to genetic programming for fast scenario based decision making tasks, and (3) a conceptual framework to share models in the hope of enabling research synthesis. Subsequent to this, the quality of the method, evaluated with the true skill statistic, was examined with two case studies. The first with a dataset obtained by defining a virtual species, and the second with data extracted from the North American Breeding Bird Survey relating to mourning dove (Zenaida macroura). In these studies, the produced models effectively predicted the species distribution up to 30% of error rate both presence and absence samples. The parallel implementation based on a twenty-node c3.xlarge Amazon EC2 StarCluster showed a linear speedup due to the multiple-deme coarse-grained design. The hybrid fuzzy genetic programming algorithm generated under certain consitions during the case studies significantly better transferable models.
Biodiversidade, a variedade de vida no planeta, está em declínio às alterações climáticas, mudanças nas interações das populações e espécies, bem como nas alterações demográficas e na dinâmica de paisagens. Avaliações integradas baseadas em modelo desempenham um papel fundamental na compreensão e na exploração destas dinâmicas complexas e tem o seu uso comprovado no planejamento de conservação da biodiversidade. Os objetivos deste estudo de doutorado foram investigar; (1) o uso de técnicas de programação genética e fuzzy para construir modelos de alta qualidade que lida com presença e ausência de dados ruidosos do mundo real, (2) a extensão desta solução para explorar o paralelismo inerente à programação genética para acelerar tomadas de decisão e (3) um framework conceitual para compartilhar modelos, na expectativa de permitir a síntese de pesquisa. Subsequentemente, a qualidade do método, avaliada com a true skill statistic, foi examinado com dois estudos de caso. O primeiro utilizou um conjunto de dados fictícios obtidos a partir da definição de uma espécie virtual, e o segundo utilizou dados de uma espécie de pomba (Zenaida macroura) obtidos do North American Breeding Bird Survey. Nestes estudos, os modelos foram capazes de predizer a distribuição das espécies maneira correta mesmo utilizando bases de dados com até 30% de erros nas amostras de presença e de ausência. A implementação paralela utilizando um cluster de vinte nós c3.xlarge Amazon EC2 StarCluster, mostrou uma aceleração linear devido ao arquitetura de múltiplos deme de granulação grossa. O algoritmo de programação genética e fuzzy gerada em determinadas condições durante os estudos de caso, foram significativamente melhores na transferência do que os algoritmos do BIOMOD.

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Dempsey, Stephen J. "Evaluation of Survey Methods and Development of Species Distribution Models for Kit Foxes in the Great Basin Desert." DigitalCommons@USU, 2013. https://digitalcommons.usu.edu/etd/2011.

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Historically, kit foxes (Vulpes macrotis) once occupied the desert and semi-arid regions of southwestern North America, ranging from Idaho to central Mexico. Their range-wide decline has warranted the kit fox to be listed as endangered in Colorado, threatened in California and Oregon, and designated as a state sensitive species in Idaho and Utah. Once considered the most abundant carnivore in western Utah, the kit fox has been in steep decline over the past decade, creating a demand to determine kit fox presence. Currently there is little consensus on which survey methodology is best to detect kit fox presence. We tested 4 survey methods (scat deposition, scent station, spotlight, trapping) along 15 5-km transects within a minimum known population of radio collar kit fox. Home range sizes for kit foxes on the study site were extremely large, averaging 20.5 km2. Scat deposition surveys had both the highest detection probabilities (= 0.88) and were the most closely related to known fox abundance (r2 =0.50, P = 0.001). For detecting kit foxes in a low density population we suggest using scat deposition transects during the breeding season. This method had low costs, was resilient to weather, had low labor requirements, and entailed no risk to the study animals.Next in determining kit fox presence is estimating kit fox distribution. We developed resource selection functions (RSF) using presence data from the noninvasive scat surveys to model kit fox distribution. We evaluated the predictive performance of RSFs built using three popular techniques (Maxent, fixed-effects and mixed-effects general linear models) combined with common environmental parameters (slope, aspect, elevation, soil type). Both the Maxent and fixed-effects models performed to an acceptable level with relatively high area under the curve (AUC) scores of 0.83 and 0.75, respectively. The mixed-effects model over valued higher elevations and had poor model fit. This study demonstrated that it was possible to create valid and informative predictive maps of a species distribution using a noninvasive survey method for detecting a carnivore existing at low density. By demonstrating the application of noninvasive surveying to model habitat quality for a small mesocarnivore, wildlife management agencies will be able to develop predictive maps for species of interest and provide more knowledge to help guide future management decisions.

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Dashuk, Valerii [Verfasser], and Joachim [Akademischer Betreuer] Winter. "Approaches for testing the joint hypotheses for multivariate normal distribution. Applications in panel data models / Valerii Dashuk ; Betreuer: Joachim Winter." München : Universitätsbibliothek der Ludwig-Maximilians-Universität, 2021. http://d-nb.info/1240145365/34.

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Artois, Jean. "Pathogens and parasites, species unlike others: The spatial distribution of avian influenzas in poultry." Doctoral thesis, Universite Libre de Bruxelles, 2019. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/283016.

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What explains the geographic distribution of pathogens? Better understanding and characterising disease patterns will help scientists to identify areas likely to host future epidemics and epizootics and to prioritise surveillance and intervention. However, the use of disease surveillance data to assess the risk of transmission and generate risk maps raises conceptual and methodological issues. Indeed, pathogens and more particularly viruses aren't ”species” like others that live in the open environment and must be studied with methods and concepts of their own. Avian influenza (AI), a disease caused by a virus infecting bird populations, has been selected to study these issues. AI has a major economic impact on the poultry industry in many countries, raises concerns of livelihood in low and middle-income countries, and represents a major concern for human health. The aim of this PhD thesis was to improve the knowledge on the spatial epidemiology of AI in different settings and conditions (i). For this, recent epizootics caused by the subtypes A (H5N1) and A (H7N9) were selected as case studies. First, highly pathogenic subtypes of the A (H5N1) virus have been studied in poultry farms (ducks and chickens) at different spatial scales: at the continental scale and the regional scale in the Mekong (Cambodia, Laos, Vietnam, Thailand) and the Nile Delta in Egypt. All these cases occurred between 2003, the date on which the virus starts to spread outside China, and 2015; the HPAI A (H5N1) subtypes are still reported today in many countries. Human infections caused by the A (H7N9) virus in China from March 2013 to 2017 were also studied. Studied different AI subtypes at different spatial scales within different host species also allowed to develop a conceptual model of AI transmission and to discuss the issue of the transferability of results in epidemiology (ii). Lastly, this PhD thesis leads to a discussion about the transfer of methods and concepts from ecology to spatial epidemiology, with a particular emphasis on their possible limitations (iii).
Doctorat en Sciences agronomiques et ingénierie biologique
info:eu-repo/semantics/nonPublished

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Rocha, Susana Cristina Machado. "Genetic and ecological consequences of a shifted phenology in a forest defoliator." Doctoral thesis, ISA, 2018. http://hdl.handle.net/10400.5/15333.

