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Artykuły w czasopismach na temat „Habitat predictive model”

Autor: Grafiati

Data publikacji: 4 czerwca 2021

Data aktualizacji: 1 lutego 2022

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1

Reisinger, Ryan R., Ari S. Friedlaender, Alexandre N. Zerbini, Daniel M. Palacios, Virginia Andrews-Goff, Luciano Dalla Rosa, Mike Double, et al. "Combining Regional Habitat Selection Models for Large-Scale Prediction: Circumpolar Habitat Selection of Southern Ocean Humpback Whales." Remote Sensing 13, no. 11 (May 25, 2021): 2074. http://dx.doi.org/10.3390/rs13112074.

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Machine learning algorithms are often used to model and predict animal habitat selection—the relationships between animal occurrences and habitat characteristics. For broadly distributed species, habitat selection often varies among populations and regions; thus, it would seem preferable to fit region- or population-specific models of habitat selection for more accurate inference and prediction, rather than fitting large-scale models using pooled data. However, where the aim is to make range-wide predictions, including areas for which there are no existing data or models of habitat selection,

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Meißner, Karin, and Alexander Darr. "Distribution of Magelona species (Polychaeta: Magelonidae) in the German Bight (North Sea): a modeling approach." Zoosymposia 2, no. 1 (August 31, 2009): 567–86. http://dx.doi.org/10.11646/zoosymposia.2.1.39.

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The aim of the present study was the development of species-habitat models for four Magelona species (Polychaeta: Magelonidae) found in the German Bight in the SE North Sea. Analyses were based on field data and data obtained from reexamination of material deposited in museum collections. In addition, data on environmental variables were retrieved from the sediment map by Figge (1981) and from long-term monitoring data sets. The statistical modeling technique applied was multivariate adaptive regression splines (MARS). Predictive accuracy measures were calculated for each model. The candidate

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Enwright, Nicholas M., Lei Wang, Hongqing Wang, Michael J. Osland, Laura C. Feher, Sinéad M. Borchert, and Richard H. Day. "Modeling Barrier Island Habitats Using Landscape Position Information." Remote Sensing 11, no. 8 (April 24, 2019): 976. http://dx.doi.org/10.3390/rs11080976.

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Barrier islands are dynamic environments because of their position along the marine–estuarine interface. Geomorphology influences habitat distribution on barrier islands by regulating exposure to harsh abiotic conditions. Researchers have identified linkages between habitat and landscape position, such as elevation and distance from shore, yet these linkages have not been fully leveraged to develop predictive models. Our aim was to evaluate the performance of commonly used machine learning algorithms, including K-nearest neighbor, support vector machine, and random forest, for predicting barri

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Rice, M. B., A. D. Apa, and L. A. Wiechman. "The importance of seasonal resource selection when managing a threatened species: targeting conservation actions within critical habitat designations for the Gunnison sage-grouse." Wildlife Research 44, no. 5 (2017): 407. http://dx.doi.org/10.1071/wr17027.

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Context The ability to identify priority habitat is critical for species of conservation concern. The designation of critical habitat under the US Endangered Species Act 1973 identifies areas occupied by the species that are important for conservation and may need special management or protection. However, relatively few species’ critical habitats designations incorporate habitat suitability models or seasonal specificity, even when that information exists. Gunnison sage-grouse (GUSG) have declined substantially from their historical range and were listed as threatened by the US Fish and Wildl

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Haxton, Tim J., C. Scott Findlay, and R. W. Threader. "Predictive Value of a Lake Sturgeon Habitat Suitability Model." North American Journal of Fisheries Management 28, no. 5 (October 2008): 1373–83. http://dx.doi.org/10.1577/m07-146.1.

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Street, Garrett M., Lucas M. Vander Vennen, Tal Avgar, Anna Mosser, Morgan L. Anderson, Arthur R. Rodgers, and John M. Fryxell. "Habitat selection following recent disturbance: model transferability with implications for management and conservation of moose (Alces alces)." Canadian Journal of Zoology 93, no. 11 (November 2015): 813–21. http://dx.doi.org/10.1139/cjz-2015-0005.

