Relevant bibliographies by topics / Species distribution modeling (SDM)

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Species distribution modeling (SDM)'

Author: Grafiati
Published: 3 June 2025
Last updated: 31 July 2025

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Journal articles on the topic "Species distribution modeling (SDM)"

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Morales-Ramirez, Carlos A., and Pearlyn Y. Pang. "Using Open-Source Data in Correlative Species Distribution Modeling of Marine Species." American Biology Teacher 80, no. 6 (2018): 457–61. http://dx.doi.org/10.1525/abt.2018.80.6.457.

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Open-source data are information provided free online. It is gaining popularity in science research, especially for modeling species distribution. MaxEnt is an open-source software that models using presence-only data and environmental variables. These variables can also be found online and are generally free. Using all of these open-source data and tools makes species distribution modeling (SDM) more accessible. With the rapid changes our planet is undergoing, SDM helps understand future habitat suitability for species. Due to increasing interest in biogeographic research, SDM has increased f
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Senay, Senait D., and Susan P. Worner. "Multi-Scenario Species Distribution Modeling." Insects 10, no. 3 (2019): 65. http://dx.doi.org/10.3390/insects10030065.

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Correlative species distribution models (SDMs) are increasingly being used to predict suitable insect habitats. There is also much criticism of prediction discrepancies among different SDMs for the same species and the lack of effective communication about SDM prediction uncertainty. In this paper, we undertook a factorial study to investigate the effects of various modeling components (species-training-datasets, predictor variables, dimension-reduction methods, and model types) on the accuracy of SDM predictions, with the aim of identifying sources of discrepancy and uncertainty. We found tha
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Seo, Eugene, Rebecca A. Hutchinson, Xiao Fu, et al. "StatEcoNet: Statistical Ecology Neural Networks for Species Distribution Modeling." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 1 (2021): 513–21. http://dx.doi.org/10.1609/aaai.v35i1.16129.

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This paper focuses on a core task in computational sustainability and statistical ecology: species distribution modeling (SDM). In SDM, the occurrence pattern of a species on a landscape is predicted by environmental features based on observations at a set of locations. At first, SDM may appear to be a binary classification problem, and one might be inclined to employ classic tools (e.g., logistic regression, support vector machines, neural networks) to tackle it. However, wildlife surveys introduce structured noise (especially under-counting) in the species observations. If unaccounted for, t
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Lowen, J. Benjamin, Devorah R. Hart, Ryan R. E. Stanley, Sarah J. Lehnert, Ian R. Bradbury, and Claudio DiBacco. "Assessing effects of genetic, environmental, and biotic gradients in species distribution modelling." ICES Journal of Marine Science 76, no. 6 (2019): 1762–75. http://dx.doi.org/10.1093/icesjms/fsz049.

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Abstract To develop more reliable marine species distribution models (SDMs), we examine how genetic, climatic, and biotic interaction gradients give rise to prediction error in marine SDM. Genetic lineages with distinct ecological requirements spanning genetic gradients have yet to be treated separately in marine SDM, which are often constrained to modeling the potential distribution of one biological unit (e.g. lineage or species) at a time. By comparing SDM performance for the whole species or where observation and predictions were partitioned among geographically discontinuous genetic linea
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Støa, Bente, Rune Halvorsen, Jogeir N. Stokland, and Vladimir I. Gusarov. "How much is enough? Influence of number of presence observations on the performance of species distribution models." Sommerfeltia 39, no. 1 (2019): 1–28. http://dx.doi.org/10.2478/som-2019-0001.

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Abstract Species distribution modeling (SDM) can be useful for many applied purposes, e.g., mapping and monitoring of rare and endangered species. Sparse presence data are a recurrent, major obstacle to precise modeling of species distributions. Thus, knowing the minimum number of presences required to obtain reliable distribution models is of fundamental importance for applied use of SDM. This study uses a novel approach to assess the critical sample size (CSS) sufficient for an accurate prediction of species distributions with Maximum Entropy Modeling (MaxEnt). Large presence datasets for th
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Özkan Tümer, Y., I. Caglayan, and A. Yeşi̇l. "Taxonomic classification of tree species distribution models: a review and assessment." International Forestry Review 27, no. 1 (2025): 72–93. https://doi.org/10.1505/146554825839764913.

