Integrating Fuzzy Logic and Statistics to Improve the Reliable Delimitation of Biogeographic Regions and Transition Zones

Olivero, Jesús; Márquez, Ana Luz; Real, Raimundo

doi:10.1093/sysbio/sys061

Cited by 43 publications

(73 citation statements)

References 113 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…These boundaries, most notably defined for marine biota by Briggs [32] as the demarcation between areas of high endemic diversity [33], can themselves be elusive to draw on a map [34] because of the assortment of independent lineages into niches of varying breadths, as well as spatial and temporal sampling uncertainties [3].…”

Section: Introductionmentioning

confidence: 99%

Edges and Overlaps in Northwest Atlantic Phylogeography

et al. 2013

View full text Add to dashboard Cite

As marine environments change, the greatest ecological shifts—including resource usage and species interactions—are likely to take place in or near regions of biogeographic and phylogeographic transition. However, our understanding of where these transitional regions exist depends on the defining criteria. Here we evaluate phylogeographic transitions using a bootstrapping procedure that allows us to focus on either the strongest genetic transitions between a pair of contiguous populations, versus evaluation of transitions inclusive of the entire overlap between two intraspecific genetic lineages. We compiled data for the Atlantic coast of the United States, and evaluate taxa with short- and long-dispersing larval phases separately. Our results are largely concordant with previous biogeographic and phylogeographic analyses, indicating strong biotic change associated with the regions near Cape Cod, the Delmarva Peninsula, and eastern Florida. However, inclusive analysis of the entire range of sympatry for intraspecific lineages suggests that broad regions—the Mid-Atlantic Bight and eastern Florida–already harbor divergent intraspecific lineages, suggesting the potential for ecological evaluation of resource use between these lineages. This study establishes baseline information for tracking how such patterns change as predicted environmental changes take place

show abstract

Section: Introductionmentioning

confidence: 99%

Edges and Overlaps in Northwest Atlantic Phylogeography

et al. 2013

View full text Add to dashboard Cite

show abstract

“…For example, assessments of spatial biodiversity have typically used simple geographic measures as the unit of analysis, such as the distribution range of individual species, though recent methodological refinements include the integration of phylogenetic relationships among species and their evolutionary age 2,7 . Moreover, carefully parameterized species distribution models can generate accurate estimates of species ranges 14 and novel, more objective, approaches are being developed to translate patterns of species richness, endemism and turnover for determining those biogeographic regions in greatest need for conservation and protection 2,7,8,[15][16][17] . Although biological explanation of these patterns is still in its methodological infancy, considerable recent development of conceptual and statistical tools now allows for integrative multivariate approaches to more realistically estimate underlying processes.…”

mentioning

confidence: 99%

A necessarily complex model to explain the biogeography of the amphibians and reptiles of Madagascar

et al. 2014

View full text Add to dashboard Cite

Pattern and process are inextricably linked in biogeographic analyses, though we can observe pattern, we must infer process. Inferences of process are often based on ad hoc comparisons using a single spatial predictor. Here, we present an alternative approach that uses mixedspatial models to measure the predictive potential of combinations of hypotheses. Biodiversity patterns are estimated from 8,362 occurrence records from 745 species of Malagasy amphibians and reptiles. By incorporating 18 spatially explicit predictions of 12 major biogeographic hypotheses, we show that mixed models greatly improve our ability to explain the observed biodiversity patterns. We conclude that patterns are influenced by a combination of diversification processes rather than by a single predominant mechanism. A 'one-size-fits-all' model does not exist. By developing a novel method for examining and synthesizing spatial parameters such as species richness, endemism and community similarity, we demonstrate the potential of these analyses for understanding the diversification history of Madagascar's biota.

show abstract

“…The fuzzy logic approach allowed us, however, to avoid subjectively classifying species as sustainable or unsustainable. This way of weighting the constituents of a diversity index (in our case, F i ) with a factor representing degrees of fuzzy membership (in our case, in the set of species whose hunting is sustainable), has been a successful procedure as demonstrated in Olivero et al [52], [53].…”

Section: Methodsmentioning

confidence: 99%

Integrating Sustainable Hunting in Biodiversity Protection in Central Africa: Hot Spots, Weak Spots, and Strong Spots

Olivero

Farfán

et al. 2014

PLoS ONE

Self Cite

View full text Add to dashboard Cite

Wild animals are a primary source of protein (bushmeat) for people living in or near tropical forests. Ideally, the effect of bushmeat harvests should be monitored closely by making regular estimates of offtake rate and size of stock available for exploitation. However, in practice, this is possible in very few situations because it requires both of these aspects to be readily measurable, and even in the best case, entails very considerable time and effort. As alternative, in this study, we use high-resolution, environmental favorability models for terrestrial mammals (N = 165) in Central Africa to map areas of high species richness (hot spots) and hunting susceptibility. Favorability models distinguish localities with environmental conditions that favor the species' existence from those with detrimental characteristics for its presence. We develop an index for assessing Potential Hunting Sustainability (PHS) of each species based on their ecological characteristics (population density, habitat breadth, rarity and vulnerability), weighted according to restrictive and permissive assumptions of how species' characteristics are combined. Species are classified into five main hunting sustainability classes using fuzzy logic. Using the accumulated favorability values of all species, and their PHS values, we finally identify weak spots, defined as high diversity regions of especial hunting vulnerability for wildlife, as well as strong spots, defined as high diversity areas of high hunting sustainability potential. Our study uses relatively simple models that employ easily obtainable data of a species' ecological characteristics to assess the impacts of hunting in tropical regions. It provides information for management by charting the geography of where species are more or less likely to be at risk of extinction from hunting.

show abstract

Integrating Fuzzy Logic and Statistics to Improve the Reliable Delimitation of Biogeographic Regions and Transition Zones

Cited by 43 publications

References 113 publications

Edges and Overlaps in Northwest Atlantic Phylogeography

Edges and Overlaps in Northwest Atlantic Phylogeography

A necessarily complex model to explain the biogeography of the amphibians and reptiles of Madagascar

Integrating Sustainable Hunting in Biodiversity Protection in Central Africa: Hot Spots, Weak Spots, and Strong Spots

Contact Info

Product

Resources

About