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Site-specific variation in relative habitat abundance and disturbance regimes may produce differences in habitat preferences of associated populations. An evaluation of the predictive power of habitat selection models across space would benefit our understanding of the reliability of models of selection and space use in predicting animal occurrence. We used presence–absence data from winter surveys of moose (Alces alces (L., 1758)) to estimate resource selection functions (RSFs) across two study sites using Far North Land Cover updated with recent disturbance from fire and timber harvest. Moos

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TAKEMURA, Shion, Yoshihisa AKAMATSU, and Mahito KAMADA. "Evaluation of vulnerability of mangrove habitats using predictive habitat distribution model in Palau Islands." Journal of Japan Society of Civil Engineers, Ser. G (Environmental Research) 68, no. 5 (2012): I_105—I_110. http://dx.doi.org/10.2208/jscejer.68.i_105.

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Buechling, Arne, and Claudine Tobalske. "Predictive Habitat Modeling of Rare Plant Species in Pacific Northwest Forests." Western Journal of Applied Forestry 26, no. 2 (April 1, 2011): 71–81. http://dx.doi.org/10.1093/wjaf/26.2.71.

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Abstract Certification requirements associated with the Sustainable Forestry Initiative include efforts to identify and protect occurrences of endangered plant species. Habitat models were constructed in this study using maximum entropy and random forest algorithms to generate independent predictions for four selected rare plants, Castilleja chambersii, Erythronium elegans, Filipendula occidentalis, and Sidalcea nelsoniana, associated with divergent physical environments. Explanatory variables used to model rare plant occurrence included Landsat Enhanced Thematic Mapper Plus spectral imagery,

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Alabia, Irene D., Sei-Ichi Saitoh, Hiromichi Igarashi, Yoichi Ishikawa, Norihisa Usui, Masafumi Kamachi, Toshiyuki Awaji, and Masaki Seito. "Ensemble squid habitat model using three-dimensional ocean data." ICES Journal of Marine Science 73, no. 7 (May 6, 2016): 1863–74. http://dx.doi.org/10.1093/icesjms/fsw075.

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Abstract Neon flying squid (Ommastrephes bartramii) is a large pelagic squid internationally harvested in the North Pacific. Here, we examined its potential habitat in the central North Pacific using an ensemble modelling approach. Initially, ten statistical models were constructed by combining the squid fishing points, selected vertical layers of the sea temperature and salinity, sea surface height (SSH), and SSH gradient from the multi-variate ocean variational estimation system for the western North Pacific from June to July 1999–2011. The variable selection analyses have captured the impor

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Socolar, Jacob B., and David S. Wilcove. "Forest-type specialization strongly predicts avian responses to tropical agriculture." Proceedings of the Royal Society B: Biological Sciences 286, no. 1913 (October 23, 2019): 20191724. http://dx.doi.org/10.1098/rspb.2019.1724.

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Species’ traits influence how populations respond to land-use change. However, even in well-characterized groups such as birds, widely studied traits explain only a modest proportion of the variance in response across species. Here, we show that associations with particular forest types strongly predict the sensitivity of forest-dwelling Amazonian birds to agriculture. Incorporating these fine-scale habitat associations into models of population response dramatically improves predictive performance and markedly outperforms the functional traits that commonly appear in similar analyses. Moreove

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Holmes, Stephen B., Lisa A. Venier, Brian J. Naylor, and J. Ryan Zimmerling. "A test of Ontario's Habitat Suitability Matrix as a forest management planning tool for forest birds." Forestry Chronicle 83, no. 4 (August 1, 2007): 570–79. http://dx.doi.org/10.5558/tfc83570-4.

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We used point-count data collected as part of Bird Studies Canada's Boreal Forest Bird Program to validate habitat suitability models for 22 forest bird species in Ontario's Habitat Suitability Matrix. We found that many of the species'models performed relatively poorly in discriminating between occupied and unoccupied sites, primarily due to the high error of commission rates (false positive predictions). Since species presence and abundance were assessed by single, five minute point counts, insufficient sampling was at least partly responsible for some of the observed over-prediction. Result

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Dadashi-Jourdehi, Amirhossein, Bahman Shams Esfandabad, Abbas Ahmadi, Hamid Reza Rezaei, and Hamid Toranj-Zar. "Predicting the potential distribution of striped hyena Hyaena hyaena in Iran." Zoology and Ecology 29, no. 2 (July 30, 2019): 109–14. http://dx.doi.org/10.35513/21658005.2019.2.6.

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Predictive potential distribution modelling is crucial in outlining habitat usage and establishing conservation management priorities. Species distribution models estimate the relationship between species occurrences and environmental and spatial characteristics. Herein, we used maximum entropy distribution modelling (MaxEnt) for predicting the potential distribution of the striped hyena Hyaena hyaena in the entire country of Iran, using a number of occurrence records (i.e. 118) and environmental variables derived from remote sensing. The MaxEnt model had a high success rate according to test

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Bayne, Erin M., Samuel Haché, and Keith A. Hobson. "Comparing the predictive capability of forest songbird habitat models based on remotely sensed versus ground-based vegetation information." Canadian Journal of Forest Research 40, no. 1 (January 2010): 65–71. http://dx.doi.org/10.1139/x09-170.

