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Academic literature on the topic 'Habitat suitability model'

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Published: 4 June 2021
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Journal articles on the topic "Habitat suitability model"

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Rew, Jehyeok, Yongjang Cho, Jihoon Moon, and Eenjun Hwang. "Habitat Suitability Estimation Using a Two-Stage Ensemble Approach." Remote Sensing 12, no. 9 (May 6, 2020): 1475. http://dx.doi.org/10.3390/rs12091475.

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Biodiversity conservation is important for the protection of ecosystems. One key task for sustainable biodiversity conservation is to effectively preserve species’ habitats. However, for various reasons, many of these habitats have been reduced or destroyed in recent decades. To deal with this problem, it is necessary to effectively identify potential habitats based on habitat suitability analysis and preserve them. Various techniques for habitat suitability estimation have been proposed to date, but they have had limited success due to limitations in the data and models used. In this paper, we propose a novel scheme for assessing habitat suitability based on a two-stage ensemble approach. In the first stage, we construct a deep neural network (DNN) model to predict habitat suitability based on observations and environmental data. In the second stage, we develop an ensemble model using various habitat suitability estimation methods based on observations, environmental data, and the results of the DNN from the first stage. For reliable estimation of habitat suitability, we utilize various crowdsourced databases. Using observational and environmental data for four amphibian species and seven bird species in South Korea, we demonstrate that our scheme provides a more accurate estimation of habitat suitability compared to previous other approaches. For instance, our scheme achieves a true skill statistic (TSS) score of 0.886, which is higher than other approaches (TSS = 0.725 ± 0.010).
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Hightower, Joseph E., Julianne E. Harris, Joshua K. Raabe, Prescott Brownell, and C. Ashton Drew. "A Bayesian Spawning Habitat Suitability Model for American Shad in Southeastern United States Rivers." Journal of Fish and Wildlife Management 3, no. 2 (December 1, 2012): 184–98. http://dx.doi.org/10.3996/082011-jfwm-047.

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Abstract Habitat suitability index models for American shad Alosa sapidissima were developed by Stier and Crance in 1985. These models, which were based on a combination of published information and expert opinion, are often used to make decisions about hydropower dam operations and fish passage. The purpose of this study was to develop updated habitat suitability index models for spawning American shad in the southeastern United States, building on the many field and laboratory studies completed since 1985. We surveyed biologists who had knowledge about American shad spawning grounds, assembled a panel of experts to discuss important habitat variables, and used raw data from published and unpublished studies to develop new habitat suitability curves. The updated curves are based on resource selection functions, which can model habitat selectivity based on use and availability of particular habitats. Using field data collected in eight rivers from Virginia to Florida (Mattaponi, Pamunkey, Roanoke, Tar, Neuse, Cape Fear, Pee Dee, St. Johns), we obtained new curves for temperature, current velocity, and depth that were generally similar to the original models. Our new suitability function for substrate was also similar to the original pattern, except that sand (optimal in the original model) has a very low estimated suitability. The Bayesian approach that we used to develop habitat suitability curves provides an objective framework for updating the model as new studies are completed and for testing the model's applicability in other parts of the species' range.
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McLeod, S. R., and A. R. Pople. "Modelling the distribution and relative abundance of feral camels in the Northern Territory using count data." Rangeland Journal 32, no. 1 (2010): 21. http://dx.doi.org/10.1071/rj09057.

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The objectives of this study were to predict the potential distribution, relative abundance and probability of habitat use by feral camels in southern Northern Territory. Aerial survey data were used to model habitat association. The characteristics of ‘used’ (where camels were observed) v. ‘unused’ (pseudo-absence) sites were compared. Habitat association and abundance were modelled using generalised additive model (GAM) methods. The models predicted habitat suitability and the relative abundance of camels in southern Northern Territory. The habitat suitability maps derived in the present study indicate that camels have suitable habitat in most areas of southern Northern Territory. The index of abundance model identified areas of relatively high camel abundance. Identifying preferred habitats and areas of high abundance can help focus control efforts.
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Aryanti, Nirmala Ayu, Tander Scila Serata Dwi Susilo, Ari Nadya Ningtyas, and Mahmuddin Rahmadana. "Pemodelan Spasial Kesesuaian Habitat Elang Jawa (Nisaetus bartelsi) di Taman Nasional Bromo Tengger Semeru (Spatial Modeling of Javan Hawk-Eagle (Nisaetus bartelsi) Habitat Suitability in Bromo Tengger Semeru National Park)." Jurnal Sylva Lestari 9, no. 1 (January 29, 2021): 179. http://dx.doi.org/10.23960/jsl19179-189.

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Bromo Tengger Semeru National Park (TNBTS) is a conservation area as the habitat of endemic species in Java Island, such as the Javan hawk-eagle (Nisaetus bartelsi). One of the spatial models of habitat is the Ecological Niche Modeling (ENM) approach. This study aimed to determine habitat suitability for the Javan hawk-eagle in TNBTS. The research was conducted from September 2019 to January 2020. The habitat suitability model used the present coordinate point data and the Javan hawk-eagle habitat environment variables. The data were then analyzed to build a Javan hawk-eagle habitat suitability model using the Maximum Entropy (MaxEnt) algorithm. The results showed three models of habitat suitability categories, i.e.: high of 15,131.18 ha (30%), medium 11,216.61 ha (22%), and low 23,298.41 ha (48%). The evaluation of the Javan hawk-eagle habitat suitability model in TNBTS has an excellent model accuracy with an AUC value of 0.97 and a standard deviation of 0.93.Keywords: endemic, habitat, Javan hawk-eagle, maximum entropy, spatial modeling
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Jeong, Seunggyu, Changwan Seo, Jaehyun Yoon, Dong Kun Lee, and Jonghoon Park. "A Study on Riparian Habitats for Amphibians Using Habitat Suitability Model." Journal of Environmental Impact Assessment 24, no. 2 (April 30, 2015): 175–89. http://dx.doi.org/10.14249/eia.2015.24.2.175.

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Li, Jie, Hui Qin, Shaoqian Pei, Liqiang Yao, Wei Wen, Liang Yi, Jianzhong Zhou, and Lingyun Tang. "Analysis of an Ecological Flow Regime during the Ctenopharyngodon Idella Spawning Period Based on Reservoir Operations." Water 11, no. 10 (September 29, 2019): 2034. http://dx.doi.org/10.3390/w11102034.

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The study of fish habitats is important for us to better understand the impact of reservoir construction on river ecosystems. Many habitat models have been developed in the past few decades. In this study, a fuzzy logic-based habitat model, which couples fuzzy inference system, two-dimensional laterally averaged hydrodynamic model, and two-dimensional shallow water hydrodynamic model, is proposed to identify the baseline condition of suitable habitat for fish spawning activities. The proposed model considers the reservoir and the downstream river channel, and explores the comprehensive effects of water temperature, velocity, and water depth on habitat suitability. A real-world case that considers the Ctenopharyngodon idella in the Xuanwei Reservoir of Qingshui River is studied to investigate the effect of in- and outflow of reservoir on fish habitat and the best integrative management measure of the model. There were 64 simulations with different reservoir in- and outflows employed to calculate the weighted usable area and hydraulic habitat suitability. The experimental results show that the ecological flow for Ctenopharyngodon idella spawning can satisfy the basic demand when the reservoir inflow is greater than 60 m3/s and the reservoir outflow is greater than 100 m3/s. The habitat ecological suitability is the best when the reservoir outflow is 120 m3/s. A more reasonable and reliable ecological flow range can be obtained based on the habitat model in this paper, which provides the best scenario for water resources planning and management in the Qingshui River Basin.
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Ouellet, Valerie, André St-Hilaire, Yves Secretan, Marc Mingelbier, Jean Morin, and Stephen J. Dugdale. "The Importance of Including Water Temperature Simulations in a 2D Fish Habitat Model for the St. Lawrence River." Water 13, no. 13 (June 23, 2021): 1736. http://dx.doi.org/10.3390/w13131736.

