Ecology最新文献

Analysis of time series data is fundamental in ecology for understanding community dynamics, and the mechanisms driving such dynamics. However, ecological time series commonly contain missing values, which can arise due to methodological changes in monitoring programs, poor weather conditions, logistical constraints, or human error. State-space models are a useful suite of techniques for analyzing ecological time series with missing data. Such models can estimate the unobserved true abundances as latent variables, even for putative census occasions that lack observations. Nevertheless, the impact of missing data on parameter accuracy and precision in these state-space models remains poorly investigated, particularly in species-rich systems. We evaluated the performance of a multivariate process-based state-space model for time series of varying lengths and sampling frequencies, using simulated data informed by empirical counts of reef fish communities from the Great Barrier Reef in Australia. We found that despite containing missing data, the models fitted to longer time series produced more accurate and precise parameter estimates compared to shorter, complete-case time series. Additionally, higher spatial replication with uneven census intervals enhanced parameter precision more than maintaining census frequency at the expense of reducing the number of sites. Analysis of reef fish community data revealed attenuation in intrinsic population growth parameters and weaker intraspecific density dependence when modeling longer time series whose inter-census intervals change, while estimates of variability in species' population growth parameters due to environmental fluctuations remained consistent regardless of sampling design. Nonetheless, analyses of shorter, complete-case time series still produced reliable parameter estimates. Our findings highlight the robustness of Bayesian state-space models to missing data, demonstrating that flexibility in long-term monitoring programs does not compromise ecological inference from these models.

Consumers play a critical role in mediating plant and ecosystem responses to abiotic stress, yet their influence on belowground processes under changing environmental conditions remains underexplored. Insect consumers are vital components of grassland ecosystems that can shape ecosystem function and stability by mitigating how plant and microbial communities respond to abiotic stress, like drought. This study investigates how small-bodied consumers influence the magnitude and stability of grassland belowground functions across gradients of abiotic stress. We conducted a fully factorial field experiment manipulating consumer presence and induced drought over a growing season. Our results reveal that the presence of consumers stabilizes bacterial biomass and microbial activity across variable soil moisture conditions. Interestingly, this consumer-induced increase in ecosystem stability was driven by a destabilization of microbial communities, as indicated by increased variability in bacterial community composition and abundance. Consumer presence also shifted soil bacterial community composition and richness, while fungal communities were less affected. Combined, our results highlight another important dimension of ecosystem stability: community responsiveness and rapid adaptability. Additionally, our findings underscore the critical role of consumers in maintaining belowground ecosystem stability and highlight the need to consider trophic interactions when predicting the impacts of global change on grassland ecosystems.

Sudden habitat loss associated with environmental disturbance can trigger animals to move from affected to undisturbed areas, where increases in local density may occur. Although pathogen transmission is strongly related to local density, how crowding after habitat loss affects infection dynamics in wild populations remains unclear. Here we conceptualize the Disturbance-Density-Disease hypothesis, which posits that disturbance-induced habitat loss results in increased pathogen prevalence via increases in local density at adjacent, undisturbed patches. We then used data from before, during, and after flooding disturbance to test this hypothesis in boreal toads Anaxyrus boreas boreas co-occurring with the pathogenic fungus Batrachochytrium dendrobatidis (Bd). We collected Bd samples from captured individuals during a 5-year (2015–2019) mark-recapture study of boreal toads (n = 1295) that breed in beaver ponds in western Wyoming, USA. During spring of 2017, an extreme flooding event destroyed several beaver dams, resulting in the loss of breeding habitat. We compared host density and pathogen prevalence pre- and post-disturbance at sites affected versus unaffected by flooding. At affected sites, population density and Bd prevalence increased at adjacent, undisturbed ponds following the sudden loss of habitat. Moreover, neither host density nor Bd prevalence increased at control sites in areas unaffected by flooding. Taken together, our results support hypothesized links between disturbance, adjacent increases in density, and subsequent increases in pathogen prevalence. Our study contributes to a growing body of ecological research leveraging natural experiments to extract insights from extreme disturbance events. By doing so, we demonstrate an important consequence of disturbance beyond proximate habitat loss and introduce a clear conceptual approach (the Disturbance-Density-Disease hypothesis) to understanding how pathogen transmission can be affected by disturbance via alterations to local density.

Biological systems face multiple stressors that impact biodiversity and ecosystem functions, with complex interactions that vary spatially and temporally leading to unpredictable outcomes. In freshwater ecosystems, benthic microbial communities underpin vital functions like decomposition and primary productivity, but are threatened by stressors such as salinization and nutrient enrichment, which are intensifying and increasingly co-occurring due to climate change. We experimentally tested how stressor repetition and different orders of stressor exposure affect freshwater benthic microbial community responses over time. Communities established on tiles in 1000 L open freshwater ponds established more than 10 years ago in the field were exposed to elevated salinity and nutrient enrichment, either once or repeatedly, independently or in combination, and under different orders. Repeated exposure to nutrient enrichment led to stronger functional changes than the single exposure, while repeated exposure to elevated salinity resulted in weaker changes compared to a single exposure. Critically, we found that the sequence in which stressors occurred was a major determinant of microbial responses, driving interaction outcomes in opposing directions. When exposure to nutrient enrichment preceded elevated salinity, gross primary productivity was halved and carbon metabolic rates increased by 50% compared to communities treated in the reverse order. This study is among the first in a complex, outdoor freshwater system to demonstrate that stressor sequence can strongly shape multiple stressor effects, highlighting the order of stressor exposure as a key but often overlooked dimension of global change ecology. These findings suggest that microbial functions, including productivity and carbon cycling, will fluctuate more dramatically as stressors increasingly occur in different sequences under global change.