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Habitat suitability models allow for predictive modeling of the supply of wildlife habitat through time under various forest harvesting scenarios. These models often rely on remotely sensed data in a forest resource inventory (FRI). However, the level of detail and (or) the accuracy of a FRI may be insufficient to accurately predict habitat suitability for forest birds. We tested if detailed vegetation measurements created habitat suitability models with better predictive power than models that used FRI data alone and if rough estimates of shrub cover were sufficient to supplement FRI data to

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Lindenmayer, D. B., and R. C. Lacy. "Small mammals, habitat patches and PVA models: a field test of model predictive ability." Biological Conservation 103, no. 3 (March 2002): 247–65. http://dx.doi.org/10.1016/s0006-3207(01)00134-3.

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Pedersen, Å. Ø., J. U. Jepsen, N. G. Yoccoz, and E. Fuglei. "Ecological correlates of the distribution of territorial Svalbard rock ptarmigan (Lagopus muta hyperborea)." Canadian Journal of Zoology 85, no. 1 (January 2007): 122–32. http://dx.doi.org/10.1139/z06-197.

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Predictive habitat models have become important research and management tools for monitoring the spatial distribution and abundance of wildlife species. In this paper we develop and evaluate statistical habitat models for presence of territorial Svalbard rock ptarmigan ( Lagopus muta hyperborea Sundevall, 1845) cocks in spring and apply the best model to assess ptarmigan habitat selection in a larger extrapolated region. Terrain variables were extracted at detailed (10 m digital elevation model (DEM)) and coarse (50 m DEM) scales to compare model performance. Sets of candidate environmental va

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Evans, Andrew, Richard Odom, Lynn Resler, W. Mark Ford, and Steve Prisley. "Developing a Topographic Model to Predict the Northern Hardwood Forest Type within Carolina Northern Flying Squirrel (Glaucomys sabrinus coloratus) Recovery Areas of the Southern Appalachians." International Journal of Forestry Research 2014 (2014): 1–11. http://dx.doi.org/10.1155/2014/179415.

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The northern hardwood forest type is an important habitat component for the endangered Carolina northern flying squirrel (CNFS;Glaucomys sabrinus coloratus) for den sites and corridor habitats between boreo-montane conifer patches foraging areas. Our study related terrain data to presence of northern hardwood forest type in the recovery areas of CNFS in the southern Appalachian Mountains of western North Carolina, eastern Tennessee, and southwestern Virginia. We recorded overstory species composition and terrain variables at 338 points, to construct a robust, spatially predictive model. Terrai

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Vanderhoof, Melanie, Barbara A. Holzman, and Chris Rogers. "Predicting the Distribution of Perennial Pepperweed (Lepidium latifolium), San Francisco Bay Area, California." Invasive Plant Science and Management 2, no. 3 (July 2009): 260–69. http://dx.doi.org/10.1614/ipsm-09-005.1.

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AbstractPerennial pepperweed is an invasive plant species that occurs throughout the western United States. This study develops a predictive model for perennial pepperweed distribution for the San Francisco Bay Area, based on spatial variables. Distribution data were developed by mapping perennial pepperweed along the shoreline of the South San Francisco Bay, using geographic positioning system units. Spatial relationships between its distribution and spatial variables were tested using binomial logistic regression. Predictive models were mapped using geographic information systems (GIS), and

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Hamer, Thomas E., Daniel E. Varland, Trent L. McDonald, and Douglas Meekins. "Predictive Model of Habitat Suitability for the Marbled Murrelet in Western Washington." Journal of Wildlife Management 72, no. 4 (May 2008): 983–93. http://dx.doi.org/10.2193/2006-565.

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Rooper, CN, GR Hoff, DE Stevenson, JW Orr, and IB Spies. "Skate egg nursery habitat in the eastern Bering Sea: a predictive model." Marine Ecology Progress Series 609 (January 17, 2019): 163–78. http://dx.doi.org/10.3354/meps12809.

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Norris, D. Ryan, and Caz M. Taylor. "Predicting the consequences of carry-over effects for migratory populations." Biology Letters 2, no. 1 (November 2, 2005): 148–51. http://dx.doi.org/10.1098/rsbl.2005.0397.

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Migratory animals present a unique challenge for predicting population size because they are influenced by events in multiple stages of the annual cycle that are separated by large geographic distances. Here, we develop a model that incorporates non-fatal carry-over effects to predict changes in population size and show how this can be integrated with predictive models of habitat loss and deterioration. Examples from Barn swallows, Greater snow geese and American redstarts show how carry-over effects can be estimated and integrated into the model. Incorporation of carry-over effects should inc

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Germaine, Steve, Drew Ignizio, Doug Keinath, and Holly Copeland. "Predicting Occupancy for Pygmy Rabbits in Wyoming: An Independent Evaluation of Two Species Distribution Models." Journal of Fish and Wildlife Management 5, no. 2 (August 1, 2014): 298–314. http://dx.doi.org/10.3996/022014-jfwm-016.

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Abstract Species distribution models are an important component of natural-resource conservation planning efforts. Independent, external evaluation of their accuracy is important before they are used in management contexts. We evaluated the classification accuracy of two species distribution models designed to predict the distribution of pygmy rabbit Brachylagus idahoensis habitat in southwestern Wyoming, USA. The Nature Conservancy model was deductive and based on published information and expert opinion, whereas the Wyoming Natural Diversity Database model was statistically derived using his

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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

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Sacks, Benjamin N., Mark J. Statham, and Heiko U. Wittmer. "A Preliminary Range-Wide Distribution Model for the Sacramento Valley Red Fox." Journal of Fish and Wildlife Management 8, no. 1 (December 1, 2016): 28–38. http://dx.doi.org/10.3996/072016-jfwm-057.

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Abstract The Sacramento Valley red fox Vulpes vulpes patwin of California is a newly named subspecies recently found to be distinct both from other native red foxes and nearby introduced populations. The Sacramento Valley red fox experienced a historical demographic bottleneck resulting in a critically small genetic effective population size, causing concern over its current status and management requirements, yet little is known about its contemporary abundance, demographic trajectory, or habitat use. The hot, arid Sacramento Valley contrasts starkly in climate and physiography with the borea

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Hobday, Alistair J., Jason R. Hartog, Claire M. Spillman, and Oscar Alves. "Seasonal forecasting of tuna habitat for dynamic spatial management." Canadian Journal of Fisheries and Aquatic Sciences 68, no. 5 (May 2011): 898–911. http://dx.doi.org/10.1139/f2011-031.

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Capture of the target, bycatch, and protected species in fisheries is often regulated through spatial measures that partition fishing effort, including areal closures. In eastern Australian waters, southern bluefin tuna (SBT, Thunnus maccoyii ) are a quota-limited species in a multispecies longline fishery; minimizing capture by nonquota holders is an important management concern. A habitat preference model (conditioned with electronic tag data) coupled with ocean reanalysis data has been used since 2003 to generate real-time predicted maps of SBT distribution (nowcasts). These maps are used b

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Rizo-Aguilar, Areli, José Antonio Guerrero, Mircea G. Hidalgo-Mihart, and Alberto González-Romero. "Relationship between the abundance of the Endangered volcano rabbit Romerolagus diazi and vegetation structure in the Sierra Chichinautzin mountain range, Mexico." Oryx 49, no. 2 (May 12, 2014): 360–65. http://dx.doi.org/10.1017/s0030605313000975.

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AbstractThe volcano rabbit Romerolagus diazi is endemic to the mountains of central Mexico, where its habitat has been gradually destroyed to make way for agriculture, ranching and logging, and by forest fires. The volcano rabbit is categorized as Endangered on the IUCN Red List. We evaluated the relationship between the abundance of the volcano rabbit and vegetation structure at a small scale (0.25 ha). Using a general linear model we generated a set of 21 predictive models and proposed the best model as a habitat quality index. Our results suggest that greater height and cover of bunchgrasse

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Gardner, Beth, Patrick J. Sullivan, and Arthur J. Lembo, Jr. "Predicting stream temperatures: geostatistical model comparison using alternative distance metrics." Canadian Journal of Fisheries and Aquatic Sciences 60, no. 3 (March 1, 2003): 344–51. http://dx.doi.org/10.1139/f03-025.

