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Aim: The capacity for poleward range expansions beyond the tropics in corals hinges on ecophysiological constraints and resulting responses to climatic variability. We aimed to determine how future warming will affect coral habitat suitability at the poleward range edges of these foundational species in the Northwest Pacific. Location: Northwest Pacific. Methods: We generated models integrating thermal physiological constraints of corals adapted to extreme seasonality in Hong Kong, specifically the minimum annual temperature and the proportion of time annually spent at seasonal extremes. With these models, we projected habitat suitability for five coral species under current and future climatic conditions across the Northwest Pacific. Results: Climate model projections reveal an easing of thermal constraints on the leading‐edge of coral ecophysiological limits with an expansion of thermally suitable habitat poleward by 2°–7° in latitude depending on the coral species and model considered. We also highlight a potential divergence of present and future thermal regimes that may lead to a mismatch in suitability for corals currently inhabiting high latitude reefs. Main Conclusions: Understanding the thermal constraints on coral distributions and defining the potential range of corals under climate change is critical for adaptive management that focuses on coral conservation and ensuring ecosystem function of existing subtropical and temperate ecosystems. [ABSTRACT FROM AUTHOR]

Aims: Climate change is expected to have profound effects on species' distributions into the future. Freshwater fishes, an important component of freshwater ecosystems, are no exception. Here, we project shifts in suitable conditions for Australian freshwater fishes under different climate change scenarios to identify species that may experience significant declines in habitat suitability. Location: Australia. Methods: We use MAXENT bioclimatic models to estimate the effect of climate change on the suitable conditions for 154 species of Australian freshwater fishes, of which 109 are endemic and 29 are threatened with extinction. Suitable conditions for freshwater fish species are modelled using three different Earth System climate models (ESMs) under two different emission scenarios to the year 2100. For each species, we examine potential geographic shifts in the distribution of suitable conditions from the present day to 2100 and quantify how habitat suitability may change at currently occupied sites by the end of this century. Results: Broadscale poleward shifts in suitable conditions are projected for Australian freshwater fishes by an average of up to 0.38° (~180 km) across all species, depending on the emission scenario. Considerable loss of suitable conditions is forecast to occur within currently recognized distributional extents by 2100, with a mean projected loss of up to 17.5% across species. Predicted geographic range shifts and declines are larger under a high‐emission scenario. Threatened species are projected to be more adversely affected than nonthreatened species. Main Conclusions: Our models identify species and geographic regions that may be vulnerable to climate change, enabling freshwater fish conservation into the future. [ABSTRACT FROM AUTHOR]

Aim: Many species are adapted to a particular fire regime and major deviations from that regime may lead to localized extinction. Here, we quantify immaturity risks to an obligate‐seeder forest tree using an objectively designed climate model ensemble and a probabilistic fire regime simulator to predict future fire regimes. Location: Alpine ash (Eucalyptus delegatensis) distribution, Victoria, south‐eastern Australia. Methods: We used a fire regime model (FROST) with six climate projections from a climate model ensemble across 3.7 million hectares of native forest and non‐native vegetation to examine immaturity risks to obligate‐seeder forests dominated by alpine ash (Eucalyptus delegatensis), which has a primary juvenile period of approximately 20 years. Our models incorporated current and future projected climate including fuel feedbacks to simulate fire regimes over 100 years. We then used Random Forest modelling to evaluate which spatial characteristics of the landscape were associated with high immaturity risks to alpine ash forest patches. Results: Significant shifts to the fire regime were predicted under all six future climate projections. Increases in both wildfire extent (total area burnt, area burnt at high intensity) and frequency were predicted with an average increase of up to 110 hectares burnt annually by short‐interval fires (i.e., within the expected minimum time to reproductive maturity). The immaturity risk posed by short‐interval fires to alpine ash forest patches was well explained by Random Forest models and varied with both location and environmental variables. Main conclusions: Alpine ash forests are predicted to be burned at greater intensities and shorter intervals under future fire regimes. About 67% of the current alpine ash distribution was predicted to be at some level of immaturity risk over the 100‐year modelling period, with the greatest risks to those patches located on the periphery of the current distribution, closer to roads or surrounded by a drier landscape at lower elevations. [ABSTRACT FROM AUTHOR]

Aim: To assess the distributional patterns of fruit‐feeding butterfly species richness in Atlantic Forest (AF) based on stack species distribution models (SSDM); to evaluate the relative contribution of climate and landscape in the patterns of butterfly species richness; and to recommend conservation guidelines for AF regions based on the obtained results. Location: Brazilian Atlantic Forest. Methods: We used SSDMs to generate potential distribution maps of butterfly species richness in AF. Our dataset comprises 7,062 records of 279 species, distributed across 122 local communities. We built richness maps based on climate and landscape models and analysed them separately to understand their contribution to the pattern of richness distribution. Then, we combined both models to build a consensus map. Finally, we designed specific conservation strategies based on richness categories distributed on the consensus map. Results: The regions with high‐predicted species richness for both climate and landscape models supported the main endemism locations described for other AF taxa in previous studies. Both models predicted intermediate values of species richness for most regions, but the patterns of richness distribution were not fully congruent. High species richness based on landscape metrics was frequently concentrated in the south. Furthermore, locations suitable for high species richness according to climate are near to the endemism centres, but also to dense urban centres, highlighting the potential impacts of the landscape modification on butterfly species richness. Main conclusions: The distribution of fruit‐feeding butterfly species richness and endemism reflect the classic division of AF in different sub‐regions according to the endemism centres proposed by previous authors for other taxa. The availability of forested habitats seems to be a determining factor for the maintenance of high species richness in AF. Therefore, the loss of natural forest remnants due to landscape modification is the primary threat to butterfly diversity. [ABSTRACT FROM AUTHOR]

Aim: Lanternfish (Myctophidae) are one of the most abundant and ecologically important families of pelagic teleosts, yet how these species will respond to climate change is unclear, especially within polar regions. The aim of this study was to predict the impact of climate change on the distribution of Southern Ocean lanternfish and to relate these predicted responses to species traits. Location: Circumpolar, 35–75°S. Methods: We used MaxEnt ecological niche models to estimate the present and predict the future distributions of 10 biomass‐dominant lanternfish species throughout the region. Future conditions were simulated using eight climate models, in both stabilizing (RCP 4.5) and rising (RCP 8.5) emission scenarios, for the time periods 2006–2055 and 2050–2099. Species responses were then related to their realized thermal niche (i.e., thermal tolerance range), latitudinal preference and body size. Results: Despite large variation between climate model simulations, all but one species are consistently predicted to undergo a poleward distribution shift. Species show contrasting projections relating to a gain or loss of suitable habitat which was best explained by their thermal niche. Overall, high‐latitude Antarctic species were found to have narrower thermal niches and a higher likelihood of losing habitat than sub‐Antarctic species. Main conclusions: The direction of a species response was dependent on the interplay between physiology (realized thermal niche) and biogeography (latitudinal preference). Antarctic species with restricted thermal niches and limited available habitat in which to disperse will be the most vulnerable group of Southern Ocean lanternfish in the face of climate change. Predicted range shifts may alter the size structure of the myctophid community as smaller, sub‐Antarctic species reach further south. This could have implications for trophic interactions and thus the wider Southern Ocean ecosystem. [ABSTRACT FROM AUTHOR]

Aim: The trait‐based vulnerability assessment (TVA) uses Boolean rules to assess species sensitivity, adaptive capacity and exposure to climate change to identify those that are climate‐change vulnerable. The protocol is being increasingly used to assess climate‐change impacts to a diversity of taxa, as it requires fewer data compared to niche and mechanistic models. However, uncertainty in TVA results remains unevaluated. We present the first quantitative investigation of the impacts of uncertainty on TVA, using global freshwater crayfish (574 species) as a representative data‐poor taxon. Location: Global. Methods: To assess uncertainty in trait selection, we measured the completeness of information for each trait and how these contributed to the number of vulnerable species. To explore the sensitivity of TVA outcomes to arbitrary threshold selection, we randomly scored 25% species as high for quantitative traits and compared the results to the standard TVA. To investigate uncertainty in climate model selections, we tested the TVA using 66 alternative global climate scenarios. Results: Given the structural rules used in TVA, as more traits are included in the protocol, more species are identified as vulnerable to climate change. Some traits also have more dominant contributions. Species vulnerability was relatively robust to arbitrary thresholds in quantitative trait variables. The number (79–156) and identity of vulnerable species varied depending on which climate scenario was selected. Ensemble means of climate models identified fewer vulnerable species, potentially softening the extremes of individual climate models. Main conclusions: Assessors applying TVA across taxa and geographical scales should use ecological thresholds for quantitative traits, where possible; most importantly perform sensitivity analyses, including (a) critically assessing assumptions and correlations underpinning the selection of traits in different dimensions; and (b) capturing variability among climate‐change models. Further research is required to fill data gaps that improve the robustness of TVA. [ABSTRACT FROM AUTHOR]

