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Abstract In the intricate tapestry of environmental discourse, the field of political ecology emerges as a powerful lens through which we scrutinise the interplay of power, nature and society. This paper stages a dialogue with Paul Robbins to examine environmental justice, the decolonisation of political ecology, colonialism, sovereignty, climate change and capitalism. The dialogue challenges the conventional narratives of sovereignty and underscores the imperative of genuine decolonisation—beyond metaphorical interpretations—calling for the restitution of land and authority to Indigenous Peoples and other historically marginalised communities. The dialogue highlights the importance of moving away from capitalist systems that exacerbate environmental degradation. The dialogue calls for decolonising political ecology by including diverse perspectives, methodologies and ontologies and underlines the importance of control over productive resources. It emphasises that addressing the impacts of colonialism requires recognising and honouring the sovereignty of Indigenous Peoples and suggests that political ecology can contribute to decolonisation by focusing on sovereignty and supporting legal and institutional frameworks that empower marginalised communities. The paper discusses the way forward and the future trajectory of political ecology by suggesting that future research in political ecology should focus on diverse economies, embrace emerging technologies and rework academic institutions to value knowledge co‐production.

Abstract Climate‐smart agriculture (CSA) serves as a credible mechanism to simultaneously address food security, climate change, and agricultural productivity. Despite the widespread adoption of CSA approaches across West Africa, many countries have still not been able to resolve the problems of food insecurity and rural poverty. This systematic review evaluates published evidence on the types of CSA practices, the determinants and benefits of adoption, and the barriers confronting the adoption of CSA practices across West Africa, following the Preferred Reporting Items for Systematic Reviews and Meta‐Analyses statement checklist. Articles published in English from January 2010 to March 2023 investigating the benefits of and barriers to the adoption of CSA practices in West Africa were retrieved from ScienceDirect, Web of Science, and Scopus databases. The methodological quality of studies was assessed using Joanna Briggs Institute critical appraisal tools for use in systematic reviews. The themes emerging from the articles were extracted, and a summary was provided to illustrate each theme. After applying the eligibility criteria, 12 articles were included in the final review. The studies reviewed revealed that farmers used more knowledge‐, water‐, carbon‐, and nitrogen‐smart practices, compared to weather‐ and energy‐smart practices. Across the reviewed papers, factors such as the education level of farmers, age, gender, household size, membership of a social group, agricultural extension services, and access to credit/financial resources influenced CSA adoption. The reviewed studies identified that farmers who used CSA practices reported benefits such as improved soil fertility, higher yield, improved household income, climate resilience (such as overcoming the effects of drought and extreme temperatures), and food security. Some farmers adopted CSA practices to reduce the effect of droughts and high temperatures on their crops, and thus increase their resilience to climate variability and change. However, farmers’ adoption is confronted with challenges related to the technicality of some CSA practices, high cost of labor for CSA implementation, lack of credit and government support, limited access to weather and climate information, limited information about CSA options, high illiteracy level of smallholder farmers, and incompatibility of some practices with farmers’ crop of interest. Our findings show that most CSA practices in the studies we reviewed are not well targeted to meet farmers’ crop of interest, and that governments should provide more practical training to enhance farmers’ understanding of CSA practices, especially those related to weather‐ and energy‐smart initiatives. There should also be more robust financial and institutional support to improve the adoption and usage of CSA practices at all levels. Additionally, socio‐cultural factors such as values, customs, and beliefs should be properly integrated into CSA plans as they influence the adoption of CSA practices.

Abstract In emerging markets, investment costs tend to be associated with uncertainty, especially if the investment is policy driven. Globally, nations have agreed to reduce greenhouse gas emissions to keep the temperature increase below 1.5°C by 2100. Australia faces challenges in achieving its Paris Agreement Nationally Determined Contributions and Agenda 2030 commitments, mostly given the extraction profile of its economy. Introducing renewable carbon from forest residues in the niche markets could increase the competitiveness of the forest industry not only in terms of reduced energy costs but also in terms of ‘greening’ the primary product. Growing interest in the bioenergy market, linked with large volumes of available biomass feedstocks including forest residues, presents opportunities in Australia. Yet, ambiguity about costs and concerns about biomass supply throttle the investment potential. This paper aims to estimate a range of forest residue costs along the supply chain for the Australian market by projecting the biomass supply costs from a mature bioenergy market onto it using a benchmarking process reinforced by expert opinion. A three‐round Delphi method in which experts indicated direction and range of costs along the forest biomass supply chain revealed that roadside costs of forest residues (other than stumps), and biomass transportation costs, are lower than or equal to and equal to or higher than, the EU costs respectively. Experts ranked investment and supply‐side support as priority areas for the development of forest bioenergy in Australia. The expert estimations of forest residue cost ranges along the supply chain offer the first layer for framing a national policy for forest bioenergy within the broader bioeconomy.