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The Beaverkill Watershed in the Catskill Mountains of New York, U.S.A., shows evidence of high summer stream temperatures throughout critical trout habitat. Because habitat quality, as characterized by stream temperature, dramatically influences trout communities, it is important for biologists to identify and map these characteristics and to monitor how they change over time. Stream temperatures were recorded over time throughout the Beaverkill Watershed and were used to identify thermal refugia and areas of thermal stress. Seventy-two temperature loggers were placed throughout the watershed

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Rinaldi, A., V. Montalto, A. Manganaro, A. Mazzola, S. Mirto, M. Sanfilippo, and G. Sarà. "Predictive mechanistic bioenergetics to model habitat suitability of shellfish culture in coastal lakes." Estuarine, Coastal and Shelf Science 144 (May 2014): 89–98. http://dx.doi.org/10.1016/j.ecss.2014.04.013.

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Bashari, Hossein, and Mahmoud-Reza Hemami. "A predictive diagnostic model for wild sheep (Ovis orientalis) habitat suitability in Iran." Journal for Nature Conservation 21, no. 5 (October 2013): 319–25. http://dx.doi.org/10.1016/j.jnc.2013.03.005.

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Stansfield, W. F., J. P. McTague, and R. Lacapa. "Dominant-height and site-index equations for ponderosa pine in east-central Arizona." Canadian Journal of Forest Research 21, no. 5 (May 1, 1991): 606–11. http://dx.doi.org/10.1139/x91-083.

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A dominant-height equation for ponderosa pine (Pinusponderosa Laws.) was constructed utilizing a parameter prediction method and a model by J.E. King. The site-index equation was obtained by inverting the dominant-height equation. A method was examined for indirectly obtaining parameter prediction equations. It proved superior to two direct parameter prediction approaches. Other site-quality variables, such as habitat type groups and elevation, were included in the dominant-height and site-index equations and were successful in refining predictive capability.

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Beale, Colin M., and Jack J. Lennon. "Incorporating uncertainty in predictive species distribution modelling." Philosophical Transactions of the Royal Society B: Biological Sciences 367, no. 1586 (January 19, 2012): 247–58. http://dx.doi.org/10.1098/rstb.2011.0178.

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Motivated by the need to solve ecological problems (climate change, habitat fragmentation and biological invasions), there has been increasing interest in species distribution models (SDMs). Predictions from these models inform conservation policy, invasive species management and disease-control measures. However, predictions are subject to uncertainty, the degree and source of which is often unrecognized. Here, we review the SDM literature in the context of uncertainty, focusing on three main classes of SDM: niche-based models, demographic models and process-based models. We identify sources

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Hastie, Gordon D., René J. Swift, George Slesser, Paul M. Thompson, and William R. Turrell. "Environmental models for predicting oceanic dolphin habitat in the Northeast Atlantic." ICES Journal of Marine Science 62, no. 4 (January 1, 2005): 760–70. http://dx.doi.org/10.1016/j.icesjms.2005.02.004.

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Abstract Dolphin distributions have been related to a range of oceanographic determinants. The complex topography and hydrography of the Faroe-Shetland Channel have a significant influence on the distribution of many species. However, there is no published detail on how dolphin distributions there are influenced by either topography or hydrography. The study therefore aims to relate dolphin distributions in the Faroe-Shetland Channel to environmental variables, using a general additive modelling framework applied to passive acoustic survey data. Models were created using data from 2001, and we

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Almarinez, Billy Joel M., Mary Jane A. Fadri, Richard Lasina, Mary Angelique A. Tavera, Thaddeus M. Carvajal, Kozo Watanabe, Jesusa C. Legaspi, and Divina M. Amalin. "A Bioclimate-Based Maximum Entropy Model for Comperiella calauanica Barrion, Almarinez and Amalin (Hymenoptera: Encyrtidae) in the Philippines." Insects 12, no. 1 (January 4, 2021): 26. http://dx.doi.org/10.3390/insects12010026.

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Comperiella calauanica is a host-specific endoparasitoid and effective biological control agent of the diaspidid Aspidiotus rigidus, whose outbreak from 2010 to 2015 severely threatened the coconut industry in the Philippines. Using the maximum entropy (Maxent) algorithm, we developed a species distribution model (SDM) for C. calauanica based on 19 bioclimatic variables, using occurrence data obtained mostly from field surveys conducted in A. rigidus-infested areas in Luzon Island from 2014 to 2016. The calculated the area under the ROC curve (AUC) values for the model were very high (0.966, s

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Cameron, Robert, Ian Goudie, and David Richardson. "Habitat loss exceeds habitat regeneration for an IUCN flagship lichen epiphyte: Erioderma pedicellatum." Canadian Journal of Forest Research 43, no. 11 (November 2013): 1075–80. http://dx.doi.org/10.1139/cjfr-2013-0024.

