Future climate change will severely reduce habitat suitability of the Critically Endangered Chinese giant salamander

1. Being the largest extant amphibian in the world, the IUCN Critically Endangered Chinese giant salamander Andrias davidianus is a charismatic species with great international public interest. While threats such as commercial overexploitation and habitat degradation have been extensively documented to affect natural populations of A. davidianus, still no information is available about the species sensitivity to climate change.
2. Here, we develop an ensemble of species distribution models (SDMs) for A. davidianus and projected its habitat suitability under present-day and future climate change scenarios. We based our SDMs on bioclimatic and topographic predictors, and recent (2012–2018) field-collected occurrence data across the whole distribution range of the species.
3. The ensemble SDMs exhibited good predictive capacity and suggested that slope, maximum temperature of warmest month, precipitation of driest month, and isothermality are the most influential predictors in determining distribution patterns in this species. The projections of our models point to a pronounced impact of climate changes over A. davidianus, with more than two-thirds of its suitable range expected to be lost in all scenarios of future climates tested.
4. In concert with the numerous other threats that are affecting this species, climate change poses a serious hindrance to the long-term survival of A. davidianus. We emphasise the urgent need of undertaking strict measures to manage this species and safeguard the few remaining available suitable habitats. We suggest that adaptive management strategies including designation of new reserves should be considered to mitigate the impacts of climate change on A. davidianus.

     

Limited transferability of stream‐fish distribution models among river catchments: reasons and implications

相似文献   

Indirect effects of deer on insect pests and soybean plants

1. White-tailed deer (Odocoileus virginianus Zimmermann) and insect pests negatively affect soybean production; however, little is known about how these herbivores potentially interact to affect soybean yield. Previous studies have shown deer browse on non-crop plants affects insect density and insect-mediated leaf damage, which together reduce plant reproductive output. In soybeans, reproductive output is influenced by direct and indirect interactions of different herbivores.
2. Here, we quantified indirect interactions between two groups of herbivores (mammals and insects) and their effects on soybean growth and yield. We examined responses of insect pest communities along a gradient of deer herbivory (29% to 49% browsed stems) in soybean monocultures.
3. Structural equation models showed that deer browse had direct negative effects on soybean plant height and yield. Deer browse indirectly decreased insect-mediated leaf damage by reducing plant height. Deer browse also indirectly increased pest insect abundance through reductions in plant height. Similarly, deer herbivory had an indirect positive effect on leaf carbon: nitrogen ratios through changes in plant height, thereby decreasing leaf nutrition.
4. These results suggest that pest insect abundance may be greater on soybean plants in areas of higher deer browse, but deer browse may reduce insect herbivory through reduced leaf nutrition.

     

Dynamic distribution modelling of the swamp tigertail dragonfly Synthemis eustalacta (Odonata: Anisoptera: Synthemistidae) over a 20-year bushfire regime

1. Intensity and severity of bushfires in Australia have increased over the past few decades due to climate change, threatening habitat loss for numerous species. Although the impact of bushfires on vertebrates is well-documented, the corresponding effects on insect taxa are rarely examined, although they are responsible for key ecosystem functions and services. Understanding the effects of bushfire seasons on insect distributions could elucidate long-term impacts and patterns of ecosystem recovery.
2. Here, the authors investigated the effects of recent bushfires, land-cover change, and climatic variables on the distribution of a common and endemic dragonfly, the swamp tigertail (Synthemis eustalacta) (Burmeister, 1839), which inhabits forests that have recently undergone severe burning. The authors used a temporally dynamic species distribution modelling approach that incorporated 20 years of community-science data on dragonfly occurrence and predictors based on fire, land cover, and climate to make yearly predictions of suitability. The authors also compared this to an approach that combines multiple temporally static models that use annual data.
3. The authors found that for both approaches, fire-specific variables had negligible importance for the models, while the percentage of tree and non-vegetative cover were most important. The authors also found that the dynamic model outperformed the static ones, based on cross-validation omission rate. Model predictions indicated temporal variation in area and spatial arrangement of suitable habitat, but no patterns of habitat expansion, contraction, or shifting.
4. These results highlight not only the efficacy of dynamic modelling to capture spatiotemporal variables such as vegetation cover for an endemic insect species, but also provide a novel approach to mapping species distributions with sparse locality records.

     

Utilizing the density of inventory samples to define a hybrid lattice for species distribution models: DISTRIB‐II for 135 eastern U.S. trees

相似文献   

Same species,same habitat preferences? The distribution of aquatic plants is not explained by the same predictors in lakes and streams

1. Studying the geographical distribution of species can reveal conditions and processes that may drive species presence and abundance. Organism distribution has frequently been explained by climate, but the relative role of local environmental predictors is not fully understood. Moreover, in the freshwater realm, intrinsic differences existing between different categories of water bodies can lead to significant differences in species–environment relationships. Here, we tested the relative importance of broad-scale climate and local environmental predictors in explaining plant species distributions in freshwater lakes and streams.
2. We built species distribution models to investigate which predictors best explain aquatic plant distribution in two categories of water bodies. We used species inventories and records of three climate and eight local environmental predictors for 150 lakes and 150 streams in Finland.
3. We found that sets of predictors that explain the distribution of macrophyte species are unique depending on if species are in a lake or a stream. Overall, air temperature and ecosystem size were essential to predict aquatic plant species presence in both water body categories. Broad-scale climate predictors were always very important in explaining species distribution, while local environmental conditions such as water chemistry were of variable influence, depending on species and water body category.
4. These results are probably due to high spatial and temporal variability and range of water physico-chemical parameters, especially in streams. Nonetheless, despite a lower relative importance than climatic factors, local environmental predictors also strongly affected species distributions.
5. Our findings highlight that incorporating local environmental conditions to species distribution models in addition to climate predictors is necessary to improve predictions, particularly for distribution of stream flora. Considering the species-specific responses of aquatic plants to their environment, studying species individually with species distribution models represents a useful analysis.

     

Niche conservatism and the potential for the crayfish Procambarus clarkii to invade South America

相似文献   

Species‐level image classification with convolutional neural network enables insect identification from habitus images

1. Changes in insect biomass, abundance, and diversity are challenging to track at sufficient spatial, temporal, and taxonomic resolution. Camera traps can capture habitus images of ground‐dwelling insects. However, currently sampling involves manually detecting and identifying specimens. Here, we test whether a convolutional neural network (CNN) can classify habitus images of ground beetles to species level, and estimate how correct classification relates to body size, number of species inside genera, and species identity.
2. We created an image database of 65,841 museum specimens comprising 361 carabid beetle species from the British Isles and fine‐tuned the parameters of a pretrained CNN from a training dataset. By summing up class confidence values within genus, tribe, and subfamily and setting a confidence threshold, we trade‐off between classification accuracy, precision, and recall and taxonomic resolution.
3. The CNN classified 51.9% of 19,164 test images correctly to species level and 74.9% to genus level. Average classification recall on species level was 50.7%. Applying a threshold of 0.5 increased the average classification recall to 74.6% at the expense of taxonomic resolution. Higher top value from the output layer and larger sized species were more often classified correctly, as were images of species in genera with few species.
4. Fine‐tuning enabled us to classify images with a high mean recall for the whole test dataset to species or higher taxonomic levels, however, with high variability. This indicates that some species are more difficult to identify because of properties such as their body size or the number of related species.
5. Together, species‐level image classification of arthropods from museum collections and ecological monitoring can substantially increase the amount of occurrence data that can feasibly be collected. These tools thus provide new opportunities in understanding and predicting ecological responses to environmental change.

     

The impacts of invasive ecosystem engineers in freshwaters: A review

1. Invasive species are a key stressor in freshwater ecosystems. When these species are also ecosystem engineers, their impacts are exacerbated because they modulate resource availability for a wide range of other species. The aim of this review is to synthesise existing knowledge of the impacts of invasive ecosystem engineers in freshwaters and identify knowledge gaps requiring further research.
2. The four questions explored in this review are: (1) What are the trends in research into invasive ecosystem engineers? (2) What are common negative effects of invasive ecosystem engineers in freshwater? (3) Do all impacts of invasive ecosystem engineers have negative consequences for biodiversity? (4) What happens when multiple ecosystem engineers interact? Four literature searches in Web of Science have been used to identify articles for the review and to estimate relative research effort between terrestrial, marine and freshwater ecosystems.
3. The number of research articles focusing on ecosystem engineers across all ecosystem types is increasing. Despite well-known examples of ecosystem engineer species in freshwaters (e.g. beaver), more research has focussed on terrestrial environments and invasive species.
4. The effects of invasive ecosystem engineers in freshwater systems are varied and often context dependent. Their effects on biodiversity or native ecosystem engineers are often shown to be negative; however, not all effects associated with these species are deleterious to native species. For instance, some invasive ecosystem engineers support native species through the provision of food or refuges.
5. Although freshwater ecosystems are often influenced by multiple species of ecosystem engineers (including native, invasive or both), little is known about interactions between these species or the combined effects of multiple ecosystem engineers. More research is also needed that relates the results of laboratory experiments to the field and develops methods for measuring factors that govern the impact of engineers on ecosystems. Understanding the spatial variability of the impacts of invasive ecosystem engineers as well as their interaction with anthropogenic stressors (e.g. hydrologic modification) is also necessary.
6. The lag in research surrounding invasive ecosystem engineers in freshwater compared to other biomes is concerning, as freshwater ecosystems support biodiversity disproportionate to the area they occupy. Creating predictive models of the impacts of freshwater ecosystem engineers would help anticipate the effects of invasive ecosystem engineers in freshwater and add to the broader understanding of their effects in other biomes.

     

Plant phylogeny drives arboreal caterpillar assemblages across the Holarctic

1. Assemblages of insect herbivores are structured by plant traits such as nutrient content, secondary metabolites, physical traits, and phenology. Many of these traits are phylogenetically conserved, implying a decrease in trait similarity with increasing phylogenetic distance of the host plant taxa. Thus, a metric of phylogenetic distances and relationships can be considered a proxy for phylogenetically conserved plant traits and used to predict variation in herbivorous insect assemblages among co‐occurring plant species.
2. Using a Holarctic dataset of exposed‐feeding and shelter‐building caterpillars, we aimed at showing how phylogenetic relationships among host plants explain compositional changes and characteristics of herbivore assemblages.
3. Our plant–caterpillar network data derived from plot‐based samplings at three different continents included >28,000 individual caterpillar–plant interactions. We tested whether increasing phylogenetic distance of the host plants leads to a decrease in caterpillar assemblage overlap. We further investigated to what degree phylogenetic isolation of a host tree species within the local community explains abundance, density, richness, and mean specialization of its associated caterpillar assemblage.
4. The overlap of caterpillar assemblages decreased with increasing phylogenetic distance among the host tree species. Phylogenetic isolation of a host plant within the local plant community was correlated with lower richness and mean specialization of the associated caterpillar assemblages. Phylogenetic isolation had no effect on caterpillar abundance or density. The effects of plant phylogeny were consistent across exposed‐feeding and shelter‐building caterpillars.
5. Our study reveals that distance metrics obtained from host plant phylogeny are useful predictors to explain compositional turnover among hosts and host‐specific variations in richness and mean specialization of associated insect herbivore assemblages in temperate broadleaf forests. As phylogenetic information of plant communities is becoming increasingly available, further large‐scale studies are needed to investigate to what degree plant phylogeny structures herbivore assemblages in other biomes and ecosystems.

     

Seasonal habitat use indicates that depth may mediate the potential for invasive round goby impacts in inland lakes

1. The round goby (Neogobius melanostomus) is among the fastest-spreading introduced aquatic species in North America and is radiating inland from the Great Lakes into freshwater ecosystems across the landscape. Predicting and managing the impacts of round gobies requires information on the factors influencing their distribution in habitats along the invasion front, yet this information is not available for many recently invaded ecosystems. We evaluated the seasonal habitat use and biomass of round gobies in an inland temperate lake to define the spatiotemporal scope of biological interactions at the leading edge of the round goby invasion.
2. Using novel statistical approaches, we combined hierarchical models that control for imperfect species detection with flexible smooth terms to describe non-linear relationships between round goby abundance and environmental gradients. Subsequently, we generated accurate detection-corrected estimates of the standing stock biomass of round gobies.
3. Our results show seasonally differentiated habitat niches, where suitable round goby habitat in summer months is restricted to shallow depths (<18.4 m) with a mixture of vegetative and mussel cover. We found high round goby biomass of 122 kg/ha in occupied habitats during the summer, with a total lake-wide biomass of 766,000 kg. In winter, round gobies migrate to deep offshore habitats and disperse, dramatically altering their scope for biological interactions with resident aquatic species across summer and winter seasons.
4. The results of this study indicate that the scope of biological interactions in inland lakes may be seasonally variable, with potential for high round goby biomass in shallow lakes or at the periphery of deep lakes in the summer months. Such shallow-water habitats may therefore present higher risk of ecological impacts from round gobies in invaded lentic ecosystems. As round gobies expand inland, consideration of seasonal habitat use will be an important factor in predicting the impacts of this pervasive invader.