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Doutoramento em Engenharia Florestal e dos Recursos Naturais - Instituto Superior de Agronomia
Thaumetopoea pityocampa is a major pine defoliatior over the Mediterranean Basin. An atypical population with a shifted phenology, ongoing an allochronic differentiation process, was recently discovered in Mata Nacional Leiria, Portugal. The shifted population reproduces in spring achieving its larval development during summer (SP), whereas the sympatric typical population reproduces in summer and has winter larval development (WP). They are reproductively isolated through time, although sharing the same space and host species. General objectives of this work were to characterize the current and potential distribution range of this population, its spatial/temporal genetic and demographic patterns, and ecological adaptations. Field monitoring of presence/absence of SP nests throughout Leiria showed that it is expanding to North and South. Current distribution is restricted to coastal areas, along ca. 120 x 20 km area. Distribution models predict that its distribution will be restricted to coastal areas, due to unsuitable climate inland, being the maximal temperatures of the summer months the main constraint. A phylogeographic study confirmed high SP differentiation from other Portuguese populations. A spatio-temporal sampling along two geographic transects in Leiria zone revealed high stability in time of the genetic composition and structure. A striking demographic result showed that SP tends to apparently displace the WP from the coastal zones suggesting a possible competition phenomenon. Gene flow between the two populations was shown to remain low, even if some SP males actually emerge late. Ecological differentiation was assessed at egg and larval stages. The effect of a wide range of high temperatures on egg survival and development showed higher performances of the SP. Furthermore, SP larvae showed a better ability to cope with host plant water stress, evidencing adaptation to summer feeding activity. This study highlights intra-specific variations on the response of this insect to environmental constraints evidencing ecological adaptation following allochronic differentiation
N/A

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Rose, Peter. "Prediction of Fish Assemblages in Eastern Australian Streams Using Species Distribution Models: Linking Ecological Theory, Statistical Advances and Management Applications." Thesis, Griffith University, 2018. http://hdl.handle.net/10072/384279.

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Rivers and streams are among the most imperilled ecosystems on earth owing to overexploitation; water quality impacts, altered flow regimes, habitat destruction, proliferation of alien species and climate change. There is a pressing need to address these threats through stream bioassessment, stream rehabilitation and species conservation actions. Species distribution models (SDMs) can offer a practical, spatially explicit means to assess the impact of these threats, prioritise stream rehabilitation and direct conservation decisions. However, applications of SDMs for stream bioassessment and real-world conservation outcomes in freshwater ecosystems is still in its infancy. This thesis set out to link conceptual advances in fish ecology with emerging statistical methods applied to stream bioassessment and species conservation issues facing eastern Australian freshwater fish species. One of the primary uses of SDMs in freshwater environments is bioassessment, or assessment of “river health”. A network of reference sites underpins most stream bioassessment programs, however, there is an ongoing challenge of objectively selecting high quality reference sites, particularly in highly modified assessment regions. To address subjectivity associated with ‘best professional judgement’ and similar methods, I developed a novel, data-driven approach using species turnover modelling (generalised dissimilarity modelling) to increase objectivity and transparency in reference site selection. I also tested whether biogeographic legacies of fish assemblages among discrete coastal catchments limited the use of reference sites in southeast Queensland and northeast New South Wales. The data-driven approach was then used to select reference sites and sample fish assemblages to develop freshwater fish SDMs for subsequent data chapters. Another factor potentially limiting the accuracy of SDMs for bioassessment and conservation is the modelling strategy employed. In particular, site-specific models for stream bioassessment usually still use ‘shortcut’ methods such as community classification and discriminant function analysis, despite growing evidence that machine learning algorithms provide greater predictive performance. I tested how reference coastal fish assemblages are structured in relation different species assembly theories (e.g., species arrangement in discrete communities, species sorting independently across environmental gradients, or elements of both) by comparing different modelling approaches reflective of these processes (community level modelling, stacked ‘single species’ models and multi-species response models). Evaluation of the modelling was used to determine which of these modelling paradigms best suit stream bioassessment and other conservation applications such as survey gap analysis, estimating range changes owing to climate or land use change and estimating biodiversity. The taxonomic completeness index is the most commonly used site-specific index for stream bioassessment programs, despite several recognised limitations of this index, including use of an arbitrary threshold; omission of rare taxa that may be responsive to subtle levels of disturbance; and omission of potentially useful information on taxa gained at disturbed sites. I developed and tested an index that incorporated both native species losses, and gains of tolerant and alien species into a unified index of assemblage change for stream bioassessment. This study used a single species ensemble modelling approach to predict species occurrence and combined predictions into an index akin to Bray-Curtis dissimilarity. The resultant index, ‘BCA’, markedly outperformed the widely used taxonomic completeness index derived from community classification (discriminant function analysis) models and has considerable potential for improving stream bioassessment index sensitivities for a range of freshwater indicators (e.g. diatoms, macroinvertebrates, macrophytes). It is recognised that there are very few peer-reviewed SDM studies that have ‘real world’ conservation applications; most are instead academic exercises concerned with addressing methodological challenges, or hypothetical examples of how one might apply a SDM for a conservation problem. To address this gap between modelling and management, I used SDMs to inform a conservation plan for declining southern pygmy perch (Murray-Darling Basin lineage) (Nannoperca australis) in northern Victoria. This study incorporated alien species abundance models as predictors into an ensemble SDM to identify remnant habitats of this declining species. The models indicated that ~ 70% of N. australis habitat has become unsuitable since European settlement owing to anthropogenic pressures and interaction with alien fish species, particularly brown trout (Salmo trutta). Model outputs were used for survey gap analysis and to identify stream segments suitable for targeted management and reintroduction of the species. This study formed the basis for a captive breeding and translocation plan for southern pygmy perch in northern Victoria. The thesis concludes with practical learnings from these modelling studies for freshwater bioassessment and conservation practitioners; namely: (1) that machine learning multispecies response and ensemble models offer improved predictive performance compared with traditional approaches and that model choice depends on the intended use of the model; (2) that a newly developed index, “BCA”, provides a more conceptually sound and sensitive index than the traditionally used taxonomic completeness index for stream bioassessment; and, (3) that SDMs developed using readily available and high quality stream bioassessment datasets provide an excellent foundation for applied freshwater fish species conservation and management. The thesis concludes with future challenges and directions for freshwater fish SDM research.
Thesis (PhD Doctorate)
Doctor of Philosophy (PhD)
School of Environment and Sc
Science, Environment, Engineering and Technology
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36

Moore, Cordelia Holly. "Defining and predicting species-environment relationships : understanding the spatial ecology of demersal fish communities." University of Western Australia. Faculty of Natural and Agricultural Sciences, 2009. http://theses.library.uwa.edu.au/adt-WU2010.0002.