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The boreal felt lichen (Erioderma pedicellatum (Hue) P.M. Jørg.) is globally critically endangered, being threatened by forestry operations, habitat disturbance, and air pollution. To determine if loss of habitat due to forestry activities has occurred in Nova Scotia, a predictive habitat model was built using historical data from 1988. Satellite data were used for the period between 1987 and 2005 to determine the amount of suitable habitat harvested during this period. Available habitat was modeled through time from 1988 to 2005 in which area harvested was subtracted and regeneration was adde

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Sun, Yue, Yanze Yu, Jinhao Guo, and Minghai Zhang. "The Winter Habitat Selection of Red Deer (Cervus elaphus) Based on a Multi-Scale Model." Animals 10, no. 12 (December 21, 2020): 2454. http://dx.doi.org/10.3390/ani10122454.

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Single-scale frameworks are often used to analyze the habitat selections of species. Research on habitat selection can be significantly improved using multi-scale models that enable greater in-depth analyses of the scale dependence between species and specific environmental factors. In this study, the winter habitat selection of red deer in the Gogostaihanwula Nature Reserve, Inner Mongolia, was studied using a multi-scale model. Each selected covariate was included in multi-scale models at their “characteristic scale”, and we used an all subsets approach and model selection framework to asses

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Anlauf-Dunn, Kara J., Eric J. Ward, Matt Strickland, and Kim Jones. "Habitat connectivity, complexity, and quality: predicting adult coho salmon occupancy and abundance." Canadian Journal of Fisheries and Aquatic Sciences 71, no. 12 (December 2014): 1864–76. http://dx.doi.org/10.1139/cjfas-2014-0162.

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The distribution, quality, and connectivity of instream habitat can influence adult salmon occupancy and abundance patterns and alter population dynamics. In this study, we evaluated the relationships between adult coho salmon (Oncorhynchus kisutch) occupancy and abundance with instream habitat conditions, including measures of spawning gravel, habitat complexity, and juvenile rearing habitat. We used corresponding adult salmon spawning and instream habitat data collected within coastal Oregon watersheds as part of a long-term monitoring program. We modeled two processes as a function of habit

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Iampietro, Pat J., Rikk G. Kvitek, and Erica Morris. "Recent Advances in Automated Genus-specific Marine Habitat Mapping Enabled by High-resolution Multibeam Bathymetry." Marine Technology Society Journal 39, no. 3 (September 1, 2005): 83–93. http://dx.doi.org/10.4031/002533205787442495.

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There is a great need for accurate, comprehensive maps of seafloor habitat for use in fish stock assessments, marine protected area design, and other resource management pursuits. Recent advances in acoustic remote sensing technology have made it possible to obtain high-resolution (meter to sub-meter) digital elevation models (DEMs) of seafloor bathymetry that can rival or surpass those available for the terrestrial environment. The acquisition and processing of these data are expensive, however, requiring specialized equipment, expertise, and large amounts of both field and laboratory effort

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Hofmann, Michaela M., Constantin M. Zohner, and Susanne S. Renner. "Narrow habitat breadth and late-summer emergence increases extinction vulnerability in Central European bees." Proceedings of the Royal Society B: Biological Sciences 286, no. 1898 (March 6, 2019): 20190316. http://dx.doi.org/10.1098/rspb.2019.0316.

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Evaluating intrinsic and extrinsic traits that predispose species to local extinction is important for targeting conservation efforts. Among the species of special concern in Europe are bees, which, along with butterflies, are the best monitored insects. Bees are most species-rich in Mediterranean-type climates with short winters, warm springs, and dry summers. In Central Europe, climate warming per se is, therefore, expected to benefit most bee species, while pesticides and the loss of habitats and plant diversity should constitute threats. Here, we use the bee fauna of Germany, which has bee

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Ritter, Michael W., and Julie A. Savidge. "A Predictive Model of Wetland Habitat Use on Guam by Endangered Mariana Common Moorhens." Condor 101, no. 2 (May 1999): 282–87. http://dx.doi.org/10.2307/1369991.

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PEARSON, Kara, Robert CAMERON, and R. Troy MCMULLIN. "Habitat associations and distribution model forFuscopannaria leucostictain Nova Scotia, Canada." Lichenologist 50, no. 4 (July 2018): 487–97. http://dx.doi.org/10.1017/s0024282918000300.

