Ecology最新文献

Plant functional group is increasingly recognized as vital for supporting multiple ecosystem functions simultaneously. However, variations in "ecosystem multifunctionality" relative to plant functional groups remain unclear, particularly in Antarctic terrestrial ecosystems. In particular, how plant presence relates to multifunctionality, whether this directly relates to their carbon inputs, or indirectly, via local changes in abiotic (soil moisture and pH), and biotic (soil biodiversity and their interactions) factors, is still an unresolved question. In this study, we collected soil samples from five areas in the Antarctic region, ranging from bare soil to areas dominated by nonvascular plants such as lichens, mosses, and vascular plants. We examined 12 ecosystem functions associated with carbon sequestration, nitrogen stock and cycling, soil organic matter (SOM) decomposition, microbial biomass and pathogen control to calculate ecosystem multifunctionality. Our results showed that ecosystem multifunctionality was higher in areas colonized by nonvascular plants and vascular plants compared to bare soil, which was concurrent with enhanced levels of carbon sequestration, SOM decomposition, and microbial biomass. Our structural equation model (SEM) showed that increased ecosystem multifunctionality beneath plants was associated with a higher number of microbial module hubs (indicative of stronger interdependence among microbial taxa) in nonvascular plants, but not in vascular plants. Analysis of SEM standardized contributions revealed the direct pathway as predominant in the connectivity pattern between vascular plant presence and ecosystem multifunctionality. Overall, these findings enhance our understanding of the differences in the pathways linking nonvascular plants, vascular plants, and ecosystem multifunctionality. It further highlights the necessity of incorporating microbial interactions to more effectively evaluate ecosystem multifunctionality, particularly in the context of Antarctic ecosystems.

To contribute to our growing understanding of the urban ecological filtering process in highly biodiverse regions, we conducted a study on bird species assemblages across the landscape of Medellín and its surrounding areas in the Colombian Andes. Nonurban land cover categories included well-preserved and second-growth forests, exotic-tree plantations, and open areas. Urban areas were categorized into four urbanization levels ranging from 0% to 100% built cover at intervals of 25%. Well-preserved and second-growth forests exhibited the highest bird species richness, followed by open areas, while the 76%-100% urbanization level displayed the lowest richness. Based on either taxonomic or functional composition, the bird assemblages across all urbanization levels resembled open areas. The other nonurban land cover categories shared a lower proportion of bird species with open areas and all urbanization levels, with well-preserved forests showing distinct compositions. These results suggest that bird species inhabiting open areas face a broad urban ecological filtering until reaching a threshold above 75% built cover, while birds inhabiting well-preserved forest face a narrow ecological filtering at the urban edge. Our findings provide insights into urban ecological filtering at the landscape scale and pose significant challenges for urban planners aiming to maintain favorable environmental conditions for highly biodiverse species pools.

Temperature responses of many biological traits-including population growth, survival, and development-are described by thermal performance curves (TPCs) with phenomenological models like the Briere function or mechanistic models related to chemical kinetics. Existing TPC models are either simple but inflexible in shape or flexible yet difficult to interpret in biological terms. Here we present flexTPC, a model that is parameterized exclusively in terms of biologically interpretable quantities: the thermal minimum, optimum, and maximum, the peak trait value, and thermal breadth. FlexTPC can describe unimodal temperature responses of any skewness and thermal breadth, enabling direct comparisons across populations, traits, or taxa with a single model. We apply flexTPC to various microbial and entomological datasets, compare results with the widely used Briere model, and find that flexTPC often has better predictive performance. The interpretability of flexTPC makes it ideal for modeling how thermal responses change with ecological stressors or evolve over time.

Complex landscapes are challenging to study because both the higher level contextual and interacting lower level mechanistic processes underpinning their ecological characteristics occur simultaneously. However, food-web structures can provide process insight in such landscapes by identifying these processes in specific contexts. Here, we used stable isotopes to identify spatially separate resources and infer resource flows underpinning food-web structures in a braided river. We found that river resources used by mobile consumers, including birds and fish, were spatially heterogeneous. Consumer resource use was related to four key structural food-web attributes: (1) spatiotemporal variation in foraging, (2) subsidies, (3) omnivory, and (4) ontogenetic niche shifts. Thus, both physical heterogeneity (contextual physical processes) and adaptive characteristics of consumers (mechanistic processes) were likely contributing to important food-web structures. Identifying these food-web structures in landscapes, across scales of resource use and spatial distribution, provides a way to identify processes and scales likely contributing to food-web stabilization.

