Ecological Monographs最新文献

In ecology and related sciences, missing data are common and occur in a variety of different contexts. When missing data are not handled properly, subsequent statistical estimates tend to be biased, inefficient, and lack proper confidence interval coverage. Missing data are often grouped into three categories: missing completely at random (MCAR), missing at random (MAR), and missing not at random (MNAR). We review each category and compare their benefits and drawbacks. We review several approaches to handling missing data including complete case analysis, imputation, inverse probability weighting, and data augmentation. We clarify what types of variables should accompany imputation methods and how those variables are influenced by the analysis methods. Additionally, we discuss missing data that lack a formal basis for measurement and hence are fundamentally different from MCAR, MAR, and MNAR missing data. Throughout, we introduce concepts and numeric examples using both simulated data and data from the United States Environmental Protection Agency's 2016 National Wetland Condition Assessment. We conclude by providing five considerations for ecologists and other scientists handling missing data.

Theory and experiments show that diverse ecosystems often have higher levels of function (for instance, biomass production), yet it remains challenging to identify the biological mechanisms responsible. We synthesize developments in coexistence theory into a general theoretical framework linking community coexistence to ecosystem function. Our framework, which we term functional coexistence theory, identifies three components determining the total function of a community of coexisting species. The first component directly corresponds to the niche differences that enable pairwise species coexistence and to the complementarity component from the additive partition of biodiversity effects. The second component measures whether higher functioning species also have higher fitness under competition, providing a missing link between the additive partition's selection effect and modern coexistence theory's concept of equalization. The third component is least well studied: reducing functional imbalances between species increases niche difference's positive effect on function. Using a mechanistic model of resource competition, we show that our framework can link the structure and function of multispecies communities and that it can predict changes in coexistence and ecosystem function along gradients of resource availability. In particular, we expect the effect of resource level on biodiversity–function relationships to be limited in magnitude and variable in sign because it should be primarily mediated by fitness. Next, we confirm our theoretical expectations by fitting this model to data from a classic plant competition experiment. Finally, we apply our framework to simulations of multiple ecosystem functions, demonstrating that relationships between niche, fitness, and function also predict a community's multifunctionality, or ability to simultaneously show high levels of multiple functions. Taken together, our results highlight fundamental links between species coexistence and its consequences for ecosystem function, providing an avenue toward mechanistic and predictive understanding of community–ecosystem feedbacks.

Interactions between plants and soil microbes play a key role in structuring plant communities. In a rapidly changing Arctic environment, we urgently need to uncover how these interactions are responding to environmental changes. Here, we disentangle two contributions to variation in plant–fungus interactions along geographic and environmental gradients of the Arctic: abiotic impacts on the pool of fungal species present in the soil, and abiotic and biotic impacts on variation in the pool of fungi associated with plant roots. Given the low species richness and harsh conditions in the Arctic, we expected opportunistic associations to emerge, along with strong impacts of the environment on interaction structure. Across multiple spatial scales, we sampled roots of 12 widely distributed plant taxa. To characterize the pool of species available for colonization, we quantified the pool of fungi present in the soil, and to characterize realized interactions, we quantified root-associated fungal communities. Data from DNA metabarcoding of each fungal community were modeled by Hierarchical Modeling of Species Communities (HMSC). To determine whether the realized networks deviated from random expectations, we compared the observed networks to those expected under null models. Overall, we found strong support for opportunistic associations, along with some level of selectivity. Fungal communities within the soil and rhizosphere shared 85% of their fungal genera, but the composition of these communities significantly differed among ecosystem compartments. The two compartments showed similar responses to the environment, with low levels of partner fidelity among both plant and fungal taxa. Plant–fungus networks showed a distinctly nonrandom structure, which was driven by gradients in pH and temperature. Across the Arctic, the structure of fungal communities in the plant rhizosphere is thus mainly driven by abiotic rather than by biotic conditions (i.e., host identity or microbes–microbes associations). Environmental conditions will dictate what interaction partners occur where, but interactions among locally occurring plants and fungi are dominated by opportunistic partner choice. Overall, our findings suggest that the dynamics and structure of plant–root-associated interactions will be altered by abiotic changes in the Arctic realm, and that the flexibility of associations may contribute to the resilience of the system.

Soil microorganisms can have profound impacts on plant community dynamics and have received increasing attention in the context of plant–soil feedback. The effects of soil microbes on plant community dynamics are classically evaluated with a two-phase experimental design that consists of a conditioning phase, during which plants modify the soil microbial community, and a response phase, during which the biomass performance of plants is measured as their response to the soil modification. Predicting plant community-level outcomes based on these greenhouse experimental results implicitly assumes that plant–soil microbe interactions remain constant through time. However, a growing body of research points to a complex temporal trajectory of plant–soil microbe interactions, with microbial effects varying with the conditioning duration, plant development, and time since conditioning. Most previous studies also implicitly assume that measuring plant biomass performance alone adequately captures the most critical impacts soil microbes have on plant population dynamics, neglecting that soil microbes also govern other key demographic processes over the plant life cycle. Here, we discuss the relevance of these temporal and demographic dimensions of plant–soil microbe interactions when extrapolating experimental results and propose modeling frameworks that can incorporate the new empirical evidence. By integrating empirical and theoretical approaches, we provide a roadmap for more nuanced predictions of the long-term consequences of plant–soil microbe interactions in nature.

Mutualistic interactions among organisms are fundamental to the origin and maintenance of biodiversity. Yet, the study of community dynamics often relies on values averaged at the species level, ignoring how intraspecific variation can affect those dynamics. We developed a theoretical approach to evaluate the extent to which variation within populations, in terms of interactions, can influence structural stability, a robust measure of species' likelihood of persistence in mutualistic systems. Next, we examine how intraspecific variation in mutualistic interactions affects species' persistence theoretically in a simplified community, which provides a solid foundation for contextualizing empirical results. This theoretical exploration revealed that differences in the benefits received by different individual types by mutualistic partners, as driven by the way interactions are distributed among those types due to individual specialization, strongly influence species persistence. Building on these insights, we move beyond the theoretical framework and work through an empirical case study involving three co-occurring plant species. Drawing from detailed field data on plant–pollinator interactions and plant fitness, we quantify intraspecific variation in the mutualistic benefits received by plants and incorporate this variation into estimations of structural stability. Through explicit consideration of this facet of intraspecific variation, we found that, for all three focal plant species, populations composed of individuals specialized in pollinator use promote the persistence of the plant species they belong to and their associated pollinator community, only in the absence of heterospecific plant competitors. However, more importantly, these positive effects do not hold when plant species compete with a broader, diverse plant community. In this case, two of the focal plant populations are more vulnerable when they comprise more specialized individuals and therefore are less likely to persist. By integrating the proposed theoretical approach with empirical data, this study highlights the importance of individual variation in promoting species persistence in mutualistic systems. In doing so, it not only advances our understanding of basic mechanisms that foster biodiversity maintenance but also provides practical insights for biodiversity conservation in the face of changing environmental conditions.

Kelp forests are among the most diverse and productive ecosystems in the world, providing critical habitat for numerous ecologically and economically important species. However, kelps are at risk from climate change, and declining populations worldwide demonstrate the need to characterize and quantify the effects of anthropogenic stressors on kelp physiology. Here, we performed a meta-analysis on true kelps (order Laminariales) in response to ocean warming and acidification based on a global synthesis of 7000 data points from 143 experimental studies. Our results show that ocean warming has a strong negative impact on kelps at all life stages and across various physiological levels, including growth, reproduction, and survival. In contrast, ocean acidification generally has no effect, except for its negative impact on reproduction. In most cases, co-occurring warming and acidification acted synergistically. Response to warming, acidification, and multiple driver scenarios increased as the intensity and duration of exposure increased. In our analyses, the genera Eualaria, Hedophyllum, Lessonia, and Postelsia were among the most vulnerable to warming. Studies conducted in the temperate northern Pacific showed extreme negative effects of warming. We also identify key gaps in our understanding of kelp responses to climate change, such as the impacts on microscopic spores and the combined effects of warming and acidification. This analysis synthesizes trends in a rapidly expanding field of literature and provides a deeper understanding of how kelps will respond to a rapidly changing ocean.

Metacommunity theory offers a compelling framework for understanding the processes that govern biodiversity patterns across space and time. Yet, a persistent challenge remains: integrating the wide array of ecological drivers into a unified model using observational data from complex, dynamic ecosystems. In this study, we present a novel, process-explicit path modeling approach that bridges recent theoretical advances in metacommunity ecology with empirical data. Focusing on fish communities in the floodplains of the Danube River, we leverage environmental DNA (eDNA) metabarcoding to characterize community composition across a spatiotemporal network of sites. We partition beta diversity into its species replacement and richness difference components and apply structural equation modeling to evaluate the relative influence of multiple ecological drivers—including spatial and temporal dispersal, demographic stochasticity, abiotic filtering, and interspecific interactions. Our results reveal that river-floodplain fish metacommunities are shaped by a complex web of interacting processes. Notably, we find that species replacement is primarily driven by spatial distance and environmental filtering, while richness differences are more influenced by biotic interactions and community size. Lateral hydrological connectivity emerged as a pivotal landscape feature, governing beta diversity both directly and indirectly through its modulation of local environmental conditions. This connectivity acted as a structural conduit, mediating dispersal, environmental heterogeneity, and biotic interactions. By disentangling the contributions of multiple processes, our model underscores the dominant role of spatial structuring and abiotic filtering over temporal dynamics and biotic interactions in shaping metacommunity assembly. The model also demonstrates improved explanatory power and stronger model fit, outperforming previous studies. These findings underscore the need for integrative frameworks that consider the simultaneous influence of multiple ecological processes, particularly in highly dynamic systems like river-floodplains. Our conceptual and modeling approach advances metacommunity theory by offering a robust, data-driven means to assess complex assembly mechanisms and by emphasizing the critical role of connectivity and habitat complementarity in sustaining biodiversity within dynamic landscapes.

Climate change is intensifying droughts via reduced snowpack and accelerated snowmelt in high mountains globally, altering community structure in snow-dependent rivers. To predict impending ecological change in rivers, we must understand the importance of the abiotic and biotic mechanisms connecting hydrologic change to biodiversity change and whether these mechanisms operate similarly across space and time. Here, we studied abiotic effects of drought and invertebrate communities in a minimally disturbed watershed in California's Sierra Nevada. Our study employed a highly replicated design of 60 nested sites (capturing microhabitat to reach-level variation) and over two decades of change (2002–2023) in a subset of sites, including the driest period on record. We used spatial stream network (SSN) models and autoregressive (AR) models to partition the spatial and temporal variance into covariate-driven versus autocorrelation effects. Structural equation modeling allowed us to identify causal pathways connecting hydrologic change to invertebrate community change. We found that drought-driven variation in temperature, water velocity, and fine sediment all explained variation in abundance in over a third of the species in the community. Notably, the influence of abiotic effects differed across space and time: no taxa had their variance explained by the same abiotic effect in the same direction across space and time, and total spatial variance explained by abiotic effects for each species had no relationship with its temporal counterpart. We also found that community dissimilarity across space was poorly explained by abiotic effects, while temporal dissimilarity was driven by differences in temperature and water velocity causing species turnover. Finally, we tested the scale dependency of our inferences by changing the extent and resolution of our data (resampling from seasonal to interannual; from microhabitat to watershed-level data) and found that pathways of community change varied depending on scale and on whether comparisons were made across space or time. These differences between space and time likely arise from some ecological drivers operating more strongly in one dimension and from spatial and temporal autocorrelation in species abundances masking environmental effects. Our study illustrates that projecting riverine community composition under future hydroclimates requires accounting for mechanism context dependency over space and time.

The metabolic theory of ecology (MTE) has been an important strand in ecology for almost a quarter of a century, renewing interest in the importance of body size and the role of energy. The core of the MTE is a hydrodynamic model of the vertebrate cardiovascular system that predicts allometric scaling of metabolic rate with exponents in the range 0.75 at infinite size to ~0.80 at more realistic sizes, though most studies using the model have assumed an exponent of 0.75. The model is broadly supported by data for resting and routine metabolic rate in ectothermic vertebrates and also a wide range of invertebrates with a circulatory system. Scaling in endotherms is influenced by additional factors, possibly associated with heat flow, and is essentially isometric in prokaryotes, unicellular eukaryotes, and diploblastic invertebrates. This suggests that the presence of any form of circulatory system, even one much simpler than the closed high-pressure system that is the basis of the model, results in allometric scaling of metabolic rate, though the value of the scaling exponent varies across taxa. The temperature sensitivity of metabolism is captured by a simple Boltzmann factor, with an assumed apparent activation energy of 0.65 eV (Q₁₀ ~ 2.4). Empirical data are frequently lower than this, typically in the range 0.52–0.57 eV (Q₁₀ ~ 2.0–2.2). Attempts to broaden the scope of the MTE into areas such as growth, speciation, and life-history have met with mixed success. The major use of the MTE has been to explore the consequences of the central scaling tendency for topics as diverse as migration, acoustic communication, trophic interactions, ecosystem structure, and the energetics of deep-sea or extinct taxa. Although it cannot predict absolute metabolic rates, the MTE has been an important tool for exploring how energy flow influences ecology. Its greatest potential for future use is likely to come from building energetics into ecosystem models and in exploring potential consequences of climate change. In both cases, however, it will be important to encompass the range of empirical data for both scaling and temperature sensitivity rather than the widely assumed canonical values.

Stream and riparian habitats are meta-ecosystems that can be strongly connected via the emergence of aquatic insects, which form an important prey subsidy for terrestrial consumers. Anthropogenic perturbations that impact these habitats may indirectly propagate across traditional ecosystem boundaries, thus weakening aquatic-terrestrial food web linkages. We investigated how algal production, aquatic invertebrates, and terrestrial spiders influence cross-ecosystem connectivity in temperate streams across four European catchments with varying levels of human disturbance. We used fatty acid biomarkers to measure putative aquatic linkages to riparian spiders. Variation-partitioning analysis indicated that aquatic insect dispersal traits explained a relatively large proportion of variability in the fatty acid profile of spiders. Trophic connectivity, as measured by the proportion of the polyunsaturated fatty acid eicosapentaenoic acid (EPA) and the ratio of EPA to its chemical precursor, alpha-linolenic acid (ALA), was positively associated with abundances of “aerial active” dispersing aquatic insects. However, this positive influence was also associated with changes in environmental context and arachnid beta diversity. Structural equation modeling disentangled how aquatic insect communities influence trophic connectivity with riparian predators after accounting for biological and environmental contingencies. Our results show how subsidies of stream insects are a putative source of essential fatty acids for adjacent terrestrial food webs. Catchment-wide impacts indirectly propagated to the local scale through impacts on aquatic invertebrate communities, thus affecting stream-riparian food webs. Increased riparian tree cover enhanced stream insect subsidies via dispersal traits despite reducing aquatic primary production through shading. Consequently, ecosystem properties such as woody riparian buffers that increase aquatic-terrestrial trophic connectivity have the potential to affect a wide range of consumers in modified landscapes.