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At least 19 recordsLinked to original sources

PubMed2026

Species distribution models predict genome-wide polymorphism and gene flow in an endangered amphibian.

Species distribution models (SDMs) are widely used to predict habitat suitability but their usefulness and accuracy for inferring population health is still debated. Here, we evaluate whether SDM-derived relative habitat suitability (RHS) predicts genome-wide genetic diversity and connectivity-which are key proxies for population health and the functional integrity of landscapes. We addressed this issue in the Yellow-bellied toad (Bombina variegata), an endangered amphibian species with limited dispersal. We combined hierarchical SDMs, integrating both continental-level bioclimatic data and regional-level landscape variables, with genome-wide SNP data from 404 individuals sampled across 92 sites in southeastern France. We then used a multi-scale modelling framework to test the effect of bioclimatic (BRHS) and landscape (LRHS) habitat suitability on observed heterozygosity and pairwise genetic differentiation, accounting for heterogeneous genetic drift using gravity models. Our results show that both BRHS and LRHS are significant predictors of heterozygosity, with their effects expressed at different spatial scales-11 km and 3 km for BRHS and LRHS, respectively. Connectivity patterns also widely varied depending on scale and were best explained by gravity models integrating LRHS, BRHS, and local heterozygosity, underscoring the combined role of landscape resistance and population size in shaping patterns of genetic differentiation. These findings show that SDMs, when carefully calibrated and interpreted, can provide proxies for genetic diversity and landscape resistance in species with limited dispersal.

Journal Article↗

PubMed2006

Modeling species' distributions to improve conservation in semiurban landscapes: koala case study.

Models of species' distributions are commonly used to inform landscape and conservation planning. In urban and semiurban landscapes, the distributions of species are determined by a combination of natural habitat and anthropogenic impacts. Understanding the spatial influence of these two processes is crucial for making spatially explicit decisions about conservation actions. We present a logistic regression model for the distribution of koalas (Phascolarctos cinereus) in a semiurban landscape in eastern Australia that explicitly separates the effect of natural habitat quality and anthropogenic impacts on koala distributions. We achieved this by comparing the predicted distributions from the model with what the predicted distributions would have been if anthropogenic variables were at their mean values. Similar approaches have relied on making predictions assuming anthropogenic variables are zero, which will be unreliable if the training data set does not include anthropogenic variables close to zero. Our approach is novel because it can be applied to landscapes where anthropogenic variables are never close to zero. Our model showed that, averaged across the study area, natural habitat was the main determinant of koala presence. At a local scale, however anthropogenic impacts could be more important, with consequent implications for conservation planning. We demonstrated that this modeling approach, combined with the visual presentation of predictions as a map, provides important information for making decisions on how different conservation actions should be spatially allocated. This method is particularly useful for areas where wildlife and human populations exist in close proximity.

Animals↗

PubMed2026

Species Distribution Models Support Distinct and Non-Random Climatic Constraints on Globally Distributed Generalist Fungi.

Fungi play essential roles in ecosystems as pathogens, mutualists, and ubiquitous decomposers. However, like many important microbes, the spatial distribution of species and natural populations remains poorly understood compared to plants and animals. Many fungi are described as global generalists because they occur across wide geographic areas, but it remains unclear how and if these species are constrained by climate or geographic barriers. In this study, we used Species Distribution Models to infer the global climatic suitability of three common and globally distributed fungi: Aspergillus flavus, Penicillium chrysogenum and Aspergillus fumigatus. Models were constructed using global occurrence data from the Global Biodiversity Information Facility and were trained with Bioclimatic variables from the WorldClim dataset. All species' models showed high prediction fit, with predicted occurrence concentrated in the temperate and subtropical regions and broadly structured patterns. Each species showed distinct predicted distributions, but they displayed considerable spatial overlap on a global scale. Together, these results demonstrate that even apparently globally occurring and generalist fungal species occupy climatically structured niches. This study highlights the utility of SDMs and it provides a framework for future studies integrating ecological, genomics and evolutionary perspectives among the difficult to assess geographically widespread and common fungi.

comparative biogeography↗

PubMed2006

Building statistical models to analyze species distributions.

Models of the geographic distributions of species have wide application in ecology. But the nonspatial, single-level, regression models that ecologists have often employed do not deal with problems of irregular sampling intensity or spatial dependence, and do not adequately quantify uncertainty. We show here how to build statistical models that can handle these features of spatial prediction and provide richer, more powerful inference about species niche relations, distributions, and the effects of human disturbance. We begin with a familiar generalized linear model and build in additional features, including spatial random effects and hierarchical levels. Since these models are fully specified statistical models, we show that it is possible to add complexity without sacrificing interpretability. This step-by-step approach, together with attached code that implements a simple, spatially explicit, regression model, is structured to facilitate self-teaching. All models are developed in a Bayesian framework. We assess the performance of the models by using them to predict the distributions of two plant species (Proteaceae) from South Africa's Cape Floristic Region. We demonstrate that making distribution models spatially explicit can be essential for accurately characterizing the environmental response of species, predicting their probability of occurrence, and assessing uncertainty in the model results. Adding hierarchical levels to the models has further advantages in allowing human transformation of the landscape to be taken into account, as well as additional features of the sampling process.

Bayes Theorem↗

PubMed2005

Reserve selection using nonlinear species distribution models.

Reserve design is concerned with optimal selection of sites for new conservation areas. Spatial reserve design explicitly considers the spatial pattern of the proposed reserve network and the effects of that pattern on reserve cost and/or ability to maintain species there. The vast majority of reserve selection formulations have assumed a linear problem structure, which effectively means that the biological value of a potential reserve site does not depend on the pattern of selected cells. However, spatial population dynamics and autocorrelation cause the biological values of neighboring sites to be interdependent. Habitat degradation may have indirect negative effects on biodiversity in areas neighboring the degraded site as a result of, for example, negative edge effects or lower permeability for animal movement. In this study, I present a formulation and a spatial optimization algorithm for nonlinear reserve selection problems in grid-based landscapes that accounts for interdependent site values. The method is demonstrated using habitat maps and nonlinear habitat models for threatened birds in the Netherlands, and it is shown that near-optimal solutions are found for regions consisting of up to hundreds of thousands grid cells, a landscape size much larger than those commonly attempted even with linear reserve selection formulations.

Algorithms↗

PubMed2005

Process-based models of species distributions and the mid-domain effect.

Null models that place species ranges at random within a bounded geographical domain produce hump-shaped species richness gradients (the "mid-domain effect," or MDE). However, there is debate about the extent to which these models are a suitable null expectation for effects of environmental gradients on species richness. Here, I present a process-based framework for modeling species distributions within a bounded geographical domain. Analysis of null models consistent with the mid-domain hypothesis shows that MDEs are indeed likely to be ubiquitous consequences of geographical domain boundaries. Comparing the probability distributions of range locations for the process-based and randomization-based models reveals that randomization models probably overestimate the contribution of MDEs to empirical patterns of species richness, but it also indicates that other testable predictions from randomization models are likely to be robust. I also show how this process-based framework can be extended beyond null models to incorporate effects of environmental gradients within the domain. This study provides a first step toward an ecological theory of species distributions in geographical space that can incorporate both "geometric constraints" and effects of environmental gradients, and it shows how such a theory can inform our understanding of species richness gradients in nature.

Biodiversity↗

PubMed2002

Species sensitivity distributions: data and model choice.

Species sensitivity distributions (SSDs) are increasingly incorporated into ecological risk assessment procedures. Although these new techniques offer a more transparent approach to risk assessment they demand more and superior quality data. Issues of data quantity and quality are especially important for marine datasets that tend to be smaller (and have fewer standard test methods) when compared with freshwater data. An additional source of uncertainty when using SSDs is appropriate selection from the range of methods used in their construction. We show through examples the influence of data quantity, data quality, and choice of model. We then show how regulatory decisions may be affected by these factors.

Decision Making↗

PubMed2025

Time-lagged genomic erosion and future environmental risks in a bird on the brink of extinction.

