Dataset Information

Habitat generalist species constrain the diversity of mimicry rings in heterogeneous habitats.

ABSTRACT: How evolution creates and maintains trait patterns in species-rich communities is still an unsolved topic in evolutionary ecology. One classical example of community-level pattern is the unexpected coexistence of different mimicry rings, each of which is a group of mimetic species with the same warning signal. The coexistence of different mimicry rings in a community seems paradoxical because selection among unpalatable species should favor convergence to a single warning pattern. We combined mathematical modeling based on network theory and numerical simulations to explore how different types of selection, such as mimetic and environmental selections, and habitat use by mimetic species influence the formation of coexisting rings. We show that when habitat and mimicry are strong sources of selection, the formation of multiple rings takes longer due to conflicting selective pressures. Moreover, habitat generalist species decrease the distinctiveness of different mimicry rings' patterns and a few habitat generalist species can generate a "small-world effect", preventing the formation of multiple mimicry rings. These results may explain why the coexistence of mimicry rings is more common in groups of animals that tend towards habitat specialism, such as butterflies.

SUBMITTER: Birskis-Barros I

PROVIDER: S-EPMC7930205 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Habitat generalist species constrain the diversity of mimicry rings in heterogeneous habitats.

Birskis-Barros Irina I Freitas André V L AVL Guimarães Paulo R PR

Scientific reports 20210303 1

How evolution creates and maintains trait patterns in species-rich communities is still an unsolved topic in evolutionary ecology. One classical example of community-level pattern is the unexpected coexistence of different mimicry rings, each of which is a group of mimetic species with the same warning signal. The coexistence of different mimicry rings in a community seems paradoxical because selection among unpalatable species should favor convergence to a single warning pattern. We combined ma ...[more]

PMID: 33658554

Similar Datasets

Project description:Plant communities on tropical high islands, such as the Hawaiian Islands, are predicted to experience rapid climate change, resulting in novel climates. If increased temperature and/or drought exceed plant species' current tolerances, species that are unable to adapt or shift ranges risk extinction. By definition, habitat generalists have a wide niche breadth and thrive in a variety of habitats, whereas habitat specialists have a narrow niche breadth, and typically thrive under more specific climatic characteristics (e.g., cold). The objectives of this study were to: (1) classify plant species in the Hawaiian Islands along a habitat generalist-specialist continuum; (2) independently test the validity of species rankings, using environmental and biogeographic ranges; and (3) identify species' life-history traits that predict species location along the continuum. We quantified specialization for 170 plant species using species co-occurrence data from over one thousand plots to rank species' realized habitat niche breadth using the Jaccard index. The distribution of species along this continuum differed by species biogeographic origin, with endemic plant species ranked on the specialist end and non-native plant species ranked on the generalist end. Habitat specialization rankings also differed for four of nine tested variables (while controlling for biogeographic origin): number of habitat moisture types, minimum elevation, number of Hawaiian Islands, and life form. Life form was the only trait tested that differed across the continuum, with woody species ranked as stronger generalists than herbaceous species; this pattern was particularly evident for non-native species. This indirect method of estimating species' potential climatic flexibility uses increasingly available large plant community data sets with output rankings which represent species' realized habitat niches. Identifying species and plant communities that are on the habitat specialist end of the continuum allows for their prioritization in conservation planning, as globally the loss of specialists is an indication of degradation.

Project description:BackgroundOne of the biggest challenges in conservation is to manage multiple habitats for the effective conservation of multiple species, especially when the focal species are mobile and use multiple resources across heterogeneous protected areas. The application of ecological network tools and the analysis of the resulting species-habitat networks can help to describe such complex spatial associations and improve the conservation of species at the landscape scale.MethodsTo exemplify the application of species-habitat networks, we present a case study on butterflies inhabiting multiple grassland types across a heterogeneous protected area in North-East Italy. We sampled adult butterflies in 44 sites, each belonging to one of the five major habitat types in the protected area, that is, disturbed grasslands, continuous grasslands, evolved grasslands, hay meadows and wet meadows. First, we applied traditional diversity analyses to explore butterfly species richness and evenness. Second, we built and analyzed both the unipartite network, linking habitat patches via shared species, and the bipartite network, linking species to individual habitat patches.Aims(i) To describe the emerging properties (connectance, modularity, nestedness, and robustness) of the species-habitat network at the scale of the whole protected area, and (ii) to identify the key habitats patches for butterfly conservation across the protected area, that is, those supporting the highest number of species and those with unique species assemblages (e.g., hosting specialist species).ResultsThe species-habitat network appeared to have a weak modular structure, meaning that the main habitat types tended to host different species assemblages. However, the habitats also shared a large proportion of species that were able to visit multiple habitats and use resources across the whole study area. Even butterfly species typically considered as habitat specialists were actually observed across multiple habitat patches, suggesting that protecting them only within their focal habitat might be ineffective. Our species-habitat network approach helped identifying both central habitat patches that were able to support the highest number of species, and habitat patches that supported rare specialist species.

