Species distribution models (SDMs) are increasingly proposed to support conservation decision making. However, evidence of SDMs supporting solutions for on-ground conservation problems is still scarce in the scientific literature. Here, we show that successful examples exist but are still largely hidden in the grey literature, and thus less accessible for analysis and learning. Furthermore, the decision framework within which SDMs are used is rarely made explicit. Using case studies from biological invasions, identification of critical habitats, reserve selection and translocation of endangered species, we propose that SDMs may be tailored to suit a range of decision-making contexts when used within a structured and transparent decision-making process. To construct appropriate SDMs to more effectively guide conservation actions, modellers need to better understand the decision process, and decision makers need to provide feedback to modellers regarding the actual use of SDMs to support conservation decisions. This could be facilitated by individuals or institutions playing the role of 'translators' between modellers and decision makers. We encourage species distribution modellers to get involved in real decision-making processes that will benefit from their technical input; this strategy has the potential to better bridge theory and practice, and contribute to improve both scientific knowledge and conservation outcomes.

/pdf/predicting-species-distributions-for-conservation-decisions-2ycxvy2131.pdf

Predicting species distributions for conservation decisions

Estimating optimal complexity for ecological niche models: A jackknife approach for species with small sample sizes

Severe gaps and biases in digital accessible information (DAI) of species distributions hamper prospects of safeguarding biodiversity and ecosystem services and reliably addressing central questions in ecology and evolution. Accordingly, governments have agreed on improving and sharing biodiversity knowledge by 2020 (United Nations Convention on Biological Diversity’s Aichi target 19). To achieve this target, gaps in DAI must be identified, and actions prioritized to address their root causes. We take terrestrial vertebrates, an iconic and comparatively well-studied group, as a model and present the first globally comprehensive assessment of patterns and drivers of gaps in DAI, based on an integration of 157 million validated point records with 21,170 expert-based distribution maps. We demonstrate that outside a few well-sampled regions, DAI provides a very limited and spatially highly biased inventory of actual biodiversity. Coarser spatial grains result in more complete inventories, but provide insufficient detail for conservation and resource management. Surprisingly, large emerging economies are particularly under-represented in global DAI, even more so than species-rich, developing countries in the tropics. Multi-model inference reveals that completeness is mainly limited by distance to researchers, locally available research funding, and political participation in data-sharing networks, rather than transportation infrastructure, or size and funding of Western data contributors as often assumed. Our study provides an empirical baseline to advance strategies of enhancing the global information basis of biodiversity. In particular, our results highlight the need for targeted data integration from non-Western data holders and intensified cooperation to more effectively address societal biodiversity information needs.

/pdf/global-priorities-for-an-effective-information-basis-of-cwo73ut6fb.pdf

Global priorities for an effective information basis of biodiversity distributions.

Accurate mapping of species distributions is a fundamental goal of modern biogeography, both for basic and applied purposes. This is commonly done by plotting known species occurrences, expert-drawn range maps or geographical estimations derived from species distribution models. However, all three kinds of maps are implicitly subject to uncertainty, due to the quality and bias of raw distributional data, the process of map building, and the dynamic nature of species distributions themselves. Here we review the main sources of uncertainty suggesting a code of good practices in order to minimize their effects.

/pdf/accounting-for-uncertainty-when-mapping-species-ywqkx57mw3.pdf

Accounting for uncertainty when mapping species distributions: The need for maps of ignorance

Summary 1. Compilation of vegetation databases has contributed significantly to the advancement of vegetation science all over the world. Yet, methodological problems result from the use of plant names, particularly in data that originate from numerous and heterogeneous sources. One of the main problems is the inordinate number of synonyms that can be found in vegetation lists. 2. We present Taxonstand ,a nr package to automatically standardise plant names using The Plant List (http://www.theplantlist.org). The scripts included in this package allow connection to the online search engine of the Plant List and retrieve information from each species about its current taxonomic status. In those cases where the species name is a synonym, it is replaced by the current accepted name. In addition, this package can help correcting orthographic errors in specific epithets. 3. This tool greatly facilitates the preparation of large vegetation databases prior to their analyses, particularly when they cover broad geographical areas (supranational or even continental scale) or contain data from regions with rich floras where taxonomic problems have not been resolved for many of their taxa. Automated workflows such as the one provided by the taxonstand package can ease considerably this task using a widely accessible working nomenclatural authority list for plant species names such as The Plant List.

https://besjournals.onlinelibrary.wiley.com/doi/pdf/10.1111/j.2041-210X.2012.00232.x

taxonstand: An r package for species names standardisation in vegetation databases

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.

/pdf/species-distribution-modeling-in-the-tropics-problems-bm1udgkvu4.pdf

F. S. de Alburquerque

Papers

Species Distribution Modeling in the Tropics: Problems, Potentialities, and the Role of Biological Data for Effective Species Conservation: