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

Monnier‐Corbel, Alice; Robert, Alexandre; Hingrat, Yves; Benito, Blas M.; Monnet, Anne‐Christine

doi:10.1016/j.gecco.2023.e02442

Cited by 5 publications

(4 citation statements)

References 61 publications

(93 reference statements)

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“…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.…”

Section: Discussionmentioning

confidence: 68%

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

Bennion,

Anderson,

Rowden

et al. 2024

Fisheries Management Eco

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In the high seas, regional fishery management organisations are required to implement measures to prevent significant adverse impacts on vulnerable marine ecosystems (VMEs). Our objectives were to develop habitat suitability models for use in the spatial management of bottom fisheries in the South Pacific and to evaluate these and existing models using independent data from high‐quality seafloor imagery. Presence‐only models for seven VME indictor taxa were developed to complement previous modelling. Evaluation of habitat suitability models using withheld data indicated high mean True Skill Statistic scores of 0.44–0.64. Most habitat suitability models performed adequately when assessed with independent data on taxon presence and absence but were poor surrogates for abundance. We therefore advocate caution when using presence‐only models for spatial management and call for more systematically collected data to develop abundance models.

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Section: Discussionmentioning

confidence: 68%

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

Bennion,

Anderson,

Rowden

et al. 2024

Fisheries Management Eco

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“…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.…”

Section: Discussionmentioning

confidence: 99%

“…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].…”

Section: Discussionmentioning

confidence: 99%

“…(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];…”

Section: Climatic Suitabilitymentioning

confidence: 99%

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

Schnase,

Carroll,

Montesano

et al. 2023

Preprint

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Cassin's Sparrow (Peucaea cassinii) is a grassland resident of the American Southwest. Despite decades of study, there remains uncertainty regarding the conservation status of the species. The species' past response to a changing climate may help explain this uncertainty, especially if patterns vary across the species' range. In this study, we combine data from NASA's Modern-Era Reanalysis for Research and Applications, Version 2 (MERRA-2; M2) with field observations spanning the past 40 years to examine historical changes in climatic suitability for Cassin's Sparrow across its full annual range within the continental United States. We examine two time- and variable-specific time series using MaxEnt. The M2 times series uses a mix of 30 microclimatic variables and ecosystem functional attributes related to energy and water fluxes for predictors; the MERRAclim (MC) time series uses 19 MERRA-2-derived bioclimatic variables for predictors. Trend analysis reveals complex patterns of slowly increasing climatic suitability over 69.5% of the study area in the MC time series accompanied by decreases over 24.4% of the area. Shifts in the study area-wide, weighted centroid for climatic suitability show a northwesterly, 40-year displacement of 1.85 km/yr. The M2 time series points to a less favorable history with increasing and decreasing trends over 54.9% and 40.1% of the study area, respectively, and a westerly weighted centroid shift of 2.60 km/yr. A clear subset of seven M2 and MC variables emerged as the most important determinants of suitability over the past 40 years. These variables also demonstrated complex patterns of non-constant trends across the study area. Suitability trends in both time series appear to have little in common with current, state-level, abundance-derived conservation status assessments. Increasing winds, drying land surface conditions, and variability in North American Monsoon rainfall appear to be dominating, climate-related influences on the species. We thus see complex patterns of historical change in climatic suitability depending on whether time series models are driven by bioclimatic variables alone or by variables more aligned with ecological function. This leads us to conclude that modeled estimates of climatic suitability for Cassin's Sparrow can vary widely depending on the temporal frame, spatial extent, and environmental drivers considered, and that this variability mirrors the uncertainty in the literature regarding the species' conservation status. Furthermore, these factors should be taken into account in future conservation assessments for the species, and retrospective ecological niche modeling, as applied here, offers a promising approach to addressing these issues.

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Distributions of non‐native and native plants are not determined by the same environmental factors

Steen,

Adde,

Schlaepfer

et al. 2024

Ecol Sol and Evidence

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Global environmental change will cause shifts in species communities, with non‐native species likely replacing native ones at an unprecedented rate. This will have consequences for biodiversity and ecosystem services, in addition to the ecological and economic damage caused by those non‐native species that are invasive. Understanding general patterns driving distributions of native and non‐native species is therefore vital, but no study has compared yet whether environmental variables that correlate with a species' presence differ between the two groups other than at local scale and often with very limited sample size. In this study, we focus on 141 native and non‐native congeneric plant species pairs at the scale of Switzerland. In the framework of correlative species distribution models, we used newly developed methods for efficient automated selection of a parsimonious number of predictor environmental variables to determine which ones, out of a large candidate set in eight classes, have the strongest explanatory power for both species groups. Our results indicated that variables influence the two groups in significantly different ways. Climate was by far the strongest determinant of both native and non‐native species distributions, although it had significantly more explanatory power in native species models. Models for non‐native species were significantly more influenced by anthropogenic factors, land use variables and forest cover. The presence of non‐native species was also associated with habitats with a significantly lower mean naturality value than native species. These findings provide novel empirical evidence for the different environmental factors driving native and non‐native plants' distributions and guidance for non‐native species management. Practical implications: species distribution models are an increasingly frequently advised tool for conservation management and our results provide guidelines on which covariates should be specifically considered to assess the habitat suitability of non‐native versus native species. The distributions of the former group of species are particularly important to research, as, in time, they may turn invasive. In addition, areas close to infrastructure should be scanned regularly for incipient colonizations by non‐native species, especially in as yet uninvaded areas, such as high mountains.

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

Cited by 5 publications

References 61 publications

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

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

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

Distributions of non‐native and native plants are not determined by the same environmental factors

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