     

Incorporating intraspecific variation into species distribution models improves distribution predictions,but cannot predict species traits for a wide-spread plant species

The most common approach to predicting how species ranges and ecological functions will shift with climate change is to construct correlative species distribution models (SDMs). These models use a species’ climatic distribution to determine currently suitable areas for the species and project its potential distribution under future climate scenarios. A core, rarely tested, assumption of SDMs is that all populations will respond equivalently to climate. Few studies have examined this assumption, and those that have rarely dissect the reasons for intraspecific differences. Focusing on the arctic-alpine cushion plant Silene acaulis, we compared predictive accuracy from SDMs constructed using the species’ full global distribution with composite predictions from separate SDMs constructed using subpopulations defined either by genetic or habitat differences. This is one of the first studies to compare multiple ways of constructing intraspecific-level SDMs with a species-level SDM. We also examine the contested relationship between relative probability of occurrence and species performance or ecological function, testing if SDM output can predict individual performance (plant size) and biotic interactions (facilitation). We found that both genetic- and habitat-informed SDMs are considerably more accurate than a species-level SDM, and that the genetic model substantially differs from and outperforms the habitat model. While SDMs have been used to infer population performance and possibly even biotic interactions, in our system these relationships were extremely weak. Our results indicate that individual subpopulations may respond differently to climate, although we discuss and explore several alternative explanations for the superior performance of intraspecific-level SDMs. We emphasize the need to carefully examine how to best define intraspecific-level SDMs as well as how potential genetic, environmental, or sampling variation within species ranges can critically affect SDM predictions. We urge caution in inferring population performance or biotic interactions from SDM predictions, as these often-assumed relationships are not supported in our study.     

Nondetection sampling bias in marked presence‐only data

相似文献   

The normalized segment classification model: A new tool to compare spectral reflectance curves

1. Color patterns are complex traits under selective pressures from conspecifics, mutualists, and antagonists. To evaluate the salience of a pattern or the similarity between colors, several visual models are available. Color discrimination models estimate the perceptual difference between any two colors. Their application to a diversity of taxonomic groups has become common in the literature to answer behavioral, ecological, and evolutionary questions. To use these models, we need information about the visual system of our beholder species. However, many color patterns are simultaneously subject to selective pressures from different species, often from different taxonomic groups, with different visual systems. Furthermore, we lack information about the visual system of many species, leading ecologists to use surrogate values or theoretical estimates for model parameters.
2. Here, we present a modification of the segment classification method proposed by Endler (Biological Journal of the Linnean Society, 1990 41, 315–352): the normalized segment classification model (NSC). We explain its logic and use, exploring how NSC differs from other visual models. We also compare its predictions with available experimental data.
3. Even though the NSC model includes no information about the visual system of the receiver species, it performed better than traditional color discrimination models when predicting the output of some behavioral tasks. Although vision scientists define color as independent of stimulus brightness, a likely explanation for the goodness of fit of the NSC model is that its distance measure depends on brightness differences, and achromatic information can influence the decision‐making process of animals when chromatic information is missing.
4. Species‐specific models may be insufficient for the study of color patterns in a community context. The NSC model offers a species‐independent solution for color analyses, allowing us to calculate color differences when we ignore the intended viewer of a signal or when different species impose selective pressures on the signal.

     

Evolutionary history predicts high‐impact invasions by herbivorous insects

相似文献   

Aggregative oviposition varies with density in processionary moths—Implications for insect outbreak propensity

1. In gregarious insects, groups commonly originate from females laying eggs in masses and feeding groups are established as soon as larvae hatch. Some group-living insect species may aggregate beyond the individual parent level, such that offspring from two or more egg masses develop within a common resource.
2. Here we show that aggregative oviposition can vary with population density at oviposition and possibly be an important factor in outbreak dynamics of phytophagous insects.
3. We analysed density data with respect to egg mass aggregation for two species of pine processionary moths, Thaumetopoea pinivora (in Sweden 2005–2019) and T. pityocampa (in Spain 1973–1991). Both species lay their eggs in egg masses and feed in groups. During the study periods, insect population density for both species varied by at least an order of magnitude.
4. The two species showed strikingly similar patterns of egg mass aggregation. Egg masses were overdispersed at high population density, with few trees showing a high load of egg masses.
5. Our data suggest that aggregative oviposition can be important in explaining the previously documented higher propensity for outbreaks in insects laying eggs in clusters, compared with those laying individual eggs.