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Extreme climatic conditions likely caused a massive fish mortality during the summer of 2001 in the St. Lawrence River. To corroborate this hypothesis, we used a physical habitat simulation approach incorporating hydraulic and water temperature models. Spawning Habitat Suitability Indices (HSI) for common carp (Cyprinus carpio) were developed using fuzzy logic and applied to the model outputs to estimate habitat weighted usable area during the event. The results revealed that areas suitable for common carp spawning (HSI > 0.3) were severely reduced by high water temperatures, which exceeded 28 °C during the mortality event. During the mortality event, the amount of suitable habitat was reduced to <200 ha/day, representing less than 15% of the maximum potential suitable habitat in the study reach. In addition, the availability of cooler habitats that could have been used as thermal refuges was also reduced. These results indicate that the high water temperature in spawning areas and reduced accessibility to thermal refuge habitats exposed the carp to substantial physiological and environmental stress. The high water temperatures were highly detrimental to the fish and eventually led to the observed mortalities. This study demonstrates the importance of including water temperature in habitat suitability models.
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Shiroyama, Risa, Manna Wang, and Chihiro Yoshimura. "Effect of sample size on habitat suitability estimation using random forests: a case of bluegill, Lepomis macrochirus." Annales de Limnologie - International Journal of Limnology 56 (2020): 13. http://dx.doi.org/10.1051/limn/2020010.

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Species distribution models (SDMs) have been used to understand the habitat suitability of key species. Habitat suitability plots, one outcome from SDMs, are valuable for understanding the habitat suitability and behavior of organisms. The sample size is often constrained by budget and time, and could largely influence the reliability of habitat suitability plots. To understand the effect of sample size on habitat suitability plots, the present study utilized random forests (RF) combined with partial dependence function. And the bluegill (Lepomis macrochirus), a main exotic fish species in the Japan rivers, was selected as target species in this study. Total of 1010 samples of bluegill observations along with four environmental variables were surveyed by the National Censuses on River Environments. The area under curves was calculated after generating RF models, to assess the predictive model performance, and this process was repeated 1000 times. To draw habitat suitability plots, we applied partial dependence function to the formulated RF models, and 15 different sample sizes were set to examine the effect on habitat suitability plots. We concluded that habitat suitability plots are affected by sample size and prediction performance. Notably, habitat suitability plots drawn from the sample size of 50 greatly varied among the 1000-time iterations, and they are all different from the observations. Furthermore, to deal with the case of limited samples, we proposed a novel approach “averaged habitat suitability plot” for delineating habitat suitability plots. The proposed approach enables us to assess the habitat suitability even with a small sample size.
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Adamczyk, Mikołaj, Piotr Parasiewicz, Paolo Vezza, Paweł Prus, and Giovanni De Cesare. "Empirical Validation of MesoHABSIM Models Developed with Different Habitat Suitability Criteria for Bullhead Cottus Gobio L. as an Indicator Species." Water 11, no. 4 (April 8, 2019): 726. http://dx.doi.org/10.3390/w11040726.

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Application of instream habitat models such as the Mesohabitat Simulation Model (MesoHABSIM) is becoming increasingly popular. Such models can predict alteration to a river physical habitat caused by hydropower operation or river training. They are a tool for water management planning, especially in terms of requirements of the Water Framework Directive. Therefore, model verification studies, which investigate the accuracy and reliability of the results generated, are essential. An electrofishing survey was conducted in September 2014 on the Stura di Demonte River located in north-western Italy. One hundred and sixteen bullhead—Cottus gobio L.—were captured in 80 pre-exposed area electrofishing (PAE) grids. Observations of bullhead distribution in various habitats were used to validate MesoHABSIM model predictions created with inductive and deductive habitat suitability indices. The inductive statistical models used electrofishing data obtained from multiple mountainous streams, analyzed with logistic regression. The deductive approach was based on conditional habitat suitability criteria (CHSC) derived from expert knowledge and information gathered from the literature about species behaviour and habitat use. The results of model comparison and validation show that although the inductive models are more precise and reflect site- and species-specific characteristics, the CHSC model provides quite similar results. We propose to use inductive models for detailed planning of measures that could potentially impair riverine ecosystems at a local scale, since the CHSC model provides general information about habitat suitability and use of such models is advised in pre-development or generic scale studies. However, the CHSC model can be further calibrated with localized electrofishing data at a lower cost than development of an inductive model.
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SASS, EMMA M., JENNIFER L. MORTENSEN, and J. MICHAEL REED. "Habitat suitability models indicate the White-breasted Thrasher Ramphocinclus brachyurus occupies all suitable habitat in Saint Lucia." Bird Conservation International 27, no. 1 (May 23, 2016): 96–110. http://dx.doi.org/10.1017/s0959270915000374.

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SummaryHabitat suitability models can guide species conservation by identifying correlates of occurrence and predicting where species are likely to occur. We created habitat suitability models for the White-breasted Thrasher Ramphocinclus brachyurus, a narrowly distributed endangered songbird that occupies dry forest in Saint Lucia and Martinique. Eighty-five percent of the global population inhabits two ranges in Saint Lucia, both of which are largely unprotected and threatened by development. We developed three habitat suitability models using Maxent techniques and published occupancy datasets collected from the species’ two Saint Lucian ranges, and used abiotic, land cover, and predator distribution predictors. We built one model with occupancy data from both ranges, and two others with occupancy data specific to each range. The best full-range model included 11 predictors; high suitability was associated with close proximity to Saint Lucia fer-de-lance Bothrops caribbeaus range, moderately low precipitation, and areas near streams. Our assessment of suitable sites island-wide was more restricted than results from a recent model that considered older land cover data and omitted predator distributions. All sites identified in our full-range model as highly suitable were in or adjacent to the species’ current designated range. The model trained on southern range occurrences predicted zero suitable habitat in the northern range, where the population is much smaller. In contrast, the model trained on northern range occurrences identified areas of moderate suitability within the southern range and patches of moderately suitable habitat in the western part of the island, where no White-breasted Thrashers currently occur. We interpret these results as suggesting that White-breasted Thrashers currently occupy virtually all suitable habitat on the island, that birds in the northern range occupy marginal habitat, or that an important correlate of suitability is missing from the model. Our results suggest that habitat management should focus on currently occupied areas.
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Dissertations / Theses on the topic "Habitat suitability model"

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Johansson, Maya. "Modelling habitat suitability index for golden eagle." Thesis, Stockholms universitet, Institutionen för naturgeografi, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-197086.

