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

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CONFRONTING MULTICOLLINEARITY IN ECOLOGICAL MULTIPLE REGRESSION

MICHAEL GRAHAM (2003)

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The status of the world's land and marine mammals: diversity, threat, and knowledge.

Jan Schipper, Janice S Chanson, Federica Chiozza … (2008)

Knowledge of mammalian diversity is still surprisingly disparate, both regionally and taxonomically. Here, we present a comprehensive assessment of the conservation status and distribution of the world's mammals. Data, compiled by 1700+ experts, cover all 5487 species, including marine mammals. Global macroecological patterns are very different for land and marine species but suggest common mechanisms driving diversity and endemism across systems. Compared with land species, threat levels are higher among marine mammals, driven by different processes (accidental mortality and pollution, rather than habitat loss), and are spatially distinct (peaking in northern oceans, rather than in Southeast Asia). Marine mammals are also disproportionately poorly known. These data are made freely available to support further scientific developments and conservation action.

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Niches and distributional areas: concepts, methods, and assumptions.

Jorge Soberón, Miguel Nakamura (2009)

Estimating actual and potential areas of distribution of species via ecological niche modeling has become a very active field of research, yet important conceptual issues in this field remain confused. We argue that conceptual clarity is enhanced by adopting restricted definitions of "niche" that enable operational definitions of basic concepts like fundamental, potential, and realized niches and potential and actual distributional areas. We apply these definitions to the question of niche conservatism, addressing what it is that is conserved and showing with a quantitative example how niche change can be measured. In this example, we display the extremely irregular structure of niche space, arguing that it is an important factor in understanding niche evolution. Many cases of apparently successful models of distributions ignore biotic factors: we suggest explanations to account for this paradox. Finally, relating the probability of observing a species to ecological factors, we address the issue of what objects are actually calculated by different niche modeling algorithms and stress the fact that methods that use only presence data calculate very different quantities than methods that use absence data. We conclude that the results of niche modeling exercises can be interpreted much better if the ecological and mathematical assumptions of the modeling process are made explicit.

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Journal

Title: Progress in Physical Geography

Abbreviated Title: Progress in Physical Geography

Publisher: SAGE Publications

ISSN (Print): 0309-1333

ISSN (Electronic): 1477-0296

Publication date Created: March 31 2011

Publication date (Print): March 31 2011

Volume: 35

Issue: 2

Pages: 211-226

Article

DOI: 10.1177/0309133311399491

SO-VID: 7c02f8cd-cb42-4faf-8a81-bc4b9493ddd3

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