The projected effect on insects, vertebrates, and plants of limiting global warming to 1.5°C rather than 2°C

Radical Response: Effects of Heat Stress-Induced Oxidative Stress on Lipid Metabolism in the Avian Liver

Lipid metabolism in avian species places unique demands on the liver in comparison to most mammals. The avian liver synthesizes the vast majority of fatty acids that provide energy and support cell membrane synthesis throughout the bird. Egg production intensifies demands to the liver as hepatic lipids are needed to create the yolk. The enzymatic reactions that underlie de novo lipogenesis are energetically demanding and require a precise balance of vitamins and cofactors to proceed efficiently. External stressors such as overnutrition or nutrient deficiency can disrupt this balance and compromise the liver’s ability to support metabolic needs. Heat stress is an increasingly prevalent environmental factor that impairs lipid metabolism in the avian liver. The effects of heat stress-induced oxidative stress on hepatic lipid metabolism are of particular concern in modern commercial chickens due to the threat to global poultry production. Chickens are highly vulnerable to heat stress because of their limited capacity to dissipate heat, high metabolic activity, high internal body temperature, and narrow zone of thermal tolerance. Modern lines of both broiler (meat-type) and layer (egg-type) chickens are especially sensitive to heat stress because of the high rates of mitochondrial metabolism. While this oxidative metabolism supports growth and egg production, it also yields oxidative stress that can damage mitochondria, cellular membranes and proteins, making the birds more vulnerable to other stressors in the environment. Studies to date indicate that oxidative and heat stress interact to disrupt hepatic lipid metabolism and compromise performance and well-being in both broilers and layers. The purpose of this review is to summarize the impact of heat stress-induced oxidative stress on lipid metabolism in the avian liver. Recent advances that shed light on molecular mechanisms and potential nutritional/managerial strategies to counteract the negative effects of heat stress-induced oxidative stress to the avian liver are also integrated.

Current distribution and voltinism of the brown marmorated stink bug, Halyomorpha halys, in Switzerland and its response to climate change using a high-resolution CLIMEX model

Climate change can alter the habitat suitability of invasive species and promote their establishment. The highly polyphagous brown marmorated stinkbug, Halyomorpha halys Stål (Hemiptera: Pentatomidae), is native to East Asia and invasive in Europe and North America, damaging a wide variety of fruit and vegetable crops. In Switzerland, crop damage and increasing populations have been observed since 2017 and related to increasing temperatures. We studied the climatic suitability, population growth, and the number of generations under present and future climate conditions for H. halys in Switzerland, using a modified version of the bioclimatic model package CLIMEX. To address the high topographic variability in Switzerland, model simulations were based on climate data of high spatial resolution (approx. 2 km), which significantly increased their explanatory power, and identified many more climatically suitable areas in comparison to previous models. The validation of the CLIMEX model using observational records collected in a citizen science initiative between 2004 and 2019 revealed that more than 15 years after its accidental introduction, H. halys has colonised nearly all bioclimatic suitable areas in Switzerland and there is limited potential for range expansion into new areas under present climate conditions. Simulations with climate change scenarios suggest an extensive range expansion into higher altitudes, an increase in generations per year, an earlier start of H. halys activity in spring and a prolonged period for nymphs to complete development in autumn. A permanent shift from one to two generations per year and the associated population growth of H. halys may result in increasing crop damages in Switzerland. These results highlight the need for monitoring the spread and population development in the north-western part of Switzerland and higher altitudes of the valleys of the south.

Identifying island safe havens to prevent the extinction of the World's largest lizard from global warming

The Komodo dragon (Varanus komodoensis) is an endangered, island‐endemic species with a naturally restricted distribution. Despite this, no previous studies have attempted to predict the effects of climate change on this iconic species. We used extensive Komodo dragon monitoring data, climate, and sea‐level change projections to build spatially explicit demographic models for the Komodo dragon. These models project the species’ future range and abundance under multiple climate change scenarios. We ran over one million model simulations with varying model parameters, enabling us to incorporate uncertainty introduced from three main sources: (a) structure of global climate models, (b) choice of greenhouse gas emission trajectories, and (c) estimates of Komodo dragon demographic parameters. Our models predict a reduction in range‐wide Komodo dragon habitat of 8%–87% by 2050, leading to a decrease in habitat patch occupancy of 25%–97% and declines of 27%–99% in abundance across the species' range. We show that the risk of extirpation on the two largest protected islands in Komodo National Park (Rinca and Komodo) was lower than other island populations, providing important safe havens for Komodo dragons under global warming. Given the severity and rate of the predicted changes to Komodo dragon habitat patch occupancy (a proxy for area of occupancy) and abundance, urgent conservation actions are required to avoid risk of extinction. These should, as a priority, be focused on managing habitat on the islands of Komodo and Rinca, reflecting these islands’ status as important refuges for the species in a warming world. Variability in our model projections highlights the importance of accounting for uncertainties in demographic and environmental parameters, structural assumptions of global climate models, and greenhouse gas emission scenarios when simulating species metapopulation dynamics under climate change.

Approximate calculations of the net economic impact of global warming mitigation targets under heightened damage estimates

Efforts to mitigate global warming are often justified through calculations of the economic damages that may occur absent mitigation. The earliest such damage estimates were speculative mathematical representations, but some more recent studies provide empirical estimates of damages on economic growth that accumulate over time and result in larger damages than those estimated previously. These heightened damage estimates have been used to suggest that limiting global warming this century to 1.5 °C avoids tens of trillions of 2010 US$ in damage to gross world product relative to limiting global warming to 2.0 °C. However, in order to estimate the net effect on gross world product, mitigation costs associated with decarbonizing the world’s energy systems must be subtracted from the benefits of avoided damages. Here, we follow previous work to parameterize the aforementioned heightened damage estimates into a schematic global climate-economy model (DICE) so that they can be weighed against mainstream estimates of mitigation costs in a unified framework. We investigate the net effect of mitigation on gross world product through finite time horizons under a spectrum of exogenously defined levels of mitigation stringency. We find that even under heightened damage estimates, the additional mitigation costs of limiting global warming to 1.5 °C (relative to 2.0 °C) are higher than the additional avoided damages this century under most parameter combinations considered. Specifically, using our central parameter values, limiting global warming to 1.5 °C results in a net loss of gross world product of roughly forty trillion US$ relative to 2 °C and achieving either 1.5 °C or 2.0 °C require a net sacrifice of gross world product, relative to a no-mitigation case, though 2100 with a 3%/year discount rate. However, the benefits of more stringent mitigation accumulate over time and our calculations indicate that stabilizing warming at 1.5 °C or 2.0 °C by 2100 would eventually confer net benefits of thousands of trillions of US$ in gross world product by 2300. The results emphasize the temporal asymmetry between the costs of mitigation and benefits of avoided damages from climate change and thus the long timeframe for which climate change mitigation investment pays off.

Arthropods and climate change - arctic challenges and opportunities

The harsh climate, limited human infrastructures, and basic autecological knowledge gaps represent substantial challenges for studying arthropods in the Arctic. At the same time, rapid climate change, low species diversity, and strong collaborative networks provide unique and underexploited Arctic opportunities for understanding species responses to environmental change and testing ecological theory. Here, I provide an overview of individual, population, and ecosystem level responses to climate change in Arctic arthropods. I focus on thermal performance, life history variation, population dynamics, community composition, diversity, and biotic interactions. The species-poor Arctic represents a unique opportunity for testing novel, automated arthropod monitoring methods. The Arctic can also potentially provide insights to further understand and mitigate the effects of climate change on arthropods worldwide.

Investigating effect of climate warming on the population declines of Sympetrum frequens during the 1990s in three regions in Japan

Climate warming is of concern as a key factor in the worldwide decline in insect populations. In Japan, numbers of a common dragonfly in rice paddy fields, Sympetrum frequens, decreased sharply in the 1990s. Because S. frequens migrates to cooler mountains in summer, climate warming has been suggested as one of the main causes of the population decline in addition to agronomic factors. Here, we analysed the relation between summer temperatures and population densities of S. frequens and the related S. infuscatum, which does not migrate to mountains in summer, using published population monitoring data and temperature data from three regions (Toyama, Ishikawa, and Shizuoka) in Japan. Decadal differences in summer temperatures lay within the range of fluctuations among years, suggesting that an increase in summer temperatures cannot explain the past sharp population declines. However, regression analyses using monitoring data from Toyama showed that the population dynamics of both species in autumn are negatively correlated with summer temperatures in the same year. These results suggest that high temperatures in summer directly affect adult mortality to an extent that results in a decrease in population growth.

Remote Sensing Applications in Monitoring of Protected Areas

Protected areas (PAs) have been established worldwide for achieving long-term goals in the conservation of nature with the associated ecosystem services and cultural values. Globally, 15% of the world’s terrestrial lands and inland waters, excluding Antarctica, are designated as PAs. About 4.12% of the global ocean and 10.2% of coastal and marine areas under national jurisdiction are set as marine protected areas (MPAs). Protected lands and waters serve as the fundamental building blocks of virtually all national and international conservation strategies, supported by governments and international institutions. Some of the PAs are the only places that contain undisturbed landscape, seascape and ecosystems on the planet Earth. With intensified impacts from climate and environmental change, PAs have become more important to serve as indicators of ecosystem status and functions. Earth’s remaining wilderness areas are becoming increasingly important buffers against changing conditions. The development of remote sensing platforms and sensors and the improvement in science and technology provide crucial support for the monitoring and management of PAs across the world. In this editorial paper, we reviewed research developments using state-of-the-art remote sensing technologies, discussed the challenges of remote sensing applications in the inventory, monitoring, management and governance of PAs and summarized the highlights of the articles published in this Special Issue.

Comparing and synthesizing quantitative distribution models and qualitative vulnerability assessments to project marine species distributions under climate change

Species distribution shifts are a widely reported biological consequence of climate-driven warming across marine ecosystems, creating ecological and social challenges. To meet these challenges and inform management decisions, we need accurate projections of species distributions. Quantitative species distribution models (SDMs) are routinely used to make these projections, while qualitative climate change vulnerability assessments are becoming more common. We constructed SDMs, compared SDM projections to expectations from a qualitative expert climate change vulnerability assessment, and developed a novel approach for combining the two methods to project the distribution and relative biomass of 49 marine species in the Northeast Shelf Large Marine Ecosystem under a “business as usual” climate change scenario. A forecasting experiment using SDMs highlighted their ability to capture relative biomass patterns fairly well (mean Pearson’s correlation coefficient between predicted and observed biomass = 0.24, range = 0–0.6) and pointed to areas needing improvement, including reducing prediction error and better capturing fine-scale spatial variability. SDM projections suggest the region will undergo considerable biological changes, especially in the Gulf of Maine, where commercially-important groundfish and traditional forage species are expected to decline as coastal fish species and warmer-water forage species historically found in the southern New England/Mid-Atlantic Bight area increase. The SDM projections only occasionally aligned with vulnerability assessment expectations, with agreement more common for species with adult mobility and population growth rates that showed low sensitivity to climate change. Although our blended approach tried to build from the strengths of each method, it had no noticeable improvement in predictive ability over SDMs. This work rigorously evaluates the predictive ability of SDMs, quantifies expected species distribution shifts under future climate conditions, and tests a new approach for integrating SDMs and vulnerability assessments to help address the complex challenges arising from climate-driven species distribution shifts.

The projected timing of abrupt ecological disruption from climate change

As anthropogenic climate change continues the risks to biodiversity will increase over time, with future projections indicating that a potentially catastrophic loss of global biodiversity is on the horizon^1-3. However, our understanding of when and how abruptly this climate-driven disruption of biodiversity will occur is limited because biodiversity forecasts typically focus on individual snapshots of the future. Here we use annual projections (from 1850 to 2100) of temperature and precipitation across the ranges of more than 30,000 marine and terrestrial species to estimate the timing of their exposure to potentially dangerous climate conditions. We project that future disruption of ecological assemblages as a result of climate change will be abrupt, because within any given ecological assemblage the exposure of most species to climate conditions beyond their realized niche limits occurs almost simultaneously. Under a high-emissions scenario (representative concentration pathway (RCP) 8.5), such abrupt exposure events begin before 2030 in tropical oceans and spread to tropical forests and higher latitudes by 2050. If global warming is kept below 2 °C, less than 2% of assemblages globally are projected to undergo abrupt exposure events of more than 20% of their constituent species; however, the risk accelerates with the magnitude of warming, threatening 15% of assemblages at 4 °C, with similar levels of risk in protected and unprotected areas. These results highlight the impending risk of sudden and severe biodiversity losses from climate change and provide a framework for predicting both when and where these events may occur.

Developing a temporally accurate air temperature dataset for Mainland China

Spatially continuous satellite data have been widely used to estimate monthly air temperature (Ta). However, it is still not clear whether the estimated monthly Ta is temporally consistent with observed Ta or not. In this study, the accuracies of interannual variations and temporal trends in estimated monthly Ta were systematically analyzed for Mainland China during 2001-2018. The differences in accuracy among five ways to input data into the model were investigated. The Cubist algorithm and ten variables were used to estimate monthly Ta. It was found that inputting data for the same month into the model can generate more accurate results than inputting all data into the model. Using temporal variables (i.e., month and year) can significantly increase the accuracy of estimated Ta. These results can be explained by different relationships between Ta and auxiliary variables that appear at different times. Thus, using temporal variables can help distinguish between different relationships and improve accuracy levels of the estimated Ta. When applying the best method (inputting data for the same month into the model and using the year as a temporal variable), the coefficient of determination (R²) of estimated monthly mean Ta, interannual variations in monthly mean Ta and temporal trends in monthly mean Ta were recorded as 0.997, 0.731 and 0.848, respectively. The root mean squared errors (RMSEs) of estimated monthly mean Ta, interannual variations in monthly mean Ta and temporal trends in monthly mean Ta were recorded as 0.629 °C, 0.593 °C and 0.201 °C/decade, respectively. An accurate, national coverage, 1 km spatial resolution and long time series (2001-2018) monthly mean, maximum and minimum Ta dataset was finally developed. The dataset can be of great use to many fields such as climatology, hydrology and ecology.