Leaf herbivory is a ubiquitous ecological interaction that varies significantly in intensity across species, habitats, and biogeographic regions. Although quantification of leaf damage is crucial for understanding many ecological processes, the accuracy and precision of various damage estimation methods used by researchers, including visual estimation, digital image analysis, and artificial intelligence, have not been evaluated and compared. We use a phylogenetically diverse group of tropical plants to compare the accuracy and precision of damage estimation methods and use the results to provide a guide to herbivory estimation that balances the advantages and disadvantages of each method. We found that visual estimation tended to overestimate herbivory levels compared to digital methods but was 15 times faster and improved in accuracy and speed with training. Conversely, deep-learning algorithms underestimated herbivory relative to image analysis with ImageJ when it was on the margin, but showed similar accuracy for damage inside of leaf margins. Our results indicate that while visual methods allow for rapid assessment of large sample sizes and are suitable for detecting broad patterns of damage, image analysis is crucial for accurate and precise quantification. The disadvantages of each method, however, can be minimized through proper training and efficient use of each tool, and we therefore provide a guide of practical approaches to herbivory estimation.

In an era of change, the survival and adaptability of ecosystems will be tested. An optimal ecosystem would be both resistant and resilient to negative disturbance but also efficient and redundant in its growth when given positive subsidies. However, initial evidence has suggested that these properties cannot all be maximized at the same time, and so we sought to quantitatively assess whether there are fundamental trade-offs between them at the ecosystem level. To achieve this aim, we used a 250-m resolution NASA MODIS dataset of gross primary productivity (GPP) to monitor 145,871 tidal wetland locations across the conterminous United States every 16 days from March 2000 to December 2020. We quantified the size and duration of the perturbation events in tidal wetland GPP (n = 13,754,386) and modeled their frequency distributions. Event sizes and recurrence intervals were exponentially distributed and event durations were closely modeled by an inverse power law. This scale-free manner through which tidal wetlands dissipated perturbations to their GPP flux provided them with long-term stability across a wide range of geography. We also found that a tidal wetland's positive event responses traded off between properties of efficiency and redundancy, its negative events traded off between resistance and resilience, and that all four properties were orthogonally related to one another. We then constructed a conceptual model to help understand the potential mechanism behind this four-quadrant trade-off. The trade-off appeared to be driven by a feedback between the waiting time and magnitude of positive and negative events, the duration of their effects, and the environmental and physical constraints limiting an ecosystem's growth and productivity. In summary, we detail an emergent pattern of trade-offs and constraints associated with how tidal wetland ecosystems respond to both positive and negative perturbations in carbon flux.

Quantitative evidence synthesis is a prominent path towards generality in ecology. Generality is typically discussed in terms of central tendencies, such as an average effect across a compilation of studies, and the role of heterogeneity for assessing generality is less well developed. Heterogeneity examines the transferability of ecological effects across contexts, though between-study variance is typically assumed as constant (i.e., homoscedastic). Here, I use two case studies to show how location-scale models that relax the assumption of homoscedasticity and cross validation can combine to further the goals of evidence syntheses. First, I examine scale-dependent heterogeneity for a meta-analysis of plant native-exotic species richness relationships, quantifying the relationships among unexplained effect size variation, spatial grain and extent. Second, I examine relationships among habitat fragment size, study-level covariates and unexplained variation in patch-scale species richness using a database of fragmentation studies. Heteroscedastic models quantify where effects can be transferred with more or less certainty and provide new descriptions of transferability for both case studies. Cross validation can be applied to a single or multiple models, adapted to either the goal of assessing intervention efficacy or generalization and, for the case studies examined here, showed that assuming homoscedasticity limits transferability.

Climate change has substantially shifted the phenology of many organisms. These shifts vary across species and habitats and are shaped by species' natural history traits and local environmental conditions, yet the relative importance of these drivers remains unclear. Moreover, climate can have diverse effects on different aspects of phenology, such as the timing and duration of activity, but this complexity is rarely captured by commonly used phenological metrics. We used multidecadal butterfly surveys and climate data from five montane sites spanning an elevational gradient to investigate how climate affects different aspects of the annual flight period of 135 butterfly species. Using a hierarchical Bayesian framework, we modeled annual probability of occurrence distributions for species using polynomial models that capture changes in abundance, timing, and length of flight. Spring maximum and minimum temperatures and winter precipitation were the best predictors of interannual variation in phenology. High winter precipitation, which usually comes in the form of snow, delayed phenology, while warmer spring maximum temperatures advanced phenology across elevations. Even modest increases in spring minimum (nighttime) temperatures caused strong phenological shifts. Climate effects varied among sites, among species within sites, and even among populations of the same species across sites, with particularly pronounced variation among species at a single location. Variation in climate effects was slightly better explained by local climate than by natural history traits. Among natural history traits, voltinism and overwintering stage were particularly influential. Importantly, climate influenced different aspects of the flight period (e.g., timing versus duration) in distinct ways, with both natural history traits and local climate modulating these responses. Our findings highlight the often-overlooked importance of winter precipitation and nighttime temperatures in shaping phenology and demonstrate the value of considering the entire flight period, rather than distinct aspects alone, to improve our understanding and predictions of species response to climate change.