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[Truncated abstract] The aim of this research was to define key species-environment relationships to better understand the spatial ecology of demersal fish. To help understand these relationships a combination of multivariate analyses, landscape analysis and species distribution models were employed. Of particular interest was to establish the scale at which these species respond to their environment. With recent high resolution surveying and mapping of the benthos in five of Victoria's Marine National Parks (MNPs), full coverage bathymetry, terrain data and accurate predicted benthic habitat maps were available for each of these parks. This information proved invaluable to this research, providing detailed (1:25,000) benthic environmental data, which facilitated the development and implementation of a very targeted and robust sampling strategy for the demersal fish at Cape Howe MNP. The sampling strategy was designed to provide good spatial coverage of the park and to represent the park's dominant substrate types and benthic communities, whilst also satisfying the assumptions of the statistical and spatial analyses applied. The fish assemblage data was collected using baited remote underwater stereo-video systems (stereo- BRUVS), with a total of 237 one-hour drops collected. Analysis of the video footage identified 77 species belonging to 40 families with a total of 14,449 individual fish recorded. ... This research revealed that the statistical modelling techniques employed provided an accurate means for predicting species distributions. These predicted distributions will allow for more effective management of these species by providing a robust and spatially explicit map of their current distribution enabling the identification and prediction of future changes in these species distributions. This research demonstrated the importance of the benthic environment on the spatial distribution of demersal fish. The results revealed that different species responded to different scales of investigation and that all scales must be ix considered to establish the factors fish are responding to and the strength and nature of this response. Having individual, continuous and spatially explicit environmental measures provided a significant advantage over traditional measures that group environmental and biological factors into 'habitat type'. It enabled better identification of individual factors, or correlates, driving the distribution of demersal fish. The environmental and biological measures were found to be of ecological relevance to the species and the scale of investigation and offered a more informative description of the distributions of the species examined. The use of species distribution modelling provided a robust means for the characterisation of the nature and strength of these relationships. In addition, it enabled species distributions to be predicted accurately across unsampled locations. Outcomes of the project include a greater understanding of how the benthic environment influences the distribution of demersal fish and demonstrates a suite of robust and useful marine species distribution tools that may be used by researcher and managers to understand, monitor, manage and predict marine species distributions.

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Serra, Díaz Josep M. "Applying correlative ecological niche models to global change studies." Doctoral thesis, Universitat Autònoma de Barcelona, 2012. http://hdl.handle.net/10803/96302.

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La distribució de les espècies ha estat objecte d’estudi per part de diverses disciplines donada la seva naturalesa multifactorial. Així, entendre veritablement la distribució de les espècies implica necessàriament un millor coneixement del funcionament de la biosfera. D’altra banda, el canvi global que està patint el nostre planeta previsiblement afectarà en gran mesura moltes espècies, variant així la distribució i composició dels ecosistemes tal i com els coneixem avui dia i implícitament dels serveis que proporcionen. La modelització ha permès augmentar el nostre grau de comprensió sobre el sistema Terra així com de les potencials conseqüències que els canvis antropogènics poden provocar (canvi climàtic, alteració de cicles biogeoquímics, destrucció d’hàbitats, etc.). En el camp de la distribució d’espècies, els models de nínxol ecològic han estat àmpliament utilitzats per estudiar i preveure canvis en la distribució dels organismes. Aquests models es basen en la determinació de les condicions ambientals òptimes on una determinada espècie pot viure i reproduir-se (nínxol). Tanmateix, aquests models fan ús d’aproximacions correlatives entre presències i variables ambientals actuals, fet que presenta diverses desavantatges que posen de manifest una gran incertesa en les prediccions i fins i tot, qüestionen la seva utilitat en el context de canvi global. El conjunt dels treballs que s’exposen pretenen donar una visió sintètica de la possibilitat d’ús d’aquests models per a prediccions de distribució d’espècies vegetals, tant presents com futures. La present recerca se centra en l’anàlisi de diversos aspectes problemàtics per a aquests models en la predicció de la distribució´ d’espècies vegetals en el context del canvi global. Específicament s’ha avaluat la diferència entre prediccions basades en models ecofisiològics i models correlatius sobre l’efecte de prediccions actuals i futures , la variació entre prediccions a nivell de taxó o a nivell de comunitat, la variació en la predicció de canvi de nínxol davant possibles invasions i finalment, l’addició de l’escala temporal en les prediccions. S’ha pogut constatar que el fet de basar-se en correlacions estàtiques minva la seva capacitat de transferència a noves situacions i no incorpora trets biològics que poden tenir una importància cabdal (p.ex. fisiologia). En situacions de projeccions en l’espai i en el temps, s’observen importants variacions espacials en les prediccions, tant a nivell de comunitat com a nivell de poblacions de diversa provinença. Això comporta que les assumpcions i l’escala geogràfica i biològica hagin de ser adaptades segons la qüestió a la que el model s’adreça així com de la disponibilitat de dades. A més, incorporar l’escala temporal pot afegir una cert grau de dinamisme a aquests models estàtics, malgrat que no es poden inferir efectes a una resolució temporal adequada per a alguns fenòmens climàtics extrems . Dels resultats se’n desprèn que la utilització d’aquests models pot servir com a una bona eina de generació d’hipòtesis sobre dels diferents factors que actualment constrenyen la distribució de les espècies. A més, pot ser una tècnica potent per estimar el grau d’exposició de les espècies davant noves situacions de canvi global. Tot i això, les seves prediccions han de ser confrontades amb d’altres tècniques oimés quan es tracta de valorar escenaris plausibles subjectes a una gran incertesa. En general, aquests models són molt significatius per a la caracterització de l’exposició a noves situacions.
La distribución de las especies ha sido objetos de estudio por parte de diversas disciplinas dada su naturaleza multifactorial. Así, entender verdaderamente la distribución de las especies implica necesariamente un mejor conocimiento del funcionamiento de la biosfera. Por otro lado, el cambio global que esta sufriendo nuestro planeta previsiblemente afectará en gran medida muchas especies, variando su distribución y en última instancia, la composición de los ecosistemas tal y como los conocemos hoy día así como los servicios que proporcionan. La modelización ha permitido aumentar nuestro grado de comprensión sobre el sistema Tierra así como de las potenciales consecuencias que los cambios antropogénicos pueden provocar (cambio climático, alteración de ciclos biogeoquímicos, destrucción de hábitats, etc.). En el campo de la distribución de especies, los modelos de nicho ecológico han sido ampliamente utilizados para estudiar y predecir cambios en la distribución de los organismos. Estos modelos se basan en la determinación de las condiciones ambientales óptimas en las que una determinada especie puede vivir y reproducirse (nicho). Sin embargo, estos modelos utilizan una aproximación correlativa entre presencia de un organismo y las variables ambientales actuales, hecho que presenta diversas desventajas que ponen de manifiesto una gran incertidumbre en las predicciones e incluso, cuestionan su utilidad en el contexto del cambio global. El conjunto de los trabajos que aquí se exponen pretenden dar una visión sintética de la posibilidad de uso de estos modelos para predicciones de la distribución de especies vegetales, tanto presentes como futuras. La presente investigación se centra en el análisis de aspectos problemáticos de índole diversa de este tipo de modelos, cuando son aplicados para predecir la distribución de especies vegetales bajo supuestos de cambio global. Específicamente se ha evaluado la diferencia entre predicciones basadas en modelos ecofisiológicos y modelos correlativos en la predicción de distribuciones presentes y futuras, la variación entre predicciones a nivel de taxón o a niveles de comunidad, la variación en la predicción según la población bajo riesgos potenciales de cambio de nicho i finalmente, la adición de la escala temporal en las predicciones. Se ha podido constatar que el hecho de basarse en correlaciones estáticas disminuye su capacidad de transferencia a nuevas situaciones i no incorpora características biológicas que pueden tener una importancia vital (p.ej. fisiología). En situaciones de proyecciones en el espacio y el tiempo, se observan variaciones espaciales significativas en las predicciones, tanto a nivel de comunidad como a nivel de poblaciones de diverso origen. Esto comporta que las asunción i la correcta elección de la escala geográfica i biológica según el objetivo del modelo. Además, la incorporación de la escala temporal puede añadir un cierto grado de dinamismo a estos modelos estáticos, a pesar que no se pueden inferir efectos a una resolución temporal adecuada para algunos fenómenos climáticos extremos. En general, dichos modelos son relevantes para caracterizar la exposición a nuevas situaciones.
The distribution of species has been studied by various disciplines due to its multifactorial nature. Thus, to truly understand the distribution of species necessarily implies a better understanding of the functioning of the biosphere. On the other hand, the overall change our planet is undergoing, it is expected to greatly affect many species, varying distribution and ultimately the composition of ecosystems as we know them today and the services they provide. The modeling has enhanced our level of understanding of the Earth system and the potential consequences that anthropogenic changes can cause (climate change, alteration of biogeochemical cycles, habitat destruction, etc..). In the field of species distribution, ecological niche models have been widely used to study and predict changes in the distribution of organisms. These models are based on determining the optimum environmental conditions in which a species can live and reproduce (niche). However, these models use a correlative approach between the presence of an organism and the current environmental variables, which has several disadvantages that cause a uncertainty in predictions and even question their usefulness in the context of global change. All the works presented here are intended to give a synthetic view of the possibility of using these models for predictions of the distribution of plant species, both present and future. This research focuses on the analysis of problematic aspects of these models, when applied to predict the distribution of plant species under global change scenarios. Specifically we evaluated the difference between model predictions and ecophysiological models to predict correlative and future distributions, the variation between predictions at the level of taxon or community levels, the variation in the prediction at the population levels and finally, the addition of the timescale in the predictions. It has been shown that basing predictions on static correlations diminishes their transference capacity to new situations and does not incorporate key biological traits that may play a key role (e.g. physiology). In projections in space and time, it has been observed significant spatial variations in predictions, whether at the community or individual level of species or different populations across continents. This implies that the choice of the biological or geographical scale may be fit for model’s purpose. Furthermore, the incorporation of the temporal scale may add a certain degree of dynamism to these static modles, despite they cannot be infered for effects at higher temporal resolution for some extreme climatic events. In general, such models are relevant to characterize exposure to new situations.

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Oleas, Nora. "Landscape Genetics of Phaedranassa Herb. (Amaryllidaceae) in Ecuador." FIU Digital Commons, 2011. http://digitalcommons.fiu.edu/etd/443.

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Speciation can be understood as a continuum occurring at different levels, from population to species. The recent molecular revolution in population genetics has opened a pathway towards understanding species evolution. At the same time, speciation patterns can be better explained by incorporating a geographic context, through the use of geographic information systems (GIS). Phaedranassa (Amaryllidaceae) is a genus restricted to one of the world’s most biodiverse hotspots, the Northern Andes. I studied seven Phaedranassa species from Ecuador. Six of these species are endemic to the country. The topographic complexity of the Andes, which creates local microhabitats ranging from moist slopes to dry valleys, might explain the patterns of Phaedranassa species differentiation. With a Bayesian individual assignment approach, I assessed the genetic structure of the genus throughout Ecuador using twelve microsatellite loci. I also used bioclimatic variables and species geographic coordinates under a Maximum Entropy algorithm to generate distribution models of the species. My results show that Phaedranassa species are genetically well-differentiated. Furthermore, with the exception of two species, all Phaedranassa showed non-overlapping distributions. Phaedranassa viridiflora and P. glauciflora were the only species in which the model predicted a broad species distribution, but genetic evidence indicates that these findings are likely an artifact of species delimitation issues. Both genetic differentiation and non-overlapping geographic distribution suggest that allopatric divergence could be the general model of genetic differentiation. Evidence of sympatric speciation was found in two geographically and genetically distinct groups of P. viridiflora. Additionally, I report the first register of natural hybridization for the genus. The findings of this research show that the genetic differentiation of species in an intricate landscape as the Andes does not necessarily show a unique trend. Although allopatric speciation is the most common form of speciation, I found evidence of sympatric speciation and hybridization. These results show that the processes of speciation in the Andes have followed several pathways. The mixture of these processes contributes to the high biodiversity of the region

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Alagador, Diogo André Alves Salgado Rodrigues. "Quantitative methods in spatial conservation planning integrating climate change and uncertainties." Doctoral thesis, ISA/UTL, 2011. http://hdl.handle.net/10400.5/3877.

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Doutoramento em Biologia - Instituto Superior de Agronomia
Spatial Conservation Planning is a scientific-driven procedure to identify cost effective networks of areas capable of representing biodiversity through time. This conceptually simple task accommodates sufficient complexity to justify the existence of an active research line with more than 20 years already. But costefficiency and representation of biodiversity is only part of the whole challenge of Spatial Conservation Planning.The recognition that Nature operates dynamically has stimulated researchers to embrace the additional challenges of developing methods to make conventional (static) conservation approaches more dynamic and therefore increase the chances that biodiversity are preserved in the longer term. In this thesis, I present a set of tools to assist spatial conservation decision-making and address issues such as uncertainty and spatial dynamics of species ranges. These two topics are particularly relevant in the context of ongoing climate changes. I start by investigating two connectivity paradigms for the identification of conservation areas. In the first, a distance-based approach is applied for the identification of areas representing a set of species. In the second, I present a conceptual framework based on the analysis of environmental similarity between protected areas. The framework seeks to identify effective spatial linkages between protected areas while ensuring that these linkages are as efficient as possible. Then, I introduce a methodology to refine the matching of species distributions and protected area data in gap analysis. Forth, I present a comprehensive assessment for the expected impacts of climate change among European conservation areas. Finally, I address a framework for cost-efficient identification of the best areas that, in each time period, assist species’ range adjustments induced by severe climate changes. There exists a wealth of theoretical insight and algorithmic power available to ecologists. This thesis took advantage of it and (I hope) it offers useful guidance for genuine biodiversity protection.

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Guillaumot, Charlène. "Modelling the response of Antarctic marine species to environmental changes. Methods, applications and limitations." Electronic Thesis or Diss., Bourgogne Franche-Comté, 2021. http://www.theses.fr/2021UBFCK020.

