Choosing among correlative, mechanistic, and hybrid models of species' niche and distribution

Biodiversity modeling advances will improve predictions of nature's contributions to people

Accurate predictions of ecosystem functions and nature's contributions to people (NCP) are needed to prioritize environmental protection and restoration in the Anthropocene. However, our ability to predict NCP is undermined by approaches that rely on biophysical variables and ignore those describing biodiversity, which have strong links to NCP. To foster predictive mapping of NCP, we should harness the latest methods in biodiversity modeling. This field advances rapidly, and new techniques with promising applications for predicting NCP are still underutilized. Here, we argue that employing recent advances in biodiversity modeling can enhance the accuracy and scope of NCP maps and predictions. This enhancement will contribute significantly to the achievement of global objectives to preserve NCP, for both the present and an unpredictable future.

Predicting the Potential Distribution of the Szechwan Rat Snake (Euprepiophis perlacea) and Its Response to Climate Change in the Yingjing Area of the Giant Panda National Park

Climate change is a significant driver of changes in the distribution patterns of species and poses a threat to biodiversity, potentially resulting in species extinctions. Investigating the potential distribution of rare and endangered species is crucial for understanding their responses to climate change and for the conservation of biodiversity and ecosystem management. The Szechwan rat snake (Euprepiophis perlacea) is an endemic and endangered species co-distributed with giant pandas, and studying its potential distribution contributes to a better understanding of the distribution pattern of endangered species. In this study, we confirmed seven presence points of this species in the Yingjing Area of the Giant Panda National Park, and selected eleven key factors to predict the potential distribution of E. perlacea under current and future scenarios using MaxEnt models. Our study consistently achieved AUC values exceeding 0.79, meeting the precision requirements of the models. The results indicated that the high potential distribution area of E. perlacea is mainly located near Yunwu mountain and the giant panda rewilding and reintroduction base, accounting for approximately 12% of the protected area. Moreover, we identified the primary environmental factors influencing the distribution of E. perlacea as the distance from streams and the slope degree, with their contribution rates exceeding 41% and 31%, respectively. In comparison to the current scenario, the potential habitat range for E. perlacea did not show an overall reduction in the context of future climate scenarios. To ensure the long-term preservation of E. perlacea, it is advisable to validate its actual distribution based on the models' results. Particular attention should be given to safeguarding its core distribution areas and raising awareness among residents within the potential distribution range about the conservation of E. perlacea.

Biophysical models accurately characterize the thermal energetics of a small invasive passerine bird

Effective management of invasive species requires accurate predictions of their invasion potential in different environments. By considering species' physiological tolerances and requirements, biophysical mechanistic models can potentially deliver accurate predictions of where introduced species are likely to establish. Here, we evaluate biophysical model predictions of energy use by comparing them to experimentally obtained energy expenditure (EE) and thermoneutral zones (TNZs) for the common waxbill Estrilda astrild, a small-bodied avian invader. We show that biophysical models accurately predict TNZ and EE and that they perform better than traditional time-energy budget methods. Sensitivity analyses indicate that body temperature, metabolic rate, and feather characteristics were the most influential traits affecting model accuracy. This evaluation of common waxbill energetics represents a crucial step toward improved parameterization of biophysical models, eventually enabling accurate predictions of invasion risk for small (sub)tropical passerines.

Commonly collected thermal performance data can inform species distributions in a data-limited invader

Predicting potential distributions of species in new areas is challenging. Physiological data can improve interpretation of predicted distributions and can be used in directed distribution models. Nonnative species provide useful case studies. Panther chameleons (Furcifer pardalis) are native to Madagascar and have established populations in Florida, USA, but standard correlative distribution modeling predicts no suitable habitat for F. pardalis there. We evaluated commonly collected thermal traits- thermal performance, tolerance, and preference-of F. pardalis and the acclimatization potential of these traits during exposure to naturally-occurring environmental conditions in North Central Florida. Though we observed temperature-dependent thermal performance, chameleons maintained similar thermal limits, performance, and preferences across seasons, despite long-term exposure to cool temperatures. Using the physiological data collected, we developed distribution models that varied in restriction: time-dependent exposure near and below critical thermal minima, predicted activity windows, and predicted performance thresholds. Our application of commonly collected physiological data improved interpretations on potential distributions of F. pardalis, compared with correlative distribution modeling approaches that predicted no suitable area in Florida. These straightforward approaches can be applied to other species with existing physiological data or after brief experiments on a limited number of individuals, as demonstrated here.