The Paris Agreement objectives will likely halt future declines of emperor penguins

The Paris Agreement is a multinational initiative to combat climate change by keeping a global temperature increase in this century to 2°C above preindustrial levels while pursuing efforts to limit the increase to 1.5°C. Until recently, ensembles of coupled climate simulations producing temporal dynamics of climate en route to stable global mean temperature at 1.5 and 2°C above preindustrial levels were not available. Hence, the few studies that have assessed the ecological impact of the Paris Agreement used ad-hoc approaches. The development of new specific mitigation climate simulations now provides an unprecedented opportunity to inform ecological impact assessments. Here we project the dynamics of all known emperor penguin (Aptenodytes forsteri) colonies under new climate change scenarios meeting the Paris Agreement objectives using a climate-dependent-metapopulation model. Our model includes various dispersal behaviors so that penguins could modulate climate effects through movement and habitat selection. Under business-as-usual greenhouse gas emissions, we show that 80% of the colonies are projected to be quasiextinct by 2100, thus the total abundance of emperor penguins is projected to decline by at least 81% relative to its initial size, regardless of dispersal abilities. In contrast, if the Paris Agreement objectives are met, viable emperor penguin refuges will exist in Antarctica, and only 19% and 31% colonies are projected to be quasiextinct by 2100 under the Paris 1.5 and 2 climate scenarios respectively. As a result, the global population is projected to decline by at least by 31% under Paris 1.5 and 44% under Paris 2. However, population growth rates stabilize in 2060 such that the global population will be only declining at 0.07% under Paris 1.5 and 0.34% under Paris 2, thereby halting the global population decline. Hence, global climate policy has a larger capacity to safeguard the future of emperor penguins than their intrinsic dispersal abilities.

Recent responses to climate change reveal the drivers of species extinction and survival

Climate change may be a major threat to biodiversity in the next 100 years. Although there has been important work on mechanisms of decline in some species, it generally remains unclear which changes in climate actually cause extinctions, and how many species will likely be lost. Here, we identify the specific changes in climate that are associated with the widespread local extinctions that have already occurred. We then use this information to predict the extent of future biodiversity loss and to identify which processes may forestall extinction. We used data from surveys of 538 plant and animal species over time, 44% of which have already had local extinctions at one or more sites. We found that locations with local extinctions had larger and faster changes in hottest yearly temperatures than those without. Surprisingly, sites with local extinctions had significantly smaller changes in mean annual temperatures, despite the widespread use of mean annual temperatures as proxies for overall climate change. Based on their past rates of dispersal, we estimate that 57-70% of these 538 species will not disperse quickly enough to avoid extinction. However, we show that niche shifts appear to be far more important for avoiding extinction than dispersal, although most studies focus only on dispersal. Specifically, considering both dispersal and niche shifts, we project that only 16-30% of these 538 species may go extinct by 2070. Overall, our results help identify the specific climatic changes that cause extinction and the processes that may help species to survive.

Impacts of current and future large dams on the geographic range connectivity of freshwater fish worldwide

Freshwater fish are highly threatened by dams that disrupt the longitudinal connectivity of rivers and may consequently impede fish movements to feeding and spawning grounds. In a comprehensive global analysis covering ∼10,000 freshwater fish species and ∼40,000 existing large dams we identified the most disconnected geographical ranges for species in the United States, Europe, South Africa, India, and China. The completion of near-future plans for ∼3,700 large hydropower dams will greatly increase habitat fragmentation in (sub)tropical river basins, where many livelihoods depend on inland fisheries. Our assessment can support infrastructure planning on multiple scales and assist in setting conservation priorities for species and basins at risk.

Dams contribute to water security, energy supply, and flood protection but also fragment habitats of freshwater species. Yet, a global species-level assessment of dam-induced fragmentation is lacking. Here, we assessed the degree of fragmentation of the occurrence ranges of ∼10,000 lotic fish species worldwide due to ∼40,000 existing large dams and ∼3,700 additional future large hydropower dams. Per river basin, we quantified a connectivity index (CI) for each fish species by combining its occurrence range with a high-resolution hydrography and the locations of the dams. Ranges of nondiadromous fish species were more fragmented (less connected) (CI = 73 ± 28%; mean ± SD) than ranges of diadromous species (CI = 86 ± 19%). Current levels of fragmentation were highest in the United States, Europe, South Africa, India, and China. Increases in fragmentation due to future dams were especially high in the tropics, with declines in CI of ∼20 to 40 percentage points on average across the species in the Amazon, Niger, Congo, Salween, and Mekong basins. Our assessment can guide river management at multiple scales and in various domains, including strategic hydropower planning, identification of species and basins at risk, and prioritization of restoration measures, such as dam removal and construction of fish bypasses.

Insect Declines in the Anthropocene

Insect declines are being reported worldwide for flying, ground, and aquatic lineages. Most reports come from western and northern Europe, where the insect fauna is well-studied and there are considerable demographic data for many taxonomically disparate lineages. Additional cases of faunal losses have been noted from Asia, North America, the Arctic, the Neotropics, and elsewhere. While this review addresses both species loss and population declines, its emphasis is on the latter. Declines of abundant species can be especially worrisome, given that they anchor trophic interactions and shoulder many of the essential ecosystem services of their respective communities. A review of the factors believed to be responsible for observed collapses and those perceived to be especially threatening to insects form the core of this treatment. In addition to widely recognized threats to insect biodiversity, e.g., habitat destruction, agricultural intensification (including pesticide use), climate change, and invasive species, this assessment highlights a few less commonly considered factors such as atmospheric nitrification from the burning of fossil fuels and the effects of droughts and changing precipitation patterns. Because the geographic extent and magnitude of insect declines are largely unknown, there is an urgent need for monitoring efforts, especially across ecological gradients, which will help to identify important causal factors in declines. This review also considers the status of vertebrate insectivores, reporting bias, challenges inherent in collecting and interpreting insect demographic data, and cases of increasing insect abundance.

Biodiversity can benefit from climate stabilization despite adverse side effects of land-based mitigation

Limiting the magnitude of climate change via stringent greenhouse gas (GHG) mitigation is necessary to prevent further biodiversity loss. However, some strategies to mitigate GHG emission involve greater land-based mitigation efforts, which may cause biodiversity loss from land-use changes. Here we estimate how climate and land-based mitigation efforts interact with global biodiversity by using an integrated assessment model framework to project potential habitat for five major taxonomic groups. We find that stringent GHG mitigation can generally bring a net benefit to global biodiversity even if land-based mitigation is adopted. This trend is strengthened in the latter half of this century. In contrast, some regions projected to experience much growth in land-based mitigation efforts (i.e., Europe and Oceania) are expected to suffer biodiversity loss. Our results support the enactment of stringent GHG mitigation policies in terms of biodiversity. To conserve local biodiversity, however, these policies must be carefully designed in conjunction with land-use regulations and societal transformation in order to minimize the conversion of natural habitats.

Greenhouse gas mitigation can involve land-use changes that alter the habitat available for wildlife. Here, Ohashi et al. perform an integrated assessment showing that climate mitigation can be beneficial for global biodiversity but may entail local biodiversity losses where land-based mitigation is implemented.

Selection of Reference Genes for Normalization of Real-Time PCR Data in Calliptamus italicus (Orthoptera: Acrididae) Under Different Temperature Conditions

Global warming has dominated worldwide climate change trends, and adaptability to high temperatures is the main factor underlying the spread of the pest Calliptamus italicus in Xinjiang Province, China. However, knowledge about the molecular mechanisms responsible for this adaptability and other related biological properties of C. italicus remain relatively unclear. Real-time quantitative polymerase chain reaction (RT-qPCR) is a key tool for gene expression analysis associated with various biological processes. Reference genes are necessary for normalizing gene expression levels across samples taken from specific experimental conditions. In this study, transcript level of five genes (GAPDH, 18S, TUB, ACT, and EF1α), commonly used as reference genes, were evaluated under nine different temperatures (27, 30, 33, 36, 39, 42, 45, 48, and 51°C) to assess their expression stability and further select the most suitable to be used on normalization of target gene expression data. Gene expression profiles were analyzed using geNorm, NormFinder, and BestKeeper software packages. The combined results demonstrated that the best-ranked reference genes for C. italicus are EF1α, GAPDH, and ACT under different thermal stress conditions. This is the first study that assesses gene expression analysis across a range of temperatures to select the most appropriate reference genes for RT-qPCR data normalization in C. italicus. These results should assist target gene expression analysis associated with heat stress in C. italicus.

The effect of global change on mosquito-borne disease

More than 80% of the global population is at risk of a vector-borne disease, with mosquito-borne diseases being the largest contributor to human vector-borne disease burden. Although many global processes, such as land-use and socioeconomic change, are thought to affect mosquito-borne disease dynamics, research to date has strongly focused on the role of climate change. Here, we show, through a review of contemporary modelling studies, that no consensus on how future changes in climatic conditions will impact mosquito-borne diseases exists, possibly due to interacting effects of other global change processes, which are often excluded from analyses. We conclude that research should not focus solely on the role of climate change but instead consider growing evidence for additional factors that modulate disease risk. Furthermore, future research should adopt new technologies, including developments in remote sensing and system dynamics modelling techniques, to enable a better understanding and mitigation of mosquito-borne diseases in a changing world.

