A frequency distribution approach to hotspot identification

Bartolino, Valerio; Maiorano, Luigi; Colloca, Francesco

doi:10.1007/s10144-010-0229-2

Cited by 34 publications

(42 citation statements)

References 38 publications

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“…1. One can easily realise that a tangent with \45°slope does not necessarily correspond to areas where the variable considered, herb species richness or bird density, respectively, is found at high densities and vice versa, as pointed out by Bartolino et al (2011). In both datasets, several points with both low and high values fulfill the 45°slope tangent rule (Fig.…”

Section: Limits To the Crfd Curve Approachmentioning

confidence: 87%

Comments on Bartolino et al. (2011): limits of cumulative relative frequency distribution curves for hotspot identification

et al. 2011

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The recent paper by Bartolino et al. (Popul Ecol 53:351–359, ) presents a new method to objectively select hotspots using cumulative relative frequency distribution (CRFD) curves. This method is presented as being independent from the selection of any threshold and, therefore, less arbitrary than traditional approaches. We argue that this method, albeit mathematically sound, is based on likewise arbitrary decisions regarding threshold selection. Specifically, the use of the CRFD curve approach requires the occurrence of two criteria for the method to be applied correctly: the selection of a 45° tangent to the curve, and the need to consider the highest relative value of the study parameter corresponding to a 45° slope tangent to the curve. Using two case studies (dealing with species richness and abundance of a particular species), we demonstrate that these two criteria are really unrelated to the underlying causes that shape the spatial pattern of the phenomena under study, but rather related to sampling design and spatial scale; hence, one could likewise use different but valid criteria. Consequently, the CRFD curve approach is based on the selection of a pre‐defined threshold that has little, if any, ecological justification, and that heavily influences the final hotspot selection. Therefore, we conclude that the CRFD curve approach itself is not necessarily better and more objective than any of the global methods typically used for hotspot identification. Indeed, mathematical and/or statistical approaches should not be viewed as a panacea to solve conservation problems, but rather used in combination with biological, practical, economic and social considerations.

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Section: Limits To the Crfd Curve Approachmentioning

confidence: 87%

Comments on Bartolino et al. (2011): limits of cumulative relative frequency distribution curves for hotspot identification

et al. 2011

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“…We understand that the choice of an arbitrary threshold for the identification of biodiversity hotspots is debatable [40], but several previous analyses showed that the richest 1–10% of surface could represent a substantial proportion of terrestrial species [53,54]. …”

Section: Discussionmentioning

confidence: 99%

“…Given the relatively coarse cell size we adopted, we chose the smallest neighborhood structure possible (acting as a smoothing factor [40]), corresponding to 9 cells. Then, using the same spatial randomization approach [39] with 9,999 permutations, we tested whether local correlation between species richness in one pixel and the risk of extreme climate averaged over the 9 neighboring pixels was significantly different from what would be expected in case of spatial randomness.…”

Section: Methodsmentioning

confidence: 99%

Threats from Climate Change to Terrestrial Vertebrate Hotspots in Europe

et al. 2013

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We identified hotspots of terrestrial vertebrate species diversity in Europe and adjacent islands. Moreover, we assessed the extent to which by the end of the 21st century such hotspots will be exposed to average monthly temperature and precipitation patterns which can be regarded as extreme if compared to the climate experienced during 1950-2000. In particular, we considered the entire European sub-continent plus Turkey and a total of 1149 species of terrestrial vertebrates. For each species, we developed species-specific expert-based distribution models (validated against field data) which we used to calculate species richness maps for mammals, breeding birds, amphibians, and reptiles. Considering four global circulation model outputs and three emission scenarios, we generated an index of risk of exposure to extreme climates, and we used a bivariate local Moran’s I to identify the areas with a significant association between hotspots of diversity and high risk of exposure to extreme climates. Our results outline that the Mediterranean basin represents both an important hotspot for biodiversity and especially for threatened species for all taxa. In particular, the Iberian and Italian peninsulas host particularly high species richness as measured over all groups, while the eastern Mediterranean basin is particularly rich in amphibians and reptiles; the islands (both Macaronesian and Mediterranean) host the highest richness of threatened species for all taxa occurs. Our results suggest that the main hotspots of biodiversity for terrestrial vertebrates may be extensively influenced by the climate change projected to occur over the coming decades, especially in the Mediterranean bioregion, posing serious concerns for biodiversity conservation.

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“…Similarly, Bartolino et al (2011) found that local and global methods, including CRFD curves, provided rather different results in their case study on terrestrial vertebrate species diversity where the spatial autocorrelation was rather low. We agree with Cayuela et al (2011) when they say that autocorrelation is a property of the spatial process itself.…”

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confidence: 93%