Ecology and Evolution最新文献

Biotic interactions are crucial for determining the structure and dynamics of communities; however, direct measurement of these interactions can be challenging in terms of time and resources, especially when numerous species are involved. Inferring species interactions from species co-occurrence patterns is increasingly being used; however, recent studies have highlighted some limitations. To our knowledge, no attempt has been made to test the accuracy of the existing methods for detecting mutualistic interactions in terrestrial ecosystems. In this study, we compiled two literature-based, long-term datasets of interactions between butterflies and herbaceous plant species in two regions of Germany and compared them with observational abundance and presence/absence data collected within a year in the same regions. We tested how well the species associations generated by three different co-occurrence analysis methods matched those of empirically measured mutualistic associations using sensitivity and specificity analyses and compared the strength of associations. We also checked whether flower abundance data (instead of plant abundance data) increased the accuracy of the co-occurrence models and validated our results using empirical flower visitation data. The results revealed that, although all methods exhibited low sensitivity, our implementation of the Relative Interaction Intensity index with pairwise null models performed the best, followed by the probabilistic method and Spearman's rank correlation method. However, empirical data showed a significant number of interactions that were not detected using co-occurrence methods. Incorporating flower abundance data did not improve sensitivity but enhanced specificity in one region. Further analysis demonstrated incongruence between the predicted co-occurrence associations and actual interaction strengths, with many pairs exhibiting high interaction strength but low co-occurrence or vice versa. These findings underscore the complexity of ecological dynamics and highlight the limitations of current co-occurrence methods for accurately capturing species interactions.

Understanding patterns of biodiversity change is essential as coral reefs experience recurrent cycles of disturbance and recovery. Shifts in the total cover and species composition of habitat-forming corals can have far-reaching consequences, including shifts in coral functional traits and impacts on local fish assemblages. We surveyed coral and fish assemblages along the southern coast of Hainan Island near Sanya, China, in 2006, 2010, and 2018, during a period with repeated mass bleaching events. We showed that coral biodiversity in this region is in a state of flux, with losses and gains in coral cover and an increase in species richness over time. Despite increasing species diversity, the region suffered a loss of coral trait diversity by 2010, with an incomplete recovery by 2018, owing to declines in species with key habitat-forming traits (e.g., high surface areas and fractal structure) such as corymbose corals. Concurrently, there was an increase in functional redundancy due to the proliferation of the dominant encrusting and massive corals. Coral cover was positively associated with the abundance of reef fish, indicating that the changes observed in coral abundance can impact reef-associated species. These results demonstrate that the slow recovery of coral biodiversity in southern Hainan Island has been hampered by the loss of specific coral traits and highlight the importance of protecting vulnerable coral traits in conservation and management strategies.

Animal-mediated pollination is a key ecosystem service required to some extent by almost three-quarters of the leading human food crops in global food production. Anthropogenic pressures such as habitat loss and land-use intensification are causing shifts in ecological community composition, potentially resulting in declines in pollination services and impacting crop production. Previous research has often overlooked interspecific differences in pollination contribution, yet such differences mean that biodiversity declines will not necessarily negatively impact pollination. Here, we use a novel species-level ecosystem service contribution matrix along with mixed-effects models to explore how groups of terrestrial species who contribute differently to crop pollination respond globally to land-use type, land-use intensity, and availability of natural habitats in the surrounding landscape. We find that the species whose contribution to crop pollination is higher generally respond less negatively (and in some cases positively) to human disturbance of land, compared to species that contribute less or not at all to pollination. This result may be due to these high-contribution species being less sensitive to anthropogenic land conversions, which has led humans to being more reliant on them for crop pollination. However, it also suggests that there is potential for crop pollination to be resilient in the face of anthropogenic land conversions. With such a high proportion of food crops requiring animal-mediated pollination to some extent, understanding how anthropogenic landscapes impact ecological communities and the consequences for pollination is critical for ensuring food security.