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Species Distribution Models (SDMs) are powerful tools for identifying key environmental factors that shape species ranges and predicting how those ranges may shift under changing climate conditions. Despite their broad utility, current Species Distribution Model (SDM) research on tree species often lacks a consistent framework for comparing methods and results, making it difficult to synthesize findings and inform best practices. To address this gap, we propose a new, six-category taxonomy (scale, location, tree species, data, data processing and modeling, and model calibration and evaluation)
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Rhodes, Charlotte G., Jose R. Loaiza, Luis Mario Romero, et al. "Anopheles albimanus (Diptera: Culicidae) Ensemble Distribution Modeling: Applications for Malaria Elimination." Insects 13, no. 3 (2022): 221. http://dx.doi.org/10.3390/insects13030221.

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In the absence of entomological information, tools for predicting Anopheles spp. presence can help evaluate the entomological risk of malaria transmission. Here, we illustrate how species distribution models (SDM) could quantify potential dominant vector species presence in malaria elimination settings. We fitted a 250 m resolution ensemble SDM for Anopheles albimanus Wiedemann. The ensemble SDM included predictions based on seven different algorithms, 110 occurrence records and 70 model projections. SDM covariates included nine environmental variables that were selected based on their importa
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Zhang, Feixue, Chunjing Wang, Chunhui Zhang, and Jizhong Wan. "Comparing the Performance of CMCC-BioClimInd and WorldClim Datasets in Predicting Global Invasive Plant Distributions." Biology 12, no. 5 (2023): 652. http://dx.doi.org/10.3390/biology12050652.

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Species distribution modeling (SDM) has been widely used to predict the distribution of invasive plant species based on bioclimatic variables. However, the specific selection of these variables may affect the performance of SDM. This investigation elucidates a new bioclimate variable dataset (i.e., CMCC-BioClimInd) for its use in SDM. The predictive performance of SDM that includes WorldClim and CMCC-BioClimInd was evaluated by AUC and omission rate and the explanatory power of both datasets was assessed by the jackknife method. Furthermore, the ODMAP protocol was used to record CMCC-BioClimIn
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Urbina-Cardona, Nicolás, Mary E. Blair, Maria C. Londoño, Rafael Loyola, Jorge Velásquez-Tibatá, and Hernan Morales-Devia. "Species Distribution Modeling in Latin America: A 25-Year Retrospective Review." Tropical Conservation Science 12 (January 2019): 194008291985405. http://dx.doi.org/10.1177/1940082919854058.

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Species distribution modeling (SDM) is a booming area of research that has had an exponential increase in use and development in recent years. We performed a search of scientific literature and found 5,533 documents published from 1993 to 2018 using SDM, representing a global network of 4,329 collaborating institutions from 155 countries, with Brazil and Mexico being in the top 10 of the most prolific countries globally. National Autonomous University of Mexico, Chinese Academy of Sciences, University of Kansas, and U.S. Geological Survey are the most prolific institutions worldwide. Latin Ame
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Johnson, Bethany A., Gonzalo E. Pinilla-Buitrago, Andrea Paz, Jamie M. Kass, Sarah I. Meenan, and Robert P. Anderson. "Creating and Optimizing Species Distribution Models: A Vignette for Wallace Ecological Modeling Application v2.0." Lessons in Conservation 13 (2023): 76–118. https://doi.org/10.5531/cbc.linc.13.1.6.

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Species distribution modeling (SDM) enables ecologists and conservation scientists to make range estimates for species of concern, as well as predictions of potential range in unsampled areas and for different time periods. Although advances in model building and evaluation are widespread in the ecology and evolution literature, most cutting-edge modeling methods are inaccessible to those who cannot read and write computer code, resulting in a “barrier to use” for many who would like to apply SDM to their research or to conservation efforts. The Wallace ecological modeling application, impleme
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Dissertations / Theses on the topic "Species distribution modeling (SDM)"

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Flessner, Brandon P. "SPECIES DISTRIBUTION MODELING OF AMERICAN BEECH (FAGUS GRANDIFOLIA EHRH.) DISTRIBUTION IN SOUTHWESTERN OHIO." Miami University / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=miami1399040680.

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

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Subsistence fishing is a vital component of Alaska’s North Slope borough economy and culture that is being threatened by human disturbance. These threats mean the fish must be protected, but the size of the region makes conservation planning difficult. Fortunately, advances in species distribution models (SDMs), environmental DNA (eDNA), and remote sensing technologies provide potential to better understand species’ needs and guide management. The objectives of my study were to: (1) map the current habitat suitability for twelve fish species, occurring in Alaska’s North Slope,(2) determine if
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Urvois, Teddy. "Structure génétique et modélisation de la distribution des populations de deux espèces invasives de Xylosandrus (Scolytinae - Xyleborini) : deux espèces proches aux histoires d’invasion différentes." Electronic Thesis or Diss., Orléans, 2022. https://theses.univ-orleans.fr/prive/accesESR/2022ORLE1031_va.pdf.

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Xylosandrus compactus et X. crassiusculus sont deux scolytes originaires d’Asie du Sud-Est et invasifs sur plusieurs continents, dont la biologie et l’écologie atypiques favorisent l’invasion. Une approche pluridisciplinaire a été utilisée au cours de cette thèse afin (i) d’identifier l’origine des populations invasives et leurs routes d’invasion, et (ii) de déterminer les zones dans lesquelles elles pourraient s'étendre et s’établir. Les routes d’invasion ont été retracées à l’aide d’un marqueur mitochondrial et de marqueurs génomiques, et les zones favorables à l’établissement de chaque espè
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Sheehan, Meghan Marie. "Determining Drivers for Wildebeest (Connochaetes taurinus) Distribution in the Masai Mara National Reserve and Surrounding Group Ranches." Miami University / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=miami1452550498.

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Fournier, Alice. "Modéliser et prédire les invasions biologiques." Thesis, Université Paris-Saclay (ComUE), 2018. http://www.theses.fr/2018SACLS144/document.

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Les invasions biologiques, deuxième cause de perte de biodiversité à l’échelle mondiale, représentent un risque majeur auquel nos sociétés doivent faire face. On parle d’invasion biologique lorsque des activités humaines permettent à une espèce de franchir des barrières qui jusqu’alors limitaient sa dispersion ou sa multiplication, entrainant une explosion géographique et démographique de l’espèce dans un nouvel écosystème et s’accompagnant éventuellement d’impacts économiques, sociétaux ou écologiques. La façon la plus efficace et la moins coûteuse de limiter les impacts causés par les espèce
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Dal, Maso Elisa. "Epidemiology and control strategies applied to ash dieback and chestnut ink disease." Doctoral thesis, Università degli studi di Padova, 2015. http://hdl.handle.net/11577/3424092.

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Main goal of forest diseases’ management is to reduce economic, biological and aesthetic damages and biodiversity loss caused by plant parasites. The many strategies used can be grouped under two main actions, prevention (prophylaxis in some early writings) and therapy (treatment or cure). Prevention is limited primarily by the lack of knowledge of the organisms involved, including host plants. Mathematical models have been used to extend the understanding of plant disease epidemiology on a number of fronts, providing an opportunity for a more rational use of resources on expensive field trial
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Serrano, Atuesta Yuliett Marcela. "Patterns of distribution of tree species in the neotropical lowland rainforest biome." Thesis, University of Edinburgh, 2018. http://hdl.handle.net/1842/31237.

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This thesis aims to explore distributional patterns of tree species in the neotropical lowland rain forest biome based on diversity analyses, dated phylogenies and species distribution models, using the family Sapotaceae as a case study. Sapotaceae is an abundant and diverse group in the neotropical lowland rain forest and its distributional patterns are representative of other tree clades in this biome. These characteristics make this family a good model to test ecological and biogeographic hypothesis in neotropical rain forests. An analysis of beta-diversity measured by the number of shared
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Dutrieux, Mariane. "Spatio-temporal species distribution modeling: Application to invasive alien species’ monitoring." Thesis, KTH, Hållbar utveckling, miljövetenskap och teknik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-224319.

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The developments of species distribution modeling techniques have brought new opportunities in the field of biological invasion management. In particular, statistical niche modeling for spatio-temporal predictions of species’ distribution is a widely spread tool that has proved its efficiency. The main purpose of this Master thesis is to study applicability of species distribution modeling to invasive alien species, with the aim of supporting efficient decision-making for their prevention. Some research questions are: how useful can species distribution modeling be for invasives’ prevention? I
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Andrade, André Felipe Alves de. "Estimativa da vulnerabilidade dos corais brasileiros." Universidade Federal de Goiás, 2016. http://repositorio.bc.ufg.br/tede/handle/tede/5592.

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Submitted by Cláudia Bueno (claudiamoura18@gmail.com) on 2016-05-19T19:46:17Z No. of bitstreams: 2 Dissertação - André Felipe Alves de Andrade - 2016.pdf: 2007118 bytes, checksum: 69341ce5bc6c459857d1feff5d92366e (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5)<br>Approved for entry into archive by Luciana Ferreira (lucgeral@gmail.com) on 2016-05-20T13:54:17Z (GMT) No. of bitstreams: 2 Dissertação - André Felipe Alves de Andrade - 2016.pdf: 2007118 bytes, checksum: 69341ce5bc6c459857d1feff5d92366e (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714
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Bracken, Jason. "A Consensus Model for Predicting the Distribution of the Threatened Plant Telephus Spurge (Euphorbia Telephioides)." Miami University / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=miami1480622681613979.

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Books on the topic "Species distribution modeling (SDM)"

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Modeling of Species Distribution and Biodiversity in Forests. MDPI, 2021. http://dx.doi.org/10.3390/books978-3-0365-1180-1.

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Applied Hierarchical Modeling in Ecology: Analysis of Distribution, Abundance and Species Richness in R and BUGS. Elsevier, 2021. http://dx.doi.org/10.1016/c2015-0-04070-9.

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Royle, J. Andrew, and Marc Kery. Applied Hierarchical Modeling in Ecology: Analysis of Distribution, Abundance and Species Richness in R and Bugs - Prelude and Static Models. Elsevier Science & Technology Books, 2015.

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Royle, J. Andrew, and Marc Kery. Applied Hierarchical Modeling in Ecology : Analysis of Distribution, Abundance and Species Richness in R and BUGS : Volume 2: Dynamic and Advanced Models. Elsevier Science & Technology, 2020.

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Royle, J. Andrew, and Marc Kery. Applied Hierarchical Modeling in Ecology : Analysis of Distribution, Abundance and Species Richness in R and BUGS : Volume 2: Dynamic and Advanced Models. Elsevier Science & Technology Books, 2020.

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Applied Hierarchical Modeling in Ecology : Analysis of Distribution, Abundance and Species Richness in R and BUGS : Volume 2: Dynamic and Advanced Models. Elsevier Science & Technology, 2020.

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Newman, M. E. J., and R. G. Palmer. Modeling Extinction. Oxford University Press, 2003. http://dx.doi.org/10.1093/oso/9780195159455.001.0001.

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Developed after a meeting at the Santa Fe Institute on extinction modeling, this book comments critically on the various modeling approaches. In the last decade or so, scientists have started to examine a new approach to the patterns of evolution and extinction in the fossil record. This approach may be called "statistical paleontology," since it looks at large-scale patterns in the record and attempts to understand and model their average statistical features, rather than their detailed structure. Examples of the patterns these studies examine are the distribution of the sizes of mass extinct
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Royle, J. Andrew, and Marc Kery. Applied Hierarchical Modeling in Ecology : Analysis of Distribution, Abundance and Species Richness in R and BUGS Vol. 1 : Volume 1: Prelude and Static Models. Elsevier Science & Technology Books, 2015.

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Bethke, Craig M. Geochemical Reaction Modeling. Oxford University Press, 1996. http://dx.doi.org/10.1093/oso/9780195094756.001.0001.

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Geochemical reaction modeling plays an increasingly vital role in several areas of geoscience, from environmental geochemistry and petroleum geology to the study of geothermal and hydrothermal fluids. This book provides an up-to-date overview of the use of numerical methods to model reaction processes in the Earth's crust and on its surface. Early chapters develop the theoretical foundations of the field, derive a set of governing equations, and show how numerical methods can be used to solve these equations. Other chapters discuss the distribution of species in natural waters; methods for com
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Fitzpatrick, Matthew C., and Aaron M. Ellison. Estimating the exposure of carnivorous plants to rapid climatic change. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198779841.003.0028.

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Climatic change likely will exacerbate current threats to carnivorous plants. However, estimating the severity of climatic change is challenged by the unique ecology of carnivorous plants, including habitat specialization, dispersal limitation, small ranges, and small population sizes. We discuss and apply methods for modeling species distributions to overcome these challenges and quantify the vulnerability of carnivorous plants to rapid climatic change. Results suggest that climatic change will reduce habitat suitability for most carnivorous plants. Models also project increases in habitat su
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Book chapters on the topic "Species distribution modeling (SDM)"

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Pinto-Ledezma, Jesús N., and Jeannine Cavender-Bares. "Using Remote Sensing for Modeling and Monitoring Species Distributions." In Remote Sensing of Plant Biodiversity. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-33157-3_9.

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AbstractInterpolated climate surfaces have been widely used to predict species distributions and develop environmental niche models. However, the spatial coverage and density of meteorological sites used to develop these surfaces vary among countries and regions, such that the most biodiverse regions often have the most sparsely sampled climatic data. We explore the potential of satellite remote sensing (S-RS) products—which have consistently high spatial and temporal resolution and nearly global coverage—to quantify species-environment relationships that predict species distributions. We prop
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Barewar, Harish, Manish Kuntal Buragohain, and Suvha Lama. "Mapping the Impact of Climate Change on Eco-sensitive Hotspots Using Species Distribution Modelling (SDM): Gaps, Challenges, and Future Perspectives." In Ecosystem and Species Habitat Modeling for Conservation and Restoration. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-0131-9_4.

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Urban, Dean L. "Species Distribution Modeling." In Landscape Ecology. Springer Nature Switzerland, 2024. https://doi.org/10.1007/978-3-031-72251-6_2.

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Wimberly, Michael C. "Application—Species Distribution Modeling." In Geographic Data Science with R. Chapman and Hall/CRC, 2023. http://dx.doi.org/10.1201/9781003326199-12.

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Tiel, Nina van, Robin Zbinden, Emanuele Dalsasso, Benjamin Kellenberger, Loïc Pellissier, and Devis Tuia. "Multi-scale and Multimodal Species Distribution Modeling." In Lecture Notes in Computer Science. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-92387-6_10.

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Farashi, Azita, and Mohammad Alizadeh-Noughani. "Basic Introduction to Species Distribution Modelling." In Ecosystem and Species Habitat Modeling for Conservation and Restoration. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-0131-9_2.

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Evans, Jeffrey S., Melanie A. Murphy, Zachary A. Holden, and Samuel A. Cushman. "Modeling Species Distribution and Change Using Random Forest." In Predictive Species and Habitat Modeling in Landscape Ecology. Springer New York, 2010. http://dx.doi.org/10.1007/978-1-4419-7390-0_8.

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Zbinden, Robin, Nina van Tiel, Gencer Sumbul, Benjamin Kellenberger, and Devis Tuia. "MaskSDM: Adaptive Species Distribution Modeling Through Data Masking." In Lecture Notes in Computer Science. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-92387-6_14.

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Panunzi, Greta, Jafet Belmont, Janine Illian, and Sara Martino. "Species Distribution Modeling Approach for Biased Citizen Science Data." In Italian Statistical Society Series on Advances in Statistics. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-64447-4_64.

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Lawler, Josh J., Yolanda F. Wiersma, and Falk Huettmann. "Using Species Distribution Models for Conservation Planning and Ecological Forecasting." In Predictive Species and Habitat Modeling in Landscape Ecology. Springer New York, 2010. http://dx.doi.org/10.1007/978-1-4419-7390-0_14.

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Conference papers on the topic "Species distribution modeling (SDM)"

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Liu, Yajun, and Xianming Shi. "Stochastic Modeling of Service Life of Concrete Structures in Chloride-laden Environments." In CORROSION 2011. NACE International, 2011. https://doi.org/10.5006/c2011-11004.

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Abstract Chloride-induced rebar corrosion is a common degradation process for concrete infrastructure, which is a practical concern especially for cold-climate states and coastal areas. In this work, numeric models based on Finite Element Method (FEM) are utilized to study service life of concrete structures subject to chloride ingress. The stochastic nature of model inputs is taken into consideration. Specifically, the surface chloride concentrations and concrete cover depth follow the normal distribution; the diffusion coefficients obey the gamma distribution; and the actual chloride thresho
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Manvelidze, Nino, Medea Burjanadze, Lali Jgenti, and Natela Varshanidze. "SPECIES DIVERSITY OF HARMFUL BARK BEETLES IN SPRUCE FORESTS OF ADJARA REGION (GEORGIA)." In 24th SGEM International Multidisciplinary Scientific GeoConference 2024. STEF92 Technology, 2024. https://doi.org/10.5593/sgem2024v/3.2/s13.39.

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Several species of Bark beetles (Coleoptera: Scolytinae) are capable of causing significant amounts of tree mortality in conifer forests throughout much of the world and in the South Caucasian Mountain as well. In the paper, is discussed about species diversity of harmful bark beetles, which are damage and cause the decline of the Picea orientalis, in the conifer forest of Shuakhevi and Khulo municipalities of Adjara (Western Georgia), at an altitude of 700-1500 m a.s.l. This is one of the current problems in spruce forests of mentioned region. Field studies were carried out in Shuakhevi munic
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Ortiz, A., A. Ruiz-García, J. Genescá, and R. Montoya. "Acidification of the Electrolyte in the Carbon Steel/ Aluminum Alloys Galvanic Couple: Modeling and Experimental Study." In CORROSION 2021. AMPP, 2021. https://doi.org/10.5006/c2021-16334.

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Abstract An electrochemical model was developed to predict the transient distribution of species generated during corrosion of carbon steel (CS) /aluminum alloy (AA) galvanic couples under thin NaCl electrolyte films at room temperature (24 °C). Using specific geometrical configurations, strong acidification of the electrolyte, localized above the AA surface and close to the carbon steel electrode, was predicted. However, a small zone evolved (also above the AA surface) between the strong acidified area and the AA/CS joint, where the pH was neutral due to the OH- production on the CS surface.
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Engelhardt, G. R., D. D. Macdonald, and M. Urquidi-Macdonald. "Development of Fast Algoritms for Estimating Stress Corrosion Crack Growh Rate in Sentized Stainless Steels in Boiling Water Reactor Coolant Environments." In CORROSION 1999. NACE International, 1999. https://doi.org/10.5006/c1999-99452.