Global biodiversity is rapidly declining due to habitat degradation and genomic erosion, highlighting the urgent need to monitor endangered species and their genetic health. Temporal genomics and ecological modelling offer finer resolution than single-time-point measurements, providing a comprehensive view of species' recent and future trajectories. We investigated genomic erosion and environmental suitability in the critically endangered regent honeyeater (Anthochaera phrygia) by sequencing whole genomes of historical and modern specimens and building multi-temporal species distribution models (SDMs) across the last century. The species has declined from hundreds of thousands of individuals to fewer than 300 over the past 100 years. SDMs correctly predicted known patterns of local extinction in southeast Australia. Our demographic reconstructions revealed a gradual population decline from 2000 to 2500 years ago, sharply accelerating in the last 500 years due to climate variability and habitat loss. Despite this substantial demographic collapse, the regent honeyeater has lost only 9% of its genetic diversity, with no evidence of inbreeding or connectivity loss. Also, it exhibits higher diversity than many other threatened bird species. Forward-in-time genomic simulations indicate that this time lag between population decline and genetic diversity loss conceals the risk of ongoing genomic erosion into a future of rapidly degrading environmental suitability. Our work underscores the need for targeted conservation efforts and continuous genetic monitoring to prevent species extinction.

Animals↗

PubMed2006

Propagule vs. niche limitation: untangling the mechanisms behind plant species' distributions.

Distinguishing the roles of propagule limitation and niche requirements in controlling plant species distributions is important for understanding community structure, invasion, and restoration. We used species distribution models based on plant and environmental survey data to assess the strength of species' affinities for particular environmental conditions. We hypothesized that species with statistically detectable environmental requirements were primarily niche-limited, while species with weak habitat affinities were primarily propagule-limited. We tested this hypothesis via a seeding experiment in which we compared species' reproductive fitness in occupied and unoccupied sites. Species that appeared to be niche-limited based on distribution models had lower fitness when planted in unoccupied sites, while species that models suggested were propagule-limited had equivalent fitness when planted in occupied and unoccupied sites. Our results demonstrate that within a single community, both species limited primarily by niche availability or primarily by propagule availability can be identified using observational data.

Ecosystem↗

PubMed2025

Common to rare transfer learning (CORAL) enables inference and prediction for a quarter million rare Malagasy arthropods.

DNA-based biodiversity surveys result in massive-scale data, including up to millions of species-of which, most are rare. Making the most of such data for inference and prediction requires modeling approaches that can relate species occurrences to environmental and spatial predictors, while incorporating information about their taxonomic or phylogenetic placement. Even if the scalability of joint species distribution models to large communities has greatly advanced, incorporating hundreds of thousands of species has not been feasible to date, leading to compromised analyses. Here we present a 'common to rare transfer learning' (CORAL) approach, based on borrowing information from the common species to enable statistically and computationally efficient modeling of both common and rare species. We illustrate that CORAL leads to much improved prediction and inference in the context of DNA metabarcoding data from Madagascar, comprising 255,188 arthropod species detected in 2,874 samples.

Animals↗

PubMed2004

Living with uncertainty: genetic imprints of climate shifts in East Pacific anchovy (Engraulis mordax) and sardine (Sardinops sagax).

In the upwelling zone of the northeastern Pacific, cold nutrient-rich conditions alternate with warm nutrient-poor intervals on timescales ranging from months to millennia. In this setting, the abundances of Pacific sardine (Sardinops sagax) and northern anchovy (Engraulis mordax) fluctuate by several orders of magnitude, with sardine dominating during warm conditions and anchovy dominating during cool conditions. Two population models can explain the response of these fishes to adverse conditions. Under the basin model, species distributions contract to a central (optimal) range during population crashes. Expectations of this model may include a single range-wide population with a decline in genetic diversity on both sides of a central refuge. In contrast, the self-recruitment model invokes a series of local oceanographic domains that maintain semi-isolated subpopulations. During adverse conditions, some subpopulations cannot complete the life cycle within the local environment and are extirpated. Expectations of this model include some degree of population genetic structure and no clear gradient in genetic diversity. We examined mitochondrial DNA cytochrome b sequences to assess these competing models for anchovy (N = 196; 539 bp) and sardine (N = 107; 425 bp). The mitochondrial DNA gene genealogies are shallow but diverse for both species. Haplotype frequencies are homogeneous among subpopulations, but genetic diversities peak for both species along Baja California and adjacent southern California. Mismatch distributions and Tajima's D-values reveal distinctive signatures of population bottlenecks and expansions. Sardine haplotypes coalesce at approximately 241,000 years bp, with an initial female effective population size Nf0 = 0 followed by exponential growth to Nf1 = 115 million. Anchovy haplotypes coalesce at approximately 282,000 years bp, with an initial population size of Nf0 = 14,000, followed by exponential growth to Nf1 = 2.3 million. These results indicate a founder event for sardine and a severe population decline for anchovy in the California Current during the late Pleistocene. Overall, these data support the basin model on decadal timescales, although local recruitment may dominate on shorter timescales.

Animals↗

PubMedDate not supplied

The effect of pH on the decomposition of hydrophenols in aqueous solutions by ultraviolet direct photolysis and the ultraviolet-hydrogen peroxide process.

The decomposition of catechol (o-hydrophenol) and resorcinol (m-hydrophenol) in aqueous solution by 254-nm UV direct photolysis and the UV-hydrogen peroxide (H2O2) process under various solution pH values was studied. The light absorbance and photolytic properties of catechol and resorcinol were found to be highly dependent on solution pH and can be adequately described with a three-species distribution model. For the UV-H2O2 process, the individual contribution to the decomposition of pollutants by direct photolysis and indirect hydroxyl radical destruction was differentiated by studying the linear addition of UV light absorbance of various reactant species. The contribution to the decomposition of the two hydrophenols by hydroxyl radical destruction was more than 95% in acidic and neural solutions for treatment with the UV-H2O2 process.

Catechols↗

PubMed2004

In vivo synchrotron study of thallium speciation and compartmentation in Iberis intermedia.

Thallium (TI) is a metal of great toxicological concern and its prevalence in the natural environment has steadily increased as a result of manufacturing and combustion practices. Due to its low natural abundance and increasing demand, TI is the fourth most expensive metal, thus, recovery and reuse could be a profitable endeavor. The hyperaccumulator Iberis intermedia was examined via in vivo micro-X-ray absorption near edge (micro-XANES) and micro-X-ray fluorescence (micro-XRF) spectroscopies to determine the speciation and distribution of TI within leaves of the plant. I. intermedia plants were cultivated under controlled conditions in 0, 10, and 20 mg TI kg(-1) soil leading to a shoot concentration of up to 13 430 mg TI kg(-1) dry weight plant mass during 10 weeks of growth. Live plant leaves were examined by micro-XANES and micro-XRF which determined aqueous TI(I) to be the model species distributed primarily throughout the vascular network. A direct relationship of vein size to TI concentration was observed. The high uptake of TI and high potential biomass of I. intermedia, combined with knowledge of TI speciation and compartmentation within the plant, are discussed in terms of accumulation/tolerance mechanisms, consequences for potential food chain contamination, and phytomining strategies to reclaim TI-contaminated soils, sediments, and waters.

Biodegradation, Environmental↗

PubMed2025

Eco-Evolutionary Genomics Reveal Mountain Range-Specific Adaptation and Intraspecific Variation in Vulnerability to Climate Change of Alpine Endemics.

Alpine plants restricted to rocky habitats exhibit intraspecific diversification due to range fragmentation during Holocene warming, complicating predictions of their climate vulnerability. A lack of understanding of eco-evolutionary mechanisms driving their response to climate change results in ineffective conservation efforts. To uncover the genomic basis of their diversification and explain spatial patterns of their vulnerability, we combine landscape genomics and species distribution modelling. Our model, the Campanula lehmanniana complex, occurs in three distinct central Asian mountain ranges, considered both a biodiversity hotspot and a vascular plant diversity darkspot. Genome-environment association confirmed the adaptive basis of intraspecific diversification, driven by numerous loci of small effect. Genomic and ecological data indicate mountain range-specific climate sensitivity driven by altitude, temperature and precipitation. The cold-dry adapted group from Zeravshan-Hissar Mts will face niche decline but show a higher degree of preadaptation to future climate, while the temperate-humid group from Tian Shan shows an opposite response, with a higher risk of maladaptation despite predicted niche expansion. Maladapted populations at northern margins may require an influx of adaptive variation to cope with predicted changes. However, limited landscape connectivity between island-like habitats, combined with long migration distances required to minimise genotype-environment disruption, highlights the role of human-assisted migration in enabling evolutionary rescue. These results underscore the need to facilitate gene flow from pre- to maladapted populations and the importance of population-specific approaches to inform effective conservation strategies in heterogeneous mountain ecosystems. The results may be relevant to numerous Central Asian mountain species that show similar phylogeographic patterns.

Climate Change↗

PubMed2025

Heat-Induced Secondary Dormancy Contributes to Local Adaptation in Arabidopsis thaliana.

