Ecology最新文献

Dispersal is one of the most important aspects of animal behavior and can have far-reaching consequences for organismal ecology and evolution. Despite recent theoretical advances in understanding why individuals within the same population vary in dispersal behavior, relatively few studies have empirically evaluated the long-term causes and consequences of variable dispersal within natural populations. In this study, we used life history data collected over the course of 16 years to examine fitness outcomes in 867 known-age female tree swallows breeding in New York, USA, that differed in their dispersal status: "immigrant" females, defined as dispersers that hatched elsewhere, and "local" females, defined as non-dispersers that hatched within the study site and returned there after migration to breed. We also compared the life history responses of immigrant and local females to natural variation in weather, nest predation risk, and social environment at their breeding site. Local females were more likely to produce fledglings that recruited into the study area as adults. We also found several instances in which dispersal status interacted with an environmental metric to influence relative fitness, and these responses were largely consistent across life history measures. Overall, immigrant females were relatively resilient to variation in their extrinsic environment, while local females were highly sensitive to environmental conditions at the breeding site, performing relatively well when conditions were benign and faring relatively poorly as conditions became more stressful. We found little evidence that distance dispersed within a study site impacted female fitness, suggesting that the dispersal-associated differences in fitness that we observed operate mostly across broader spatial scales. Future work should undertake the direct and simultaneous measurement of behavior, physiology, and fitness of immigrant and local females across environmental contexts and should seek to understand whether and how context-dependent fitness variation of dispersers and non-dispersers scales up to influence larger ecological and evolutionary processes.

Forest pests pose critical threats to forest ecosystems worldwide, yet accurately predicting their spatial spread remains challenging due to complex dispersal behaviors, weather effects, and the inherent difficulty of tracking small organisms across large landscapes. These challenges have resulted in divergent estimates of typical dispersal distances across studies. Here, we use high-quality data from helicopter and field-crew surveys to parameterize dispersal kernels for the mountain pine beetle, a destructive pest that has recently expanded its range into Alberta, Canada. We find that fat-tailed kernels-those which allow for a small number of long-distance dispersal events-consistently provide the best fit to these data. Specifically, the radially symmetric Student's t-distribution with parameters $\rho =0.012$ km and $\nu =1.45$ stands out as parsimonious and user-friendly; this model predicts a median dispersal distance of 60 m, with the $95\mathrm{th}$ percentile of dispersers traveling nearly 5 km. The best-fitting mathematical models have biological interpretations. The Student's t-distribution, derivable as a mixture of diffusive processes with varying settling times, is consistent with observations that mountain pine beetle adults fly short distances while few travel far; early-emerging beetles fly farther; and larger beetles from larger trees exhibit greater variance in flight distance. This phenotypic variability is mirrored in other forest pests, resulting in a stratified dispersal pattern where most individuals disperse locally while rare long-distance "jumpers" drive range expansion. Our approach demonstrates how aerial survey data can be used to characterize dispersal patterns, as many insects create diagnostic signatures-combining foliage damage patterns and host-tree preferences-that are visible from above. Since aerial surveys of North American forests are widely available, our methodology can be broadly used to create parsimonious dispersal models for many forest insects.

Dispersal is becoming increasingly critical to understand as climate change forces species to shift their ranges to track changing environments. Although we know that warmer temperatures can prompt species to shift their ranges, we have little understanding of how temperature affects the speed at which they can do so by altering the rate of range expansion. Warmer temperatures could accelerate the rate of range expansion by increasing random, density-independent movement and/or by increasing population growth rates and driving density-dependent movement. To test the effect of temperature on the rate of range expansion, we grew populations of the flour beetle Tribolium castaneum in linear connected landscapes at 27.5, 30, or 32.5°C and tracked their expansion for 18 weeks. We then conducted separate assays to isolate the effect of temperature on density-independent dispersal probability and population growth rates. We found that beetles at 32.5°C exhibited the fastest range expansion, and that higher temperatures increased both dispersal probability and population growth rates, suggesting that both mechanisms likely contributed to faster range expansions under warming. Our findings highlight the importance of assessing the effects of temperature on range expansion dynamics in order to fully understand how, and how quickly, ranges will shift under climate change.

Under the current global biodiversity crisis, there is a need for automated and noninvasive monitoring techniques that can gather large amounts of data cost-effectively at various ecological scales, from local to large spatial scales. These data can then be analyzed to inform stakeholders and decision-makers. One such technique is passive acoustic monitoring, which is commonly coupled with automatic identification of animal species based on their sound. Automated sound analyses usually require the training of sound detection and identification algorithms. These algorithms are based on annotated acoustic datasets which mark the occurrence of sounds of species inside sound recordings. However, compiling large annotated acoustic datasets is time-consuming and requires experts, and therefore, they normally cover reduced spatial, temporal, and taxonomic scales. This data paper presents WABAD, the World Annotated Bird Acoustic Dataset for passive acoustic monitoring. WABAD is designed to provide the public, the research community, and conservation managers with a novel and globally representative annotated acoustic dataset. This database includes 5047 min of audio files annotated to species-level by local experts with the start and end time and the upper and lower frequencies of each identified bird vocalization in the recordings. The database has a wide taxonomic and spatial coverage, including information on 91,931 vocalizations from 1192 bird species recorded at 72 recording sites in 29 recording locations (mainly countries) and distributed across 13 biomes. WABAD can be used, for example, for developing and/or validating automatic species detection algorithms, answering ecological questions, such as assessing geographical variations on bird vocalizations, or comparing acoustic diversity indices with species-based diversity indices. The dataset is published under a Creative Commons Attribution 4.0 International license that permits redistribution and reuse on the condition that the original work is properly credited.

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.