Widespread Effects of Climate Change on Local Plant Diversity

Human activity has sent many measures of biodiversity into long-term decline, and there are suggestions that the sheer scale of this impact is sufficient to consider the modern era as a geological epoch of its own, known as "The Anthropocene" [1]. However, recent meta-analyses show that local alpha diversity is often stable or slightly increasing [2-4]. Here, we show that the local alpha diversity (species richness) of plants found in quadrats and transects has increased the most in cooler regions of the world that have experienced the highest absolute changes (i.e., changes in either direction) in climate. The greatest statistical support is for the effects of precipitation change. On average, alpha diversity declined slightly (-4.2% per decade) in the third of sites that experienced the lowest precipitation change but increased (+10.8% per decade) in the third of sites with the highest precipitation change. These results suggest that the "perturbation" of local communities during climatic transitions increases the average number of species, at least temporarily, an effect likely to remain important as climate change continues.

Engineering feasibility, economic viability and environmental sustainability of energy recovery from nitrous oxide in biological wastewater treatment plant

Currently, the biological wastewater treatment has been challenged by their high energy consumption. An increasing effort has been devoted to exploring energy recovery from nitrous oxide (N₂O) as a powerful fuel additive rather than as an unwanted byproduct during biological nitrogen removal. This review aims to offer a holistic and critical analysis of the ideas for N₂O production and energy recovery in terms of engineering feasibility, economic viability and environmental sustainability. It turns out that the recoverable energy from N₂O produced in municipal wastewater is below 0.03 kWh/m³, which is insignificant compared with the in-plant energy consumption, while complicated process configuration and high cost associated with harvesting and post-purification of N₂O will be incurred. An environmental risk related to global climate change due to the emission of residual dissolved N₂O is also concerned. Further effort on N₂O production and recovery technologies is indeed required to improve the overall energy balance.

A Resilience Approach to Community-Scale Climate Adaptation

Climate risk is expected to impact rural communities in West Africa in multiple ways. However, most current research addresses resilience and climate adaptation at either the national or the household scale; very little is known about community-scale interventions. We interviewed 934 community members in six communities in southeastern Nigeria about sources of climate risk and community-based actions for climate change adaptation. We found these communities contained multiple active and engaged groups that have implemented a wide range of interventions to reduce climate risk, most of which are seen as effective by community members. Flooding was the most common form of risk in this region, but drought, windstorms, and irregular rainy seasons are also frequent, implying that effective climate adaptation will have to be sensitive to multiple types of risk. Structural interventions (constructing roads, bridges, etc.) were the most common type of intervention, suggesting that communities are capable of marshalling considerable organizational and human power for adaptation efforts, even in the absence of external assistance. Efforts to boost community resilience and adaptation to climate change would benefit from first understanding what community actions are currently underway, and working with the groups implementing these actions to support and extend them.

Spatial and habitat variation in aphid, butterfly, moth and bird phenologies over the last half century

Global warming has advanced the timing of biological events, potentially leading to disruption across trophic levels. The potential importance of phenological change as a driver of population trends has been suggested. To fully understand the possible impacts, there is a need to quantify the scale of these changes spatially and according to habitat type. We studied the relationship between phenological trends, space and habitat type between 1965 and 2012 using an extensive UK dataset comprising 269 aphid, bird, butterfly and moth species. We modelled phenologies using generalized additive mixed models that included covariates for geographical (latitude, longitude, altitude), temporal (year, season) and habitat terms (woodland, scrub, grassland). Model selection showed that a baseline model with geographical and temporal components explained the variation in phenologies better than either a model in which space and time interacted or a habitat model without spatial terms. This baseline model showed strongly that phenologies shifted progressively earlier over time, that increasing altitude produced later phenologies and that a strong spatial component determined phenological timings, particularly latitude. The seasonal timing of a phenological event, in terms of whether it fell in the first or second half of the year, did not result in substantially different trends for butterflies. For moths, early season phenologies advanced more rapidly than those recorded later. Whilst temporal trends across all habitats resulted in earlier phenologies over time, agricultural habitats produced significantly later phenologies than most other habitats studied, probably because of nonclimatic drivers. A model with a significant habitat-time interaction was the best-fitting model for birds, moths and butterflies, emphasizing that the rates of phenological advance also differ among habitats for these groups. Our results suggest the presence of strong spatial gradients in mean seasonal timing and nonlinear trends towards earlier seasonal timing that varies in form and rate among habitat types.