Aim: Predictions of future suitable habitat for plant species with climate change are known to be affected by uncertainty associated with statistical approaches, climate models and occurrence records. However, life history characteristics related to dispersal and establishment processes as well as sensitivity to barriers created by land‐use may also play important roles in shaping future distributions with climate change. We compared the uncertainty in predicted distributions associated with climate projections to uncertainty associated with species interactions related to dispersal and establishment and land‐use barriers with four common animal‐dispersed tree species in pinyon–juniper woodlands in the western United States, a region experiencing increasing fragmentation due to land‐use. Location: Western USA. Methods: We compared the effects of life history characteristics related to species interactions (long‐distance dispersal and facilitation), land‐use fragmentation and variation in climate projections on species distributions with climate change using a simulation model. We evaluated the impacts of these factors on three characteristics of species distributions, area occupied, range size, and distance between patches, across four 30‐year intervals centred on 2020, 2040, 2060 and 2080. Results: We found that uncertainty associated with climate projections and the potential effects of facilitation on establishment had the greatest impact in distribution characteristics. The effects of all factors varied by species, despite their overlapping initial distributions and relatively similar dispersal traits, highlighting the impact of life history characteristics on model outcomes. Main conclusions: These results suggest that assessments of species future range shifts and vulnerability to climate change should incorporate land‐use barriers and life history traits related to dispersal and establishment, particularly for species with strong facilitative interactions. [ABSTRACT FROM AUTHOR]

Abstract: Aim: This study presents a bioclimate modelling approach, using responses to extreme climate events, rather than historical distributional associations, to project future species vulnerability and refugia. We aim to illustrate the compounding effects of groundwater loss and climate on species vulnerability. Location: California, USA. Methods: As a case study, we used the 2012–2015 California drought and resulting extensive dieback of blue oak (Quercus douglasii). We used aerial dieback surveys, downscaled climate data and subsurface water change data to develop boosted regression tree models identifying key thresholds associated with dieback throughout the blue oak distribution. We (1) combined observed dieback–climatic threshold relationships with climate futures to anticipate future areas of vulnerability and (2) used satellite‐derived measurements of subsurface water loss in drought/dieback modelling to capture the mediating effect of groundwater on species response to climatic drought. Results: A model including climate, climate anomalies and subsurface water change explained 46% of the variability in dieback. Precipitation in 2015 and subsurface water change accounted for 62.6% of the modelled probability of dieback. We found an interaction between precipitation and subsurface water in which dieback probability increased with low precipitation and subsurface water loss. The relationship between precipitation and dieback was nonlinear, with 99% of dieback occurring in areas that received <363 mm precipitation. Based on a MIROC_rcp85 future climate scenario, relative to historical conditions, 13% of the blue oak distribution is predicted to experience more frequent years below this precipitation threshold by mid‐century and 81% by end of century. Main conclusions: As ongoing climate change and extreme events impact ecological processes, the identification of thresholds associated with observed dieback may be combined with climate futures to help identify vulnerable populations and refugia and prioritize climate change‐related conservation efforts. [ABSTRACT FROM AUTHOR]

Understanding and predicting complex biological systems are best accomplished through the synthesis and integration of information across relevant spatial, temporal and thematic scales. We propose that mechanistic transport models, which integrate atmospheric turbulence with information on relevant biological attributes, can effectively incorporate key elements of aerial transport processes at scales ranging from a few centimetres and fractions of seconds, to hundreds of kilometres and decades. This capability of mechanistic models is critically important for modelling the flow of organisms through the atmosphere because diverse aerial transport processes— such as pathogen spread, seed dispersal, spider ballooning and bird migration— are sensitive to the details of small-scale short-term turbulent deviations from the mean airflow. At the same time, all these processes are strongly influenced by the typical larger-scale variation in landscape structure, through its effects on wind flow patterns. We therefore highlight the useful coupling of detailed atmospheric models such as large eddy simulations (LES), which can provide a high-resolution description of turbulent airflow, with regional atmospheric models, which can capture the effects of landscape heterogeneity at various scales. Further progress in computational fluid dynamics (CFD) will enable rigorous exploration of transport processes in heterogeneous landscapes. [ABSTRACT FROM AUTHOR]