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

Author: Grafiati

Published: 3 June 2025

Last updated: 31 July 2025

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1

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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2

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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3

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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4

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. YeşiÌ‡l. "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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9

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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11

Hayes, Mark A., Katharine Ozenberger, Paul M. Cryan, and Michael B. Wunder. "Not to Put Too Fine a Point on It — Does Increasing Precision of Geographic Referencing Improve Species Distribution Models for a Wide-Ranging Migratory Bat?" Acta Chiropterologica 17, no. 1 (2015): 159–69. https://doi.org/10.5281/zenodo.13457934.

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(Uploaded by Plazi for the Bat Literature Project) Bat specimens held in natural history museum collections can provide insights into the distribution of species. However, there are several important sources of spatial error associated with natural history specimens that may influence the analysis and mapping of bat species distributions. We analyzed the importance of geographic referencing and error correction in species distribution modeling (SDM) using occurrence records of hoary bats (Lasiurus cinereus). This species is known to migrate long distances and is a species of increasing concern

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Hayes, Mark A., Katharine Ozenberger, Paul M. Cryan, and Michael B. Wunder. "Not to Put Too Fine a Point on It — Does Increasing Precision of Geographic Referencing Improve Species Distribution Models for a Wide-Ranging Migratory Bat?" Acta Chiropterologica 17, no. 1 (2015): 159–69. https://doi.org/10.5281/zenodo.13457934.

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(Uploaded by Plazi for the Bat Literature Project) Bat specimens held in natural history museum collections can provide insights into the distribution of species. However, there are several important sources of spatial error associated with natural history specimens that may influence the analysis and mapping of bat species distributions. We analyzed the importance of geographic referencing and error correction in species distribution modeling (SDM) using occurrence records of hoary bats (Lasiurus cinereus). This species is known to migrate long distances and is a species of increasing concern

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Hayes, Mark A., Katharine Ozenberger, Paul M. Cryan, and Michael B. Wunder. "Not to Put Too Fine a Point on It — Does Increasing Precision of Geographic Referencing Improve Species Distribution Models for a Wide-Ranging Migratory Bat?" Acta Chiropterologica 17, no. 1 (2015): 159–69. https://doi.org/10.5281/zenodo.13457934.

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Abstract:

(Uploaded by Plazi for the Bat Literature Project) Bat specimens held in natural history museum collections can provide insights into the distribution of species. However, there are several important sources of spatial error associated with natural history specimens that may influence the analysis and mapping of bat species distributions. We analyzed the importance of geographic referencing and error correction in species distribution modeling (SDM) using occurrence records of hoary bats (Lasiurus cinereus). This species is known to migrate long distances and is a species of increasing concern

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14

Hayes, Mark A., Katharine Ozenberger, Paul M. Cryan, and Michael B. Wunder. "Not to Put Too Fine a Point on It — Does Increasing Precision of Geographic Referencing Improve Species Distribution Models for a Wide-Ranging Migratory Bat?" Acta Chiropterologica 17, no. 1 (2015): 159–69. https://doi.org/10.5281/zenodo.13457934.

Full text

Abstract:

(Uploaded by Plazi for the Bat Literature Project) Bat specimens held in natural history museum collections can provide insights into the distribution of species. However, there are several important sources of spatial error associated with natural history specimens that may influence the analysis and mapping of bat species distributions. We analyzed the importance of geographic referencing and error correction in species distribution modeling (SDM) using occurrence records of hoary bats (Lasiurus cinereus). This species is known to migrate long distances and is a species of increasing concern

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15

Hayes, Mark A., Katharine Ozenberger, Paul M. Cryan, and Michael B. Wunder. "Not to Put Too Fine a Point on It — Does Increasing Precision of Geographic Referencing Improve Species Distribution Models for a Wide-Ranging Migratory Bat?" Acta Chiropterologica 17, no. 1 (2015): 159–69. https://doi.org/10.5281/zenodo.13457934.

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(Uploaded by Plazi for the Bat Literature Project) Bat specimens held in natural history museum collections can provide insights into the distribution of species. However, there are several important sources of spatial error associated with natural history specimens that may influence the analysis and mapping of bat species distributions. We analyzed the importance of geographic referencing and error correction in species distribution modeling (SDM) using occurrence records of hoary bats (Lasiurus cinereus). This species is known to migrate long distances and is a species of increasing concern

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16

Ervin, Gary N., and D. Christopher Holly. "Examining Local Transferability of Predictive Species Distribution Models for Invasive Plants: An Example with Cogongrass (Imperata cylindrica)." Invasive Plant Science and Management 4, no. 4 (2011): 390–401. http://dx.doi.org/10.1614/ipsm-d-10-00077.1.

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AbstractSpecies distribution modeling is a tool that is gaining widespread use in the projection of future distributions of invasive species and has important potential as a tool for monitoring invasive species spread. However, the transferability of models from one area to another has been inadequately investigated. This study aimed to determine the degree to which species distribution models (SDMs) for cogongrass, developed with distribution data from Mississippi (USA), could be applied to a similar area in neighboring Alabama. Cogongrass distribution data collected in Mississippi were used

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17

Vasconcelos, Rodrigo N., Taimy Cantillo-Pérez, Washington J. S. Franca Rocha, et al. "Advances and Challenges in Species Ecological Niche Modeling: A Mixed Review." Earth 5, no. 4 (2024): 963–89. https://doi.org/10.3390/earth5040050.

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Species distribution modeling (SDM) is a vital tool for ecological and biogeographical research, allowing precise predictions of species distributions based on environmental variables. This study reviews the evolution of SDM techniques from 1985 to 2023, focusing on model development and applications in conservation, climate change adaptation, and invasive species management. We employed a mixed review with bibliometric and systematic element approaches using the Scopus database, analyzing 982 documents from 275 sources. The MaxEnt model emerged as the most frequently used technique, applied i

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18

Kamino, Luciana H. Y., João Renato Stehmann, Silvana Amaral, et al. "Challenges and perspectives for species distribution modelling in the neotropics." Biology Letters 8, no. 3 (2011): 324–26. http://dx.doi.org/10.1098/rsbl.2011.0942.

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The workshop ‘ Species distribution models: applications, challenges and perspectives ’ held at Belo Horizonte (Brazil), 29–30 August 2011, aimed to review the state-of-the-art in species distribution modelling (SDM) in the neotropical realm. It brought together researchers in ecology, evolution, biogeography and conservation, with different backgrounds and research interests. The application of SDM in the megadiverse neotropics—where data on species occurrences are scarce—presents several challenges, involving acknowledging the limitations imposed by data quality, including surveys as an inte

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Cosandey, Vivien, Olivier Broennimann, and Antoine Guisan. "Modeling the distribution of coprophagous beetle species in the Western Swiss Alps." Alpine Entomology 6 (July 6, 2022): 25–38. https://doi.org/10.3897/alpento.6.83730.

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Coprophagous beetles are essential for fecal matter removal and are thus considered key ecosystem services providers. Yet, our knowledge of these beetles' distribution and ecology remains very limited. Here, we used Species Distribution Models (SDM) to investigate the species-environment relationships (i.e. their niche) and predict the geographic distribution of coprophagous beetles in the Western Swiss Alps. We used our own sampled data and existing national data from the Swiss faunal database to calibrate, for each species, a regional and a national SDM respectively. In both models, the best

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Lee, Wang-Hee, Jae-Woo Song, Sun-Hee Yoon, and Jae-Min Jung. "Spatial Evaluation of Machine Learning-Based Species Distribution Models for Prediction of Invasive Ant Species Distribution." Applied Sciences 12, no. 20 (2022): 10260. http://dx.doi.org/10.3390/app122010260.

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Recent advances in species distribution models (SDMs) associated with artificial intelligence (AI) and increased volumes of available data for model variables have allowed reliable evaluation of the potential distribution of any species. A reliable SDM requires suitable occurrence records and variables with optimal model structures. In this study, we developed three different machine learning-based SDMs [MaxEnt, random forest (RF), and multi-layer perceptron (MLP)] to predict the global potential distribution of two invasive ants under current and future climates. These SDMs showed that the po

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Turan, Cemal. "Impacts of climate change and species distribution modelling: Future scenarios to invasive alien lionfish distribution in the Mediterranean Sea." Biodiversity Information Science and Standards 3 (June 26, 2019): e37363. https://doi.org/10.3897/biss.3.37363.

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The progress on species distribution modelling (SDM) methods has brought new insights into the field of biological invasion management. In particular, statistical niche modelling, for spatio-temporal predictions of marine species' distribution, is an increasingly used tool, supporting efficient decision-making for prevention and conservation. Earth's climate has changed significantly in the last century and the number of alien species penetrating from Indo-Pacific Ocean and South part of the Atlantic in the Mediterranean will continue to increase over the next decades. The purpose of the prese

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Bae, Mi-Jung, Seo-Ha Kim, Dae-Seong Lee, Da-Young Lee, and Young-Seuk Park. "Developing a Robust SDM Pipeline for Predicting Climate-Driven Shifts in Freshwater Fish Distributions." ARPHA Conference Abstracts 8 (May 28, 2025): e150278. https://doi.org/10.3897/aca.8.e150278.

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Understanding climate-induced shifts in freshwater biodiversity requires rigorous modeling approaches. This study applies a spatially explicit species distribution modeling (SDM) framework, incorporating high-resolution (1 km) environmental predictors and 3,307 field survey sites collected between 2016 and 2022 in South Korea. Using Maxent modeling, we assessed the potential distribution shifts of 130 freshwater fish species under three climate scenarios (SSP1-2.6, SSP3-7.0 and SSP5-8.5). To enhance model accuracy and applicability across regions, we implemented a robust preprocessing pipeline

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Karyakin, I. V., and K. I. Knizhov. "Species Distribution, Abundance and Survival Modeling: New Opportunities and Methods." Raptors Conservation, no. 2 (2023): 347–57. http://dx.doi.org/10.19074/1814-8654-2023-2-347-357.

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Many large raptor species are currently rare and most of them are endangered, and thus details of their distribution, abundance, and survival are the most important indicators for planning conservation and restoration measures and assessing the impacts of anthropogenic transformation of the environment and/or climate change on the populations of these species. Abundance and spatial distribution of the birds under study are determined during field surveys. At the result, we obtain the distribution density in individuals, pairs, nests per unit area (for example, pairs/100 km2), or the distance b

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Kariyawasam, Champika S., Lalit Kumar, and Sujith S. Ratnayake. "Invasive Plants Distribution Modeling: A Tool for Tropical Biodiversity Conservation With Special Reference to Sri Lanka." Tropical Conservation Science 12 (January 2019): 194008291986426. http://dx.doi.org/10.1177/1940082919864269.

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The potential threats and habitat preferences of noxious plants in tropical countries are poorly known. Species distribution modeling (SDM) is a robust tool that can be used in conservation planning for early detection of invasion risks. However, the use of SDM for the strategic management of increasing risks of such plant invasions in Sri Lanka has not been undertaken due to several underlying reasons including the long-lasting data gap, technical, technological, and financial issues. In addition, the literature relevant to SDM applications in the country is substantially poor, scattered, and

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Entiauspe-Neto, Omar Machado, Márcia Ferret Renner, Conrado Mario-da-Rosa, Arthur Diesel Abegg, Daniel Loebmann, and Thales De Lema. "Redescription, geographic distribution and ecological niche modeling of Elapomorphus wuchereri (Serpentes: Dipsadidae)." Phyllomedusa: Journal of Herpetology 16, no. 2 (2017): 225. http://dx.doi.org/10.11606/issn.2316-9079.v16i2p225-242.

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The original description of Elapomorphus wuchereri Günther, 1861 included a drawing and brief comments about the morphology of three specimens; two of the latter belong to another species and the holotype is lost. Based on the discovery of new specimens, we redescribe Elapomorphus wuchereri and designate a neotype. We discuss the variation and the taxonomic history of the species, and based on the results of a species distribution model analysis (SDM), we describe the distribution, extent of occurrence, and conservation status.

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Booth, Trevor H. "The Origins of Modern Species Distribution Modelling: Some Comments on the Vasconcelos et al. (2024) Review." Earth 6, no. 1 (2025): 12. https://doi.org/10.3390/earth6010012.

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A recent review of species distribution modelling (SDM) published in Earth contains much useful information. However, the introductory paragraphs lack basic information about the first SDM package called BIOCLIM, which became available in January 1984. For example, BIOCLIM-related advances underpinned the development of the most used SDM variables and data. The first SDM climate change studies published in 1988 highlighted the importance of ex situ and native distribution data. This brief note highlights the importance of the early SDM work and its continuing relevance.

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Valdez-Mondragón, Alejandro, and Mayra R. Cortez-Roldán. "Effects of climate change and species distribution modeling of Loxosceles (Araneae: Sicariidae) from Central Mexico." Revista Mexicana de Biodiversidad 95 (September 23, 2024): e955376. http://dx.doi.org/10.22201/ib.20078706e.2024.95.5376.

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With 40 of the 149 described species, Mexico harbors the highest diversity of the spider genus Loxosceles. However,knowledge about these spiders’ distribution patterns in a climate change (CC) context is poorly known. In this study,the distributions of 4 species from Central Mexico, Loxosceles malintzi, L. misteca, L. tenochtitlan and L. zapoteca, were estimated and evaluated based on species distribution modeling (SDM) and the possible effects of CC. Two future scenarios were simulated (years 2050 and 2080) to show possible increases or reductions in species distributions. The most important

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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 (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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Pshegusov, R. Kh. "From Spatial Distribution to Ecological Niche: Modeling Issues within the Correlation Approach." Известия Российской академии наук. Серия биологическая, no. 8 (December 1, 2023): 16–24. http://dx.doi.org/10.31857/s1026347023600802.

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One of the most important tasks in modern ecology theory is the formalization of the ecological niche. Advances in spatial analysis techniques and the availability of global databases on biodiversity and environmental parameters provide an unprecedented opportunity to integrate ecological niche components within a correlational modeling approach. The paper presents methods for formalizing biotic, spatial (environmental accessibility) and anthropogenic restrictions on the distribution of biological objects (components of an ecological niche) when constructing SDM (Species distribution modeling)

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HUAMÁN-MERA, ALEXANDER, YURIKO SUMIYO MURILLO-DOMEN, DANNA Z. AMAYA-REYES, FLOR Y. SAUCEDO-BURGA, PEDRO MANUEL VILLA, and LEOPOLDO P. VÁSQUEZ-NÚÑEZ. "Update of the taxonomic circumscription and biogeographical delimitation range of Neltuma pallida (Fabaceae) to the Seasonally Dry Forests of Marañon from Peru." Phytotaxa 691, no. 1 (2025): 1–18. https://doi.org/10.11646/phytotaxa.691.1.1.

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Several specimens collected along Seasonally Dry Tropical Forests (SDTF) from Peru have been named as Neltuma pallida (Prosopis pallida before); however, morphological and ecological traits are different among these specimens. The update of the taxonomic circumscription and biogeographical delimitation of N. pallida are presented here based on morphological characteristics and Species Distribution Modeling (SDM) based on the principle of Maximum Entropy and 19 bioclimatic variables from historical data. 262 specimens distributed along the SDTF were morphologically evaluated, and 62 specimens c

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Singleton, Alyson L., Caroline K. Glidden, Andrew J. Chamberlin, et al. "Species distribution modeling for disease ecology: A multi-scale case study for schistosomiasis host snails in Brazil." PLOS Global Public Health 4, no. 8 (2024): e0002224. http://dx.doi.org/10.1371/journal.pgph.0002224.