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Abstract A simplified method is proposed for modeling the chemistry and potential distribution in a stress corrosion crack in sensitized stainless steel in boiling water reactor (BWR) coolant environments. The model is based on an assumption that only those species that are present at the largest concentrations in the crevice determine the potential distribution down the crack. The advantage of this method is that it permits simplification of the mathematics and allows predictions to be made of the potential and concentration distributions without knowing various parameters, such as the equili
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Miyaji, Renato O., and Pedro L. P. Corrêa. "Interpreting ML in Ecology: A RAG-Based Approach to Explainability in Species Distribution Modeling." In Workshop de Computação Aplicada à Gestão do Meio Ambiente e Recursos Naturais. Sociedade Brasileira de Computação - SBC, 2025. https://doi.org/10.5753/wcama.2025.8219.

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Species Distribution Modeling (SDM) relies increasingly on Machine Learning (ML), but many models remain opaque, limiting their usability for non-experts. While SHAP and LIME improve interpretability, they still require technical expertise. This study proposes an agentic Retrieval-Augmented Generation (RAG) framework, integrating ML models (Logistic Regression, Random Forests, MLP), XAI techniques (SHAP, LIME), and a LLM-powered explanation system to enhance explainability. Using GoAmazon 2014/15 environmental data and GBIF species occurrences, we evaluated explanations based on completeness,
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Popović, Teodora, Nina B. Ćurčić, Snežana Đurđić, Gorica Stanojević, and Marko Raković. "IMPORTANCE OF SPECIES DISTRIBUTION MODELLING IN NATURE CONSERVATION: CASE STUDY OF GLACIAL RELICT THREE-TOED WOODPECKER „PICOIDES TRIDACTYLUS“." In Book of Abstracts and Contributed Papers. Geographical Institute "Jovan Cvijić" SASA, 2024. http://dx.doi.org/10.46793/csge5.24tp.

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Identifying geographic areas with habitats suitable for the presence of priority species is of essential importance in conservation planning. A useful tool to identify these areas is a species distribution modelling (SDM), which is a method that defines statistical relationship between species records and environmental variables in the localities where the species is present. To test the possibility of applying this method in conservation planning, this study focused on the Three-toed Woodpecker Picoides tridactylus (Linnaeus, 1758) (Piciformes: Picidae) because it is a glacial relict on the B
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Hassan, Anas M., Emad W. Al-Shalabi, Ahmed S. Adila, et al. "Surface Complexation Modeling for Low Salinity Polymer (LSP) Injection in Carbonate Reservoirs Under Harsh Conditions." In ADIPEC. SPE, 2023. http://dx.doi.org/10.2118/216501-ms.

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Abstract Low-Salinity Polymer (LSP) flooding is a hybrid enhanced-oil-recovery (EOR) technique, which can improve the displacement efficiency by synergistically combining the advantages of low-salinity (LS) waterflooding and polymer-injection methods. However, comprehensive design of the LSP technique at field-scale requires a predictive mechanistic model that captures the polymer-brine-rock (PBR) interactions accurately. So far, very few studies have described the effects of surface complexes, surface potential, and effluent concentrations of potential-determining-ions (PDIs) within the PBR-s
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Bieleveld, Michel J. M., Wilian F. Costa, and Antonio M. Saraiva. "Shaping an ecosystem for species distribution modeling." In MEDES '15: The 7th International Conference on Management of computational and collective IntElligence in Digital EcoSystems. ACM, 2015. http://dx.doi.org/10.1145/2857218.2857231.

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Nash, Thomas, and Aspen Olmsted. "shinySDM: Point and click species distribution modeling." In 2017 12th International Conference for Internet Technology and Secured Transactions (ICITST). IEEE, 2017. http://dx.doi.org/10.23919/icitst.2017.8356444.

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Phillips, Steven J., Miroslav Dudík, and Robert E. Schapire. "A maximum entropy approach to species distribution modeling." In Twenty-first international conference. ACM Press, 2004. http://dx.doi.org/10.1145/1015330.1015412.

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Reports on the topic "Species distribution modeling (SDM)"

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Aiello-Lammens, Matthew E., Robert Anderson, Mary E. Blair, et al. Species Distribution Modeling for Conservation Educators and Practitioners. American Museum of Natural History, 2023. http://dx.doi.org/10.5531/cbc.ncep.0184.