     

种间作用对物种分布模拟的影响及建模方法

物种分布模型(SDMs)通过量化物种分布和环境变量之间的关系,并将其外推到未知的景观单元,模拟、预测地理空间中生物的潜在分布,是生态学、生物地理学、保护生物学等研究领域的重要工具.然而,目前物种分布模型主要采用非生物因素作为预测变量,由于数据量化和建模表达困难,生物因素特别是种间作用在物种分布模型中常被忽略,将种间作用...     

Weak climatic associations among British plant distributions

Aim Species distribution models (SDMs) are used to infer niche responses and predict climate change‐induced range shifts. However, their power to distinguish real and chance associations between spatially autocorrelated distribution and environmental data at continental scales has been questioned. Here this is investigated at a regional (10 km) scale by modelling the distributions of 100 plant species native to the UK. Location UK. Methods SDMs fitted using real climate data were compared with those utilizing simulated climate gradients. The simulated gradients preserve the exact values and spatial structure of the real ones, but have no causal relationships with any species and so represent an appropriate null model. SDMs were fitted as generalized linear models (GLMs) or by the Random Forest machine‐learning algorithm and were either non‐spatial or included spatially explicit trend surfaces or autocovariates as predictors. Results Species distributions were significantly but erroneously related to the simulated gradients in 86% of cases (P < 0.05 in likelihood‐ratio tests of GLMs), with the highest error for strongly autocorrelated species and gradients and when species occupied 50% of sites. Even more false effects were found when curvilinear responses were modelled, and this was not adequately mitigated in the spatially explicit models. Non‐spatial SDMs based on simulated climate data suggested that 70–80% of the apparent explanatory power of the real data could be attributable to its spatial structure. Furthermore, the niche component of spatially explicit SDMs did not significantly contribute to model fit in most species. Main conclusions Spatial structure in the climate, rather than functional relationships with species distributions, may account for much of the apparent fit and predictive power of SDMs. Failure to account for this means that the evidence for climatic limitation of species distributions may have been overstated. As such, predicted regional‐ and national‐scale impacts of climate change based on the analysis of static distribution snapshots will require re‐evaluation.     

Behavior underpins the predictive power of a trait‐based model of butterfly movement

1. Dispersal ability is key to species persistence in times of environmental change. Assessing a species' vulnerability and response to anthropogenic changes is often performed using one of two methods: correlative approaches that infer dispersal potential based on traits, such as wingspan or an index of mobility derived from expert opinion, or a mechanistic modeling approach that extrapolates displacement rates from empirical data on short‐term movements.
2. Here, we compare and evaluate the success of the correlative and mechanistic approaches using a mechanistic random‐walk model of butterfly movement that incorporates relationships between wingspan and sex‐specific movement behaviors.
3. The model was parameterized with new data collected on four species of butterfly in the south of England, and we observe how wingspan relates to flight speeds, turning angles, flight durations, and displacement rates.
4. We show that flight speeds and turning angles correlate with wingspan but that to achieve good prediction of displacement even over 10 min the model must also include details of sex‐ and species‐specific movement behaviors.
5. We discuss what factors are likely to differentially motivate the sexes and how these could be included in mechanistic models of dispersal to improve their use in ecological forecasting.

     

Niche separation and weak interactions in the high tidal zone of saltmarsh‐mangrove mixing communities

1. Saltmarsh‐mangrove ecotones occur at the boundary of the natural geographic distribution of mangroves and salt marshes. Climate warming and species invasion can also drive the formation of saltmarsh‐mangrove mixing communities. How these coastal species live together in a “new” mixed community is important in predicting the dynamic of saltmarsh‐mangrove ecosystems as affected by ongoing climate change or human activities. To date, the understanding of species interactions has been rare on adult species in these ecotones.
2. Two typical coastal wetlands were selected as cases to understand how mangrove and saltmarsh species living together in the ecotones. The leaves of seven species were sampled from these coastal wetlands based on their distribution patterns (living alone or coexisting) in the high tidal zone, and seven commonly used functional traits of these species were analyzed.
3. We found niche separation between saltmarsh and mangrove species, which is probably due to the different adaptive strategies they adopted to deal with intertidal environments.
4. Weak interactions between coexisting species were dominated in the high tidal zone of the two saltmarsh‐mangrove communities, which could be driven by both niche differentiation and neutral theory.
5. Synthesis. Our field study implies a potential opportunity to establish a multispecies community in the high tidal zone of saltmarsh‐mangrove ecotones, where the sediment was characterized by low salinity and high nitrogen.