Reconstruction of high spatial resolution surface air temperature data across China: A new geo-intelligent multisource data-based machine learning technique

Good knowledge of the surface air temperature (SAT) is critical for scientific understanding of ecological environment changes and land-atmosphere thermodynamic interactions. However, sparse and uneven spatial distribution of the temperature gauging stations introduces remarkable uncertainties into analysis of the SAT pattern. From a geo-intelligent perspective, here we proposed a new SAT reconstruction method based on the multisource data and machine learning technique which was developed by considering autocorrelation of the in situ observed SAT in both space and time, or simply STAML, i.e. Geoi-SVM (Geo-Intelligent Support Vector Machine), Geoi-BPNN (Geo-Intelligent Back Propagation Neural Network) and Geoi-RF (Geo-Intelligent Random Forest). The multisource data used in this study include the in situ observed SAT and multisource remotely sensed data such as MODIS land surface temperature, NDVI (Normalized Difference Vegetation Index) data. Intermodel comparisons amidst reconstructed SAT data were done to evaluate reconstructing performance of abovementioned models. Besides, the SAT reconstructed by CART (Classification and Regression Tree) was also included to evaluate the reconstructing performance of the models considered in this study when compared to SAT data by CART algorithm. We found that the estimation error of the reconstructed SAT by the STAML is smaller than 0.5K (Kelvin). In addition, it is interesting to note that the Geoi-RF performs better with Mean Absolute Error (MAE) of lower than 0.25K, and Root Mean Squared Error (RMSE) and Standard Deviation (SD) of lower than 0.5K respectively. Correlation coefficients between the reconstructed SAT by Geoi-RF and the observed SAT are close to 1. Besides, the estimation accuracy of the SAT by the Geoi-RF technique is 18.51-63.17% higher than that by the other techniques considered in this study. This study provides a new idea and technique for reconstruction of SAT over large spatial extent at regional and even global scale.

Climate and land-use change homogenise terrestrial biodiversity, with consequences for ecosystem functioning and human well-being

Biodiversity continues to decline under the effect of multiple human pressures. We give a brief overview of the main pressures on biodiversity, before focusing on the two that have a predominant effect: land-use and climate change. We discuss how interactions between land-use and climate change in terrestrial systems are likely to have greater impacts than expected when only considering these pressures in isolation. Understanding biodiversity changes is complicated by the fact that such changes are likely to be uneven among different geographic regions and species. We review the evidence for variation in terrestrial biodiversity changes, relating differences among species to key ecological characteristics, and explaining how disproportionate impacts on certain species are leading to a spatial homogenisation of ecological communities. Finally, we explain how the overall losses and homogenisation of biodiversity, and the larger impacts upon certain types of species, are likely to lead to strong negative consequences for the functioning of ecosystems, and consequently for human well-being.

Analysis of Climate Change Impacts on Tree Species of the Eastern US: Results of DISTRIB-II Modeling

Forests across the globe are faced with a rapidly changing climate and an enhanced understanding of how these changing conditions may impact these vital resources is needed. Our approach is to use DISTRIB-II, an updated version of the Random Forest DISTRIB model, to model 125 tree species individually from the eastern United States to quantify potential current and future habitat responses under two Representative Concentration Pathways (RCP 8.5 -high emissions which is our current trajectory and RCP 4.5 -lower emissions by implementing energy conservation) and three climate models. Climate change could have large impacts on suitable habitat for tree species in the eastern United States, especially under a high emissions trajectory. On average, of the 125 species, approximately 88 species would gain and 26 species would lose at least 10% of their suitable habitat. The projected change in the center of gravity for each species distribution (i.e., mean center) between current and future habitat moves generally northeast, with 81 species habitat centers potentially moving over 100 km under RCP 8.5. Collectively, our results suggest that many species will experience less pressure in tracking their suitable habitats under a path of lower greenhouse gas emissions.

Incorporating Local Adaptation Into Species Distribution Modeling of Paeonia mairei, an Endemic Plant to China

Paeonia (Paeoniaceae), a culturally and economically important plant genus, has an isolated taxonomy while the evolution of this genus is unclear. A plant species endemic to southwest China, Paeonia mairei is precious germplasm for evolution-related research and cultivar improvement, and its conservation is urgent. However, little is known about its patterns of habitat distribution and responses to climate change. Using 98 occurrence sites and data of 19 bioclimatic variables, we conducted principal component analysis and hierarchical cluster analysis to delineate different climatic populations. Maximum entropy algorithm (MaxEnt) was applied to each population to evaluate the importance of environmental variables in shaping their distribution, and to identify distribution shifts under different climate change scenarios. We also applied MaxEnt to all of the P. mairei presence sites (P_Whole) to evaluate the need to construct separate species distribution models for separate populations rather than a common approach by treating them as a whole. Our results show that local adaptation exists within the distribution range of P. mairei and that all presence sites were clustered into a western population (P_West) and an eastern population (P_East). Two variables (precipitation of the driest month and temperature seasonality) are important when shaping the distribution of P_West, and another two variables (mean diurnal range and mean temperature of the wettest quarter) are important for P_East. Both populations are likely to shift upward under climate change, while P_East may lose most current suitable areas while P_West may not. P_Whole produced a narrower area compared to the combination of P_West and P_East but a suitable area (south Chongqing) may have been missed in the prediction. Accordingly, a population-based approach in constructing a species distribution model is needed to provide a detailed appreciation of the distribution of P. mairei, allowing for a population-based conservation strategy. In this case, it could include assisted migration to new and suitable distribution areas for P_West and in situ conservation in high elevation regions for P_East. The results of our study could be a useful reference for implementing the long-term conservation and further research of P. mairei.

Genetic-Based Susceptibility of a Foundation Tree to Herbivory Interacts With Climate to Influence Arthropod Community Composition, Diversity, and Resilience

Understanding how genetic-based traits of plants interact with climate to affect associated communities will help improve predictions of climate change impacts on biodiversity. However, few community-level studies have addressed such interactions. Pinyon pine (Pinus edulis) in the southwestern U.S. shows genetic-based resistance and susceptibility to pinyon needle scale (Matsucoccus acalyptus). We sought to determine if susceptibility to scale herbivory influenced the diversity and composition of the extended community of 250+ arthropod species, and if this influence would be consistent across consecutive years, an extreme drought year followed by a moderate drought year. Because scale insects alter the architecture of susceptible trees, it is difficult to separate the direct influences of susceptibility on arthropod communities from the indirect influences of scale-altered tree architecture. To separate these influences, scales were experimentally excluded from susceptible trees for 15 years creating susceptible trees with the architecture of resistant trees, hereafter referred to as scale-excluded trees. Five patterns emerged. (1) In both years, arthropod abundance was 3-4X lower on susceptible trees compared to resistant and scale-excluded trees. (2) Species accumulation curves show that alpha and gamma diversity were 2-3X lower on susceptible trees compared to resistant and scale-excluded trees. (3) Reaction norms of arthropod richness and abundance on individual tree genotypes across years showed genotypic variation in the community response to changes in climate. (4) The genetic-based influence of susceptibility on arthropod community composition is climate dependent. During extreme drought, community composition on scale-excluded trees resembled susceptible trees indicating composition was strongly influenced by tree genetics independent of tree architecture. However, under moderate drought, community composition on scale-excluded trees resembled resistant trees indicating traits associated with tree architecture became more important. (5) One year after extreme drought, the arthropod community rebounded sharply. However, there was a much greater rebound in richness and abundance on resistant compared to susceptible trees suggesting that reduced resiliency in the arthropod community is associated with susceptibility. These results argue that individual genetic-based plant-herbivore interactions can directly and indirectly impact community-level diversity, which is modulated by climate. Understanding such interactions is important for assessing the impacts of climate change on biodiversity.

Bioenergy cropland expansion may offset positive effects of climate change mitigation for global vertebrate diversity

Understanding how land-use and climate change interact is of major importance to project the future of biodiversity. We assessed how the global species richness of vertebrates may become affected by these two threats, especially under a scenario following the Paris Agreement, which aims to limit global warming to 2 °C or even 1.5 °C. We found that combined effects of climate and land-use change will be most severe under such a scenario, due to the massive expansion of bioenergy cropland for climate change mitigation. While our findings suggest that the Paris goals will reduce direct climate change impacts on biodiversity, biodiversity will suffer as severely as under a high-level emission scenario if bioenergy remains a major component of climate change mitigation strategies.

Climate and land-use change interactively affect biodiversity. Large-scale expansions of bioenergy have been suggested as an important component for climate change mitigation. Here we use harmonized climate and land-use projections to investigate their potential combined impacts on global vertebrate diversity under a low- and a high-level emission scenario. We combine climate-based species distribution models for the world’s amphibians, birds, and mammals with land-use change simulations and identify areas threatened by both climate and land-use change in the future. The combined projected effects of climate and land-use change on vertebrate diversity are similar under the two scenarios, with land-use change effects being stronger under the low- and climate change effects under the high-emission scenario. Under the low-emission scenario, increases in bioenergy cropland may cause severe impacts in biodiversity that are not compensated by lower climate change impacts. Under this low-emission scenario, larger proportions of species distributions and a higher number of small-range species may become impacted by the combination of land-use and climate change than under the high-emission scenario, largely a result of bioenergy cropland expansion. Our findings highlight the need to carefully consider both climate and land-use change when projecting biodiversity impacts. We show that biodiversity is likely to suffer severely if bioenergy cropland expansion remains a major component of climate change mitigation strategies. Our study calls for an immediate and significant reduction in energy consumption for the benefit of both biodiversity and to achieve the goals of the Paris Agreement.