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The aim in this study was to develop a model for the probability of finding active golden eagle nests during their breeding season. It was done by using environmental variables derived from expert models which were tested against empirical data. This resulted in a habitat suitability index (HSI), which in this case is assumed to indicate the probability of active nests of golden eagles. The study was conducted together with the County Administrative Board of Västernorrland with the purpose to improve golden eagle’s ecological status.To develop the model, different combinations of several explanatory variables were tested in a model selection process, where the most optimal and parsimonious model was chosen. The tested variables have earlier been shown to affect golden eagles, as slope, aspect, forest age, foraging habitat, suitable flight routes, human population density, roads, railways, power lines, wind power plants, hiking trails and clear cuts. The variables where applied in in ArcMAP at three different scales: nest scale (25 x 25 meter), proximate scale (a circle with the radius of 500 meter) and home range scale (a circle with the radius of 8253 meter). A preliminary test of the variables showed that all golden eagle nests were found in slopes with at least 5֯ degreesas well as in home ranges with human population density not more than 8 people/km2. Due to that a stratified analysis wasperformed. The variables where analysed by multiple logistic regression in R, where the occurrence of golden eagles’ nestswas compared towards random points in the landscape. All variables were also tested one by one by logistic regression. Afterperforming the multiple logistic regression, it was possible to apply its equation into ArcMap to obtain suitability maps withHSI values over Västernorrland’s county.The comparisons of different models show that it is better to combine different spatial scales in the model than only using one spatial scale. The result indicate that three different models might be the best, which all had different combinations of slope and aspect at nest scale and power lines at the proximate scale. Two of these models also include hiking trails and human population density, both at home range scale, in their equation. Since it was some unclarity about the causality between hiking trails and human population density, the conclusion was not to choose any of these as the final model. The final model was more parsimonious and had an additive effect from slope and southern aspect at the nest scale and an antagonistic effect from power lines at the proximate scale.This study clarifies that golden eagles’ habitat preferences for nesting sites during their breeding period is steep slopes (at minimum 5֯ degrees) in more southern aspects with few power lines in the proximate area surrounding the nest. Their homeranges are also situated in areas with less than 8 people/km2. The study also pinpoints a potential conflict between golden eagleand wind power planning, as golden eagles prefer steep slopes and remote areas, which also are valuable areas for wind powerplants. Golden eagles’ preference of remote areas also indicate that they might be affected by human persecution, why certainconservation effort should be focused into this issue. Out from the final model, you can find cluster in the landscape where youcan focus conservation management and restrict exploitation. Due to low number of wind power plants in the landscape, nothingcould be concluded about their effect on golden eagle in this study. An advice from the golden eagle’s perspective is to use theprecautionary principle and further plan wind power plants in areas which already have high disturbance, as for example closeto power lines or roads. The result also indicates that forest age from SLU Forest Map is not suitable for telling where to findgolden eagle nests. GIS-data over forest age would facilitate conservation management for plenty of species connected to theforest.Although good statistical results for the final model, cautions need to be taken in general, since neither population viability analysis have been included, nor changes over time in the landscape. Another issue is the low sample size, where a larger sample size would make it possible to perform profound calibration and validation of the data. To develop a more robust model, the advice is to include these into the model and use a larger sample size.
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Kearns, Amy E. "Verifying Manitoba's 1994 draft barred owl habitat suitability index model." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp01/MQ41660.pdf.

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Dine, James. "A habitat suitability model for Ricord's iguana in the Dominican Republic." Connect to resource online, 2009. http://hdl.handle.net/1805/1889.

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Thesis (M.S.)--Indiana University, 2009.
Title from screen (viewed on August 27, 2009). Department of Geography, Indiana University-Purdue University Indianapolis (IUPUI). Advisor(s): Jan Ramer, Aniruddha Banergee, Jeffery Wilson. Includes vita. Includes bibliographical references (leaves 47-52).
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Burroughs, Virginia. "An Assessment of Habitat Suitability for Pronghorn Populations of the Central Valley Region of California." DigitalCommons@CalPoly, 2013. https://digitalcommons.calpoly.edu/theses/1142.

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Efforts to reintroduce and maintain populations of pronghorn (Antilocapra americana) to the California Central Valley, specifically the Carrizo Plain National Monument (CPNM) and the Mojave Desert (Antelope Valley) portion of Tejon Ranch, have largely been unsuccessful due to dwindling numbers of translocated animals. The objective of this study was to improve upon previous models for the CPNM using aerial survey data and then apply the model to the Tejon Ranch. Aerial survey data collected from 2000-2010 on the CPNM was used to establish “use” and “non-use” areas in the model. Model variables included vegetation type (forest, shrub, grassland, semi-desert scrub, crops, and bare areas), slope, and road density. Vegetation and road density variables were treated categorically and slope as a continuous variable. Kernel density estimation (KDE) was used to estimate utilization distributions and home ranges (Fieberg 2007). An 80% isopleth was used to define “used” and “unused” habitat areas within the study site. Binary logistic regression was used to detect correlations between habitat variables and habitat use by pronghorn. Results of the regression analysis indicated overall significance with a p-value of < 0.0001 (testing that all slopes = 0). Each habitat variable comparison was made after adjusting for the other variables (e.g., slope effects were evaluated after adjusting for road density and vegetation type) and was found to be significant. Each variable coefficient was then included in a predictive equation and entered into GIS to generate a map to predict where pronghorn would likely be observed. Similar layers were created for the Tejon Ranch and the predictive equation was run with the CPNM statistical analysis. Limited conclusions about habitat suitability on the CPNM or the Tejon Ranch can be made based on the habitat data available for this model. While slope, road density, and vegetation type are all significant habitat variables influencing pronghorn habitat use, further study is needed to understand the mechanisms driving these relationships. With additional data expansion of the current habitat suitability model would help to further define pronghorn habitat use, specifically the creation of a focused model of a particular season, life history period, or individual animal use to identify more detailed habitat use patterns.
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Gallien, Laure. "Comprendre et prédire l'expansion géographique des espèces végétales invasives dans les Alpes." Thesis, Grenoble, 2013. http://www.theses.fr/2013GRENV062/document.