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AbstractFuscopannaria leucostictais a rare and understudied cyanolichen with an interesting and unusual distribution in tertiary relict hotspots worldwide. There is a relatively large population in eastern North America, where it occurs mostly throughout the Appalachian Mountains and reaches its northernmost extent in New Brunswick and Nova Scotia, Canada. The ability to detect this species, and thus determine its habitat requirements, is critical for understanding how it might be affected by human-induced environmental degradation. Maximum entropy modelling with MaxEnt was used to predict the

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McCleary, Richard J., and Marwan A. Hassan. "Predictive modeling and spatial mapping of fish distributions in small streams of the Canadian Rocky Mountain foothills." Canadian Journal of Fisheries and Aquatic Sciences 65, no. 2 (February 1, 2008): 319–33. http://dx.doi.org/10.1139/f07-161.

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We developed an automated procedure for modeling spatial distribution of fish occurrence using logistic regression models and geographic information system (GIS) tools. Predictors were measured from a digital elevation model (DEM) and stream layers. We evaluated the accuracy of GIS measures of reach slope through a comparison with field measures. Resource selection function models were used to explain presence-absence of bull trout (Salvelinus confluentus), rainbow trout, (Oncorhynchus mykiss), nonnative brook trout (Salvelinus fontinalis), and all fishes. Our models were extrapolated based on

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Evangelista, Paul H., John Norman, Lakew Berhanu, Sunil Kumar, and Nathaniel Alley. "Predicting habitat suitability for the endemic mountain nyala (Tragelaphus buxtoni) in Ethiopia." Wildlife Research 35, no. 5 (2008): 409. http://dx.doi.org/10.1071/wr07173.

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The use of statistical models to predict species distributions and suitable habitat has become an essential tool for wildlife management and conservation planning. Models have been especially useful with rare and endangered wildlife species. One such species is the mountain nyala (Tragelaphus buxtoni), a spiral-horned antelope endemic to the Ethiopian highlands. The full range of the species has never been adequately defined and recent discoveries of new populations suggest that others may exist undetected. To identify potential mountain nyala occurrences, we used classification tree analysis

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Perzanowski, Kajetan, Maciej Januszczak, and Rafał Łopucki. "Historical changes in land use influence current habitat preferences of large herbivores." Landscape Ecology 34, no. 10 (September 12, 2019): 2251–59. http://dx.doi.org/10.1007/s10980-019-00899-4.

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Abstract Context Predicting habitat use patterns is a key issue in the management of large herbivore populations. Particularly, indicators providing a model of the spatial distribution of a population in a simple way, without the necessity of laborious field research, are still being sought. Analysis of historical landscape changes can be one of such predictive tools. Objectives We tested the hypothesis that historical changes in land use can be used as an effective factor enabling prediction of spatial distribution. As a case study, data on habitat preferences of European bison Bison bonasus

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Thorson, James T., and Lewis A. K. Barnett. "Comparing estimates of abundance trends and distribution shifts using single- and multispecies models of fishes and biogenic habitat." ICES Journal of Marine Science 74, no. 5 (January 14, 2017): 1311–21. http://dx.doi.org/10.1093/icesjms/fsw193.

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Several approaches have been developed over the last decade to simultaneously estimate distribution or density for multiple species (e.g. “joint species distribution” or “multispecies occupancy” models). However, there has been little research comparing estimates of abundance trends or distribution shifts from these multispecies models with similar single-species estimates. We seek to determine whether a model including correlations among species (and particularly species that may affect habitat quality, termed “biogenic habitat”) improves predictive performance or decreases standard errors fo

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Theodoropoulos, Christos, Nikolaos Skoulikidis, Anastasios Stamou, and Elias Dimitriou. "Spatiotemporal Variation in Benthic-Invertebrates-Based Physical Habitat Modelling: Can We Use Generic Instead of Local and Season-Specific Habitat Suitability Criteria?" Water 10, no. 11 (October 24, 2018): 1508. http://dx.doi.org/10.3390/w10111508.

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Generic habitat suitability criteria (HC) are often developed from spatially and temporally variable hydroecological datasets to increase generality, cost-effectiveness, and time-efficiency of habitat models. For benthic macroinvertebrates (BMIs), however, there is no prior knowledge on the spatiotemporal variation in their habitat preferences and how this may be reflected in the final environmental flow (e-flow) predictions. In this study, we used a large, spatiotemporally variable BMI-hydroecological dataset and developed generic, local, and season-specific subsets of HC for three seasons an

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McCleery, Robert A., and Christa L. Zweig. "Leveraging limited information to understand ecological relationships of endangered Florida salt marsh vole." Journal of Mammalogy 97, no. 4 (May 9, 2016): 1249–55. http://dx.doi.org/10.1093/jmammal/gyw084.