Seeds should not germinate in conditions unsuitable for seedling growth. Dormancy, which allows seeds to remain inactive in an environment that would otherwise enable germination, helps optimise the timing of germination. Primary dormancy, developed during seed maturation on the parent plant, prevents immediate germination post-dispersal, regardless of external conditions. Secondary dormancy, however, is triggered post-dispersal when seeds face unfavourable conditions, enabling them to re-enter dormancy even if initially non-dormant. This mechanism allows seeds to fine-tune germination according to environmental conditions. In this study, we examined the role of heat-induced secondary dormancy in local adaptation by analysing natural variations within 361 Arabidopsis thaliana accessions from across Europe. We discovered that secondary dormancy acquisition varies with primary dormancy levels and after-ripening. Both primary and heat-induced secondary dormancy exhibited adaptive clines along temperature and precipitation gradients, with secondary dormancy showing a steeper cline, indicating its significant role in local adaptation. Using species distribution models, we predicted that genotypes with high secondary dormancy would show greater resilience to future climate changes. Additionally, we identified specific genomic regions controlling secondary dormancy levels including a novel candidate gene for secondary dormancy variation. Our findings show that secondary dormancy is a complex adaptive mechanism and a predominant contributor to the dormancy trait syndrome that favours plant survival in habitats exposed to harsh summers.

Arabidopsis↗

PubMed2006

From descriptive to predictive distribution models: a working example with Iberian amphibians and reptiles.

BACKGROUND: Aim of the study was to identify the conditions under which spatial-environmental models can be used for the improved understanding of species distributions, under the explicit criterion of model predictive performance. I constructed distribution models for 17 amphibian and 21 reptile species in Portugal from atlas data and 13 selected ecological variables with stepwise logistic regression and a geographic information system. Models constructed for Portugal were extrapolated over Spain and tested against range maps and atlas data. RESULTS: Descriptive model precision ranged from 'fair' to 'very good' for 12 species showing a range border inside Portugal ('edge species', kappa (k) 0.35-0.89, average 0.57) and was at best 'moderate' for 26 species with a countrywide Portuguese distribution ('non-edge species', k = 0.03-0.54, average 0.29). The accuracy of the prediction for Spain was significantly related to the precision of the descriptive model for the group of edge species and not for the countrywide species. In the latter group data were consistently better captured with the single variable search-effort than by the panel of environmental data. CONCLUSION: Atlas data in presence-absence format are often inadequate to model the distribution of species if the considered area does not include part of the range border. Conversely, distribution models for edge-species, especially those displaying high precision, may help in the correct identification of parameters underlying the species range and assist with the informed choice of conservation measures.

Journal Article↗

PubMed2005

Species lifetime distribution for simple models of ecologies.

Interpretation of empirical results based on a taxa's lifetime distribution shows apparently conflicting results. Species' lifetime is reported to be exponentially distributed, whereas higher-order taxa, such as families or genera, follow a broader distribution, compatible with power-law decay. We show that both forms of evidence are consistent with a simple evolutionary model that does not require specific assumptions on species interaction. The model provides a zero-order description of the dynamics of ecological communities, and its species lifetime distribution can be computed exactly. Different behaviors are found as follows: an initial t(-3/2) power law, emerging from a random walk type of dynamics, which crosses over to a steeper t(-2) branching process-like regime and finally is cut off by an exponential decay that becomes weaker and weaker as the total population increases. Sampling effects also can be taken into account and shown to be relevant. If species in the fossil record were sampled according to the Fisher log-series distribution, lifetime should be distributed according to a t(-1) power law. Such variability of behaviors in a simple model, combined with the scarcity of data available, casts serious doubt on the possibility of validating theories of evolution on the basis of species lifetime data.

Animals↗

PubMed1996

Population dynamic models generating the lognormal species abundance distribution.

This paper deals with a new class of stochastic species abundance models where the abundances are the points of an inhomogeneous Poisson process. These models are the result of a dynamic approach in which the changes in abundances through time are described by a multivariate diffusion and speciation constitutes a homogeneous Poisson process. In particular, the lognormal model is generated by assuming that the density regulation within each species is given by the Gompertz curve and that the environmental variances are constant. A substantial generalization is obtained by introducing a general type of interspecific density regulation and correlated environmental noise. This more general mechanism also generates the lognormal species abundance distribution.

Animals↗