Mechanistic models project bird invasions with accuracy

Invasive species pose a major threat to biodiversity and inflict massive economic costs. Effective management of bio-invasions depends on reliable predictions of areas at risk of invasion, as they allow early invader detection and rapid responses. Yet, considerable uncertainty remains as to how to predict best potential invasive distribution ranges. Using a set of mainly (sub)tropical birds introduced to Europe, we show that the true extent of the geographical area at risk of invasion can accurately be determined by using ecophysiological mechanistic models that quantify species' fundamental thermal niches. Potential invasive ranges are primarily constrained by functional traits related to body allometry and body temperature, metabolic rates, and feather insulation. Given their capacity to identify tolerable climates outside of contemporary realized species niches, mechanistic predictions are well suited for informing effective policy and management aimed at preventing the escalating impacts of invasive species.

Evolutionary rescue and geographic range shifts under climate change for global amphibians

By the end of this century, human-induced climate change and habitat loss may drastically reduce biodiversity, with expected effects on many amphibian lineages. One of these effects is the shift in the geographic distributions of species when tracking suitable climates. Here, we employ a macroecological approach to dynamically model geographic range shifts by coupling ecological niche models and eco-evolutionary mechanisms, aiming to assess the probability of evolutionary rescue (i.e., rapid adaptation) and dispersal under climate change. Evolutionary models estimated the probability of population persistence by adapting to changes in the temperature influenced by precipitation in the following decades, while compensating the fitness reduction and maintaining viable populations in the new climates. In addition, we evaluated emerging patterns of species richness and turnover at the assemblage level. Our approach was able to identify which amphibian populations among 7,193 species at the global scale could adapt to temperature changes or disperse into suitable regions in the future. Without evolutionary adaptation and dispersal, 47.7% of the species could go extinct until the year 2,100, whereas adding both processes will slightly decrease this extinction rate to 36.5%. Although adaptation to climate is possible for populations in about 25.7% of species, evolutionary rescue is the only possibility to avoid extinction in 4.2% of them. Dispersal will allow geographic range shifts for 49.7% of species, but only 6.5% may avoid extinction by reaching climatically suitable environments. This reconfiguration of species distributions and their persistence creates new assemblage-level patterns at the local scale. Temporal beta-diversity across the globe showed relatively low levels of species turnover, mainly due to the loss of species. Despite limitations with obtaining data, our approach provides more realistic assessments of species responses to ongoing climate changes. It shows that, although dispersal and evolutionary rescue may attenuate species losses, they are not enough to avoid a significant reduction of species’ geographic ranges in the future. Actions that guarantee a higher potential of adaptation (e.g., genetic diversity through larger population sizes) and increased connectivity for species dispersion to track suitable climates become essential, increasing the resilience of biodiversity to climate change.

Microbial Networks Reveal the Structure of Water Microbial Communities in Kalamaili Mountain Ungulate Nature Reserve

Water microorganisms contribute to the key components of ecosystems in dryland waters, which are extremely important for wildlife. However, the distribution patterns of water microbes across different basal water sources are still largely unknown. This study was conducted to compare microorganisms in the water bodies of different types of water sources in the Kalamaili Mountain Ungulate Nature Reserve in China. Bioinformatic analysis revealed that the undirected microbial co-existence network consisted of 15 main modules referring to different water sources, which indicated specific molecular co-existence relationships. It was found that the most dominant phyla (namely Proteobacteria, Patescibacteria, Firmicutes, Bacteroidota, and Actinobacteriota) of the molecular ecological network shared the same structures as the microbial community, which justified the construction of the network via a random network formation. Principal coordinate analysis (PCoA) based on Bray–Curtis distances revealed that there were still considerable variations among different habitats, showing separate sample clusters. Additionally, the different topological roles of subnetworks trimmed to a uniform size indicated different co-existence patterns in the microbiome. The artificially recharged water from concrete pond substrate (ARC) subnetworks had a relatively discrete co-occurrence, while the natural water sources (NRE) and artificially recharged water from earthen pond substrate (ARE) groups were more compact with giant modules. The NRE and ARE groups were also richer in microbial composition and had a higher number of species with low abundance. Consequently, concrete substrates may contribute to dysfunction in water microbiomes. Moreover, the functional diversity of the NRE and ARE groups is due to more intra-module connections and more inter-module connections, indirectly leading to a stable function resilient to external environmental influences. In conclusion, the microecology of the NRE was more stable than that of the concrete substrate, and artificial transportation had less effect on the microbial community.