Sex differences are predicted to play an important role in the spread and evolution of pathogens. However, attempts to generalize the “sicker” sex have been challenged by intraspecific variability of sex biases across the infection process. Sex-specific plasticity provides a framework to resolve this by elucidating how infection is shaped at the sex-pathogen-environment interface. Using the Daphnia magna and Pasteuria ramosa system, we measure infection outcomes for males and females across three temperatures and seven pathogen densities to quantify how sex-specific plasticity shapes susceptibility, pathogen loads, and ultimately transmission. We find unique forms of plasticity at each stage of infection – including equivalent, sex-specific, and divergent plasticity. Integrating these into a single estimate of transmission reveals a clear pattern—male-biased transmission at cold temperatures, and female-biased transmission at warm temperatures. Sex-specific thermal plasticity can thus determine the “sicker” sex, with implications for pathogen spread and evolution in a warming world.

Mutualisms confer both benefits and costs to participants, but costs have been largely ignored when considering how mutualisms function and evolve. Plants that are dispersed by ants produce seeds with attached nutrient-rich food rewards (elaiosomes). When ants approach a seed, they likely assess both the benefits (elaiosome mass) and costs (mass of the inedible seed) of moving it. We hypothesized that the masses of both the seed and elaiosome would affect diaspore removal rate, and predicted that when given a choice, ants would remove diaspores with higher benefits and diaspores with lower costs more quickly. To test these hypotheses, we manipulated the elaiosomes of Datura wrightii and Datura discolor (Solanaceae) and conducted choice experiments where we presented diaspores with variable benefits and costs to colonies of the seed-dispersing ant Novomessor cockerelli (Formicidae). D. discolor has a larger elaiosome-to-seed ratio since its seeds are half the mass of D. wrightii. Consistent with our hypotheses, ants removed seeds with heavier elaiosomes (larger rewards) and lighter seeds (lower costs) more quickly. Our study provides new evidence for seed dispersal costs by quantifying a cost of seed dispersal to ants and underscores the necessity of measuring both the benefits and costs of mutualistic interactions.

More widespread species tend to be more locally abundant. This hypothesis has received support when considering single species abundance (mean density of individuals across sites) and occupancy (fraction of occupied sites) through time (intraspecific relationship) and comparing different species sampled at a single point in time (interspecific relationships). But while abundance-occupancy relationships are fairly well supported in observational studies, the underlying factors driving them are less clear. For instance, variation in demographic rates, dispersal, and spatial network structure could all influence resulting abundance-occupancy relationships. We used a simulation model to explore these relationships in spatial networks of variable size and dispersal connectivity. We simulated population dynamics on spatial networks by starting from entirely neutral communities and then systematically incorporated complexity in the form of (co)variation in species demographic rates and dispersal processes. The effect of spatial network structure on abundance-occupancy relationships was dependent on the community dynamics and the covariation imposed on demographic and dispersal parameters. Together, we demonstrate the interplay between the spatial network and variation in demographic and dispersal rates, generating testable hypotheses for when abundance-occupancy relationships would be more likely to be observed, as well as how these relationships may change with habitat fragmentation and shifts in community composition.

Plant ionomes—the suite of chemical elements making up plant tissue—constrain plant performance and the nutrition of consumers. The possible mechanisms driving Nutrient Dilution—the globally distributed decline of essential element density (parts per million [ppm]) in plant tissue—are rarely evaluated together. Toward a remedy, we explored a 30+ year record of 17 elements in the grasses, forbs, and woody plants across three burn frequencies on Konza, a North American tallgrass prairie. About one quarter of ionomic variation arose among Konza's three plant functional groups, which differed in ppm and its regulation over three decades. Nutrient-poor grass biomass increased steadily with CO₂, encroaching woody plant biomass accelerated over the same period, and nutrient-rich forb biomass decreased. Each functional group revealed its own pattern of nutrient dilution across the ionome, where it was more widespread in grasses (12/17 elements) than forbs (5/17) or woody plants (2/17). Competition with other functional groups regularly depleted the ionome ppm of grasses (9 elements) and forb and woody plants (4 elements). Unexpectedly, nutrient densities often increased in response to higher CO₂ (especially in forbs), suggesting photosynthate was invested in nutrient harvest. Fire suppression had fewer, and more idiosyncratic effects. In an era of herbivore declines, grass-feeding herbivores in this tallgrass prairie are experiencing more abundant but lower quality food. Forb feeders, in contrast, must search for less abundant but sometimes enriched food.