Aquatic ecosystems are often negatively affected by invasive species. However, biotic resistance by native species, either by competition or predation, can reduce the impacts of invasions by non-native species. The Western Mosquitofish (Gambusia affinis) is one of the most impactful invasive species of freshwater fish and cause declines in native fish populations. Using two mesocosm experiments conducted in different years, we examined the ecological interactions between juveniles of the native fish, Bluegill Sunfish (Lepomis macrochirus), and adults of the invasive fish, G. affinis. We found evidence for interactions between L. macrochirus and G. affinis. However, interactions did not appear symmetric, with L. macrochirus generally more affected by intraspecific interactions than interspecific interactions whereas G. affinis was more affected by interspecific interactions than intraspecific interactions. The presence of either species of fish led to a decrease in the number of large zooplankton and a tendency for a decrease in the total number of zooplankton. Based on these results, native L. macrochirus appear to be able to reduce the ability of non-native G. affinis to establish or maintain populations through both competition and predation (i.e., acting as an intraguild predator). The consistency of our results across both experiments, with their different designs and their occurring in different years, gives weight to these conclusions. The reduction of or prevention of establishment of populations of invasive G. affinis would likely benefit the aquatic communities of ponds with fish, especially small-bodied native fish.

Understanding mechanisms and predicting natural population responses to climate is a key goal of Ecology. However, studies explicitly linking climate to population dynamics remain limited. Antecedent effect models are a set of statistical tools that capitalize on the evidence provided by climate and population data to select time windows correlated with a response (e.g., survival, reproduction). Thus, these models can serve as both a predictive and exploratory tool. We compare the predictive performance of antecedent effect models against simpler models and showcase their exploratory analysis potential by selecting a case study with high predictive power. We fit three antecedent effect models: (1) weighted mean models (WMM), which weigh the importance of monthly anomalies based on a Gaussian curve, (2) stochastic antecedent models (SAM), which weigh the importance of monthly anomalies using a Dirichlet process, and (3) regularized regressions using the Finnish horseshoe model (FHM), which estimate a separate effect size for each monthly anomaly. We compare these approaches to a linear model using a yearly climatic predictor and a null model with no predictors. We use demographic data from 77 natural populations of 34 plant species ranging between seven and 36 years in length. We then fit models to the asymptotic population growth rate (λ) and its underlying vital rates: survival, development, and reproduction. We find that models including climate do not consistently outperform null models. We hypothesize that the effect of yearly climate is too complex, weak, and confounded by other factors to be easily predicted using monthly precipitation and temperature data. On the other hand, in our case study, antecedent effect models show biologically sensible correlations between two precipitation anomalies and multiple vital rates. We conclude that, in temporal datasets with limited sample sizes, antecedent effect models are better suited as exploratory tools for hypothesis generation.

Low levels of essential mineral elements such as cobalt, copper, and iron, in organisms reduce immune function, increasing the chances of parasitic infection. This phenomenon has been demonstrated widely in domestic animals but rarely in wildlife. In this study, we used data from 7- to 9-month-old roe deer (Capreolus capreolus), living in two different populations facing contrasting environmental conditions (Trois-Fontaines and Chizé), to investigate whether the parasitic and immunological statuses could be related to essential element status. Between 2016 and 2019, we collected feces to measure parasite burdens (gastrointestinal and pulmonary nematodes), blood to measure immunological parameters (globulins and white blood cells), and hair to assess the concentration of 11 essential elements (calcium [Ca], chromium [Cr], cobalt [Co], copper [Cu], iron [Fe], magnesium [Mg], manganese [Mn], potassium [K], molybdenum [Mo], selenium [Se], and zinc [Zn]). The results showed first heterogeneity in the individual phenotypes of the two populations. Roe deer with low body mass had high concentrations of all the essential elements (in particular, Ca, Fe, Cu, K, and Mn), a high parasitic burden, and high concentrations of globulins. An association between high concentrations of essential elements and a high parasite burden was found at the two study sites despite markedly different environmental conditions. A relationship between essential element concentrations and immune parameters was also detected, with more basophils and globulins being associated with high concentrations of essential trace elements (i.e., Ca, Fe, Cu, and, to a lesser extent, Se, Cr, and Zn). These results suggest that young individuals with low body mass and high parasitism may select feeding resources rich in mineral elements, which may improve their ability to control the infestation and/or mitigate the negative consequences of parasites by maintaining immune system functions.