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Parmi les outils qui permettent de mieux comprendre les systèmes naturels, la modélisation écologique a connu un essor particulièrement important depuis une vingtaine d’années. Les modèles écologiques, représentation simplifiée d’une réalité complexe, permettent de mettre en avant les facteurs environnementaux qui déterminent la niche écologique des espèces et de mieux comprendre leur réponse aux changements de l’environnement. Dans le cas des faunes marines antarctiques, la modélisation écologique fait face à plusieurs défis méthodologiques. Les jeux de données de présence des espèces sont très souvent agrégés dans le temps et dans l’espace, à proximité des stations de recherche. Ces données sont souvent trop peu nombreuses pour caractériser l’espace environnemental occupé par les espèces ainsi que leur physiologie. Enfin, les jeux de données environnementales manquent encore de précision pour finement représenter la complexité des habitats marins. Dans ces conditions, est-il possible de générer des modèles performants et justes à l’échelle de l’océan Austral ? Quelles sont les approches possibles et leurs limites ? Comment améliorer les méthodes afin de générer de meilleurs modèles ? Au cours de ce travail de thèse, trois types de modèles ont été étudiés et leurs performances évaluées. (1) Les modèles physiologiques de type DEB (Dynamic Energy Budget) simulent la manière dont l’environnement abiotique influe sur le métabolisme des individus et proposent une représentation de la niche fondamentale des espèces. (2) Les modèles de distribution d’espèces (SDMs pour Species Distribution Models) prédisent la probabilité de distribution des espèces en étudiant la relation spatiale entre données de présence et environnement. Ils proposent une représentation de la niche réalisée des espèces. Enfin (3), les modèles de dispersion de type lagrangien prédisent le mouvement de propagules dans les masses d’eau. Les résultats montrent que les modèles physiologiques réussissent à simuler les variations métaboliques des espèces antarctiques en fonction de l’environnement et à prédire les dynamiques de populations. Cependant, davantage de données sont nécessaires pour pouvoir caractériser finement les différences physiologiques entre populations et évaluer correctement les modèles. Les résultats obtenus pour les SDMs montrent que les modèles générés à l’échelle de l’océan Austral et leurs prédictions futures ne sont pas fiables du fait du manque de données disponibles pour caractériser l’espace occupé par les espèces, du manque de précision des scénarios climatiques futurs et de l’impossibilité d’évaluer les modèles. De plus, les modèles extrapolent sur une très grande proportion de l’espace projeté. L’apport d’information complémentaire sur les limites physiologiques des espèces (observations, résultats d’expériences, sorties de modèles physiologiques) permet de réduire l’extrapolation et d’augmenter la capacité des modèles à décrire la niche réalisée des espèces. L’agrégation spatiale des données, qui influençait les prédictions et l’évaluation des modèles a également pu être corrigée. Enfin, les modèles de dispersion ont montré un potentiel intéressant pour révéler le rôle des barrières géographiques ou à l’inverse, la connectivité spatiale, mais également le lien existant entre distribution, physiologie et histoire phylogénétique des espèces. Ce travail de thèse propose de nombreux conseils et fournit des codes annotés parfois sous forme de tutoriels, afin de constituer une aide utile aux futurs travaux de modélisation sur les espèces marines antarctiques
Among tools that are used to fill knowledge gaps on natural systems, ecological modelling has been widely applied during the last two decades. Ecological models are simple representations of a complex reality. They allow to highlight environmental drivers of species ecological niche and better understand species responses to environmental changes. However, applying models to Southern Ocean benthic organisms raises several methodological challenges. Species presence datasets are often aggregated in time and space nearby research stations or along main sailing routes. Data are often limited in number to correctly describe species occupied space and physiology. Finally, environmental datasets are not precise enough to accurately represent the complexity of marine habitats. Can we thus generate performant and accurate models at the scale of the Southern Ocean ? What are the limits of such approaches ? How could we improve methods to build more relevant models ? In this PhD thesis, three different model categories have been studied and their performance evaluated. (1) Mechanistic physiological models (Dynamic Energy Budget models, DEB) simulate how the abiotic environment influences individual metabolism and represent the species fundamental niche. (2) Species distribution models (SDMs) predict species distribution probability by studying the relationship between species presences and the environment. They represent the species realised niche. (3) Dispersal lagrangian models predict the drift of propagules in water masses. Results show that physiological models can be developed for marine Southern Ocean species to simulate the metabolic variations in link with the environment and predict population dynamics. However, more data are necessary to highlight detailed physiological contrasts between populations and to accurately evaluate models. Results obtained for SDMs suggest that models generated at the scale of the Southern Ocean and future simulations are not relevant, given the lack of data available to characterise species occupied space, the lack of precision and accuracy of future climate scenarios and the impossibility to evaluate models. Moreover, model extrapolate on a large proportion of the projected area. Adding information on species physiological limits (observations, results from experiments, physiological model outputs) was shown to reduce extrapolation and to improve the capacity of models to estimate the species realised niche. Spatial aggregation of occurrence data, which influenced model predictions and evaluation was also succefully corrected. Finally, dispersal models showed an interesting potential to highlight the role of geographic barriers or conversely of spatial connectivity and also the link between species distribution, physiology and phylogeny history. This PhD thesis provides methodological advices, annoted codes and tutorials to help implement future modelling works applied to Southern Ocean marine species

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Nadeau, Julie L. "Testing the reliability of Canada-wide and regional species distribution models with independent field surveys and evaluating their use for conservation." Thesis, University of Ottawa (Canada), 2010. http://hdl.handle.net/10393/28612.

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For purposes of conservation, we require methods to predict where species occur currently, and where they are likely to move in the future. Species distribution models can be useful tools, by predicting where species are in areas that cannot be surveyed but where management decisions must occur. However, they are rarely tested using independent field surveys to determine their accuracy. These models are also generally developed over broad spatial scales; in contrast, distributions must often be predicted over local to regional scales for conservation purposes. Using butterfly surveys along transects in eastern Ontario, we tested whether independent regional observations of butterflies could be predicted from distribution models developed on Canada-wide species ranges. We also developed a set of regional models using Maximum entropy software to compare with the independent field surveys. Our results show that regional field occurrences are not accurately predicted by the national models, which explain between 0 and 31% (median 4.2%) of the deviance in species presence/absence. Even when species distribution models developed using regional variables have high apparent accuracy (AUC values exceed 0.8), they do not appear to accurately predict occurrence at local spatial extents, explaining between 0 and 46% (median 3.4%) of the deviance in species presence/absence. Species distribution models' inaccuracy in predicting species' presence within their ranges indicates that field-based observations remain indispensable when making conservation decisions. Misusing models can be costly if they lead to errors in predicting the presence of species of concern or their habitat and can result in poor management decisions if used improperly.

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Bereng, Mosiuoa Walter. "Understanding environmental factors influencing invasion of Lilium formosanum in Mpumalanga Province and models of its potential distribution in South Africa." Diss., University of Pretoria, 2014. http://hdl.handle.net/2263/79711.

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Alien invasive plants are of concern in the world because of their potential to spread into the natural environment. Invasion patterns observed in plant species can be attributed among other things to favourable environmental conditions. Understanding invasion dynamics of alien invasive plants can help in timely intervention initiatives. In Mpumalanga, Lilium formosanum (Liliaceae) appears to be an emerging plant invader and is spreading in the natural environment. The study investigated the invasion extent and predictor variables which could explain abundance patterns of L. formosanum in the invasive range in Mpumalanga province in South Africa and further predict regions of the world that could be climatically suitable. Lilium formosanum was surveyed along 11 major routes leading into the towns of Sabie and Graskop in Mpumalanga from a slow moving vehicle. A total of 241 kilometres was surveyed. Lilium formosanum was found to be invasive from the towns of Sabie and Graskop. Climatically suitable areas were predicted using DIVA-GIS and climate data was obtained from WORLDCLIM database while occurrence records were obtained from the Southern African Plant Invaders Atlas, Australia’s virtual herbarium and the Global Biodiversity Information Facility. In conclusion, distance, altitude and route were found to have an influence on the abundance of L. formosanum in Mpumalanga Province. Climatically suitable areas included the eastern coastal belt, northern provinces and the interior parts of South Africa including major parts of Limpopo and Mpumalanga.
Dissertation (MSc)--University of Pretoria, 2014.
Plant Production and Soil Science
MSc
Unrestricted

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Hanspach, Jan [Verfasser], Ingolf [Akademischer Betreuer] Kühn, Helge [Akademischer Betreuer] Bruelheide, and Niklaus [Akademischer Betreuer] Zimmermann. "Assessing the influence of global change on plant species distribution using statistical models / Jan Hanspach. Betreuer: Ingolf Kühn ; Helge Bruelheide ; Niklaus Zimmermann." Halle, Saale : Universitäts- und Landesbibliothek Sachsen-Anhalt, 2010. http://d-nb.info/1025011708/34.

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Chatfield, Brenton Sean. "How to find the one that got away : predicting the distribution of temperate demersal fish from environmental variables." University of Western Australia. School of Earth and Geographical Sciences, 2008. http://theses.library.uwa.edu.au/adt-WU2009.0009.

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Knowing where species are and understanding why is paramount for developing relevant and sustainable conservation and resource management strategies. The need for this information is becoming urgent as fishing activity, resource extraction and the impacts of coastal developments continue to put marine resources under increasing pressure. As logistical and financial constraints can restrict our ability to collect data in the marine environment, the ability to predict distributions based on known associations with different environmental variables would enhance our capacity to manage these resources. Before attempting to predict the distribution of species and groups of species, the underlying species-environment relationships must be examined to determine whether associations between species and the environment can: (i) be identified, (ii) be used to develop models that can accurately predict distributions, and (iii) are general enough to allow accurate predictions beyond the sampled area. Most studies to date have compared the composition of fish assemblages between sites to determine how different environmental variables influence distribution. While widely applied, these methods do not consider how individual species respond to multiple environmental gradients and they lack the ability to predict distributions across different combinations of variables along those gradients. This lack of prediction also limits our capacity to assess what marine biodiversity is presently threatened by global, regional, and local human pressures on marine ecosystems. '...' Thus, summarising and modelling species data at higher levels would result in models with poorer predictive accuracy and a loss of ecological information. The generality of the species-environment relationships defined by the models were assessed by evaluating the transferability of models between different areas. Models developed from data collected over a wider geographic extent could more accurately predict the distribution of species across a smaller spatial extent than vice versa. This indicated that while general theories of the ecology of temperate demersal fish can be defined, the actual patterns of distribution may vary from site to site, suggesting caution when using predictions beyond the sampled area for management purposes. Overall, species distribution modelling identified how different species and groups of species responded to the combined influence of multiple environmental gradients and was able to accurately predict distributions based on the defined associations. Their application has led to a greater understanding of the species environment relationships and will help to identify those areas that may be important for conservation. Their predictive ability will allow general predictions of distribution of fish species across unsurveyed areas and provides the ability to assess the potential impact from implementing different policy and management strategies.

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Pérez, Navarro Maria Ángeles. "Plant species climatic niche and its relationship with population responses to extreme drought." Doctoral thesis, Universitat Autònoma de Barcelona, 2020. http://hdl.handle.net/10803/669559.

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Understanding how climate affects species’ distribution and performance is a central issue in ecology since its origins. In last decades, however, the interest in this question has been reactivated by the current context of climate change. Species Niche Modelling has been widely used to assess shifts in species distribution and to test the relationship between species’ climatic niche and species physiological and demographic performance. Nevertheless it is still largely undetermined whether these models can portray population and community responses, particularly in relation to extreme climatic episodes. In this thesis I aim at exploring the capacity of niche modelling to predict species decay under extreme climatic conditions, particularly droughts, addressing some constraints of this approach and proposing possible solutions. To achieve this goal, I counted with 3 vegetation decay datasets measured in the Spanish SE after the extreme drought year 2013-2014. In the second chapter I used different Species Distribution Model (SDMs) algorithms to estimate species’ climatic suitability before (1950-2000) and during the extreme drought, in order to test the possible correlation between suitability and decay, and whether the existence of this relationship depended on the applied SDM algorithm. I consistently found a positive correlation between remaining green canopy and species’ climatic suitability before the event, suggesting that populations historically living closer to their species’ tolerance limits are more vulnerable to drought. Contrastingly, decreased climatic suitability during the drought period did not correlate with remaining green canopy, likely because of extremely low climatic suitability values achieved during the exceptional climatic episode. In order to test whether this extremely low suitability values could derive as a consequence of only considering climatic averages when calibrating SDMs, in the thired chapter I developed a method to include inter-annual climatic variability into niche characterization. I then compared the respective capacities of climatic suitabilities obtained from averaged-based and from inter-annual variability-based niches to explain demographic responses to extreme climatic events. I found that climatic suitability obtained from both niches quantifications significantly explained species demographic responses. However, climatic suitability from inter-annual variability-based niches showed higher explanatory capacity, especially for populations that tend to be more geographically marginal. In the fourth chapter I tried to overcome the inability of the SDMs to predict populations decay during extreme conditions, by using Euclidean distances to species’ niche in the environmental space. I compared the capacities of both population distances in the climatic environmental space and population climatic suitability derived from SDMs to explain population observed demographic responses to an extreme event. I found that SDMs-derived suitability failed to explain population decay while distances to the niche centroid and limit significantly explained population die-off, highlighting that population displaced farther from species’ niche during the extreme episode showed higher vulnerability to drought. In the fifth chapter, I used species niche characterizations in the environmental space and demographic data to address the impact of extreme events at community level. Particularly, I estimated the community climatic disequilibrium before and after a drought episode. I found that extreme drought nested within a decadal trend of increasingly aridity led to a reduction in community climatic disequilibrium.

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Jaeschke, Anja Verfasser], and Carl [Akademischer Betreuer] [Beierkuhnlein. "Extending the climate envelope: Methodological approaches to integrate ecological prerequisites in species distribution models at large spatial extents / Anja Jaeschke. Betreuer: Carl Beierkuhnlein." Bayreuth : Universität Bayreuth, 2015. http://d-nb.info/1073201805/34.

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Pelletier, Tara A. "Western Plethodon Salamanders as a Model System in Phylogeography." The Ohio State University, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=osu1429292290.

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Sarmento, Cabral Juliano. "Demographic processes determining the range dynamics of plant species, and their consequences for biodiversity maintenance in the face of environmental change." Phd thesis, Universität Potsdam, 2009. http://opus.kobv.de/ubp/volltexte/2010/4118/.

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The present thesis aims to introduce process-based model for species range dynamics that can be fitted to abundance data. For this purpose, the well-studied Proteaceae species of the South African Cape Floristic Region (CFR) offer a great data set to fit process-based models. These species are subject to wildflower harvesting and environmental threats like habitat loss and climate change. The general introduction of this thesis presents shortly the available models for species distribution modelling. Subsequently, it presents the feasibility of process-based modelling. Finally, it introduces the study system as well as the objectives and layout. In Chapter 1, I present the process-based model for range dynamics and a statistical framework to fit it to abundance distribution data. The model has a spatially-explicit demographic submodel (describing dispersal, reproduction, mortality and local extinction) and an observation submodel (describing imperfect detection of individuals). The demographic submodel links species-specific habitat models describing the suitable habitat and process-based demographic models that consider local dynamics and anemochoric seed dispersal between populations. After testing the fitting framework with simulated data, I applied it to eight Proteaceae species with different demographic properties. Moreover, I assess the role of two other demographic mechanisms: positive (Allee effects) and negative density-dependence. Results indicate that Allee effects and overcompensatory local dynamics (including chaotic behaviour) seem to be important for several species. Most parameter estimates quantitatively agreed with independent data. Hence, the presented approach seemed to suit the demand of investigating non-equilibrium scenarios involving wildflower harvesting (Chapter 2) and environmental change (Chapter 3). The Chapter 2 addresses the impacts of wildflower harvesting. The chapter includes a sensitivity analysis over multiple spatial scales and demographic properties (dispersal ability, strength of Allee effects, maximum reproductive rate, adult mortality, local extinction probability and carrying capacity). Subsequently, harvesting effects are investigated on real case study species. Plant response to harvesting showed abrupt threshold behavior. Species with short-distance seed dispersal, strong Allee effects, low maximum reproductive rate, high mortality and high local extinction are most affected by harvesting. Larger spatial scales benefit species response, but the thresholds become sharper. The three case study species supported very low to moderate harvesting rates. Summarizing, demographic knowledge about the study system and careful identification of the spatial scale of interest should guide harvesting assessments and conservation of exploited species. The sensitivity analysis’ results can be used to qualitatively assess harvesting impacts for poorly studied species. I investigated in Chapter 3 the consequences of past habitat loss, future climate change and their interaction on plant response. I use the species-specific estimates of the best model describing local dynamics obtained in Chapter 1. Both habitat loss and climate change had strong negative impacts on species dynamics. Climate change affected mainly range size and range filling due to habitat reductions and shifts combined with low colonization. Habitat loss affected mostly local abundances. The scenario with both habitat loss and climate change was the worst for most species. However, this impact was better than expected by simple summing of separate effects of habitat loss and climate change. This is explained by shifting ranges to areas less affected by humans. Range size response was well predicted by the strength of environmental change, whereas range filling and local abundance responses were better explained by demographic properties. Hence, risk assessments under global change should consider demographic properties. Most surviving populations were restricted to refugia, serving as key conservation focus.The findings obtained for the study system as well as the advantages, limitations and potentials of the model presented here are further discussed in the General Discussion. In summary, the results indicate that 1) process-based demographic models for range dynamics can be fitted to data; 2) demographic processes improve species distribution models; 3) different species are subject to different processes and respond differently to environmental change and exploitation; 4) density regulation type and Allee effects should be considered when investigating range dynamics of species; 5) the consequences of wildflower harvesting, habitat loss and climate change could be disastrous for some species, but impacts vary depending on demographic properties; 6) wildflower harvesting impacts varies over spatial scale; 7) The effects of habitat loss and climate change are not always additive.
Das Ziel dieser Studie bestand daher darin, prozess-basierte Modelle zu entwickeln, die mit Daten zur Abundanz von Arten parametrisiert werden können. Die außergewöhnlich gut erforschten Proteaceen der südafrikanischen Kapregion (CFR), für die ein umfangreicher Datensatz zur Verfügung steht, stellen ein sehr geeignetes Untersuchungssystem zur Erstellung derartiger prozess-basierter Modelle dar. In Kapitel 1 beschreibe ich ein prozess-basiertes Modell für die Verbreitungsdynamik sowie die Methoden zur Parametrisierung des Modells mit Daten zu Abundanzverteilungen. Das Modell umfasst ein räumlich-explizites demographisches Modul und ein Beobachtungsmodul. Das demographische Modul verbindet artspezifische Habitatmodelle, die das geeignete Habitat beschreiben, und prozess-basierte demographische Modelle, die die lokale Dynamik und die Windausbreitung von Samen umfassen. Nach der Überprüfung der Parametrisierungs¬methoden mit simulierten Daten, wende ich die Modelle auf acht Proteaceenarten mit unterschiedlichen demographischen Eigenschaften an. Außerdem untersuche ich die Rolle von positiver (Allee-Effekte) und negativer Dichte-Abhängigkeit. Die Ergebnisse zeigen, dass Allee-Effekte und überkompensatorische Dynamik für viele Arten tatsächlich eine Rolle spielen. Der Großteil der geschätzten Parameter stimmt quantitativ mit unabhängigen Daten und beschreibt erfolgreich, wie die Abundanzverteilung aus der Bewegung und Interaktion der Individuen entsteht. Die vorgestellten Methoden scheinen daher zur Untersuchung von Ungleichgewichtsszenarien geeignet, die die Ernte von Infloreszenzen in Wildbeständen (Kapitel 2) und Umweltwandel (Kapitel 3) einschließen. In Kapitel 2 untersuche ich die Effekte der Ernte von Infloreszenzen in Wildbeständen. Das Kapitel beinhaltet eine Sensitivitätsanalyse über mehrere räumliche Skalen sowie demographische Eigenschaften. Darauf folgend wurden die Effekte der Ernte anhand von drei realen Arten untersucht. Die Reaktion der Pflanzen auf die Ernte zeigte ein Verhalten mit abrupten Schwellenwerten. Die durch die Ernte am stärksten gefährdeten Arten zeichneten sich durch kurze Samenausbreitungsdistanzen, starke Allee Effekte, geringe maximale Reproduktionsrate, hohe Mortalität und hohe lokale Aussterbewahrscheinlichkeit aus. Die Betrachtung größerer räumlicher Skalen wirkte sich trotz schärferer Grenzwerte positiv auf die Reaktion der Arten aus. Die drei untersuchten realen Arten konnten sehr geringe bis mittlere nachhaltige Ernteraten ertragen. Zusammenfassend lässt sich sagen, dass Kenntnisse über die Demographie des Untersuchungssystems und die umsichtige Identifizierung der zu betrachtenden räumlichen Skala zu einer besseren Einschätzung der Ernteintensität und der Naturschutzziele führen sollten. In Kapitel 3 wird die Reaktion der Arten auf vergangene Habitatverluste und zukünftigen Klimawandel sowie die Interaktion der beiden untersucht. Der Klimawandel wirkte sich dabei vornehmlich negativ auf die Größe des Verbreitungsgebiets und die Ausnutzung des potentiellen Habitats (‚Range Filling’) aus, wobei es zu einer Verschiebung des Habitats ohne erfolgreiche Kolonisierung kam. Der Habitatverlust reduzierte vor allem die lokalen Abundanzen. Die meisten Arten wurden vor allem durch das Szenario mit beiden Klimawandel und Habitatsverlust stark beeinträchtigt. Der negative Effekt war allerdings geringer als nach einer einfachen Aufsummierung der Einzeleffekte zu erwarten wäre. Dies erklärt sich aus einer Verschiebung des Verbreitungsgebiets der Arten in Regionen, in denen es in der Vergangenheit zu geringeren Habitatverlusten kam. Die Größe des Verbreitungsgebiets wurde am besten durch die Stärke des Umweltwandels vorhergesagt, wogegen das Range Filling und die lokalen Abundanzen hauptsächlich von den demographischen Eigenschaften abhingen. Aus diesen Ergebnissen lässt sich schließen, dass Abschätzungen des Aussterbensrisikos unter Umweltwandel demographische Eigenschaften einbeziehen sollten. Die meisten überlebenden Populationen waren auf Refugien reduziert, die im Fokus der Naturschutzmaßnahmen stehen sollten. Zusammenfassend zeigen die Ergebnisse, dass 1) prozess-basierte demographische Modelle für die Verbreitungsdynamik von Arten mit Daten parametrisierbar sind; 2) die Einbeziehung demographischer Prozesse die Modelle für die Verbreitung von Arten verbessert; 3) verschiedene Arten von unterschiedlichen Prozessen beeinflusst werden und unterschiedlich auf Umweltwandel und Beerntung reagieren; 4) Dichteregulierung und Allee-Effekte bei der Untersuchung der Verbreitungsdynamik von Arten berücksichtigt werden sollten; 5) die Ernte von Infloreszenzen in Wildbeständen, sowie Habitatverlust und Klimawandel für manche Arten katastrophale Folgen haben können, deren Effekte aber von den demographischen Eigenschaften abhängen; 6) der Einfluss der Beerntung in Abhängigkeit von der betrachteten räumlichen Skala variiert; 7) die Effekte von Habitatverlust und Klimawandel nicht additiv sind.

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Menuz, Diane R. "Using Species Distribution Models to Assess Invasion Theory and Provide Management Recommendations for Riparian Areas in the Eastern Columbia and Western Missouri River Basins." DigitalCommons@USU, 2011. https://digitalcommons.usu.edu/etd/1106.

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Invasive plant species impact ecosystems by altering native plant community composition and modifying ecosystem properties such as fire and nutrient cycles. We used species distribution models to address both theoretical and applied questions regarding invasive plants in an ecosystem particularly vulnerable to invasion, riparian areas. In our first study, we asked whether a native species is closer to equilibrium than a functionally similar invasive species and determined drivers of invasion for an aggressive invader of riparian areas, Phalaris arundinacea (reed canarygrass). We modeled the presence of P. arundinacea and a comparable native species using four techniques and compared model fit between species and between models with and without dispersal processes incorporated. Non-dispersal model fit for our invasive species was lower than for the native species and improvement in fit with the addition of the dispersal constraint was greater for the invasive species than the native species. These results provide evidence that invasive species are further from equilibrium than native species and suggest that dispersal processes should be considered when modeling invasive species. In our second study, we addressed whether there was a set of site traits that make some sites more prone to invasion by non-native plants than others. We used Random Forests to individually model the presence of 11 invasive plant species that are designated as noxious weeds in our study area. We used model results to identify general patterns of invasion and to provide management recommendations for the study area. We found that a particular site type was more likely to be invaded by the majority of study species: hot, dry sites with high grass or shrub cover near roads with high nutrient levels and high stream baseflow values. Management recommendations to combat invasion by P. arundinacea in particular and invasive species in general are the same: limiting species’ spread along roads, lowering site nutrient levels, and anticipating increased spread with climate change.

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Coelho, Igor Pfeifer. "Do barro ao bamburro : relações entre a paisagem e a distribuição local de mamíferos e aves no Pantanal, Brasil." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2016. http://hdl.handle.net/10183/150709.

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A relação entre a paisagem e a distribuição da ocorrência e abundância das espécies no espaço é uma das questões centrais em ecologia, com importantes aplicações diretas em tempos de intenso uso da terra e mudanças climáticas por atividades humanas. Contudo, para inferirmos sobre essas relações, temos que descrever a paisagem da forma mais próxima possível de como as espécies realmente a percebem. Uma paisagem pode ser descrita em diferentes níveis hierárquicos de organização do ambiente (e.g. quantidade de um mineral no solo, número de plantas em uma parcela, área de cobertura de floresta...), e cada nível pode ser descrito em diferentes escalas (resolução e extensão de descrição). Os níveis e escalas com maior poder de previsão da ocorrência/abundância de uma espécie são chamados de nível de efeito e escala (extensão) de efeito. Nesta tese, utilizo armadilhas fotográficas e modelos hierárquicos para avaliar relações entre a paisagem e espécies de mamíferos e aves. Meus objetivos são: (1) avaliar se existe relação entre nível e extensão de efeito para prever a abundância de espécies e a área de vida ou massa das mesmas; (2) investigar características do solo que possam ser determinantes da distribuição de mamíferos e aves que consumem solo (geofagia); e (3) a partir de ralações espécie-paisagem, estimar a distribuição da densidade de uma espécie, o veado-catingueiro, para diferentes datas. Não há suporte para que a área de vida ou a massa de uma espécie sejam relevantes para o nível ou extensão em que uma paisagem deva ser descrita a fim de prever a abundância de uma espécie. Isso implica na importância de se avaliar diferentes níveis e extensões de uma paisagem quando na busca por relações espécie-paisagem. Fatores locais, como a argila ou minerais do solo, podem ser importantes para algumas espécies. Descobri que o veado-mateiro e o caititu selecionam solos para consumo com base na quantidade e tipo de argila. O caititu também seleciona solos com base na concentração de microminerais, assim como a juriti-azul, a arara-azul-grande, o mutum, o aracuã e a pomba-galega. Uma descrição da paisagem em nível de composição do solo pode ser relevante para avaliar a distribuição destas e outras espécies. Relações espécie-paisagem podem ser usadas para prever a abundância de espécies no espaço. Estimei a densidade do veado-catingueiro em 1992 (2,07 ind/km2) e em 2011 (7,31 ind/km2), para uma região de pecuária extensiva no nordeste do Pantanal onde foi criada uma reserva em 1997. A densidade desta espécie aumentou 3,5 vezes entre 1992 e 2011, com o fim da pecuária no local. Investigações multinível e multiescala de relações espécie-paisagem ainda são incipientes, embora importantes aplicações destas relações já venham sendo feitas há décadas.
The relationship between the landscape and the distribution of species’ occurrence and abundance is one of the main questions in ecology, with important applications for the current period of intense land use and climate change. However, to infer about these relationships, we have to describe the landscape as closely as possible to how species actually realize it. We can describe landscapes at different hierarchical levels of the environment (e.g. mineral amount in soil, number of plants in a plot, forest cover area…), and each level can be described at different scales (resolution and extent). The best levels and scales to predict species’ occurrence/abundance are known as level of effect and scale (extent) of effect. In this PhD thesis, I use camera traps and hierarchical models to assess relationships between the landscape and mammals or birds. My goals are: (1) to evaluate possible relationships between the level and extent of effect to predict species’ abundance and species’ home range or mass; (2) to investigate soil features important to the distribution of mammals and birds engaged on geophagy (soil consumption); and (3) from species-landscape relations, to estimate the density of a species, the Gray Brocket in space for different dates. There is no support for species’ home range or mass as relevant traits related to the level and scale that a landscape should be described in order to predict species’ abundance. This highlight the importance of evaluating different levels and scales of a landscape when searching for species-landscape relationships. Local factors such as clay or minerals may be important for some species. I found that the Red Brocket and Collared Peccary select soils for consumption based on clay amount and type. The Collared Peccary also selects soil based on the concentration of trace minerals, as well as Blue Ground-dove, Hyacinth Macaw, Bare-faced Curassow, Chaco Chachalaca, and Pale-vented Pigeon. Describing the landscape at soil composition level may be important to evaluate the distribution of these and another species. Species-landscape relationships can be used to predict the abundance of species in space at different dates. I estimated the density of the Gray Brocket in 1992 (2.07 ind/km2) and 2011 (7.31 ind/km2), in a livestock region in northeastern Brazilian Pantanal where a reserve was established in 1997. Gray Brocket density increased 3.5 times between 1992 and 2011, after livestock ban. Multi-level and multi-scale approaches to investigate species-landscape relationships are still emerging, though important applications of such relationships have been done for decades.

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Dissertations / Theses on the topic 'Joint species distribution models'

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