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Les invasions biologiques, deuxième menace majeure de la biodiversité, pose d'important défis pour la conservation de la biodiversité, et la recherche en éco-évolution. Les espèces invasives ont en effet été étudiées depuis plus de 150 ans, mais nos capacités à prédire leurs présences aujourd'hui et dans le futur reste rudimentaire. Ce problème est principalement dû à la difficulté d'estimer à la fois les composantes biotiques et abiotiques de la niche des espèces invasives, ainsi que leur évolution dans le temps et l'espace. L'objectif de ma thèse a été de travailler sur ces défis en améliorant les méthodes d'estimation de niche, en enrichissant notre compréhension du rôle des interactions biotiques dans le processus d'invasion, et en étudiant en détail comment les processus évolutifs peuvent affecter la dynamique spatio-temporelle des niches. Plus précisément, (1) à l'aide d'une revue de la littérature, j'ai commencé par décrire les limites des différentes approches de modélisation utilisées pour prédire la distribution des espèces invasives. (2) Ensuite, j'ai proposé un cadre de modélisation permettant d'améliorer l'estimation des niches abiotiques régionales. (3) Puis, je me suis intéressée à la caractérisation des interactions biotiques, et aux méthodes communément utilisées pour identifier les patrons de compétition symétrique en écologie des communautés. J'ai également implémenté un modèle de simulation d'assemblage de communautés pour tester la performance de ces méthodes. (4) Ces premières études m'ont permis d'étudier à la fois les composantes biotiques et abiotiques des communautés de plantes envahies dans les Alpes. (5) Finalement, j'ai étudié l'évolution de la niche environnementale chez une espèce invasive des Alpes françaises Ambrosia artemisiifolia L, à travers une approche reliant niche-trait-génétique. Dans l'ensemble, les résultats de ces études montrent à quel point les différentes facettes de l'écologie et l'évolution en invasion sont fortement intriquées. De plus, ils soulignent la nécessité d'une modélisation intégrant les processus écologiques et évolutifs pour pouvoir comprendre la dynamique des invasions et proposer des outils de protection de la biodiversité efficaces
Biological invasions, the second major threat to biodiversity, pose significant challenges to conservation management and eco-evolutionary research. Even though invasion processes have been studied for more than 150 years, our capacity to predict their presence today and in the future is still rudimentary. This deficiency stems mainly from the difficulty involved in reliably assessing the ecological niche of an invader, i.e. those environmental and biotic conditions that allow the species to maintain viable populations. In particular, disentangling the abiotic and biotic components of the ecological niche and accounting for their changing over space and time due to evolutionary dynamics is difficult, albeit crucial for the quality of predictions. The main objective of my PhD has been to address these challenges by improving methodological approaches of niche estimation, advancing our understanding of the role of biotic interactions for invasion processes and studying in greater detail how evolution may affect spatio-temporal niche dynamics. More precisely, (1) with a comprehensive literature review, I started by describing the limits of the different modelling approaches usually applied to predict invasive species distributions. (2) Then, I provided a modelling framework for improving regional environmental niche estimations. (3) Thirdly, I focused on the identification of biotic interactions, and the methods commonly used to identify patterns of symmetric competition in ecological communities. I also implemented a simulation model of community assembly to test the efficiency of these methods. (4) In a fourth part, I studied invaded alpine plant communities and showed that characteristics of the biotic environment in these communities (e.g. symmetric vs. asymmetric competition) were good predictors of invaders' presence. (5) Finally, I provided a first example of a genetic-based, climatic niche expansion of the invasive weed Ambrosia artemisiifolia L. in the French Alps by combining information on its environmental niche, genetic structure and functional traits. Taken together, the results of these studies highlight how tightly the different facets of invasion ecology and evolution are interrelated and open the way to an integrated modelling approach that would advance both eco-evolutionary research on invasion dynamics and applied tools for biodiversity protection
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Thomasson, Victor. "Habitat Suitability Modeling for the Eastern Hog-nosed Snake, 'Heterodon platirhinos', in Ontario." Thèse, Université d'Ottawa / University of Ottawa, 2012. http://hdl.handle.net/10393/23322.

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With exploding human populations and landscapes that are changing, an increasing number of wildlife species are brought to the brink of extinction. In Canada, the eastern hog-nosed snake, 'Heterodon platirhinos', is found in a limited portion of southern Ontario. Designated as threatened by the Committee on the Status of Endangered Wildlife in Canada (COSEWIC), this reptile has been losing its habitat at an alarming rate. Due to the increase in development of southern Ontario, it is crucial to document what limits the snake’s habitat to direct conservation efforts better, for the long-term survival of this species. The goals of this study are: 1) to examine what environmental parameters are linked to the presence of the species at a landscape scale; 2) to predict where the snakes can be found in Ontario through GIS-based habitat suitability models (HSMs); and 3) to assess the role of biotic interactions in HSMs. Three models with high predictive power were employed: Maxent, Boosted Regression Trees (BRTs), and the Genetic Algorithm for Rule-set Production (GARP). Habitat suitability maps were constructed for the eastern hog-nosed snake for its entire Canadian distribution and models were validated with both threshold dependent and independent metrics. Maxent and BRT performed better than GARP and all models predict fewer areas of high suitability when landscape variables are used with current occurrences. Forest density and maximum temperature during the active season were the two variables that contributed the most to models predicting the current distribution of the species. Biotic variables increased the performance of models not by representing a limiting resource, but by representing the inequality of sampling and areas where forest remains. Although habitat suitability models rely on many assumptions, they remain useful in the fields of conservation and landscape management. In addition to help identify critical habitat, HSMs may be used as a tool to better manage land to allow for the survival of species at risk.
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Alizadeh, Shabani Afshin, and afshin alizadeh@rmit edu au. "Identifying bird species as biodiversity indicators for terrestrial ecosystem management." RMIT University. Mathematical and Geospatial Sciences, 2006. http://adt.lib.rmit.edu.au/adt/public/adt-VIT20061116.161912.

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It is widely known that the world is losing biodiversity and primarily it is thought to be caused by anthropogenic activities. Many of these activities have been identified. However, we still lack a clear understanding of the causal relationships between human activities and the pressures they place on the environment and biodiversity. We need to know how ecosystems and individual species respond to changes in human activities and therefore how best to moderate our actions and reduce the rate of loss of biodiversity. One of the ways to detect these changes is to use indicators of ecosystem conditions. Indicators are statistics following changes in a particular factor usually over time. These indicators are used to summarise a complex set of data, and are seen as being representative of the wider situation in that field. So it can be assumed that if that particular factor is declining or improving, then the situation in general is also declining or improving. They are used to check the status and trends of biodiversity by both the public and policy makers. Indicators are also used to assess national performance and can be used to identify the actions required at the policy level. In this manner, they provide an important link between policy-makers and scientists collecting the data. The current thesis investigates the possibility of using bird species as indicators of biodiversity for better management of natural terrestrial ecosystems, by identifying their habitats according to various environmental factors. The study is established by drawing upon three main scientific areas: ecology, geographical information system (GIS), and statistical modelling. The Mornington Peninsula and Western Port Biosphere Reserve (MPWPBR) (Victoria, Australia) was chosen for the study area because of the combination of suburban and natural environments that made it optimum for this type of study. Once the study area was defined, the necessary data for the research were obtained from various sources. Birds Australia provided data on recorded observation of 271 bird species within the study area. Based on the nature of this study, seven species were selected for the study. The criteria for this selection are discussed in Chapter 3. Most literature state that the primary determinant for bird abundance is vegetation and land cover. Because of this, Ecological Vegetation Class (EVC) layer was used to determine which type(s) of vegetation have the greatest impact on habitat selection. Each species showed a relationship to a number of v vegetation types. These EVCs were combined to produce vegetation patches, and were considered as potentially suitable habitats of corresponding bird species. For each of the species, these habitat patches were analysed for the different aspects of patch characteristics (such as the level of patchiness, connectivity, size, shape, weighted distance between patches, etc.) by using the Landscape Context Tool (a GIS add-on). This process assisted the understanding of the importance of patch quality in habitat selection among different bird species by analysing the location of bird observation sites relative to habitat patches. In this way, the association between bird presence and the conditions of a habitat patch was identified by performing a discriminant function analysis. To investigate the probability of a species presence according to different environmental factors, a model of species distribution was created. Binary logistic regression was used to indicate the level of effect of each variable. The model was then successfully validated in the field. To define the indicators of environmental factors, it was essential to separate bird species based on their dependency on one or more of the studied variables. For this purpose, One-Way ANOVA was used. This analysis showed that some bird species can be considered as indicators of urban areas, while others could be good indicators of wellpreserved large forests. Finally, it must be mentioned that the type and quality of the datasets are crucial to this type of study, because some species have a higher degree of sensitivity to certain types of vegetation or land cover. Therefore, the vegetation data must be produced as detailed as possible. At the same time, the species data needs to be collected based on the presence and absence (versus presence-only) of the birds.
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Correa-Berger, Bryan P. "Developing a habitat suitability model for the spotted turtle using a hybrid-deductive approach /." Online version of thesis, 2007. http://hdl.handle.net/1850/4494.