Project description:BACKGROUND:Population genetic diversity and structure are determined by past and current evolutionary processes, among which spatially limited dispersal, genetic drift, and shifts in species distribution boundaries have major effects. In most wildlife species, environmental modifications by humans often lead to contraction of species' ranges and/or limit their dispersal by acting as environmental barriers. However, in species well adapted to anthropogenic habitat or open landscapes, human induced environmental changes may facilitate dispersal and range expansions. In this study, we analysed whether isolation by distance and deforestation, among other environmental features, promotes or restricts dispersal and expansion in stone marten (Martes foina) populations. RESULTS:We genotyped 298 martens from eight sites at twenty-two microsatellite loci to characterize the genetic variability, population structure and demographic history of stone martens in Poland. At the landscape scale, limited genetic differentiation between sites in a mosaic of urban, rural and forest habitats was mostly influenced by isolation by distance. Statistical clustering and multivariate analyses showed weak genetic structuring with two to four clusters and a high rate of gene flow between them. Stronger genetic differentiation was detected for one stone marten population (NE1) located inside a large forest complex. Genetic differentiation between this site and all others was 20% higher than between other sites separated by similar distances. The genetic uniqueness index of NE1 was also twofold higher than in other sites. Past demographic history analyses showed recent expansion of this species in north-eastern Poland. A decrease in genetic diversity from south to north, and MIGRAINE analyses indicated the direction of expansion of stone marten. CONCLUSIONS:Our results showed that two processes, changes in species distribution boundaries and limited dispersal associated with landscape barriers, affect genetic diversity and structure in stone marten. Analysis of local barriers that reduced dispersal and large scale analyses of genetic structure and demographic history highlight the importance of isolation by distance and forest cover for the past colonization of central Europe by stone marten. This confirmed the hypothesis that human-landscape changes (deforestation) accelerated stone marten expansion, to which climate warming probably has also been contributing over the last few decades.

Project description:Species distribution models (SDM) are increasingly used to understand the factors that regulate variation in biodiversity patterns and to help plan conservation strategies. However, these models are rarely validated with independently collected data and it is unclear whether SDM performance is maintained across distinct habitats and for species with different functional traits. Highly mobile species, such as bees, can be particularly challenging to model. Here, we use independent sets of occurrence data collected systematically in several agricultural habitats to test how the predictive performance of SDMs for wild bee species depends on species traits, habitat type, and sampling technique. We used a species distribution modeling approach parametrized for the Netherlands, with presence records from 1990 to 2010 for 193 Dutch wild bees. For each species, we built a Maxent model based on 13 climate and landscape variables. We tested the predictive performance of the SDMs with independent datasets collected from orchards and arable fields across the Netherlands from 2010 to 2013, using transect surveys or pan traps. Model predictive performance depended on species traits and habitat type. Occurrence of bee species specialized in habitat and diet was better predicted than generalist bees. Predictions of habitat suitability were also more precise for habitats that are temporally more stable (orchards) than for habitats that suffer regular alterations (arable), particularly for small, solitary bees. As a conservation tool, SDMs are best suited to modeling rarer, specialist species than more generalist and will work best in long-term stable habitats. The variability of complex, short-term habitats is difficult to capture in such models and historical land use generally has low thematic resolution. To improve SDMs' usefulness, models require explanatory variables and collection data that include detailed landscape characteristics, for example, variability of crops and flower availability. Additionally, testing SDMs with field surveys should involve multiple collection techniques.

Dataset Information

Habitat generalist species constrain the diversity of mimicry rings in heterogeneous habitats.

Publications

Habitat generalist species constrain the diversity of mimicry rings in heterogeneous habitats.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets