Abstract Connectivity is important for the structure and functioning of metaecosystems. We experimentally replicated metaecosystems in the laboratory using gradostats - a modified chemostat with flasks linked by a controlled flow of medium - as a model system. Metaecosystems were represented in our experiment as chain of flasks connected by spatial flows of medium containing glyphosate based herbicide (RoundUp). With this experimental set-up, we tested the effects of structural and functional connectivity and herbicide on phytoplankton productivity, diversity and population stability. Gradostats were composed of interconnected equally-spaced habitat nodes where resources and producers flow directionally along a gradient of increasing distance from the source of the herbicide. We predicted that connectivity would mediate the effects of the herbicide spreading through the chain of connected ecosystems. We found that RoundUp impacted overall phytoplankton productivity and diversity by reducing algal biomass and species-level abundances of phytoplankton in the treated flasks compared to controls. This effect was mediated by structural connectivity, which in interaction with flow, had reduced phytoplankton community stability by the end of the experiment at the local level, especially in the first flask receiving herbicide. The effects did do not scale up to the entire metaecosystem. Together, these results point to the importance of structural connectivity as a mediator of the ecological effects of herbicide transferred by flows across a linear chain of ecosystems.
File List Ziter_2013_Ecosphere_Analysis.R (MD5: a70d20be760cc94702c81defab37bb1d) LiveTrees.csv (MD5: 1eb43347a5e2e49b3e2ab5e006f6ad19) SnagsIdentified.csv (MD5: 7e51486d1eadfbf7e3a4ab030db36fa4) SnagsUnidentified.csv (MD5: 41cddd111f48d0c8a2e14cfaf70814dd) DWD.csv (MD5: 9c85df5ebea05a0d59c6c88cb14fa828) OrderedSpecies.csv (MD5: 189a0b4fcf6ca5e85a7ba0487bd254a8) Traits.csv (MD5: 596aa39feef4e755f598c8d3fb9510a8) Traits_FDis7.csv (MD5: 31a764843081b78fe4295534bb5ca3cf) Traits_Description.csv (MD5: 6597b6e7b8260ae8c193d0341c123fd2) Description Ziter_2013_Ecosphere_Analysis.R – Annotated R script containing the code necessary to conduct the analysis described in the text LiveTrees.csv – data file containing study site information (including SiteID (the individual plot identifier), transect direction, plot number (from edge (1) to interior (5)), management status, fragment connectivity, and fragment size), tree species ID, diameter at breast height (DBH, for saplings the mean of the DBH class, recorded under “DBH(Biomass)”, was used to calculate biomass), allometric coefficients, and biomass for each individual live tree measured in the field SnagsIdentified.csv – data file containing study site information (including SiteID (the individual plot identifier), transect direction, plot number (from edge (1) to interior (5)), management status, fragment connectivity, and fragment size), tree species ID, diameter at breast height (DBH, for saplings the mean of the DBH class, recorded under “DBH(Biomass)”, was used to calculate biomass), allometric coefficients, and biomass for each snag (dead tree) measured that was identifiable to species SnagsUnidentified.csv – data file containing study site information (including SiteID (the individual plot identifier), transect direction, plot number (from edge (1) to interior (5)), management status, fragment connectivity, and fragment size), diameter at breast height (DBH, for saplings the mean of the DBH class, recorded under “DBH(Biomass)”, was used to calculate biomass), allometric coefficients, and biomass for each snag (dead tree) measured that was not identifiable to species DWD.csv – data file containing site information (including SiteID (the individual plot identifier), transect direction, plot number (from edge (1) to interior (5)), fragment connectivity, and fragment size), and the diameter, decay class, and volume for each piece of downed woody debris measured in the field OrderedSpecies.csv – data file containing an alphabetically ordered list of all tree species found in the study region Traits.csv – data file containing the full set of functional traits for each tree species Traits_FDis7.csv – reduced traits data file containing only the traits used in the final analysis Traits_Description.csv – text file describing the information in the “Traits.csv” and “Traits_FDis7.csv” files, including explanatory codes for the functional traits used to compute functional diversity indices, trait type, transformations and trait weights, and literature sources.
Abstract Anthropogenic environmental change is causing habitat deterioration at unprecedented rates in freshwater ecosystems. Despite increasing more rapidly than other agents of global change, synthetic chemical pollution –including agrochemicals such as pesticides– has received relatively little attention in freshwater biotic assessments. Determining the effects of multiple agrochemicals on complex community and ecosystem properties remains a major challenge, requiring a cross-field integration of ecology and ecotoxicology. Using a large-scale array of experimental ponds, we investigated the response of zooplankton community properties (biomass, composition, diversity metrics) to the individual and joint presence of three widespread agrochemicals: the herbicide glyphosate, the neonicotinoid insecticide imidacloprid, and fertilisers. We tracked temporal variation in community biomass and structure (i.e., composition, diversity metrics) along single and combined pesticide gradients (each spanning eight levels), under low (mesotrophic) and high (eutrophic) nutrient-enriched conditions, and quantified (i) agrochemical interactions, (ii) response threshold concentrations, and (iii) community resistance and recovery. We found that major zooplankton groups differed in their sensitivity to pesticides: ≥3 µg/L imidacloprid impaired copepods, rotifers collapsed at glyphosate levels ≥0.3 mg/L, whereas some cladocerans were highly tolerant to pesticide contamination. Glyphosate was the most influential driver of community properties, with biomass and community structure responding rapidly but recovering unequally over time. Zooplankton biomass showed little resistance when first exposed to glyphosate, but rapidly recovered and even increased with glyphosate concentration; in contrast, richness declined in more contaminated ponds but failed to recover. Our results show that the biomass of tolerant taxa compensated for the loss of sensitive species, conferring greater resistance upon subsequent exposure; a rare example of pollution-induced community tolerance in freshwater metazoans. Overall, zooplankton biomass appears to be more resilient to agrochemical pollution than community structure, yet all community properties measured in this study were affected at glyphosate levels below common water quality guidelines in North America.
Rapid evolution can sometimes prevent population extirpation in stressful environments, but the conditions leading to “evolutionary rescue” in metacommunities are unclear. Here we studied the eco-evolutionary response of microbial metacommunities adapting to selection by the antibiotic streptomycin. Our experiment tested how the history of antibiotic selection and contrasting modes of dispersal influenced diversification and subsequent evolutionary rescue in microbial metacommunities undergoing adaptive radiation. We first tracked the change in diversity and density of Pseudomonas fluorescens morphotypes selected on a gradient of antibiotic stress. We then examined the recovery of these metacommunities following abrupt application of a high concentration of streptomycin lethal to the ancestral organisms. We show that dispersal increases diversity within the stressed metacommunities, that exposure to stress alters diversification dynamics, and that community composition, dispersal, and past exposure to stress mediate the speed at which evolutionary rescue occurs, but not the final outcome of recovery in abundance and diversity. These findings extend recent experiments on evolutionary rescue to the case of metacommunities undergoing adaptive diversification, and should motivate new theory on this question. Our findings are also relevant to evolutionary conservation biology and research on antimicrobial resistance.
The biodiversity and ecosystem functioning (BEF) relationship is expected to be scale-dependent. The autocorrelation of environmental heterogeneity is hypothesized to explain this scale dependence because it influences how quickly biodiversity accumulates over space or time. However, this link has yet to be demonstrated in a formal model. Here, we use a Lotka-Volterra competition model to simulate community dynamics when environmental conditions vary across either space or time. Species differ in their optimal environmental conditions, which results in turnover in community composition. We vary biodiversity by modelling communities with different sized regional species pools and ask how the amount of biomass per unit area depends on the number of species present, and the spatial or temporal scale at which it is measured. We find that more biodiversity is required to maintain functioning at larger temporal and spatial scales. The number of species required increases quickly when environmental autocorrelation is low, and slowly when autocorrelation is high. Both spatial and temporal environmental heterogeneity lead to scale dependence in BEF, but autocorrelation has larger impacts when environmental change is temporal. These findings show how the biodiversity required to maintain functioning is expected to increase over space and time.
Summary Biodiversity conservation in landscapes undergoing climate and land‐use changes requires designing multipurpose habitat networks that connect the movements of organisms at multiple spatial scales. Short‐range connectivity within habitat networks provides organisms access to spatially distributed resources, reduces local extinctions and increases recolonization of habitat fragments. Long‐range connectivity across habitat networks facilitates annual migrations and climate‐driven range shifts. We present a method for identifying a multipurpose network of forest patches that promotes both short‐ and long‐range connectivity. Our method uses both graph‐theoretic analyses that quantify network connectedness and circuit‐based analyses that quantify network traversability as the basis for identifying spatial conservation priorities on the landscape. We illustrate our approach in the agroecosystem, bordered by the Laurentian and Appalachian mountain ranges, that surrounds the metropolis of Montreal, Canada. We established forest conservation priorities for the ovenbird, a Neotropical migrant, sensitive to habitat fragmentation that breeds in our study area. All connectivity analyses were based on the same empirically informed resistance surface for ovenbird, but habitat pixels that facilitated short‐ and long‐range connectivity requirements had low spatial correlation. The trade‐off between connectivity requirements in the final ranking of conservation priorities showed a pattern of diminishing returns such that beyond a threshold, additional conservation of long‐range connectivity had decreased effectiveness on the conservation of short‐range connectivity. Highest conservation priority was assigned to a series of stepping stone forest patches across the study area that promote traversability between the bordering mountain ranges and to a collection of small forest fragments scattered throughout the study area that provide connectivity within the agroecosystem. Landscape connectivity is important for the ecology and genetics of populations threatened by climate change and habitat fragmentation. Our method has been illustrated as a means to conserve two critical dimensions of connectivity for a single species, but it is designed to incorporate a variety of connectivity requirements for many species. Our approach can be tailored to local, regional and continental conservation initiatives to protect essential species movements that will allow biodiversity to persist in a changing climate.
Abstract: We used socioeconomic models that included economic inequality to predict biodiversity loss, measured as the proportion of threatened plant and vertebrate species, across 50 countries. Our main goal was to evaluate whether economic inequality, measured as the Gini index of income distribution, improved the explanatory power of our statistical models. We compared four models that included the following: only population density, economic footprint (i.e., the size of the economy relative to the country area), economic footprint and income inequality (Gini index), and an index of environmental governance. We also tested the environmental Kuznets curve hypothesis, but it was not supported by the data. Statistical comparisons of the models revealed that the model including both economic footprint and inequality was the best predictor of threatened species. It significantly outperformed population density alone and the environmental governance model according to the Akaike information criterion. Inequality was a significant predictor of biodiversity loss and significantly improved the fit of our models. These results confirm that socioeconomic inequality is an important factor to consider when predicting rates of anthropogenic biodiversity loss.
Human impacts on the Earth’s biosphere are driving the global biodiversity crisis. Governments are preparing to agree on a set of actions intended to halt the loss of biodiversity and put it on a path to recovery by 2050. We provide evidence that the proposed actions can bend the curve for biodiversity, but only if these actions are implemented urgently and in an integrated manner.
Although competing species are expected to exhibit compensatory dynamics (negative temporal covariation), empirical work has demonstrated that competitive communities often exhibit synchronous dynamics (positive temporal covariation). This has led to the suggestion that environmental forcing dominates species dynamics; however, synchronous and compensatory dynamics may appear at different length scales and/or at different times, making it challenging to identify their relative importance. We compiled 58 long-term datasets of zooplankton abundance in north-temperate and sub-tropical lakes and used wavelet analysis to quantify general patterns in the times and scales at which synchronous/compensatory dynamics dominated zooplankton communities in different regions and across the entire dataset. Synchronous dynamics were far more prevalent at all scales and times and were ubiquitous at the annual scale. Although we found compensatory dynamics in approximately 14% of all combinations of time period/scale/lake, there were no consistent scales or time periods during which compensatory dynamics were apparent across different regions. Our results suggest that the processes driving compensatory dynamics may be local in their extent, while those generating synchronous dynamics operate at much larger scales. This highlights an important gap in our understanding of the interaction between environmental and biotic forces that structure communities.
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