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Species distribution models (SDMs) are increasingly popular tools for profiling disease risk in ecology, particularly for infectious diseases of public health importance that include an obligate non-human host in their transmission cycle. SDMs can create high-resolution maps of host distribution across geographical scales, reflecting baseline risk of disease. However, as SDM computational methods have rapidly expanded, there are many outstanding methodological questions. Here we address key questions about SDM application, using schistosomiasis risk in Brazil as a case study. Schistosomiasis i

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Wunderlich, Rainer Ferdinand, Yu-Pin Lin, Johnathen Anthony, and Joy R. Petway. "Two alternative evaluation metrics to replace the true skill statistic in the assessment of species distribution models." Nature Conservation 35 (June 20, 2019): 97–116. https://doi.org/10.3897/natureconservation.35.33918.

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Model evaluation metrics play a critical role in the selection of adequate species distribution models for conservation and for any application of species distribution modelling (SDM) in general. The responses of these metrics to modelling conditions, however, are rarely taken into account. This leads to inadequate model selection, downstream analyses and uniformed decisions. To aid modellers in critically assessing modelling conditions when choosing and interpreting model evaluation metrics, we analysed the responses of the True Skill Statistic (TSS) under a variety of presence-background mod

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Zamorano, Daniel, Fabio A. Labra, Marcelo Villarroel, et al. "Assessing the effect of fish size on species distribution model performance in southern Chilean rivers." PeerJ 7 (December 6, 2019): e7771. http://dx.doi.org/10.7717/peerj.7771.

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Despite its theoretical relationship, the effect of body size on the performance of species distribution models (SDM) has only been assessed in a few studies, and to date, the evidence shows unclear results. In this context, Chilean fishes provide an ideal case to evaluate this relationship due to their short size (fishes between 5 cm and 40 cm) and conservation status, providing evidence for species at the lower end of the worldwide fish size distribution and representing a relevant management tool for species conservation. We assessed the effect of body size on the performance of SDM in nine

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Delgado‐Jaramillo, Mariana, Ludmilla M. S. Aguiar, Ricardo B. Machado, Enrico Bernard, and Marion Pfeifer. "Assessing the distribution of a species‐rich group in a continental‐sized megadiverse country: Bats in Brazil." Diversity and Distributions 26, no. 5 (2020): 632–43. https://doi.org/10.5281/zenodo.13467705.

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(Uploaded by Plazi for the Bat Literature Project) Aim: The effective conservation and management of any given species frequently requires basic knowledge on its distribution, which is problematic for highly mobile, species- and ecologically-rich groups, like bats. Moreover, to produce detailed distributions for continental-sized, bat species-rich countries, like Brazil, is difficult, especially considering that ~60% of the country has not a single formal bat record. Using Species Distribution Modelling (SDM), we assessed the potential distribution of >100 species of Brazilian bats.

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Delgado‐Jaramillo, Mariana, Ludmilla M. S. Aguiar, Ricardo B. Machado, Enrico Bernard, and Marion Pfeifer. "Assessing the distribution of a species‐rich group in a continental‐sized megadiverse country: Bats in Brazil." Diversity and Distributions 26, no. 5 (2020): 632–43. https://doi.org/10.5281/zenodo.13467705.

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(Uploaded by Plazi for the Bat Literature Project) Aim: The effective conservation and management of any given species frequently requires basic knowledge on its distribution, which is problematic for highly mobile, species- and ecologically-rich groups, like bats. Moreover, to produce detailed distributions for continental-sized, bat species-rich countries, like Brazil, is difficult, especially considering that ~60% of the country has not a single formal bat record. Using Species Distribution Modelling (SDM), we assessed the potential distribution of >100 species of Brazilian bats.

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Delgado‐Jaramillo, Mariana, Ludmilla M. S. Aguiar, Ricardo B. Machado, Enrico Bernard, and Marion Pfeifer. "Assessing the distribution of a species‐rich group in a continental‐sized megadiverse country: Bats in Brazil." Diversity and Distributions 26, no. 5 (2020): 632–43. https://doi.org/10.5281/zenodo.13467705.

