Dataset Information

Predicting the effect of habitat modification on networks of interacting species.

ABSTRACT: A pressing challenge for ecologists is predicting how human-driven environmental changes will affect the complex pattern of interactions among species in a community. Weighted networks are an important tool for studying changes in interspecific interactions because they record interaction frequencies in addition to presence or absence at a field site. Here we show that changes in weighted network structure following habitat modification are, in principle, predictable. Our approach combines field data with mathematical models: the models separate changes in relative species abundance from changes in interaction preferences (which describe how interaction frequencies deviate from random encounters). The models with the best predictive ability compared to data requirement are those that capture systematic changes in interaction preferences between different habitat types. Our results suggest a viable approach for predicting the consequences of rapid environmental change for the structure of complex ecological networks, even in the absence of detailed, system-specific empirical data.In a changing world, the ability to predict the impact of environmental change on ecological communities is essential. Here, the authors show that by separating species abundances from interaction preferences, they can predict the effects of habitat modification on the structure of weighted species interaction networks, even with limited data.

SUBMITTER: Staniczenko PPA

PROVIDER: S-EPMC5630616 | biostudies-literature | 2017 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Predicting the effect of habitat modification on networks of interacting species.

Staniczenko Phillip P A PPA Lewis Owen T OT Tylianakis Jason M JM Albrecht Matthias M Coudrain Valérie V Klein Alexandra-Maria AM Reed-Tsochas Felix F

Nature communications 20171006 1

A pressing challenge for ecologists is predicting how human-driven environmental changes will affect the complex pattern of interactions among species in a community. Weighted networks are an important tool for studying changes in interspecific interactions because they record interaction frequencies in addition to presence or absence at a field site. Here we show that changes in weighted network structure following habitat modification are, in principle, predictable. Our approach combines field ...[more]

PMID: 28986532

Similar Datasets

Project description:Biodiversity conservation requires modeling tools capable of predicting the presence or absence (i.e., occurrence-state) of species in habitat patches. Local habitat characteristics of a patch (lh), the cost of traversing the landscape matrix between patches (weighted connectivity [wc]), and the position of the patch in the habitat network topology (nt) all influence occurrence-state. Existing models are data demanding or consider only local habitat characteristics. We address these shortcomings and present a network-based modeling approach, which aims to predict species occurrence-state in habitat patches using readily available presence-only records.For the tree frog Hyla arborea in the Swiss Plateau, we delineated habitat network nodes from an ensemble habitat suitability model and used different cost surfaces to generate the edges of three networks: one limited only by dispersal distance (Uniform), another incorporating traffic, and a third based on inverse habitat suitability. For each network, we calculated explanatory variables representing the three categories (lh, wc, and nt). The response variable, occurrence-state, was parametrized by a sampling intensity procedure assessing observations of comparable species over a threshold of patch visits. The explanatory variables from the three networks and an additional non-topological model were related to the response variable with boosted regression trees.The habitat network models had a similar fit; they all outperformed the non-topological model. Habitat suitability index (lh) was the most important predictor in all networks, followed by third-order neighborhood (nt). Patch size (lh) was unimportant in all three networks.We found that topological variables of habitat networks are relevant for the prediction of species occurrence-state, a step-forward from models considering only local habitat characteristics. For any habitat patch, occurrence-state is most prominently influenced by its habitat suitability and then by the number of patches in a wide neighborhood. Our approach is generic and can be applied to multiple species in different habitats.

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:BackgroundThe positive relationship between habitat area and species number is considered a fundamental rule in ecology. This relationship predicts that the link number of species interactions increases with habitat area, and structure is related to habitat area. Biological invasions can affect species interactions and area relationships. However, how these relationships change at different spatial scales has remained unexplored. We analysed understory plant-pollinator networks in seven temperate forest sites at 20 spatial scales (radius 120-2020 m) to clarify scale-associated relationships between forest area and plant-pollinator networks.ResultsThe pooled data described interactions between 18 plant (including an exotic) and 89 pollinator (including an exotic) species. The total number of species and the number of interaction links between plant and pollinator species were negatively correlated with forest area, with the highest correlation coefficient at radii of 1520 and 1620 m, respectively. These results are not concordant with the pattern predicted by species-area relationships. However, when associations with exotic species were excluded, the total number of species and the number of interaction links were positively correlated with forest area (the highest correlation coefficient at a radius of 820 m). The network structure, i.e., connectance and nestedness, was also related to forest area (the highest correlation coefficients at radii of 720-820 m), when associations with exotics were excluded. In the study area, the exotic plant species Alliaria petiolata, which has invaded relatively small forest patches surrounded by agricultural fields, may have supported more native pollinator species than initially expected. Therefore, this invasive plant may have altered the original relationships between forest area and plant-pollinator networks.ConclusionsOur results demonstrate scale-dependent effects of forest area on the size and structure of plant-pollinator networks. We also suggest that a single exotic plant species can impact plant-pollinator networks, even in temperate continental habitats.

Project description:Changes in species' trophic niches due to habitat degradation can affect intra- and interspecific competition, with implications for biodiversity persistence. Difficulties of measuring species' interactions in the field limit our comprehension of competition outcomes along disturbance gradients. Thus, information on how habitat degradation can destabilize food webs is scarce, hindering predictions regarding responses of multispecies systems to environmental changes. Seagrass ecosystems are undergoing degradation. We address effects of Posidonia oceanica coverage reduction on the trophic organization of a macroinvertebrate community in the Tyrrhenian Sea (Italy), hypothesizing increased trophic generalism, niche overlap among species and thus competition and decreased community stability due to degraded conditions. Census data, isotopic analysis, and Bayesian mixing models were used to quantify the trophic niches of three abundant invertebrate species, and intra- and interspecific isotopic and resource-use similarity across locations differing in seagrass coverage. This allowed the computation of (1) competition strength, with respect to each other and remaining less abundant species and (2) habitat carrying capacity. To explore effects of the spatial scale on the interactions, we considered both individual locations and the entire study area ("'meadow scale"). We observed that community stability and habitat carrying capacity decreased as P. oceanica coverage declined, whereas niche width, similarity of resource use and interspecific competition strength between species increased. Competition was stronger, and stability lower, at the meadow scale than at the location scale. Indirect effects of competition and the spatial compartmentalization of species interactions increased stability. Results emphasized the importance of trophic niche modifications for understanding effects of habitat loss on biodiversity persistence. Calculation of competition coefficients based on isotopic distances is a promising tool for describing competitive interactions in real communities, potentially extendible to any subset of ecological niche axes for which specimens' positions and pairwise distances can be obtained.

Project description:Conservation increasingly operates at the landscape scale. For this to be effective, we need landscape scale information on species distributions and the environmental factors that underpin them. Species records are becoming increasingly available via data centres and online portals, but they are often patchy and biased. We demonstrate how such data can yield useful habitat suitability models, using bat roost records as an example. We analysed the effects of environmental variables at eight spatial scales (500 m - 6 km) on roost selection by eight bat species (Pipistrellus pipistrellus, P. pygmaeus, Nyctalus noctula, Myotis mystacinus, M. brandtii, M. nattereri, M. daubentonii, and Plecotus auritus) using the presence-only modelling software MaxEnt. Modelling was carried out on a selection of 418 data centre roost records from the Lake District National Park, UK. Target group pseudoabsences were selected to reduce the impact of sampling bias. Multi-scale models, combining variables measured at their best performing spatial scales, were used to predict roosting habitat suitability, yielding models with useful predictive abilities. Small areas of deciduous woodland consistently increased roosting habitat suitability, but other habitat associations varied between species and scales. Pipistrellus were positively related to built environments at small scales, and depended on large-scale woodland availability. The other, more specialist, species were highly sensitive to human-altered landscapes, avoiding even small rural towns. The strength of many relationships at large scales suggests that bats are sensitive to habitat modifications far from the roost itself. The fine resolution, large extent maps will aid targeted decision-making by conservationists and planners. We have made available an ArcGIS toolbox that automates the production of multi-scale variables, to facilitate the application of our methods to other taxa and locations. Habitat suitability modelling has the potential to become a standard tool for supporting landscape-scale decision-making as relevant data and open source, user-friendly, and peer-reviewed software become widely available.

Dataset Information

Predicting the effect of habitat modification on networks of interacting species.

Publications

Predicting the effect of habitat modification on networks of interacting species.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets