Species Distribution Modeling in the Tropics: Problems, Potentialities, and the Role of Biological Data for Effective Species Conservation:
Luis Cayuela,Duncan Golicher,Adrian C. Newton,M. Kolb,F. S. de Alburquerque,Eric Arets,Eric Arets,J. R. M. Alkemade,Ana Beatriz Alvarez Perez +8 more
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TLDR
SDMs have a great potential to support biodiversity conservation in the tropics, by supporting the development of conservation strategies and plans, identifying knowledge gaps, and providing a tool to examine the potential impacts of environmental change, but for this potential to be fully realized, problems of data quality and availability need to be overcome.Abstract:
In this paper we aim to investigate the problems and potentialities of species distribution modeling (SDM) as a tool for conservation planning and policy development and implementation in tropical regions. We reviewed 123 studies published between 1995 and 2007 in five of the leading journals in ecology and conservation, and examined two tropical case studies in which distribution modeling is currently being applied to support conservation planning. We also analyzed the characteristics of data typically used for fitting models within the specific context of modeling tree species distribution in Central America. The results showed that methodological papers outnumbered reports of SDMs being used in an applied context for setting conservation priorities, particularly in the tropics. Most applications of SDMs were in temperate regions and biased towards certain organisms such as mammals and birds. Studies from tropical regions were less likely to be validated than those from temperate regions. Unpublished data from two major tropical case studies showed that those species that are most in need of conservation actions, namely those that are the rarest or most threatened, are those for which SDM is least likely to be useful. We found that only 15% of the tree species of conservation concern in Central America could be reliably modelled using data from a substantial source (Missouri Botanical Garden VAST database). Lack of data limits model validation in tropical areas, further restricting the value of SDMs. We concluded that SDMs have a great potential to support biodiversity conservation in the tropics, by supporting the development of conservation strategies and plans, identifying knowledge gaps, and providing a tool to examine the potential impacts of environmental change. However, for this potential to be fully realized, problems of data quality and availability need to be overcome. Weaknesses in current biological datasets need to be systematically addressed, by increasing collection of field survey data, improving data sharing and increasing structural integration of data sources. This should include use of distributed databases with common standards, referential integrity, and rigorous quality control. Integration of data management with SDMs could significantly add value to existing data resources by improving data quality control and enabling knowledge gaps to be identified.read more
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Predicting species distributions for conservation decisions
Antoine Guisan,Reid Tingley,John B. Baumgartner,Ilona Naujokaitis-Lewis,Patricia Sutcliffe,Ayesha I. T. Tulloch,Tracey J. Regan,Lluís Brotons,Eve McDonald-Madden,Eve McDonald-Madden,Chrystal Mantyka-Pringle,Chrystal Mantyka-Pringle,Tara G. Martin,Tara G. Martin,Jonathan R. Rhodes,Ramona Maggini,Samantha A. Setterfield,Jane Elith,Mark W. Schwartz,Brendan A. Wintle,Olivier Broennimann,Mike P. Austin,Simon Ferrier,Michael R. Kearney,Hugh P. Possingham,Hugh P. Possingham,Yvonne M. Buckley,Yvonne M. Buckley +27 more
TL;DR: It is proposed that species distribution modellers should get involved in real decision-making processes that will benefit from their technical input and have the potential to better bridge theory and practice, and contribute to improve both scientific knowledge and conservation outcomes.
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Estimating optimal complexity for ecological niche models: A jackknife approach for species with small sample sizes
TL;DR: This work evaluates a delete-one jackknife approach for tuning model settings to approximate optimal model complexity and enhance predictions for datasets with few (here, <10) occurrence records in Maxent, and identifies an optimal feature class parameter that is more complex than the default.
Journal ArticleDOI
Global priorities for an effective information basis of biodiversity distributions.
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Journal ArticleDOI
Accounting for uncertainty when mapping species distributions: The need for maps of ignorance
Duccio Rocchini,Joaquín Hortal,Szabolcs Lengyel,Jorge M. Lobo,Alberto Jiménez-Valverde,Carlo Ricotta,Giovanni Bacaro,Alessandro Chiarucci +7 more
TL;DR: In this paper, the main sources of uncertainty are reviewed and a code of good practices is proposed to minimize their effects. But the authors do not consider the effect of the quality and bias of raw distributional data, the process of map building and the dynamic nature of species distributions themselves.
Journal ArticleDOI
taxonstand: An r package for species names standardisation in vegetation databases
TL;DR: Taxonstand, a nr package to automatically standardise plant names using The Plant List is presented, which greatly facilitates the preparation of large vegetation databases prior to their analyses, particularly when they cover broad geographical areas or contain data from regions with rich floras where taxonomic problems have not been resolved for many of their taxa.
References
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Journal ArticleDOI
Biodiversity hotspots for conservation priorities
Norman Myers,Russell A. Mittermeier,Cristina G. Mittermeier,Gustavo A. B. da Fonseca,Jennifer Kent +4 more
TL;DR: A ‘silver bullet’ strategy on the part of conservation planners, focusing on ‘biodiversity hotspots’ where exceptional concentrations of endemic species are undergoing exceptional loss of habitat, is proposed.
Journal ArticleDOI
Maximum entropy modeling of species geographic distributions
TL;DR: In this paper, the use of the maximum entropy method (Maxent) for modeling species geographic distributions with presence-only data was introduced, which is a general-purpose machine learning method with a simple and precise mathematical formulation.
Journal ArticleDOI
Novel methods improve prediction of species' distributions from occurrence data
Jane Elith,Catherine H. Graham,Robert P. Anderson,Miroslav Dudík,Simon Ferrier,Antoine Guisan,Robert J. Hijmans,Falk Huettmann,John R. Leathwick,Anthony Lehmann,Jin Li,Lúcia G. Lohmann,Bette A. Loiselle,Glenn Manion,Craig Moritz,Miguel Nakamura,Yoshinori Nakazawa,Jacob C. M. Mc Overton,A. Townsend Peterson,Steven J. Phillips,Karen Richardson,Ricardo Scachetti-Pereira,Robert E. Schapire,Jorge Soberón,Stephen E. Williams,Mary S. Wisz,Niklaus E. Zimmermann +26 more
TL;DR: This work compared 16 modelling methods over 226 species from 6 regions of the world, creating the most comprehensive set of model comparisons to date and found that presence-only data were effective for modelling species' distributions for many species and regions.
Journal ArticleDOI
Extinction risk from climate change
Chris D. Thomas,Alison Cameron,Rhys E. Green,Rhys E. Green,Michel Bakkenes,Linda J. Beaumont,Yvonne C. Collingham,Barend F.N. Erasmus,Marinez Ferreira de Siqueira,Alan Grainger,Lee Hannah,Lesley Hughes,Brian Huntley,Albert S. van Jaarsveld,Guy F. Midgley,Lera Miles,Lera Miles,Miguel A. Ortega-Huerta,A. Townsend Peterson,Oliver L. Phillips,Stephen E. Williams +20 more
TL;DR: Estimates of extinction risks for sample regions that cover some 20% of the Earth's terrestrial surface show the importance of rapid implementation of technologies to decrease greenhouse gas emissions and strategies for carbon sequestration.
Journal ArticleDOI
Predictive habitat distribution models in ecology
TL;DR: A review of predictive habitat distribution modeling is presented, which shows that a wide array of models has been developed to cover aspects as diverse as biogeography, conservation biology, climate change research, and habitat or species management.
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