Ecological Monographs最新文献

Understanding the demographic drivers of range contractions is important for predicting species' responses to climate change; however, few studies have examined the effects of climate change on survival and recruitment across species' ranges. We show that climate change can drive trailing edge range contractions through the effects on apparent survival, and potentially recruitment, in a migratory songbird. We assessed the demographic drivers of trailing edge range contractions using a long-term demography dataset for the black-throated blue warbler (Setophaga caerulescens) collected across elevational climate gradients at the trailing edge and core of the breeding range. We used a Bayesian hierarchical model to estimate the effect of climate change on apparent survival and recruitment and to forecast population viability at study plots through 2040. The trailing edge population at the low-elevation plot became locally extinct by 2017. The local population at the mid-elevation plot at the trailing edge gradually declined and is predicted to become extirpated by 2040. Population declines were associated with warming temperatures at the mid-elevation plot, although results were more equivocal at the low-elevation plot where we had fewer years of data. Population density was stable or increasing at the range core, although warming temperatures are predicted to cause population declines by 2040 at the low-elevation plot. This result suggests that even populations within the geographic core of the range are vulnerable to climate change. The demographic drivers of local population declines varied between study plots, but warming temperatures were frequently associated with declining rates of population growth and apparent survival. Declining apparent survival in our study system is likely to be associated with increased adult emigration away from poor-quality habitats. Our results suggest that demographic responses to warming temperatures are complex and dependent on local conditions and geographic range position, but spatial variation in population declines is consistent with the climate-mediated range shift hypothesis. Local populations of black-throated blue warblers near the warm-edge range boundary at low latitudes and low elevations are likely to be the most vulnerable to climate change, potentially leading to local extirpation and range contractions.

Understanding mechanisms that generate range limits is central to knowing why species are found where they are and how they will respond to environmental change. There is growing awareness that biotic interactions play an important role in generating range limits. However, current theory and data overwhelmingly focus on abiotic drivers and antagonistic interactions. Here we explore the effect that mutualists have on their partner's range limits: the geographic “footprint” of mutualism. This footprint arises from two general processes: modification of a partner's niche through environment-dependent fitness effects and, for a subset of mutualisms, dispersal opportunities that lead suitable habitats to be filled. We developed a conceptual framework that organizes different footprints of mutualism and the underlying mechanisms that shape them, and evaluated supporting empirical evidence from the primary literature. In the available literature, we found that the fitness benefits and dispersal opportunities provided by mutualism can extend species' ranges; conversely, the absence of mutualism can constrain species from otherwise suitable regions of their range. Most studies found that the footprint of mutualism is driven by changes in the frequency of mutualist partners from range core to range edge, whereas fewer found changes in interaction outcomes, the diversity of partners, or varying sensitivities of fitness to the effects of mutualists. We discuss these findings with respect to specialization, dependence, and intimacy of mutualism. Much remains unknown about the geographic footprint of mutualisms, leaving fruitful areas for future work. A particularly important future direction is to explore the role of mutualism during range shifts under global change, including the promotion of shifts at leading edges and persistence at trailing edges.

Specifying, assessing, and selecting among candidate statistical models is fundamental to ecological research. Commonly used approaches to model selection are based on predictive scores and include information criteria such as Akaike's information criterion, and cross validation. Based on data splitting, cross validation is particularly versatile because it can be used even when it is not possible to derive a likelihood (e.g., many forms of machine learning) or count parameters precisely (e.g., mixed-effects models). However, much of the literature on cross validation is technical and spread across statistical journals, making it difficult for ecological analysts to assess and choose among the wide range of options. Here we provide a comprehensive, accessible review that explains important—but often overlooked—technical aspects of cross validation for model selection, such as: bias correction, estimation uncertainty, choice of scores, and selection rules to mitigate overfitting. We synthesize the relevant statistical advances to make recommendations for the choice of cross-validation technique and we present two ecological case studies to illustrate their application. In most instances, we recommend using exact or approximate leave-one-out cross validation to minimize bias, or otherwise k-fold with bias correction if k < 10. To mitigate overfitting when using cross validation, we recommend calibrated selection via our recently introduced modified one-standard-error rule. We advocate for the use of predictive scores in model selection across a range of typical modeling goals, such as exploration, hypothesis testing, and prediction, provided that models are specified in accordance with the stated goal. We also emphasize, as others have done, that inference on parameter estimates is biased if preceded by model selection and instead requires a carefully specified single model or further technical adjustments.

Climate warming is considered to be among the most serious of anthropogenic stresses to the environment, because it not only has direct effects on biodiversity, but it also exacerbates the harmful effects of other human-mediated threats. The associated consequences are potentially severe, particularly in terms of threats to species preservation, as well as in the preservation of an array of ecosystem services provided by biodiversity. Among the most affected groups of animals are insects—central components of many ecosystems—for which climate change has pervasive effects from individuals to communities. In this contribution to the scientists' warning series, we summarize the effect of the gradual global surface temperature increase on insects, in terms of physiology, behavior, phenology, distribution, and species interactions, as well as the effect of increased frequency and duration of extreme events such as hot and cold spells, fires, droughts, and floods on these parameters. We warn that, if no action is taken to better understand and reduce the action of climate change on insects, we will drastically reduce our ability to build a sustainable future based on healthy, functional ecosystems. We discuss perspectives on relevant ways to conserve insects in the face of climate change, and we offer several key recommendations on management approaches that can be adopted, on policies that should be pursued, and on the involvement of the general public in the protection effort.

Ecosystem stability has intrigued ecologists for decades, and the realization that the global climate was changing has sharpened and focused this interest. One possible early warning signal of decreasing stability is increasing variability in ecosystems over time with increasing climate variability. Determining climate change effects on community stability, however, requires long-term studies of structure and underlying dynamics, including bottom-up and top-down effects in natural ecosystems. Although relevant datasets were rare in the early years of community ecology, such information has increased in recent decades. We investigated spatiotemporal changes in mean and variability of ecological subsidies (nutrients, phytoplankton, prey colonization), performance metrics of a dominant space occupier (mussels) and its primary predator (sea stars), and sea star predation rates on mussels in relation to climatic oscillations, temperature, and disease on rocky shores. The research involved annually repeated multiyear (~1999–2018), multisite (13 sites nested within five regions along ~260 km of the Oregon coast) observations, measurements, and experiments. We analyzed associations between environmental variables and ecological performance of key elements of the sea star-mussel-dominated mid intertidal system. We found that upwelling declined in some regions, but became more variable across all study regions. Air and water temperatures oscillated, but their mean and variation increased through time, with peak values coinciding with the 2014–2016 combined El Niño and Marine Heat Wave. Ecological subsidies generally declined during the study period but increased in variability. Excepting growth rate, mussel (Mytilus californianus) performance (condition index, reproductive output) generally decreased and became more variable. Primarily due to a sea star wasting epidemic, reproductive output of the top predator Pisaster ochraceus decreased and became more variable, and predation rate on mussels decreased. Analyses indicated that the primary drivers of these changes were temperature-related environmental factors. As declining means and increasing variability of ecological performances can typify destabilizing ecosystems, and environmental trends are toward ever more stressful conditions, the outlook for this iconic ecosystem is discouraging. Immediate and rapid action to mitigate and ultimately reverse climate change likely is the only option available to prevent an irreversible shift in the future of this, and most other ecosystems.

In the high Arctic, plant community species composition generally responds slowly to climate warming, whereas less is known about the community functional trait responses and consequences for ecosystem functioning. The slow species turnover and large distribution ranges of many Arctic plant species suggest a significant role of intraspecific trait variability in functional responses to climate change. Here we compare taxonomic and functional community compositional responses to a long-term (17-year) warming experiment in Svalbard, Norway, replicated across three major high Arctic habitats shaped by topography and contrasting snow regimes. We observed taxonomic compositional changes in all plant communities over time. Still, responses to experimental warming were minor and most pronounced in the drier habitats with relatively early snowmelt timing and long growing seasons (Cassiope and Dryas heaths). The habitats were clearly separated in functional trait space, defined by 12 size- and leaf economics-related traits, primarily due to interspecific trait variation. Functional traits also responded to experimental warming, most prominently in the Dryas heath and mostly due to intraspecific trait variation. Leaf area and mass increased and leaf δ¹⁵N decreased in response to the warming treatment. Intraspecific trait variability ranged between 30% and 71% of the total trait variation, reflecting the functional resilience of those communities, dominated by long-lived plants, due to either phenotypic plasticity or genotypic variation, which most likely underlies the observed resistance of high Arctic vegetation to climate warming. We further explored the consequences of trait variability for ecosystem functioning by measuring peak season CO₂ fluxes. Together, environmental, taxonomic, and functional trait variables explained a large proportion of the variation in net ecosystem exchange (NEE), which increased when intraspecific trait variation was accounted for. In contrast, even though ecosystem respiration and gross ecosystem production both increased in response to warming across habitats, they were mainly driven by the direct kinetic impacts of temperature on plant physiology and biochemical processes. Our study shows that long-term experimental warming has a modest but significant effect on plant community functional trait composition and suggests that intraspecific trait variability is a key feature underlying high Arctic ecosystem resistance to climate warming.