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O'Leary, Rebecca A. "Informed statistical modelling of habitat suitability for rare and threatened species." Queensland University of Technology, 2008. http://eprints.qut.edu.au/17779/.

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In this thesis a number of statistical methods have been developed and applied to habitat suitability modelling for rare and threatened species. Data available on these species are typically limited. Therefore, developing these models from these data can be problematic and may produce prediction biases. To address these problems there are three aims of this thesis. The _rst aim is to develop and implement frequentist and Bayesian statistical modelling approaches for these types of data. The second aim is develop and implement expert elicitation methods. The third aim is to apply these novel approaches to Australian rare and threatened species case studies with the intention of habitat suitability modelling. The _rst aim is ful_lled by investigating two innovative approaches for habitat suitability modelling and sensitivity analysis of the second approach to priors. The _rst approach is a new multilevel framework developed to model the species distribution at multiple scales and identify excess zeros (absences outside the species range). Applying a statistical modelling approach to the identi_cation of excess zeros has not previously been conducted. The second approach is an extension and application of Bayesian classi_cation trees to modelling the habitat suitability of a threatened species. This is the _rst `real' application of this approach in ecology. Lastly, sensitivity analysis of the priors in Bayesian classi_cation trees are examined for a real case study. Previously, sensitivity analysis of this approach to priors has not been examined. To address the second aim, expert elicitation methods are developed, extended and compared in this thesis. In particular, one elicitation approach is extended from previous research, there is a comparison of three elicitation methods, and one new elicitation approach is proposed. These approaches are illustrated for habitat suitability modelling of a rare species and the opinions of one or two experts are elicited. The _rst approach utilises a simple questionnaire, in which expert opinion is elicited on whether increasing values of a covariate either increases, decreases or does not substantively impact on a response. This approach is extended to express this information as a mixture of three normally distributed prior distributions, which are then combined with available presence/absence data in a logistic regression. This is one of the _rst elicitation approaches within the habitat suitability modelling literature that is appropriate for experts with limited statistical knowledge and can be used to elicit information from single or multiple experts. Three relatively new approaches to eliciting expert knowledge in a form suitable for Bayesian logistic regression are compared, one of which is the questionnaire approach. Included in this comparison of three elicitation methods are a summary of the advantages and disadvantages of these three methods, the results from elicitations and comparison of the prior and posterior distributions. An expert elicitation approach is developed for classi_cation trees, in which the size and structure of the tree is elicited. There have been numerous elicitation approaches proposed for logistic regression, however no approaches have been suggested for classi_cation trees. The last aim of this thesis is addressed in all chapters, since the statistical approaches proposed and extended in this thesis have been applied to real case studies. Two case studies have been examined in this thesis. The _rst is the rare native Australian thistle (Stemmacantha australis), in which the dataset contains a large number of absences distributed over the majority of Queensland, and a small number of presence sites that are only within South-East Queensland. This case study motivated the multilevel modelling framework. The second case study is the threatened Australian brush-tailed rock-wallaby (Petrogale penicillata). The application and sensitivity analysis of Bayesian classi_cation trees, and all expert elicitation approaches investigated in this thesis are applied to this case study. This work has several implications for conservation and management of rare and threatened species. Novel statistical approaches addressing the _rst aim provide extensions to currently existing methods, or propose a new approach, for identi _cation of current and potential habitat. We demonstrate that better model predictions can be achieved using each method, compared to standard techniques. Elicitation approaches addressing the second aim ensure expert knowledge in various forms can be harnessed for habitat modelling, a particular bene_t for rare and threatened species which typically have limited data. Throughout, innovations in statistical methodology are both motivated and illustrated via habitat modelling for two rare and threatened species: the native thistle Stemmacantha australis and the brush-tailed rock wallaby Petrogale penicillata.
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Uhmann, Tanys V. "The development of a habitat suitability index model for burrowing owls in southwestern Manitoba and southeastern Saskatchewan." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2001. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp05/MQ62861.pdf.

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Books on the topic "Habitat suitability model"

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Schroeder, Richard L. Tests of a habitat suitability model for black-capped chickadees. Washington, D.C: U.S. Dept. of the Interior, Fish and Wildlife Service, 1990.

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Schroeder, Richard L. Tests of a habitat suitability model for black-capped chickadees. Washington, D.C: U.S. Dept. of the Interior, Fish and Wildlife Service, 1990.

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Schmitt, Christopher J. Habitat suitability index model for brook trout in streams of the southern Blue Ridge province: Surrogate variables, model evaluation, and suggested improvements. Washington, D.C: U.S. Dept. of the Interior, Fish and Wildlife Service, 1993.

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Rumble, Mark A. Habitat capability model for birds wintering in the Black Hills, South Dakota. [Fort Collins, CO]: U.S. Dept. of Agriculture, Forest Service, Rocky Mountain Research Station, 1999.

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Rumble, Mark A. A different time and place test of ArcHSI: A spatially explicit habitat model for elk in the Black Hills. Fort Collins, CO: U.S. Dept. of Agriculture, Forest Service, Rocky Mountain Research Station, 2007.

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Stevens, Scott D. Habitat suitability index for the northern leopard frog in Alberta: Model derivation and validation. Edmonton: Alberta Sustainable Resource Development, Fish & Wildlife Division, Species At Risk, 2008.

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Stevens, A. F. Joy. A habitat suitability model for burrowing owls (Athene cunicularia) in Alberta: Methods and applications. Edmonton: Alberta Sustainable Resource Development, Fish & Wildlife Division, Species At Risk, 2010.

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Germaine, Stephen S. Screening model for determining likelihood of site occupancy by Oregon spotted frogs (Rana pretiosa) in Washington State. [Olympia, Wash.]: Washington State Dept. of Transportation, 2004.

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Naylor, Brian John. Validation of a habitat suitability index model for moose in the northern portion of the Great Lakes-St. Lawrence Forest Region of Ontario. North Bay, Ont: Central Ontario Forest Technology Development Unit, Ontario Ministry of Natural Resources, 1992.

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Peterson, Allen. Habitat suitability index models. Washington, DC: Fish and Wildlife Service, U.S. Dept. of the Interior, 1986.

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Book chapters on the topic "Habitat suitability model"

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Jain, Dhruv, G. Areendran, Krishna Raj, Varun Dutta Gupta, and Mehebub Sahana. "Comparison of AHP and Maxent Model for Assessing Habitat Suitability of Wild Dog (Cuon alpinus) in Pench Tiger Reserve, Madhya Pradesh." In Spatial Modeling in Forest Resources Management, 327–63. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-56542-8_14.

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Rittenhouse, Chadwick D., Stephen R. Shifley, William D. Dijak, Zhaofei Fan, Frank R. Thompson, Joshua J. Millspaugh, Judith A. Perez, and Cynthia M. Sandeno. "Application of Landscape and Habitat Suitability Models to Conservation: The Hoosier National Forest Land-management Plan." In Landscape Ecology in Forest Management and Conservation, 299–328. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-12754-0_13.

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Takyu, Masaaki, Hisashi Matsubayashi, Nobuhiko Wakamatsu, Etsuko Nakazono, Peter Lagan, and Kanehiro Kitayama. "Guidelines for Establishing Conservation Areas in Sustainable Forest Management: Developing Models to Understand Habitat Suitability for Orangutans." In Co-benefits of Sustainable Forestry, 113–28. Tokyo: Springer Japan, 2012. http://dx.doi.org/10.1007/978-4-431-54141-7_6.