While invasive success of alien plant species is often attributed to their superior competitive abilities, it is also suggested that competitive ability depends on the target species of competition and resource availability. In addition, it remains unclear whether invaders and co-occurring plants in the introduced area exhibit distinctive inter- and intraspecific competitive intensities. This study aimed to evaluate the competitive ability of a successful invader, Lactuca serriola, through a combination of field surveys and a growth chamber experiment. First, we assessed biodiversity and the biomass of co-occurring plants in both L. serriola-invaded and uninvaded plots across nine sites in South Korea. Subsequently, a pairwise competition experiment was conducted between L. serriola and three weedy plant species commonly found in the invaded plots, Chenopodium album, Erigeron canadensis, and Oenothera biennis, under differential nutrient levels. Diversity indices of plant communities and the biomass of most co-occurring plants showed no significant difference between invaded and uninvaded plots. L. serriola and testing weedy plants exhibited mutually negative effects on biomass when grown together in the same pot, with the intensity of interspecific competition being comparable across nutrient treatments. Notably, intraspecific competition of L. serriola was weaker than testing weedy plants, particularly manifest in the high-nutrient treatment. The results of both field and growth-chamber studies demonstrated that L. serriola was not a particularly strong competitor compared to its neighboring weedy plants. Its successful invasion can be partially attributed to its weak intraspecific competition intensity, which potentially facilitate successful establishment with high density.

Species distribution models (SDMs) are widely used to address species' responses to bioclimatic conditions in the fields of ecology, biogeography and conservation. Among studies that have addressed reasons for model prediction variability, the impact of climatic variable selection has received limited attention and is rarely assessed in sensitivity analyses. Here, we tested the assumption that this aspect of model design is a major source of uncertainty, especially when projections are made to non-analogue climates. As a study system, we used 142 alien plant species introduced to the sub-Antarctic islands. Based on global occurrence data, we fitted SDMs as functions of seven bioclimatic variable sets that only differed in the identity of two temperature variables. Moreover, we calculated the overlap between the island's climatic conditions and the niches the species have realised outside of the islands. Despite comparable internal evaluation metrics, projections of these models were in sharp contrast with each other, with some models predicting the sub-Antarctic islands' climate to be almost ubiquitously suitable to most species and others unsuitable to almost all species. In particular, the mean temperature of the warmest month led to strong underpredictions of the SDMs, while its replacement by the mean temperature of the coldest month led to massive overpredictions. Partitioning the variance in projections demonstrated that predictor identity was its most important source, followed by island and species identity. The size of area projected to be suitable was also related to the overlap in predictor values realised in the global range of species (outside of the islands) and on the islands. Our findings emphasise the importance of bioclimatic variable selection in SDMs, especially when making projections to non-analogue climates. Such extrapolations are often required, especially when using SDMs to assess invasion risk under both current and future climates.

Given that terrestrial ecosystems globally are facing the loss of biodiversity from land use conversion, invasive species, and climate change, effective management requires a better understanding of the drivers and correlates of biodiversity. Increasingly, biodiversity is co-managed with aboveground carbon storage because high biodiversity in animal species is observed to correlate with high aboveground carbon storage. Most previous investigations into the relationship of biodiversity and carbon co-management do not focus on the biodiversity of the species rich plant kingdom, which may have tradeoffs with carbon storage. To examine the relationships of plant species richness with aboveground tree biomass carbon storage, we used a series of generalized linear models with understory plant species richness and diversity data from the USDA Forest Service Forest Inventory and Analysis dataset and high-resolution modeled carbon maps for the Tongass National Forest. Functional trait data from the TRY database was used to understand the potential mechanisms that drive the response of understory plants. Understory species richness and community weighted mean leaf dry matter content decreased along an increasing gradient of tree biomass carbon storage, but understory diversity, community weighted mean specific leaf area, and plant height at maturity did not. Leaf dry matter content had little variance at the community level. The decline of understory plant species richness but not diversity to increases in aboveground biomass carbon storage suggests that rare species are excluded in aboveground biomass carbon dense areas. These decreases in understory species richness reflect a tradeoff between the understory plant community and aboveground carbon storage. The mechanisms that are associated with observed plant communities along a gradient of biomass carbon storage in this forest suggest that slower-growing plant strategies are less effective in the presence of high biomass carbon dense trees in the overstory.