Ecological Monographs最新文献

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.

Global climate change will probably exacerbate crop losses from insect pests, reducing agricultural production, and threatening food security. To predict where crop losses will occur, scientists have mainly used correlative models of species' distributions, but such models are unreliable when extrapolated to future environments. To minimize extrapolation, we developed mechanistic and hybrid models that explicitly capture range-limiting processes, and we explored how incorporating mechanisms altered the projected impacts of climate change for an agricultural pest, the South American locust (Schistocerca cancellata). Because locusts are generalist herbivores surrounded by food, their population growth may be limited by thermal effects on digestion more than food availability. To incorporate this mechanism into a distribution model, we measured the thermal effects on the consumption and defecation of field-captured locusts and used these data to model energy gain in current and future climates. We then created hybrid models by using outputs of the mechanistic model as predictor variables in correlative models, estimating the potential distribution of gregarious outbreaking locusts based on multiple predictor sets, modeling algorithms, and climate scenarios. Based on the mechanistic model, locusts can assimilate relatively high amounts of energy throughout temperate and tropical South America; however, correlative and hybrid modeling revealed that most tropical areas are unsuitable for locusts. When estimating current distributions, the top-ranked model was always the one fit with mechanistic predictors (i.e., the hybrid model). When projected to future climates, top-ranked hybrid models projected range expansions that were 23%–30% points smaller than those projected by correlative models. Therefore, a combination of the correlative and mechanistic approaches bracketed the potential outcomes of climate change and enhanced confidence where model projections agreed. Because all models projected a poleward range expansion under climate change, agriculturists should consider enhanced monitoring and the management of locusts near the southern margin of the range.

Long-distance insect migration is poorly understood despite its tremendous ecological and economic importance. As a group, Nearctic hover flies (Diptera: Syrphidae: Syrphinae), which are crucial pollinators as adults and biological control agents as larvae, are almost entirely unrecognized as migratory despite examples of highly migratory behavior among several Palearctic species. Here, we examined evidence and mechanisms of migration for four hover fly species (Allograpta obliqua, Eupeodes americanus, Syrphus rectus, and Syrphus ribesii) common throughout eastern North America using stable hydrogen isotope (δ²H) measurements of chitinous tissue, morphological assessments, abundance estimations, and cold-tolerance assays. Although further studies are needed, nonlocal isotopic values obtained from hover fly specimens collected in central Illinois support the existence of long-distance fall migratory behavior in Eu. americanus, and to a lesser extent S. ribesii and S. rectus. Elevated abundance of Eu. americanus during the expected autumn migratory period further supports the existence of such behavior. Moreover, high phenotypic plasticity of morphology associated with dispersal coupled with significant differences between local and nonlocal specimens suggest that Eu. americanus exhibits a unique suite of morphological traits that decrease costs associated with long-distance flight. Finally, compared with the ostensibly nonmigratory A. obliqua, Eu. americanus was less cold tolerant, a factor that may be associated with migratory behavior. Collectively, our findings imply that fall migration occurs in Nearctic hover flies, but we consider the methodological limitations of our study in addition to potential ecological and economic consequences of these novel findings.

Size-structured differences in resource use stabilize species coexistence in animal communities, but what behavioral mechanisms underpin these niche differences? Behavior is constrained by morphological and physiological traits that scale allometrically with body size, yet the degree to which behaviors exhibit allometric scaling remains unclear; empirical datasets often encompass broad variation in environmental context and phylogenetic history, which complicates the detection and interpretation of scaling relationships between size and behavior. We studied the movement and foraging behaviors of three sympatric, congeneric spiral-horned antelope species (Tragelaphus spp.) that differ in body mass—bushbuck (26–40 kg), nyala (57–83 kg), and kudu (80–142 kg)—in an African savanna ecosystem where (i) food was patchily distributed due to ecosystem engineering by fungus-farming termites and (ii) predation risk was low due to the extirpation of several large carnivores. Because foraging behavior is directly linked to traits that scale allometrically with size (e.g., metabolic rate, locomotion), we hypothesized that habitat use and diet selection would likewise exhibit nonlinear scaling relationships. All three antelope species selected habitat near termitaria, which are hotspots of abundant, high-quality forage. Experimental removal of forage from termite mounds sharply reduced use of those mounds by bushbuck, confirming that habitat selection was resource driven. Strength of selection for termite mounds scaled negatively and nonlinearly with body mass, as did recursion (frequency with which individuals revisited locations), whereas home-range area and mean step length scaled positively and nonlinearly with body mass. All species disproportionately ate mound-associated plant taxa; nonetheless, forage selectivity and dietary composition, richness, and quality all differed among species, reflecting the partitioning of shared food resources. Dietary protein exhibited the theoretically predicted negative allometric relationship with body mass, whereas digestible-energy content scaled positively. Our results demonstrate cryptic size-based separation along spatial and dietary niche axes—despite superficial similarities among species—consistent with the idea that body-size differentiation is driven by selection for divergent resource-acquisition strategies, which in turn underpin coexistence. Foraging and space-use behaviors were nonlinearly related to body mass, supporting the hypothesis that behavior scales allometrically with size. However, explaining the variable functional forms of these relationships is a challenge for future research.

The usual theoretical condition for coexistence is that each species in a community can increase when it is rare (mutual invasibility). Traditional coexistence theory implicitly assumes that the invading species is common enough that we can ignore demographic stochasticity but rare enough that it does not compete with itself, even after it has reached a stationary spatial distribution. However, short-distance dispersal of discrete individuals leads to locally dense population clusters, and existing theory breaks down. We have an intuition that when we account for invader–invader competition, shorter-range dispersal should reduce the invader's ability to escape competition, but exactly how does this translate into lower population growth? And how will invader discreteness affect outcomes? We need a way of partitioning the contributions to coexistence, but current modern coexistence theory (MCT) does not apply under these conditions. Here we present a computationally based partitioning method to quantify the contributions to coexistence from different mechanisms, as in MCT. We also build up an intuition for how invader clumping and discreteness will affect these contributions by analyzing a case study, a lattice-based spatial lottery model. We first consider fluctuation-dependent coexistence, partitioning the contributions of variable environment, variable competition, demographic stochasticity, and their correlations and interactions. Our second example examines fluctuation-independent coexistence maintained by a fecundity–survival trade-off, and partitions the contributions to coexistence from interspecific differences in fecundity, in mortality, and in dispersal. We find that demographic stochasticity harms an invader, but only slightly. Localized invader dispersal, on the other hand, can have a strong effect. When invaders are more clumped, they compete with each other more intensely when rare, so they too become limited by environment-competition covariance. More invader clumping also means that variation in competition changes from helping the invader to harming it. More broadly, invader clumping is likely to weaken any coexistence mechanism that relies on the invader escaping competition from the resident, because invader clumping means that the resident is no longer the only source of competition.

The usual conception of character displacement is of resource competitors differentiating to specialize on different prey in order to reduce competition. However, traits that underlie many predator–prey interactions, such as chase-evade speeds, gape limitation, and toxin concentrations, do not permit such specialization, but instead result in unidirectional evolutionary arms races. Here, we develop and analyze an evolutionary model of predator–prey interactions to explore whether character displacement will still occur when such unidirectional traits define the species interactions, and if so, what environmental conditions foster or retard differentiation. Character displacement in predators and prey does occur, and this differentiation is driven by fitness component trade-offs. Instead of specialization or compartmentalization in which different sets of species have strong interactions, differentiation in this model causes a nested community structure in which species of predators and prey have the same rank interaction strengths with species at the other trophic level. Also, analyses of the model predict that character displacement is fostered in environments with higher productivity, weaker stressors, and lower structural complexity. Model comparisons suggest that character displacement should occur over a broader set of environmental conditions when traits permit prey specialization than when traits foster arms races. These results highlight how different types of phenotypic traits that underlie species interactions shape the species diversification and the structure of the resulting community.