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"Fish Habitat: Essential Fish Habitat and Rehabilitation." In Fish Habitat: Essential Fish Habitat and Rehabilitation, edited by Peter J. Rubec, Jennifer C. W. Bexley, Henry Norris, Michael S. Coyne, Mark E. Monaco, Steven G. Smith, and Jerald S. Ault. American Fisheries Society, 1999. http://dx.doi.org/10.47886/9781888569124.ch10.

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<em>Abstract.—</em> A need exists to scientifically determine optimal fish habitats to support decision making for management of essential fish habitat. Scientists have been collaborating to conduct habitat suitability index (HSI) modeling to spatially delineate fish habitats for estuarine fish and invertebrate species in Tampa Bay and Charlotte Harbor, Florida. Results from HSI modeling of juvenile spotted seatrout <em>Cynoscion nebulosus </em> in Charlotte Harbor are presented. Data obtained from 1989–1997 by fisheries-independent monitoring in the two estuaries were used along with environmental data from other sources. Standardized catch-per-unit-effort (catch rates) were calculated across gear types using fisheries-monitoring data from Charlotte Harbor and Tampa Bay. Suitability index functions were determined using three methods: (1) frequency of occurrence, (2) mean catch rates within ranges, and (3) smooth-mean catch rates determined by polynomial regression. Mean catch rates were estimated within biologically relevant ranges and, where sufficient data were available, for finer intervals across environmental gradients. Suitability index functions across environmental gradients were then derived by scaling catch rates. Gridded habitat layers for temperature, salinity, depth, and bottom type in Charlotte Harbor were also created using a geographic information system. Habitat suitability index modeling was conducted using the U.S. Fish and Wildlife Service geometric mean method linked to the ArcView Spatial Analyst module. The model integrated suitability indices associated with the habitat layers for Charlotte Harbor to create a map of the predicted distribution for juvenile spotted seatrout during the fall season. Suitability indices developed for Tampa Bay were used with Charlotte Harbor habitat layers to test transfer of the indices to another estuary. Predicted HSI maps depicted low to optimum habitat suitability zones in Charlotte Harbor. Model performance was evaluated by statistically comparing the relative ranking of mean catch rates with mean suitability indices for corresponding zones. Suitability indices obtained using polynomial regression methods yielded morereliable HSI maps for juvenile spotted seatrout than those derived using mean catch rates within biologically relevant ranges. The observed map, derived using smooth-mean suitability indices transferred from Tampa Bay, was not significantly different (Chi-square goodness-of-fit test) from the expected map derived using smooth-mean indices from Charlotte Harbor. Our modeling efforts using transferred indices indicate that it is possible to predict the geographic distributions of fish species by life stage in estuaries lacking fisheries monitoring.
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"Fish Habitat: Essential Fish Habitat and Rehabilitation." In Fish Habitat: Essential Fish Habitat and Rehabilitation, edited by Peter J. Rubec, Jennifer C. W. Bexley, Henry Norris, Michael S. Coyne, Mark E. Monaco, Steven G. Smith, and Jerald S. Ault. American Fisheries Society, 1999. http://dx.doi.org/10.47886/9781888569124.ch10.

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<em>Abstract.—</em> A need exists to scientifically determine optimal fish habitats to support decision making for management of essential fish habitat. Scientists have been collaborating to conduct habitat suitability index (HSI) modeling to spatially delineate fish habitats for estuarine fish and invertebrate species in Tampa Bay and Charlotte Harbor, Florida. Results from HSI modeling of juvenile spotted seatrout <em>Cynoscion nebulosus </em> in Charlotte Harbor are presented. Data obtained from 1989–1997 by fisheries-independent monitoring in the two estuaries were used along with environmental data from other sources. Standardized catch-per-unit-effort (catch rates) were calculated across gear types using fisheries-monitoring data from Charlotte Harbor and Tampa Bay. Suitability index functions were determined using three methods: (1) frequency of occurrence, (2) mean catch rates within ranges, and (3) smooth-mean catch rates determined by polynomial regression. Mean catch rates were estimated within biologically relevant ranges and, where sufficient data were available, for finer intervals across environmental gradients. Suitability index functions across environmental gradients were then derived by scaling catch rates. Gridded habitat layers for temperature, salinity, depth, and bottom type in Charlotte Harbor were also created using a geographic information system. Habitat suitability index modeling was conducted using the U.S. Fish and Wildlife Service geometric mean method linked to the ArcView Spatial Analyst module. The model integrated suitability indices associated with the habitat layers for Charlotte Harbor to create a map of the predicted distribution for juvenile spotted seatrout during the fall season. Suitability indices developed for Tampa Bay were used with Charlotte Harbor habitat layers to test transfer of the indices to another estuary. Predicted HSI maps depicted low to optimum habitat suitability zones in Charlotte Harbor. Model performance was evaluated by statistically comparing the relative ranking of mean catch rates with mean suitability indices for corresponding zones. Suitability indices obtained using polynomial regression methods yielded morereliable HSI maps for juvenile spotted seatrout than those derived using mean catch rates within biologically relevant ranges. The observed map, derived using smooth-mean suitability indices transferred from Tampa Bay, was not significantly different (Chi-square goodness-of-fit test) from the expected map derived using smooth-mean indices from Charlotte Harbor. Our modeling efforts using transferred indices indicate that it is possible to predict the geographic distributions of fish species by life stage in estuaries lacking fisheries monitoring.
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"Muskellunge Management: Fifty Years of Cooperation Among Anglers, Scientists, and Fisheries Biologists." In Muskellunge Management: Fifty Years of Cooperation Among Anglers, Scientists, and Fisheries Biologists, edited by John Paul Leblanc and Patricia Chow-Fraser. American Fisheries Society, 2017. http://dx.doi.org/10.47886/9781934874462.ch25.

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<em>Abstract</em>.—To support Georgian Bay’s self-sustaining Muskellunge <em>Esox masquinongy </em>fisheries, we developed two index of nursery habitat suitability (INHS) models that can be used to identify and monitor the quality of Muskellunge nursery habitats in coastal wetlands. The INHS models were based on habitat features found in wetlands with age-0 Muskellunge identified at two large embayments in northern Georgian Bay. One INHS model had five variables that included proportional abundance of Yellow Perch <em>Perca flavescens</em>, proportional abundance of cyprinids, fish species richness, the wetland’s substrate slope, and a metric related to macrophyte abundance. The other INHS model included only three variables from the five-variable INHS, omitting information on macrophyte and fish species richness. When they were applied to an independent data set, both INHS models successfully tracked deterioration in nursery suitability after 15 years of sustained low water levels in Georgian Bay, but the five-variable INHS had higher overall accuracy and showed stronger discrimination between sites with and without age-0 fish. We applied the three-variable model to classify coastal wetlands in other regions of Georgian Bay and obtained a false-negative rate less than 13%. We also obtained a higher false-positive rate with the three-variable model compared with the five-variable model (54% versus 31%) because it required a lower threshold to indicate suitability (0.6 versus 0.70, respectively). These INHS models should allow managers to screen for suitable nursery habitat near current spawning sites across Georgian Bay and allow managers to predict how changes in water-level regimes might affect the suitability of spatially explicit wetland units.
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"Challenges for Diadromous Fishes in a Dynamic Global Environment." In Challenges for Diadromous Fishes in a Dynamic Global Environment, edited by Ryan J. Woodland, David H. Secor, and Edwi n. J. Niklitschek. American Fisheries Society, 2009. http://dx.doi.org/10.47886/9781934874080.ch36.

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<em>Abstract</em>.-Diadromous species encounter highly variable water quality as they traverse freshwater, estuarine, and marine environments. The U.S. federally endangered shortnose sturgeon <em>Acipenser brevirostrum </em>is a diadromous estuarine resident species that relies heavily on tidal freshwater regions of estuaries as spawning, nursery, and foraging habitat. A recent recovery in abundance in the Hudson River shortnose sturgeon population coincided with an ecosystem shift in the tidal freshwater estuary from hypoxia to normoxia (dissolved oxygen > 4 mg/L) during the summer juvenile rearing period. Decades of persistent summertime hypoxia encompassing as much as 40% of shortnose sturgeon nursery habitat was followed by a sudden shift to normoxia (1970 to 1978) due to the U.S. Clean Water Act legislation. Here, we evaluate how past and present water quality in the tidal freshwater Hudson River affects nursery habitat suitability. Habitat suitability, as indexed by potential instantaneous growth rate, was estimated with an empirically derived bioenergetic growth model before (pre-1978: 20% and 40% dissolved oxygen [DO] saturation) and after (1988: 85% DO saturation) the shift in seasonal ecosystem oxygenation. Habitat suitability was then forecast in the context of regional climate change and potential zebra mussel <em>Dreissena polymorpha </em>oxygen demand. Results from this simulation study indicated that even moderate reductions in water quality can significantly lower habitat suitability, supporting the circumstantial association between improved water quality and shortnose sturgeon recovery. Although presently occurring at high abundance levels, Hudson River shortnose sturgeon in the future may encounter diminished nursery habitat due to warming temperatures and increased benthic oxygen demand by zebra mussels.
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Sinha, Suman. "Crisp and Fuzzy AHP in GIS-MCDA for Wildlife Habitat Suitability Analysis." In Advances in Environmental Engineering and Green Technologies, 1–23. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-5027-4.ch001.

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Geographic information system-based multi-criteria decision analysis (GIS-MCDA) is a process of decision making where geographical data and value judgments are integrated. Analytic hierarchy process (AHP) is a useful technique in MCDA for determining weights. This study focuses on the evaluation of GIS-MCDA using different uncertainty levels in AHP. Best suitable sites for tiger habitats are located and analyzed in Sariska Wildlife Reserve, India using crisp and fuzzy AHP in GIS-MCDA, and thereafter, an optimal habitat suitability model is proposed. The percentage deviation over the uncertainty levels ranges slightly over 5%. The relative difference between CAHP and FAHP is nearly 2.7%. Chi-square test reveals relationship between the degree of uncertainty and the difference between the maps. For real-world situations with increased variability, fuzzification is preferred and shows the best results. The worldwide declining status of the tigers is a serious threat to the overall biodiversity, and the methods adopted in this study thus target their conservation and management.
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Lu, B., Z. Wang, and A. Yi. "Habitat suitability index model of four major Chinese carp species in theYangtze River." In River Flow 2006. Taylor & Francis, 2006. http://dx.doi.org/10.1201/9781439833865.ch240.

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Ghanbarian, Gholamabbas, Mohammad Reza Raoufat, Hamid Reza Pourghasemi, and Roja Safaeian. "Habitat Suitability Mapping of Artemisia aucheri Boiss Based on the GLM Model in R." In Spatial Modeling in GIS and R for Earth and Environmental Sciences, 213–27. Elsevier, 2019. http://dx.doi.org/10.1016/b978-0-12-815226-3.00009-0.

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Conference papers on the topic "Habitat suitability model"

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Xiuhua Peng, Qing Wang, Yu Wang, and Zhi Li. "Discussion of Acipenser Sinensis habitat suitability index model." In 2011 Second International Conference on Mechanic Automation and Control Engineering (MACE). IEEE, 2011. http://dx.doi.org/10.1109/mace.2011.5988333.

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Igarashi, Hiromichi, Yoichi Ishikawa, Haruka Nishikawa, Norihisa Usui, Mitsuo Sakai, Sei-ichi Saitoh, and Yutaka Imamura. "Habitat suitability index Model for neon flying squid adding its stock effect." In 2016 Techno-Ocean (Techno-Ocean). IEEE, 2016. http://dx.doi.org/10.1109/techno-ocean.2016.7890696.

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Chen, Xiaoxiang, Lili Zou, and Ying He. "Suitability evaluation of habitat for ardeidae waterfowls based on logistic regression model." In 2013 Second International Conference on Agro-Geoinformatics. IEEE, 2013. http://dx.doi.org/10.1109/argo-geoinformatics.2013.6621921.

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Wang, Yuankun, and Ziqiang Xia. "Fuzzy Comprehensive Evaluation Model for Chinese Sturgeon Habitat Suitability in the Yangtze River." In 2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD). IEEE, 2008. http://dx.doi.org/10.1109/fskd.2008.224.

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Uenaka, Takashi, Naohisa Sakamoto, and Koji Koyamada. "Visual Analysis of Habitat Suitability Index Model for Predicting the Locations of Fishing Grounds." In 2014 IEEE Pacific Visualization Symposium (PacificVis). IEEE, 2014. http://dx.doi.org/10.1109/pacificvis.2014.33.

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"Development and evaluation of a spatially explicit habitat suitability model for River Red Gum on the Murray River using an inundation model." In 20th International Congress on Modelling and Simulation (MODSIM2013). Modelling and Simulation Society of Australia and New Zealand (MSSANZ), Inc., 2013. http://dx.doi.org/10.36334/modsim.2013.h5.merrin.

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"Moving window analysis links landscape-scale resource utilization to habitat suitability models of feral pigs in northern Australia." In 21st International Congress on Modelling and Simulation (MODSIM2015). Modelling and Simulation Society of Australia and New Zealand, 2015. http://dx.doi.org/10.36334/modsim.2015.f10.froese.

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Tabeta, Shigeru, Ken Okamoto, Takayoshi Kato, Rikito Hisamatsu, Hiroaki Muto, Akinori Hino, Motohiko Murai, Sho Ito, Daisuke Kitazawa, and Takeshi Kinoshita. "Environmental Regeneration for a Small-Scale Beach “Heda-Mihama Project”." In ASME 2019 38th International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/omae2019-95596.

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Abstract In 1950’s and 1960’s, Mihama beach in Heda Bay located on western coast of Izu peninsular had been famous for the richness in shell fauna, for example, about 400 species including rare ones were collected. In 2000’s, however, the impoverishment of ecosystem function has become considerable, which led us to project the investigation on the origin and restoration. The authors carried out field survey in 2007–2008 and found that the impoverishment of Mihama is derived not from surface water but from the benthic environment. The measured water current at the site was quite small, which indicated the water exchange was very weak. It must be one of the main causes of unfavorable benthic environment. Thus environmental regeneration plans for Mihama was proposed in which the pears blocking the water current be removed. In order to assess the effect of proposed plans, simulation-based habitat evaluation was conducted. A three-dimensional hydrodynamic and sediment transport models were developed to reproduce the characteristics of currents and predict the sediment size around Mihama. For the assessment of the ecological status, HEP (Habitat Evaluation Procedure) was employed, in which one of the typical species of bivalves is chosen as a target species. Water depth, sediment size, friction velocity at the bottom, etc. were considered as the environmental factors for the target species. The suitability indices (SI) for each environmental factors were calculated by using the results of hydrodynamic and sediment transport simulations. By using the developed scheme, total habitat unit was evaluated for the proposed regeneration plans and compared to that without countermeasures. It was predicted that the removal of the piers will improve the habitat condition in the target site. Based on the proposal by the authors, a water pathway under the pier was built in 2009. The authors conducted field survey again in 2014 and confirmed that the benthic environment has been improved.
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Bradter, Ute, Louise Mair, Mari Jönsson, Jonas Knape, and Tord Snäll. "Habitat suitability models for the Siberian jay (Perisoreus infaustus) from Citizen Science and systematic monitoring data: incorporating information about the reporting process." In 5th European Congress of Conservation Biology. Jyväskylä: Jyvaskyla University Open Science Centre, 2018. http://dx.doi.org/10.17011/conference/eccb2018/107740.

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Reports on the topic "Habitat suitability model"

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O'Neil, L. J. Test and Modification of a Northern Bobwhite Habitat Suitability Index Model. Fort Belvoir, VA: Defense Technical Information Center, April 1993. http://dx.doi.org/10.21236/ada265937.

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Saltus, Christina, Todd Swannack, and S. McKay. Geospatial Suitability Indices Toolbox (GSI Toolbox). Engineer Research and Development Center (U.S.), September 2021. http://dx.doi.org/10.21079/11681/41881.

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Habitat suitability models are widely adopted in ecosystem management and restoration, where these index models are used to assess environmental impacts and benefits based on the quantity and quality of a given habitat. Many spatially distributed ecological processes require application of suitability models within a geographic information system (GIS). Here, we present a geospatial toolbox for assessing habitat suitability. The Geospatial Suitability Indices (GSI) toolbox was developed in ArcGIS Pro 2.7 using the Python® 3.7 programming language and is available for use on the local desktop in the Windows 10 environment. Two main tools comprise the GSI toolbox. First, the Suitability Index Calculator tool uses thematic or continuous geospatial raster layers to calculate parameter suitability indices based on user-specified habitat relationships. Second, the Overall Suitability Index Calculator combines multiple parameter suitability indices into one overarching index using one or more options, including: arithmetic mean, weighted arithmetic mean, geometric mean, and minimum limiting factor. The resultant output is a raster layer representing habitat suitability values from 0.0 to 1.0, where zero is unsuitable habitat and one is ideal suitability. This report documents the model purpose and development as well as provides a user’s guide for the GSI toolbox.
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Duberstein, Corey A., Mary Ann Simmons, Michael R. Sackschewsky, and James M. Becker. Development of a Habitat Suitability Index Model for the Sage Sparrow on the Hanford Site. Office of Scientific and Technical Information (OSTI), January 2008. http://dx.doi.org/10.2172/926111.

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James Biggs, Mary Mullen, and Kathryn Bennett. Development and Application of a Habitat Suitability Ranking Model for the New Mexico Meadow Jumping Mouse (Zapus hudsonius luteus). Office of Scientific and Technical Information (OSTI), November 1999. http://dx.doi.org/10.2172/15132.

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Larson, Michael A., William D. Dijak, Frank R. III Thompson, and Joshua J. Millspaugh. Landscape-level habitat suitability models for twelve species in southern Missouri. St. Paul, MN: U.S. Department of Agriculture, Forest Service, North Central Research Station, 2003. http://dx.doi.org/10.2737/nc-gtr-233.

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6

Brandt, Leslie A., Cait Rottler, Wendy S. Gordon, Stacey L. Clark, Lisa O'Donnell, April Rose, Annamarie Rutledge, and Emily King. Vulnerability of Austin’s urban forest and natural areas: A report from the Urban Forestry Climate Change Response Framework. U.S. Department of Agriculture, Northern Forests Climate Hub, October 2020. http://dx.doi.org/10.32747/2020.7204069.ch.

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Abstract:
The trees, developed green spaces, and natural areas within the City of Austin’s 400,882 acres will face direct and indirect impacts from a changing climate over the 21st century. This assessment evaluates the vulnerability of urban trees and natural and developed landscapes within the City Austin to a range of future climates. We synthesized and summarized information on the contemporary landscape, provided information on past climate trends, and illustrated a range of projected future climates. We used this information to inform models of habitat suitability for trees native to the area. Projected shifts in plant hardiness and heat zones were used to understand how less common native species, nonnative species, and cultivars may tolerate future conditions. We also assessed the adaptability of planted and naturally occurring trees to stressors that may not be accounted for in habitat suitability models such as drought, flooding, wind damage, and air pollution. The summary of the contemporary landscape identifies major stressors currently threatening trees and forests in Austin. Major current threats to the region’s urban forest include invasive species, pests and disease, and development. Austin has been warming at a rate of about 0.4°F per decade since measurements began in 1938 and temperature is expected to increase by 5 to 10°F by the end of this century compared to the most recent 30-year average. Both increases in heavy rain events and severe droughts are projected for the future, and the overall balance of precipitation and temperature may shift Austin’s climate to be more similar to the arid Southwest. Species distribution modeling of native trees suggests that suitable habitat may decrease for 14 primarily northern species, and increase for four more southern species. An analysis of tree species vulnerability that combines model projections, shifts in hardiness and heat zones, and adaptive capacity showed that only 3% of the trees estimated to be present in Austin based on the most recent Urban FIA estimate were considered to have low vulnerability in developed areas. Using a panel of local experts, we also assessed the vulnerability of developed and natural areas. All areas were rated as having moderate to moderate-high vulnerability, but the underlying factors driving that vulnerability differed by natural community and between East and West Austin. These projected changes in climate and their associated impacts and vulnerabilities will have important implications for urban forest management, including the planting and maintenance of street and park trees, management of natural areas, and long-term planning.
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Latif, Quresh S., Victoria A. Saab, Jessica R. Haas, and Jonathan G. Dudley. FIRE-BIRD: A GIS-based toolset for applying habitat suitability models to inform land management planning. Ft. Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station, 2018. http://dx.doi.org/10.2737/rmrs-gtr-391.

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8

Rittenhouse, Chadwick D., William D. Dijak, Frank R. III Thompson, and Joshua J. Millspaugh. Development of landscape-level habitat suitability models for ten wildlife species in the central hardwoods region. Newtown Square, PA: U.S. Department of Agriculture, Forest Service, Northern Research Station, 2007. http://dx.doi.org/10.2737/nrs-gtr-4.

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Latif, Quresh S., Victoria A. Saab, Jessica R. Haas, and Jonathan G. Dudley. FIRE-BIRD: A GIS-based toolset for applying habitat suitability models to inform land management planning. Ft. Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station, 2018. http://dx.doi.org/10.2737/rmrs-gtr-391.

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Tirpak, John M., D. Todd Jones-Farrand, Frank R. ,. III Thompson, Daniel J. Twedt, and William B. ,. III Uihlein. Multiscale habitat suitability index models for priority landbirds in the Central Hardwoods and West Gulf Coastal Plain/Ouachitas Bird Conservation Regions. Newtown Square, PA: U.S. Department of Agriculture, Forest Service, Northern Research Station, 2009. http://dx.doi.org/10.2737/nrs-gtr-49.

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