Ecology最新文献

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.

Spatial pattern formation is recognized as a signal of ecological resilience, which could enhance ecosystems' persistence to environmental stress and make them evade catastrophic transitions. However, there is a lack of evidence and mechanisms for this phenomenon in natural ecosystems. Here, we conducted a large-scale plant community and spatial pattern survey across 116 sites in the alpine marshes on the eastern Tibetan Plateau. Our results showed that the alpine marsh shifted to a stable state characterized by multiple hummock characteristics during degradation. The hummock formation enhanced the compositional similarity between hummock-associated communities and the desired alpine marsh, thereby driving ecological resilience and making the system less susceptible to catastrophic transitions. Furthermore, an increase in hummock area and height, coupled with a reduction in hummock number, enhanced both environmental heterogeneity and plant beta diversity. In turn, greater environmental heterogeneity positively influenced beta diversity, which subsequently promoted higher compositional similarity across communities, ultimately contributing to increased ecological resilience. This study provides evidence and a mechanism for showing that spatial pattern formation drives resilience in real-world ecosystems. The findings highlight the necessity of incorporating spatial patterns into strategies for conserving biodiversity and ecosystem functioning, as well as enhancing ecological resilience in the face of accelerating environmental change.

A major challenge in invasion ecology is determining which introduced species pose a threat to resident species through competitive displacement. Since it is impossible to allocate management resources to preventing interactions among all resident and introduced species, methods for identifying instances of potential competitive displacement would greatly help focus precious management resources. Additionally, methods that use readily available data, such as species counts or functional traits, are especially advantageous under urgent invasion timelines compared to those requiring more time-intensive experimental data. Here, we provide a framework for estimating competition outcomes—including displacement—between resident and invading species using species count and functional trait data, two readily available data sources. Our framework provides methods for estimating displacement that is possibly in progress from species count data and estimating possible displacement from functional traits. We apply this framework to the native and introduced gecko species on the Caribbean island of Curaçao. Our work indicates a potential for the displacement of all three native species by introduced species and suggests that the displacement of one native species may already be underway. Given the urgency of the biodiversity crisis, our framework provides a usable tool for the early identification of potentially detrimental interactions from introduced species and provides insights to focus future studies and guide management efforts.

Living shorelines, a prevalent nature-based coastal infrastructure technique, typically merge the restoration of coastal habitats (e.g., salt marsh, oyster reef) with gray infrastructure (e.g., rock or concrete breakwaters) to provide coastal erosion protection. With increasingly frequent and severe storms, living shorelines have been shown to effectively limit coastal erosion and loss; however, there is still uncertainty regarding the effects of living shorelines on nekton communities as compared to natural marshes and gray coastal protection strategies like bulkheads. Here, we present a dataset of living shoreline-associated nekton species recorded over a 20-year period in North Carolina, USA. We harmonized nekton abundance and biomass data from five different studies (each ranging in duration from 2 to 4 years) across 12 living shorelines with paired natural marshes and, in some cases, bulkheads. These studies used different gear types and sampling methodologies, and therefore future users of this dataset must carefully consider the limitations of different subsets of the data and ensure that they do not make direct catch comparisons across sites that used different methodologies. Altogether, we identified a total of 62 species groups at living shorelines, natural reference marshes, and bulkheads across three categories (i.e., crustacean, mollusk, and fish) between 2001 and 2024. We identified 49 species groups on living shorelines, 49 species groups in natural marshes, and 5 species groups on bulkheads. For each living shoreline and paired natural marsh and/or bulkhead shoreline, we report individual species counts, biomass (when available), and the sampling method. In addition, we report on the living shoreline type, age, and location. In total, these data provide vital insight into how living shorelines function as habitat for nekton, and they can be used to evaluate living shoreline effectiveness as a predominant nature-based solution for coastal protection and biodiversity enhancement. The data are released under the Creative Commons Attribution 4.0 International License.

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.

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.

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.