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10Species may be more abundant in the centre of their geographic range or climatic 11 niche (the abundant-centre hypothesis). Recently, Osorio-Olvera et al. (2020) re-12 ported strong support for the niche abundant-centre relationship. We demonstrate 13 here that methodological decisions strongly affected perceived abundant-centre 14 support. Upon re-analysis, we show that abundant-centre relationships are quite 15 rare. 16 2The spatial distribution of abundance has long fascinated ecologists who searched 17 for general rules governing where species occur and the density at which they are 18 found (McGill et al., 2007; Sagarin & Gaines, 2002). Particularly controversial 19 rules are the abundant-centre and abundant-niche centre hypotheses, which pre-20 dict abundance to decrease gradually from the centre to the margins of species 21 Osorio-Olvera et al. (2020) estimating the species niche as a minimum volume 56 ellipsoid (MVE) by considering more than 4000 combinations of climatic variables, 57 including all 19 commonly-used bioclimatic variables together with the first 15 58 PCA components of a PCA based on the same bioclimatic variables. The authors 59 use every possible combination of two and three niche axes to estimate the niche.60We identify two main issues associated with this procedure. 61First, the authors report results only for models showing significant abundant-62 niche centre relationships, omitting non-significant correlations (Figure 2a). This 63 issue is not only present in the fit MVE models, but also in the 2 and 3 fea-64 ture models using convex hulls or MVEs, which makes Figure 3 of Osorio-Olvera 65 et al. (2020) quite a biased view of the abundant-niche centre relationship. In 66 fact, by including non-significant correlations, the mean abundant-niche centre re-67 lationship across all model sets becomes quite weak (ρ + −sd = -0.08 +− 0.01), 68 4 and many species exhibit significantly positive abundant-niche centre relationships 69 ( Figure 2b). Including these non-significant results is important, in our view, and 70 strongly influences the resulting perceived support for the abundant-centre pat-71 tern (Figure 2b). Our re-analysis suggests that only between 37% and 45% of 72 species have negative abundant-centre relationships, regardless of approach used 73 (see https://figshare.com/s/8fadf780810e73d44623), while the majority of the es-74 timated relationships are either positive or non-significant. Interestingly, this low 75 empirical support is consistent with previous findings for the geographic interpre-76 tation of the hypothesis (Pironon et al., 2017; Sagarin & Gaines, 2002). 77 Second, while the authors train an average of 1,852 models per species to cal-78 culate MVEs, they perform no form of model selection. This functionally treats 79 the poorest fit MVE and the best fit MVE as equivalent, provided the model pro-80 duced a significant abundant-centre relationship. When non-significant results are 81 included, and only best models are retained, the overall pattern changes substan...
10Species may be more abundant in the centre of their geographic range or climatic 11 niche (the abundant-centre hypothesis). Recently, Osorio-Olvera et al. (2020) re-12 ported strong support for the niche abundant-centre relationship. We demonstrate 13 here that methodological decisions strongly affected perceived abundant-centre 14 support. Upon re-analysis, we show that abundant-centre relationships are quite 15 rare. 16 2The spatial distribution of abundance has long fascinated ecologists who searched 17 for general rules governing where species occur and the density at which they are 18 found (McGill et al., 2007; Sagarin & Gaines, 2002). Particularly controversial 19 rules are the abundant-centre and abundant-niche centre hypotheses, which pre-20 dict abundance to decrease gradually from the centre to the margins of species 21 Osorio-Olvera et al. (2020) estimating the species niche as a minimum volume 56 ellipsoid (MVE) by considering more than 4000 combinations of climatic variables, 57 including all 19 commonly-used bioclimatic variables together with the first 15 58 PCA components of a PCA based on the same bioclimatic variables. The authors 59 use every possible combination of two and three niche axes to estimate the niche.60We identify two main issues associated with this procedure. 61First, the authors report results only for models showing significant abundant-62 niche centre relationships, omitting non-significant correlations (Figure 2a). This 63 issue is not only present in the fit MVE models, but also in the 2 and 3 fea-64 ture models using convex hulls or MVEs, which makes Figure 3 of Osorio-Olvera 65 et al. (2020) quite a biased view of the abundant-niche centre relationship. In 66 fact, by including non-significant correlations, the mean abundant-niche centre re-67 lationship across all model sets becomes quite weak (ρ + −sd = -0.08 +− 0.01), 68 4 and many species exhibit significantly positive abundant-niche centre relationships 69 ( Figure 2b). Including these non-significant results is important, in our view, and 70 strongly influences the resulting perceived support for the abundant-centre pat-71 tern (Figure 2b). Our re-analysis suggests that only between 37% and 45% of 72 species have negative abundant-centre relationships, regardless of approach used 73 (see https://figshare.com/s/8fadf780810e73d44623), while the majority of the es-74 timated relationships are either positive or non-significant. Interestingly, this low 75 empirical support is consistent with previous findings for the geographic interpre-76 tation of the hypothesis (Pironon et al., 2017; Sagarin & Gaines, 2002). 77 Second, while the authors train an average of 1,852 models per species to cal-78 culate MVEs, they perform no form of model selection. This functionally treats 79 the poorest fit MVE and the best fit MVE as equivalent, provided the model pro-80 duced a significant abundant-centre relationship. When non-significant results are 81 included, and only best models are retained, the overall pattern changes substan...
