Species Distribution Models predict abundance and its temporal variation in a steppe bird population

Evaluation of the full set of habitat suitability models for vulnerable marine ecosystem indicator taxa in the South Pacific high seas

“…In contrast, phylum-and class-level models for Bryozoa and Hydrozoa were poor. Some relationships between predicted habitat suitability and abundance may be non-linear (Monnier-Corbel et al, 2023;Vanderwal et al, 2009). We found that habitat suitability for some taxa corresponded well with the upper limit of abundance, while mean abundance was less well indicated.…”

MERRA-based trend analysis identifies complex, multidecadal patterns of changing climatic suitability for Cassin’s Sparrow (Peucaea cassinii)

“…Given that data on species occurrences are far more common and readily accessible than data on species abundance, it is not surprising that a significant amount of research has focused on clarifying the abundance-suitability (AS) relationship and the extent to which ENM-derived estimates of environmental suitability can serve as a proxy for population abundance [145]. While much remains to be learned about modeling the distribution of abundance, a consensus appears to be emerging around the following points: the distribution of environmental suitability based on bioclimatic variables alone generally shows little, if any, correlation with the distribution of abundance [124,146–148]; the combination of bioclimatic predictors with other environmental attributes, such as EFAs, edaphic variables, topographic data, vegetation indices, etc., can capture the influence of factors affecting abundance rather than just occurrence, thereby yielding suitability model results that are often highly correlated with abundance [145,147–149], and, in some cases, reflect well the mean and maximal local abundances of a species [150]; the AS correlation is particularly strengthened when the added non-climatic predictors capture, in one way or another, environmental drivers that influence fitness, dispersal, recruitment, or other demographic properties of a species [149,151–153]; and correlative ENM that takes into account this bioclimatic-demographic connection can provide practical benefits to spatial conservation efforts, such as readily-attainable, large-scale abundance estimates; hot-spot identification; and reduced survey and monitoring costs [24,145,147,148,150]. Our findings are consistent with the first point: we see different patterns of historical change in environmental suitability depending on whether time series models are driven by bioclimatic variables alone or by variables more aligned with ecological functioning, and therefore potentially species demography.…”

“…correlative ENM that takes into account this bioclimatic-demographic connection can provide practical benefits to spatial conservation efforts, such as readily-attainable, large-scale abundance estimates; hot-spot identification; and reduced survey and monitoring costs [24,145,147,148,150].…”

“…(2) the combination of bioclimatic predictors with other environmental attributes, such as EFAs, edaphic variables, topographic data, vegetation indices, etc., can capture the influence of factors affecting abundance rather than just occurrence, thereby yielding suitability model results that are often highly correlated with abundance [145,[147][148][149], and, in some cases, reflect well the mean and maximal local abundances of a species [150];…”