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Models that predict distributions of species by combining known occurrence records with digital layers of environmental variables have much potential for application in conservation. Through using this module, teachers will enable students to develop species distribution models, to apply the models across a series of analyses, and to interpret predictions accurately. In addition to its original components, this module features an updated and condensed synthesis document ("A Brief Introduction to Species Distribution Modeling for Conservation Educators and Practitioners," which provides theoret
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Payne, Kathleen, Sean Griffin, Susan Lyon, Robin Lopez, and Nicole Wayant. Species distribution modeling of Ixodes scapularis and associated pathogens in states east of the Mississippi River. Engineer Research and Development Center (U.S.), 2020. http://dx.doi.org/10.21079/11681/35615.

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Saltus, Christina, and Eric Britzke. Literature review : macrohabitat metrics to identify presence of chiroptera on the landscape in the United States. Engineer Research and Development Center (U.S.), 2022. http://dx.doi.org/10.21079/11681/45523.

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This special report reviews current scientific literature to identify the most commonly cited metrics used to describe the macrohabitat criteria important for Chiroptera presence in the United States. The review evaluates 69 scientific articles from 1994 to 2018. The most commonly cited metrics were divided into four main categories: tree-species-level metrics, landscape-level metrics, distance metrics, and topographic and atmospheric metrics. Of all metrics found, the top six most common metrics noted across all articles were percent canopy cover, diameter at breast height (DBH), forest type,
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Aiello-Lammens, Matthew E., Mary E. Blair, Bethany A. Johnson, Andrea Paz, and Richard Pearson. Modelado de Distribución de Especies para Educadores y Profesionales de la Conservación (Spanish). American Museum of Natural History, 2024. http://dx.doi.org/10.5531/cbc.ncep.0185.

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Esta es una actualización de “Species’ Distribution Modeling for Conservation Educators and Practitioners” (Pearson 2008). Esta actualización es una versión condensada del original, con referencias actualizadas y una introducción y un marco simplificados para reflejar los desarrollos recientes en el campo y, especialmente, para brindar mayor énfasis en los enfoques de aprendizaje automático para el modelado de distribución de especies.
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Brandt, Leslie A., Cait Rottler, Wendy S. Gordon, et al. 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, 2020. http://dx.doi.org/10.32747/2020.7204069.ch.

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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. Pro
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Heinz, Kevin, Itamar Glazer, Moshe Coll, Amanda Chau, and Andrew Chow. Use of multiple biological control agents for control of western flower thrips. United States Department of Agriculture, 2004. http://dx.doi.org/10.32747/2004.7613875.bard.

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The western flower thrips (WFT), Frankliniella occidentalis (Pergande), is a serious widespread pest of vegetable and ornamental crops worldwide. Chemical control for Frankliniella occidentalis (Pergande) (Thysanoptera: Thripidae) on floriculture or vegetable crops can be difficult because this pest has developed resistance to many insecticides and also tends to hide within flowers, buds, and apical meristems. Predatory bugs, predatory mites, and entomopathogenic nematodes are commercially available in both the US and Israel for control of WFT. Predatory bugs, such as Orius species, can suppre
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Or, Dani, Shmulik Friedman, and Jeanette Norton. Physical processes affecting microbial habitats and activity in unsaturated agricultural soils. United States Department of Agriculture, 2002. http://dx.doi.org/10.32747/2002.7587239.bard.

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experimental methods for quantifying effects of water content and other dynamic environmental factors on bacterial growth in partially-saturated soils. Towards this end we reviewed critically the relevant scientific literature and performed theoretical and experimental studies of bacterial growth and activity in modeled, idealized and real unsaturated soils. The natural wetting-drying cycles common to agricultural soils affect water content and liquid organization resulting in fragmentation of aquatic habitats and limit hydraulic connections. Consequently, substrate diffusion pathways to soil
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