The distribution range and population abundance of species provide fundamental information on the species–habitat relationship required for management and conservation. Abundance inherently provides more information about the ecology of species than do occurrence data. However, information on abundance is scarce for most species, mainly at large spatial scales. The objective of this work was, therefore, to provide information regarding the population status of six wild felids inhabiting territories in Mexico that are inaccessible or politically unstable. This was done using species distribution models derived from occurrence data. We used distribution data at a continental scale for the wild felids inhabiting Mexico: jaguar (Panthera onca), bobcat (Lynx rufus), ocelot (Leopardus pardalis), cougar (Puma concolor), margay (Leopardus wiedii), and jaguarundi (Herpailurus yagouaroundi) to predict environmental suitability (estimated by both Maxent and the distance to niche centroid, DNC). Suitability was then examined by relating to a capture rate‐based index, in a well‐monitored area in central western Mexico in order to assess their performance as proxies of relative abundance. Our results indicate that the environmental suitability patterns predicted by both algorithms were comparable. However, the strength of the relationship between the suitability and relative abundance of local populations differed across species and between algorithms, with the bobcat and DNC, respectively, having the best fit, although the relationship was not consistent in all the models. This paper presents the potential of implementing species distribution models in order to predict the relative abundance of wild felids in Mexico and offers guidance for the proper interpretation of the relationship between suitability and population abundance. The results obtained provide a robust information base on which to outline specific conservation actions and on which to examine the potential status of endangered species inhabiting remote or politically unstable territories in which on‐field monitoring programs are not feasible.
Species abundance patterns are influenced by a myriad of factors, including habitat availability and ecological niche characteristics. However, the evidence concerning the specific impact factors such as niche position and niche breadth on mean and maximum abundances in vertebrates at a broad geographical scale remains inconclusive. In this study, we investigated the influence of niche position and breadth on the abundance of 47 species of birds belonging to the Parulidae family, commonly known as New World Warblers. We obtained data on abundance and presence records spanning the reproductive distribution of these species and employed the outlying mean index analysis to calculate niche position and niche breadth. We assessed the relationship between abundance metrics and niche descriptors using phylogenetic regressions to account for the non‐independence resulting from phylogenetic ancestry. Initially, we developed individual models for each predictor and subsequently formulated a multi‐predictor model encompassing niche position, niche breadth, and their interaction. Our findings revealed a negative relationship between niche position and both mean and maximum abundance, while niche breadth exhibited a positive relationship with these niche characteristics. Notably, the results of the multi‐predictor models indicated that niche position exerted the most substantial influence on both mean and maximum abundance. Additionally, the interaction between niche position and niche breadth had the most positive and significant contribution to mean population abundance. This study underscores the need for future research in other vertebrates to delve into the mechanisms underlying these patterns. Such endeavors will not only enhance our understanding of ecological dynamics but also equip us with predictive capabilities to anticipate population responses to environmental changes effectively.
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