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Abstract We were able to substantially increase our knowledge of what is likely the least understood endangered terrestrial mammal in the United States, the Florida salt marsh vole (FSMV; Microtus pennsylvanicus dukecampbelli). We developed a predictive landscape model that estimated 264 ha of potential habitat for FSMVs. Evaluating our model, we found voles at 8 of the 36 sites sampled, yielding a model accuracy of 22% for a subspecies that previously was known from only 3 locations. Within areas of potential habitat, FSMVs selected patches of marsh vegetation &gt; 0.49 ha with at least s

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Ejigu, D., A. Bekele, L. Powell, and J. M. Lernould. "Habitat preference of the endangered Ethiopian walia ibex (Capra walie) in the Simien Mountains National Park, Ethiopia." Animal Biodiversity and Conservation 38, no. 1 (March 2015): 1–10. http://dx.doi.org/10.32800/abc.2015.38.0001.

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Walia ibex (Capra walie) is an endangered and endemic species restricted to the Simien Mountains National Park, Ethiopia. Recent expansion of human populations and livestock grazing in the park has prompted concerns that the range and habitats used by walia ibex have changed. We performed observations of walia ibex, conducted pellet counts of walia ibex and livestock, and measured vegetation and classified habitat characteristics at sample points during wet and dry seasons from October 2009 to November 2011. We assessed the effect of habitat characteristics on the presence of pellets of walia

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JOHNSON, CHRIS J., and MICHAEL P. GILLINGHAM. "An evaluation of mapped species distribution models used for conservation planning." Environmental Conservation 32, no. 2 (June 2005): 117–28. http://dx.doi.org/10.1017/s0376892905002171.

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The widespread use of spatial planning tools in conjunction with increases in the availability of geographic information systems and associated data has led to the rapid growth in the exploration and application of species distribution models. Conservation professionals can choose from a considerable number of modelling techniques, but there has been relatively little evaluation of predictive performance, data requirements, or type of inference of these models. Empirical data for woodland caribou Rangifer tarandus caribou was used to examine four species distribution models, namely a qualitati

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Gavashelishvili, Alexander, and Zura Javakhishvili. "Combining radio-telemetry and random observations to model the habitat of Near Threatened Caucasian grouseTetrao mlokosiewiczi." Oryx 44, no. 4 (October 2010): 491–500. http://dx.doi.org/10.1017/s0030605310000979.

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AbstractThe distribution of the Near Threatened Caucasian grouseTetrao mlokosiewiczi,endemic to the Caucasus, was examined to model the species’ nesting habitat, and thus facilitate its conservation and the identification of Key Biodiversity Areas in the Caucasus. The species’ occurrence was defined by field surveys and radio-telemetry. Data were managed and analysed using a geographical information system and various modelling techniques. Grouse locations were divided into training and testing datasets. Habitat variables measured at training locations were used to develop models, and testing

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Debinski, Diane, Mark Jakubaukas, and Kelly Kindscher. "Modeling Spatial and Temporal Dynamics of Montane Meadows and Biodiversity in the Greater Yellowstone Ecosystem." UW National Parks Service Research Station Annual Reports 22 (January 1, 1998): 59–64. http://dx.doi.org/10.13001/uwnpsrc.1998.3367.

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Our project is an examination of ecological dynamics in the Greater Yellowstone Ecosystem (GYE), concentrating specifically upon the spatial and temporal dynamics of montane meadow communities. We are examining both the abiotic aspects of these communities as well as the biodiversity of plant, bird and butterfly communities. Our long-term goal is to develop predictive species assemblage models based upon landscape level habitat analysis. This involves using intensive, local field sampling to test for relationships between species distribution patterns and remotely sensed data. This research in

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Debinski, Diane, Mark Jakubauskas, and Kelly Kindscher. "Modeling Spatial and Temporal Dynamics of Montane Meadows and Biodiversity in the Greater Yellowstone Ecosystem." UW National Parks Service Research Station Annual Reports 23 (January 1, 1999): 152–58. http://dx.doi.org/10.13001/uwnpsrc.1999.3399.

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Our project is an examination of ecological dynamics in the Greater Yellowstone Ecosystem (GYE), concentrating specifically upon the spatial and temporal dynamics of montane meadow communities. We are examining both the abiotic aspects of these communities as well as the biodiversity of plant, bird and butterfly communities. Our long-term goal is to develop predictive species assemblage models based upon landscape level habitat analysis. This involves using intensive, local field sampling to test for relationships between species distribution patterns and remotely sensed data. This research in

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