Ecologists are often interested in answering causal questions from observational data but generally lack the training to appropriately infer causation. When applying statistical analysis (e.g., generalized linear model) on observational data, common statistical adjustments can often lead to biased estimates between variables of interest due to processes such as confounding, overcontrol, and collider bias. To overcome these limitations, we present an overview of structural causal modeling (SCM), an emerging causal inference framework that can be used to determine cause-and-effect relationships from observational data. The SCM framework uses directed acyclic graphs (DAGs) to visualize researchers' assumptions about the causal structure of a system or process under study. Following this, a DAG-based graphical rule known as the backdoor criterion can be applied to determine statistical adjustments (or lack thereof) required to determine causal relationships from observational data. In the presence of unobserved confounding variables, an additional rule called the frontdoor criterion can be employed to determine causal effects. Here, we use simulated ecological examples to review how the backdoor and frontdoor criteria can return accurate causal estimates between variables of interest, as well as how biases can arise when these criteria are not used. We further provide an overview of studies that have applied the SCM framework in ecology. SCM, along with its application of DAGs, has been widely used in other disciplines to make valid causal inferences from observational data. Their use in ecology holds tremendous potential for quantifying causal relationships and investigating a range of ecological questions without randomized experiments.

The alteration of the timing of biological events is one of the best documented effects of climate change, with overwhelming evidence across taxa. Many studies have investigated the phenology of consumers, especially birds. However, most of these studies have focused on specific phenophases, whereas a global analysis of avian phenological trends during recent climate change across different phases of the circannual cycle is still lacking. Here, we performed a comprehensive meta-analytic synthesis of the phenological responses (temporal shifts in days year⁻¹) of birds across different phenophases (prebreeding migration, breeding, and postbreeding migration) by summarizing more than 5500 time series from 684 species from five continents during 1811–2018. Our results confirm that avian taxa have advanced prebreeding migration and breeding by ~2–3 days per decade, whereas no significant temporal changes in the timing of postbreeding migration were documented. Advancement in the timing of prebreeding migration and breeding strongly depended on migratory behavior, with the advance being the weakest for long-distance migrants and the strongest for resident species. Diet generalists and primary consumers tended to advance prebreeding migration timing more than species with different dietary specializations. Increasing body size resulted in a larger advancement in the onset (but not in the mean date) of prebreeding migration and breeding, whereas phenological advances were larger in the northern than in the southern hemisphere. Our synthesis, covering most of the world, highlighted previously unappreciated patterns in avian phenological shifts over time, suggesting that specific life-history or ecological traits may drive different responses to climate change.

Insects provide key pollination services in most terrestrial biomes, but this service depends on a multistep interaction between insect and plant. An insect needs to visit a flower, receive pollen from the anthers, move to another conspecific flower, and finally deposit the pollen on a receptive stigma. Each of these steps may be affected by climate change, and focusing on only one of them (e.g., flower visitation) may miss important signals of change in service provision. In this study, we combine data on visitation, pollen transport, and single-visit pollen deposition to estimate functional outcomes in the high Arctic plant-pollinator network of Zackenberg, Northeast Greenland, a model system for global warming–associated impacts in pollination services. Over two decades of rapid climate warming, we sampled the network repeatedly: in 1996, 1997, 2010, 2011, and 2016. Although the flowering plant and insect communities and their interactions varied substantially between years, as expected based on highly variable Arctic weather, there was no detectable directional change in either the structure of flower-visitor networks or estimated pollen deposition. For flower-visitor networks compiled over a single week, species phenologies caused major within-year variation in network structure despite consistency across years. Weekly networks for the middle of the flowering season emerged as especially important because most pollination service can be expected to be provided by these large, highly nested networks. Our findings suggest that pollination ecosystem service in the high Arctic is remarkably resilient. This resilience may reflect the plasticity of Arctic biota as an adaptation to extreme and unpredictable weather. However, most pollination service was contributed by relatively few fly taxa (Diptera: Spilogona sanctipauli and Drymeia segnis [Muscidae] and species of Rhamphomyia [Empididae]). If these key pollinators are negatively affected by climate change, network structure and the pollination service that depends on it would be seriously compromised.