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Abstract:

(Uploaded by Plazi for the Bat Literature Project) Aim: The effective conservation and management of any given species frequently requires basic knowledge on its distribution, which is problematic for highly mobile, species- and ecologically-rich groups, like bats. Moreover, to produce detailed distributions for continental-sized, bat species-rich countries, like Brazil, is difficult, especially considering that ~60% of the country has not a single formal bat record. Using Species Distribution Modelling (SDM), we assessed the potential distribution of >100 species of Brazilian bats.

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37

Delgado‐Jaramillo, Mariana, Ludmilla M. S. Aguiar, Ricardo B. Machado, Enrico Bernard, and Marion Pfeifer. "Assessing the distribution of a species‐rich group in a continental‐sized megadiverse country: Bats in Brazil." Diversity and Distributions 26, no. 5 (2020): 632–43. https://doi.org/10.5281/zenodo.13467705.

Full text

Abstract:

(Uploaded by Plazi for the Bat Literature Project) Aim: The effective conservation and management of any given species frequently requires basic knowledge on its distribution, which is problematic for highly mobile, species- and ecologically-rich groups, like bats. Moreover, to produce detailed distributions for continental-sized, bat species-rich countries, like Brazil, is difficult, especially considering that ~60% of the country has not a single formal bat record. Using Species Distribution Modelling (SDM), we assessed the potential distribution of >100 species of Brazilian bats.

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38

Delgado‐Jaramillo, Mariana, Ludmilla M. S. Aguiar, Ricardo B. Machado, Enrico Bernard, and Marion Pfeifer. "Assessing the distribution of a species‐rich group in a continental‐sized megadiverse country: Bats in Brazil." Diversity and Distributions 26, no. 5 (2020): 632–43. https://doi.org/10.5281/zenodo.13467705.

Full text

Abstract:

(Uploaded by Plazi for the Bat Literature Project) Aim: The effective conservation and management of any given species frequently requires basic knowledge on its distribution, which is problematic for highly mobile, species- and ecologically-rich groups, like bats. Moreover, to produce detailed distributions for continental-sized, bat species-rich countries, like Brazil, is difficult, especially considering that ~60% of the country has not a single formal bat record. Using Species Distribution Modelling (SDM), we assessed the potential distribution of >100 species of Brazilian bats.

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Pires-Oliveira, João Carlos, Hugo Bampi, Matheus Souza Lima-Ribeiro, and Pedro Vasconcellos Eisenlohr. "Sampling Bias Worsen the Predictive Ability of Niche Models." Revista de Gestão Social e Ambiental 18, no. 1 (2023): e04240. http://dx.doi.org/10.24857/rgsa.v18n1-039.

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Purpose: Ecological Niche Modeling (ENM) and Species Distribution Modeling (SDM) have become powerful tools in biology, biogeography, paleoecology and biodiversity conservation. ENM and SDM are evaluated using metrics that take into account the errors and successes of the models in predicting the presence or absence of species in certain locations. Here, we evaluate the effects of sampling bias on the relationship between evaluative metrics and the predictive capacity of models. Theoretical framework: ENM and SDM are powerful tools with extensive potential for use, but in order for them to pro

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Bendjeddou, Mohammed Lamine, Idriss Bouam, Stéphane Aulagnier, et al. "First record of the lesser horseshoe bat, Rhinolophus hipposideros (Borkhausen, 1797), in Libya and potential distribution in North Africa." Mammalia 86, no. 4 (2022): 328–32. https://doi.org/10.5281/zenodo.13421158.

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(Uploaded by Plazi for the Bat Literature Project) The lesser horseshoe bat has a broad distribution in warm temperate regions of Europe and Western Asia, and a patchy distribution in Africa. Common in the north-western part of North Africa, the species is missing more to the east. Hereby we report the first record in Libya, considerably extending its known geographic range. Additionally, we performed a species distribution modelling (SDM) analysis to explore its potential distribution in North Africa. The final SDM depicted a relatively wellknown distribution and predicted that the suitable b

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Bendjeddou, Mohammed Lamine, Idriss Bouam, Stéphane Aulagnier, et al. "First record of the lesser horseshoe bat, Rhinolophus hipposideros (Borkhausen, 1797), in Libya and potential distribution in North Africa." Mammalia 86, no. 4 (2022): 328–32. https://doi.org/10.5281/zenodo.13421158.

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Abstract:

(Uploaded by Plazi for the Bat Literature Project) The lesser horseshoe bat has a broad distribution in warm temperate regions of Europe and Western Asia, and a patchy distribution in Africa. Common in the north-western part of North Africa, the species is missing more to the east. Hereby we report the first record in Libya, considerably extending its known geographic range. Additionally, we performed a species distribution modelling (SDM) analysis to explore its potential distribution in North Africa. The final SDM depicted a relatively wellknown distribution and predicted that the suitable b

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Bendjeddou, Mohammed Lamine, Idriss Bouam, Stéphane Aulagnier, et al. "First record of the lesser horseshoe bat, Rhinolophus hipposideros (Borkhausen, 1797), in Libya and potential distribution in North Africa." Mammalia 86, no. 4 (2022): 328–32. https://doi.org/10.5281/zenodo.13421158.

Full text

Abstract:

(Uploaded by Plazi for the Bat Literature Project) The lesser horseshoe bat has a broad distribution in warm temperate regions of Europe and Western Asia, and a patchy distribution in Africa. Common in the north-western part of North Africa, the species is missing more to the east. Hereby we report the first record in Libya, considerably extending its known geographic range. Additionally, we performed a species distribution modelling (SDM) analysis to explore its potential distribution in North Africa. The final SDM depicted a relatively wellknown distribution and predicted that the suitable b

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Bendjeddou, Mohammed Lamine, Idriss Bouam, Stéphane Aulagnier, et al. "First record of the lesser horseshoe bat, Rhinolophus hipposideros (Borkhausen, 1797), in Libya and potential distribution in North Africa." Mammalia 86, no. 4 (2022): 328–32. https://doi.org/10.5281/zenodo.13421158.

Full text

Abstract:

(Uploaded by Plazi for the Bat Literature Project) The lesser horseshoe bat has a broad distribution in warm temperate regions of Europe and Western Asia, and a patchy distribution in Africa. Common in the north-western part of North Africa, the species is missing more to the east. Hereby we report the first record in Libya, considerably extending its known geographic range. Additionally, we performed a species distribution modelling (SDM) analysis to explore its potential distribution in North Africa. The final SDM depicted a relatively wellknown distribution and predicted that the suitable b

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44

Bendjeddou, Mohammed Lamine, Idriss Bouam, Stéphane Aulagnier, et al. "First record of the lesser horseshoe bat, Rhinolophus hipposideros (Borkhausen, 1797), in Libya and potential distribution in North Africa." Mammalia 86, no. 4 (2022): 328–32. https://doi.org/10.5281/zenodo.13421158.

Full text

Abstract:

(Uploaded by Plazi for the Bat Literature Project) The lesser horseshoe bat has a broad distribution in warm temperate regions of Europe and Western Asia, and a patchy distribution in Africa. Common in the north-western part of North Africa, the species is missing more to the east. Hereby we report the first record in Libya, considerably extending its known geographic range. Additionally, we performed a species distribution modelling (SDM) analysis to explore its potential distribution in North Africa. The final SDM depicted a relatively wellknown distribution and predicted that the suitable b

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45

Bendjeddou, Mohammed Lamine, Idriss Bouam, Stéphane Aulagnier, et al. "First record of the lesser horseshoe bat, Rhinolophus hipposideros (Borkhausen, 1797), in Libya and potential distribution in North Africa." Mammalia 86, no. 4 (2022): 328–32. https://doi.org/10.5281/zenodo.13421158.

Full text

Abstract:

(Uploaded by Plazi for the Bat Literature Project) The lesser horseshoe bat has a broad distribution in warm temperate regions of Europe and Western Asia, and a patchy distribution in Africa. Common in the north-western part of North Africa, the species is missing more to the east. Hereby we report the first record in Libya, considerably extending its known geographic range. Additionally, we performed a species distribution modelling (SDM) analysis to explore its potential distribution in North Africa. The final SDM depicted a relatively wellknown distribution and predicted that the suitable b

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Sutomo, M. H. Saputra, and N. Humaida. "Potential future distribution of Scirpophaga incertulas (Walker) in Indonesia." IOP Conference Series: Earth and Environmental Science 1182, no. 1 (2023): 012007. http://dx.doi.org/10.1088/1755-1315/1182/1/012007.

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Abstract Scircpophaga incertulas is a caterpillar that lives in rice stalks and can damage rice crops from seedling to maturity. One factor that influences this pest’s presence is the climatic factor. This study aimed to map the future potential distribution of Scircpophaga incertulas (2100). The method utilized in this study was the Species Distribution Model (SDM) from the web-based modeling platform Ecocommons by using the Artificial Neural Network (ANN). For current and climatic projections (the year 2100), the open-source climatic data from CliMond were used. The ANN result shows the clim

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Ikeda, Kentaro, and Takeshi Osawa. "Predicting disease occurrence of cabbage Verticillium wilt in monoculture using species distribution modeling." PeerJ 8 (November 17, 2020): e10290. http://dx.doi.org/10.7717/peerj.10290.

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Background Although integrated pest management (IPM) is essential for conservation agriculture, this method can be inadequate for severely infected fields. The ability to predict the potential occurrence of severe infestation of soil-borne disease would enable farmers to adopt suitable methods for high-risk areas, such as soil disinfestation, and apply other options for lower risk areas. Recently, researchers have used species distribution modeling (SDM) to predict the occurrence of target plant and animal species based on various environmental variables. In this study, we applied this techniq

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Arushi, Lohani, Suneet Naithani Dr., G. Areendran Dr., and Joshi Sunny. "SPECIES DISTRIBUTION MODELING OF MUSK DEER USING REMOTE SENSING AND G.I.S, UTTARAKHAND." International Journal of Life Sciences Research 10, no. 4 (2022): 47–56. https://doi.org/10.5281/zenodo.7335477.

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<strong>Abstract:</strong> Musk deer <em>(Moschus chrysogaster)</em> is considered Endangered by International Union for Conservation of Nature (IUCN) and is under Schedule-I of the Indian Wildlife (Protection) Act, 1972, because of its illicit hunting for musk as well as habitat loss. The present study aims to analyze the present distribution pattern of Musk Deer in the Himalayan region of Uttarakhand. Precipitation of the driest month (Bio14), mean temperature of warmest quarter (Bio10), annual mean temperature ( Bio1) and land use land cover were the major contributing variables to the mode

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Shivambu, Ndivhuwo, Tinyiko C. Shivambu, and Colleen T. Downs. "Predicting the Potential Distribution of Non-Native Mammalian Species Sold in the South African Pet Trade." Diversity 13, no. 10 (2021): 478. http://dx.doi.org/10.3390/d13100478.

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The pet trade is one of the main pathways of introduction of several mammals worldwide. In South Africa, non-native mammalian species are traded as pets, and so far, only four of these species are considered invasive. We used a list of 24 companion mammalian species compiled from a previous study. We selected a subset of 14 species for species distribution modeling (SDM) based on their trade popularity, invasion history and potential economic and socio-economic impacts. We aimed to estimate their potential distribution using their distribution records. Our SDM indicated that climate in South A

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Yin, Yingxuan, Qing He, Xiaowen Pan, Qiyong Liu, Yinjuan Wu, and Xuerong Li. "Predicting Current Potential Distribution and the Range Dynamics of Pomacea canaliculata in China under Global Climate Change." Biology 11, no. 1 (2022): 110. http://dx.doi.org/10.3390/biology11010110.

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Pomacea canaliculata is one of the 100 worst invasive alien species in the world, which has significant effects and harm to native species, ecological environment, human health, and social economy. Climate change is one of the major causes of species range shifts. With recent climate change, the distribution of P. canaliculata has shifted northward. Understanding the potential distribution under current and future climate conditions will aid in the management of the risk of its invasion and spread. Here, we used species distribution modeling (SDM) methods to predict the potential distribution

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