The spatial insurance hypothesis predicts that intermediate rates of dispersal between patches in a metacommunity allow species to track favourable conditions, preserving diversity and stabilizing ...biomass at local and regional scales. However, theory is unclear as to whether dispersal will provide spatial insurance when environmental conditions are changing directionally. In particular, increased temperatures as a result of climate change are expected to cause synchronous growth or decline across species and communities, and this has the potential to erode the stabilizing compensatory dynamics facilitated by dispersal. Here we report on an experimental test of how dispersal affects the diversity and stability of metacommunities under warming using replicate two‐patch pond zooplankton metacommunities. Initial differences in local community composition and abiotic conditions were established by seeding each patch in the metacommunities with plankton and sediment from one of two natural ponds that differed in water chemistry and species composition. We exposed metacommunities to a 2°C increase in average ambient temperature, crossed with three rates of dispersal (none, intermediate, high). In ambient conditions, intermediate dispersal rates preserved diversity and stabilized metacommunities by promoting spatially asynchronous fluctuations in biomass, especially between local populations of the dominant genus, Ceriodaphnia. However, warming synchronized their populations so that these effects of dispersal were lost. Furthermore, because the stabilizing effect of dispersal was primarily due to asynchronous fluctuations between populations of a single genus, metacommunity biomass was stabilized, but dispersal did not stabilize local community biomass. Our results show that dispersal can preserve diversity and provide stability to metacommunities, but also show that this benefit can be eroded when warming is directional and synchronous across patches of a metacommunity, as is expected with climate warming.
Predictions of the distribution of groundfish species are needed to support ongoing marine spatial planning initiatives in Canadian Pacific waters. Data to inform species distribution models are ...available from several fishery-independent surveys. However, no single survey covers the entire region and different gear types are required to survey the range of relevant habitat. Here, we demonstrated a method for integrating presence-absence data across surveys and gear types that allows us to predict the coastwide distributions of 65 groundfish species in British Columbia. Our model leverages data from multiple surveys to estimate how species respond to environmental gradients while accounting for differences in survey catchability. We find that this method has two main benefits: (1) it increases the accuracy of predictions in data-limited surveys and regions while having negligible impacts on accuracy when data are already sufficient, and (2) it reduces uncertainty, resulting in tighter confidence intervals on predicted occurrences. These benefits are particularly relevant in areas of our coast where our understanding of habitat suitability is limited due to a lack of spatially comprehensive long-term groundfish surveys.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Environmental fluctuations influence patterns of synchrony and stability in species abundances. Most of our understanding of synchrony and stability stems from competitive community and metacommunity ...ecology, when in reality species interact in more complex ways. Therefore, there is a mounting need for the integration of multi‐trophic interactions into metacommunity ecology. In particular, knowledge is lacking on: (1) whether synchrony and stability respond to environmental fluctuations similarly under competitive and multi‐trophic metacommunities; (2) how synchrony and stability change across the hierarchical levels of a metacommunity; and (3) whether trophic groups differ in their contributions to synchrony and stability. Here, we address these questions through a complementary approach, using model simulations to derive theoretical expectations for the effects of environmental fluctuations on synchrony and stability, and a microcosm experiment to test observations against these expectations. We created spatially heterogeneous metacommunities populated by eight protist and one rotifer species organized in a multi‐trophic food‐web. We controlled environmental fluctuations so that they were spatially uncorrelated and species were assumed to respond differently to environmental conditions. We contrasted the control of constant environmental conditions to the effects of periodic environmental fluctuations. We show that environmental fluctuations can reduce synchrony between patches and increase stability, but can also decouple asynchrony between species and increase population and metapopulation variability. We discuss how some of these findings apply to both competitive and multi‐trophic metacommunities but changes are stronger in multi‐trophic metacommunities, and how trophic groups differ in their contributions to synchrony and variability.
Marine spatial planning and conservation initiatives benefit from an understanding of species distributions across larger geographic areas than are often sampled by any one survey. Here, we test ...whether the integration of disparate survey data can improve habitat predictions across a region not well sampled by a single survey using Dungeness crab ( Metacarcinus magister) from British Columbia as a case study. We assemble data from dive, trawl, and baited-trap surveys to generate six candidate generalized linear mixed-effect models with spatial random fields. To compare single-survey and integrated models, we evaluate predictive performance with spatially buffered leave-one-out cross-validation and independently with two novel approaches using fisheries catch data. We find improved predictive performance and reduced uncertainty when integrating data from surveys that suffer from small sample size, low detectability, or limited spatial coverage. We demonstrate the importance of robust model evaluation when integrating data and predicting to unsampled locations. In addition, we highlight the need for careful consideration of sampling biases and model assumptions when integrating data to reduce the risk of prediction errors.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
In metacommunity ecology, a major focus has been on combining observational and analytical approaches to identify the role of critical assembly processes, such as dispersal limitation and ...environmental filtering, but this work has largely ignored temporal community dynamics. Here, we develop a “virtual ecologist” approach to evaluate assembly processes by simulating metacommunities varying in three main processes: density‐independent responses to abiotic conditions, density‐dependent biotic interactions, and dispersal. We then calculate a number of commonly used summary statistics of community structure in space and time and use random forests to evaluate their utility for inferring the strength of these three processes. We find that (i) both spatial and temporal data are necessary to disentangle metacommunity processes based on the summary statistics we test, and including statistics that are measured through time increases the explanatory power of random forests by up to 59% compared to cases where only spatial variation is considered; (ii) the three studied processes can be distinguished with different descriptors; and (iii) each summary statistic is differently sensitive to temporal and spatial sampling effort. Including repeated observations of metacommunities over time was essential for inferring the metacommunity processes, particularly dispersal. Some of the most useful statistics include the coefficient of variation of species abundances through time and metrics that incorporate variation in the relative abundances (evenness) of species. We conclude that a combination of methods and summary statistics is probably necessary to understand the processes that underlie metacommunity assembly through space and time, but we recognize that these results will be modified when other processes or summary statistics are used.
1. Climate change and other human-driven environmental perturbations are causing reductions in biodiversity and impacting the functioning of ecosystems on a global scale. Metacommunity theory ...suggests that ecosystem connectivity may reduce the magnitude of these impacts if the regional species pool contains functionally redundant species that differ in their environmental tolerances. Dispersal may increase the resistance of local ecosystems to environmental stress by providing regional species with traits adapted to novel conditions. 2. We tested this theory by subjecting freshwater Zooplankton communities in mesocosms that were either connected to or isolated from the larger regional species pool to a factorial manipulation of experimental warming and increased salinity. 3. Compensation by regional taxa depended on the source of stress. Warming tolerant regional taxa partially compensated for reductions in heat sensitive local taxa but similar compensation did not occur under increased salinity. 4. Dispersal-mediated species invasions dampened the effects of warming on summer net ecosystem productivity. However, this buffering effect did not occur in the fall or for periphyton growth, the only other ecosystem function affected by the stress treatments. 5. The results indicate that regional biodiversity can provide insurance in a dynamic environment but that the buffering capacity is limited to some ecosystem processes and sources of stress. Maintaining regional biodiversity and habitat connectivity may therefore provide some limited insurance for local ecosystems in changing environments, but is unable to impart resistance against all sources of environmental stress.
Cumulative ecological impacts of chronic, extreme, and often novel, anthropogenic environmental changes (i.e., stressors) often differ from the sum of their individual effects. Uncertainty over the ...causes of such non‐additivity among multiple stressors confounds forecasts of their net ecological impact. Although stressors can interact directly within the environment to mediate their combined effects on communities, species interactions likely also play key roles. Here, we use a simulation model to explore how species interactions cause community responses (changes in species richness and total biomass) to paired stressors to differ from what we would expect based on the individual effects of each stressor (the additive effect). We demonstrate how interspecific interactions cause communities to respond non‐additively to stressors, and how this depends on whether these interactions are negative or positive and whether the stressors have positive or negative impacts on the community property of interest. When pairwise species interactions involve at least one negative interaction (i.e., competition or predation), stressors combine to have greater than expected negative impacts (e.g., species or biomass loss) and less than expected positive impacts (e.g., biomass increases). In contrast, reciprocally positive interactions between species (i.e., facilitation) generally cause stressors to have additive, or slightly less than additive, net effects on species richness and community biomass. While species interactions determine the nature of the combined impact of multiple stressors (i.e., greater than or less than expected), species co‐tolerance and stressor timing (i.e., sequential vs simultaneous application) only modify the magnitude of this effect. These findings highlight how interactions among species can contribute to non‐additive responses by communities to environmental change, in addition to those caused by interactions among stressors themselves.
Beyond a single patch Stark, Keila A.; Thompson, Patrick L.; Yakimishyn, Jennifer ...
Marine ecology. Progress series (Halstenbek),
11/2020, Letnik:
655
Journal Article
Recenzirano
Odprti dostop
Ecological communities are jointly structured by dispersal, density-independent responses to environmental conditions, and density-dependent biotic interactions. Metacommunity ecology provides a ...framework for understanding how these processes combine to determine community seagrass meadows along the British Columbia coast. We tested the hypothesis that eelgrass Zostera marina L. epifaunal invertebrate assemblages are influenced by local environmental conditions but that high dispersal rates at larger spatial scales dampen the effects of environmental differences. We used hierarchical joint species distribution modelling to understand the contribution of environmental conditions, spatial distance between meadows, and species co-occurrences to epifaunal invertebrate abundance and distribution across the region. We found that patterns of taxonomic compositional similarity among meadows were inconsistent with dispersal limitation, and meadows in the same region were often no more similar to each other than meadows over 1000 km away. Abiotic environmental conditions (temperature, dissolved oxygen) explained a small fraction of variation in taxonomic abundance patterns across the region. We found novel co-occurrence patterns among taxa that could not be explained by shared responses to environmental gradients, suggesting the possibility that interspecific interactions influence seagrass invertebrate abundance and distribution. Our results suggest that biodiversity and ecosystem functions provided by seagrass meadows reflect ecological processes occurring both within meadows and across seascapes and that management of eelgrass habitat for biodiversity may be most effective when both local and regional processes are considered.
Conservation of marine biodiversity requires understanding the joint influence of ongoing environmental change and fishing pressure. Addressing this challenge requires robust biodiversity monitoring ...and analyses that jointly account for potential drivers of change. Here, we ask how demersal fish biodiversity in Canadian Pacific waters has changed since 2003 and assess the degree to which these changes can be explained by environmental change and commercial fishing. Using a spatiotemporal multispecies model based on fisheries independent data, we find that species density (number of species per area) and community biomass have increased during this period. Environmental changes during this period were associated with temporal fluctuations in the biomass of species and the community as a whole. However, environmental changes were less associated with changes in species occurrence. Thus, the estimated increases in species density are not likely to be due to environmental change. Instead, our results are consistent with an ongoing recovery of the demersal fish community from a reduction in commercial fishing intensity from historical levels. These findings provide key insight into the drivers of biodiversity change that can inform ecosystem-based management.
Forecasting how climate change will impact biological systems represents a grand challenge for biologists. However, climate change biology lacks an effective framework for anticipating and resolving ...uncertainty. Here, we introduce the concept of climate change wildcards: biological or bioclimatic processes with a high degree of uncertainty and a large impact on our ability to address the biotic consequences of climate change. Wildcards may occur at multiple points in the progression of research—from understanding, to predicting, to forecasting biological responses. Our understanding of biological responses is limited by the components and processes we exclude to make research tractable. Our ability to predict biological responses often requires integration between biological levels of organization, across multiple stressors, and from specific cases to general systems. However, these types of integration can be dramatically affected by, respectively, differences between biological levels in their critical points, nonadditivity of the effects of different stressors, and historical and geographic contingency. Finally, our ability to forecast biological responses to climate change requires incorporating climatic projections in bioclimatic models. Such forecasts are vulnerable to the compounding of biological and climatic uncertainty, especially when biological responses occur in novel areas of bioclimatic parameter space. Both biological responses and climate change are dynamic processes; the potential of biological systems to be buffered against or rescued from the effects of climate change depends on the relative timing of biological and climatic effects—one of the least predictable aspects of both systems. In sum, our framework identifies stress points in the research process where we should anticipate and forestall wildcards. Focusing on universal currencies, like energy and elements, and universal structures, like functional traits and ecological networks, will improve our ability to generalize results. Most importantly, by modeling and communicating uncertainty, climate change biology can identify critical foci for future research.
PDF