Abstract As we contemplate the future of forest landscapes under changing climate conditions and land‐use demands, there is increasing value in studying historic forest conditions and how these landscapes have changed following past disturbances. Historic landscape paintings are a potential source of data on preindustrial forests with highly detailed, full‐color depictions of overstory and understory environments. They display key details about forest community composition, microhabitat features, and structural complexity from a time well before the advent of color photography. Despite these paintings' potential, their scientific applications have been impeded by questions of validity. How truly accurate are the images portrayed in these paintings? How much of an image is an artist's manipulation of a scene to best illustrate an allegory or romanticized view of nature? Following an established assessment model from historical ecology for evaluating resource validity, we demonstrate how scholarship on art history can be integrated with ecological understanding of forest landscapes to follow this model and address these questions of image veracity in 19th century American art. Further, to illustrate the potential use of these historic images in ecological studies, we present in a case study assessing microhabitat features of 10 different paintings. While this paper explores 19th century landscape art broadly, we focus our art historical review in particular on Asher Durand, a prolific and influential artist associated with the so‐called “Hudson River School” in the mid‐1800s. Durand left clear records about his perspectives on accurately depicting nature, and from a review of images and writings of Durand, we find support for the potential use of many of his paintings and sketches in historic forest ecology research. However, we also identify important caveats regarding potential ecological interpretations from these images. More broadly, because 19th century landscape paintings are not always directly transcriptive, and because regional art cultures differed in the 1800s, we cannot within this paper speak about landscape image veracity across all 19th century landscape art. However, in following established methods in historical ecology and integrating tools from art history research, we show that one can identify accurate historic landscape paintings for application in scientific studies.

Abstract Current discourse relating to climate change, conflict, migration (CCM), and the causal links thereof, is polarized. It is widely acknowledged that climate change will have a detrimental effect on quality of life, and that this impact will not be homogeneous across the globe. However, proposed causal links among CCM remain contentious. This paper argues that to better grasp the implications of climate change on global society and security, it is vital to develop a more systemic understanding of the interplay among CCM. Although this nexus is already recognized, studies to date have tended to be qualitative and statistical evidence of multivariate causality has been lacking, where quantitative analysis is present, it has typically been limited to two components at a time; few studies have addressed the nexus holistically, making research conclusions sometimes difficult to reconcile. Hence, by reviewing literature from a broad range of sources, this paper suggests a suite of systemic and quantitative approaches with which to address the CCM nexus. This review critically assesses the existing research approaches employed across a range of examples and suggests how leveraging the power of ‘big data’ and modelling the nexus as a complex system encapsulating both human and environmental drivers could offer new insights, especially for those looking to explore the increasing number of ‘what if’ scenarios relating to climate and human dynamics.

Abstract Soil is central to the complex interplay among biodiversity, climate, and society. This paper examines the interconnectedness of soil biodiversity, climate change, and societal impacts, emphasizing the urgent need for integrated solutions. Human‐induced biodiversity loss and climate change intensify environmental degradation, threatening human well‐being. Soils, rich in biodiversity and vital for ecosystem function regulation, are highly vulnerable to these pressures, affecting nutrient cycling, soil fertility, and resilience. Soil also crucially regulates climate, influencing energy, water cycles, and carbon storage. Yet, climate change poses significant challenges to soil health and carbon dynamics, amplifying global warming. Integrated approaches are essential, including sustainable land management, policy interventions, technological innovations, and societal engagement. Practices like agroforestry and organic farming improve soil health and mitigate climate impacts. Effective policies and governance are crucial for promoting sustainable practices and soil conservation. Recent technologies aid in monitoring soil biodiversity and implementing sustainable land management. Societal engagement, through education and collective action, is vital for environmental stewardship. By prioritizing interdisciplinary research and addressing key frontiers, scientists can advance understanding of the soil biodiversity–climate change–society nexus, informing strategies for environmental sustainability and social equity.

Abstract Background and Aims Two main problems the globe currently facing are migration and weather variation. Weather change has a significant impact on the agricultural industry, which affects the majority of poor people. There is a dearth of adequate methodological documentation when examining the relationship between weather variation, agricultural output, and migration. We aimed to identify methodological reporting difficulties by reviewing the quantitative literature on weather‐related migration through agricultural channels. Methods A systematic evaluation was conducted using papers published between January 2010 and June 2022, indexed in the SCOPUS, PUBMED, and Google Scholar databases. Using inclusion/exclusion criteria, we selected 22 original research articles out of 18,929 distinct articles for review, in accordance with the PRISMA guidelines. We extracted data from each study to understand how various concepts, research designs, and investigative techniques influence our understanding of migration patterns related to weather in the agricultural sector. Results The majority (64%) of the study's data consisted of time series data. In 50% of the studies, secondary data were used. Additionally, 55% of these studies did not state the sample size. In 40% of the studies, model assumptions were fully adhered to, whereas in 36% of the studies, they were not followed at all. The majority of the articles used the Ordinary Least Squares technique, while about 41% applied the Two‐Stage Least Squares technique. Various tests were conducted across these studies, such as robustness checks (59.1%), endogeneity tests (31.8%), omitted variable bias tests (22.7%), sensitivity analyses (22.7%), and weak instrument tests (13.6%), to name a few. In the research we selected, the methodology section had various shortcomings and lacked organization. Furthermore, the justifications for deviations from model assumptions were unclear, potentially affecting the study outcomes. Conclusion This study has important indications for researchers in studying climatic (weather) migration through agricultural channels besides for policymakers by giving a thorough review of the methods and techniques.

Abstract Remote sensing applications have a long history in treeline research. Recent reviews have examined the topic mainly from a methodological point of view. Here, we propose a question‐oriented review of remote sensing in treeline ecology to relate remote sensing methodologies to key ecological metrics and identify knowledge gaps and promising areas for future research. We performed a meta‐analysis to assess the role of remote sensing as a tool for measuring spatial patterns and dynamics of alpine and Arctic treeline ecotone globally. We assessed the geographic distribution, scale of analysis, and relationships between remote sensing techniques and treeline ecological metrics through co‐occurrence mapping and multivariate statistics. Our analysis revealed that only 10% of treeline ecology studies applied remote sensing tools, often associated with the keyword ‘climate change’. Monitoring studies adopted coarser spatial resolutions over longer temporal extents in comparison with other treeline studies. A multiscale and multi‐sensor spatial approach was implemented in just 19% of papers. Long‐term research commonly relied on aerial and oblique photography to measure treeline shifts through photointerpretation within a multidisciplinary framework. More recent treeline dynamics were often quantified using greenness trends derived from the pixel‐based classification of satellite images. Many recent short‐term studies focused on delineating tree scale metrics derived from the object‐based classification of uncrewed aerial vehicle (UAV) images or LiDAR data. Over the past decade, high‐resolution and low‐cost UAV remote sensing has emerged as an interesting opportunity to fill the gap between local‐scale ecological patterns and coarse‐resolution satellite sensors. Additionally, treeline remote sensing applications would strongly benefit from multidisciplinary frameworks that integrate field studies in ecology and environmental science. The multi‐dimensional structural complexity of treelines typically responds to environmental drivers over multiple scales and thus is best described with multiscale and multi‐sensor approaches.

Abstract Time‐lapse cameras have been widely used as a tool to monitor the timing of seasonal vegetation growth. These simple, relatively inexpensive systems can provide high‐frequency observations of leaf development and demography which are critical data sets needed to characterize plant phenology from species to landscapes. This is important for understanding how plants are responding to global changes, as well as for validating satellite‐derived phenology products. However, in remote regions including the high‐latitude Arctic, deploying time‐lapse cameras could be challenging. The remoteness and lack of widespread power and telecommunications infrastructure limit options for the installation, maintenance and retrieval of data and equipment, and make it difficult for cameras to survive in extreme weather (e.g. long cold winters). To improve our understanding of Arctic phenology, new technologies are required to address these challenges. Here, we present a novel, low‐power, compact, lightweight time‐lapse camera system, called power‐interval camera automation module (PiCAM). The PiCAM was designed with explicit consideration to simplify deployment (i.e. without a need for external power supplies) of camera systems and to address the challenges of camera survival in harsh Arctic environments. In this paper, we describe the design, setup and technical details of the PiCAM and provide a roadmap for how to build and operate these systems. As proof of concept, we deployed 26 PiCAMs at three low‐Arctic tundra sites on the Seward Peninsula, Alaska in early August 2021 for characterizing Arctic plant phenology. Of the 26 PiCAMs, 70% remained active at the point of our revisit in late July 2022 despite the extreme winter temperatures they experienced (< −30°C, heavy snow cover). We extracted key plant phenology metrics from the PiCAMs and captured strong differences across key Arctic plant species. We showed that the PiCAM has the potential to be widely used for monitoring plant phenology across the broader Arctic region, addressing the need for ground‐based understanding of Arctic phenological diversity to develop knowledge of plant response to climate change and to validate remote sensing products.

Abstract In agriculture, the possibility of climatic hazards negatively impacting small farmers’ livelihood is high. Thus, there are reasons to contend that climate vulnerabilities could determine economic behaviour. This paper investigates whether discounting behaviour varies with exposure to natural hazards. We analyse data from a survey involving an experiment in which farmers made choices between a smaller immediate payment compared with larger future amounts. The results show that 58% heavily discounted the future in favour of the immediate payment. Among the climatic shocks examined, flood, drought and salinity were the main hazards farmers faced on their plots. However, these natural hazards varied across locations. Our examination of the effect of the experience of natural hazards and the severity of climate vulnerability on farmers’ discounting behaviour suggests that experience and vulnerability had different impacts on discounting behaviour. Recent exposure to drought and flood reduces patience. However, the opposite is the case for a recent experience of salinity. This paper shows that under circumstances of climate vulnerabilities, farmers may be willing to make decisions that result in immediate albeit lower rewards in place of potential higher rewards in the future. The implication is that experience and vulnerability to natural hazards might affect farmers’ decision‐making to the extent that it prevents them from a speedy economic recovery post‐disaster.

Abstract This paper presents the methodology for the construction of the KNMI'23 national climate scenarios for the Netherlands. We have developed six scenarios, that cover a substantial part of the uncertainty in CMIP6 projections of future climate change in the region. Different sources of uncertainty are disentangled as much as possible, partly by means of a storyline approach. Uncertainty in future emissions is covered by making scenarios conditional on different SSP scenarios (SSP1‐2.6, SSP2‐4.5, and SSP5‐8.5). For each SSP scenario and time horizon (2050, 2100, 2150), we determine a global warming level based on the median of the constrained estimates of climate sensitivity from IPCC AR6. The remaining climate model uncertainty of the regional climate response at these warming levels is covered by two storylines, which are designed with a focus on the annual and seasonal mean precipitation response (a dry‐trending and wet‐trending variant for each SSP). This choice was motivated by the importance of future water management to society. For users with specific interests we provide means how to account for the impact of the uncertainty in climate sensitivity. Since CMIP6 GCM data do not provide the required spatial detail for impact modeling, we reconstruct the CMIP6 responses by resampling internal variability in a GCM‐RCM initial‐condition ensemble. The resulting climate scenarios form a detailed storyline of plausible future climates in the Netherlands. The data can be used for impact calculations and assessments by stakeholders, and will be used to inform policy making in different sectors of Dutch society.

Abstract Exposure to extreme temperatures can negatively affect animal reproduction, by disrupting the ability of individuals to produce any offspring (fertility), or the number of offspring produced by fertile individuals (fecundity). This has important ecological consequences, because reproduction is the ultimate measure of population fitness: a reduction in reproductive output lowers the population growth rate and increases the extinction risk. Despite this importance, there have been no large‐scale summaries of the evidence for effect of temperature on reproduction. We provide a systematic map of studies testing the relationship between temperature and animal reproduction. We systematically searched for published studies that statistically test for a direct link between temperature and animal reproduction, in terms of fertility, fecundity or indirect measures of reproductive potential (gamete and gonad traits). Overall, we collated a large and rich evidence base, with 1654 papers that met our inclusion criteria, encompassing 1191 species. The map revealed several important research gaps. Insects made up almost half of the dataset, but reptiles and amphibians were uncommon, as were non‐arthropod invertebrates. Fecundity was the most common reproductive trait examined, and relatively few studies measured fertility. It was uncommon for experimental studies to test exposure of different life stages, exposure to short‐term heat or cold shock, exposure to temperature fluctuations, or to independently assess male and female effects. Studies were most often published in journals focusing on entomology and pest control, ecology and evolution, aquaculture and fisheries science, and marine biology. Finally, while individuals were sampled from every continent, there was a strong sampling bias towards mid‐latitudes in the Northern Hemisphere, such that the tropics and polar regions are less well sampled. This map reveals a rich literature of studies testing the relationship between temperature and animal reproduction, but also uncovers substantial missing treatment of taxa, traits, and thermal regimes. This database will provide a valuable resource for future quantitative meta‐analyses, and direct future studies aiming to fill identified gaps.

Abstract Decision making under deep uncertainty (DMDU) approaches are well‐suited for making decisions about infrastructure to manage flooding exacerbated by climate change. One important system for climate resilience and flood management is green infrastructure, which refers to a network of natural and semi‐engineered areas that provides ecosystem functions. Green infrastructure is often characterized as a low‐regret strategy with multiple co‐benefits under uncertainty. These attributes enable green infrastructure to be an important adaptation strategy under DMDU frameworks for flood management. However, DMDU analyses that include green infrastructure are still relatively limited, perhaps due to computational or modeling complexity and other barriers. This paper identifies and reviews publications in the flood management literature that use DMDU frameworks and refer to green infrastructure adaptation strategies, in order to identify trends and inform future research. The reviewed publications are categorized according to a variety of performance metrics, climate change scenarios, DMDU metrics, and hydrologic modeling techniques, and represent several adaptation strategies applied to case studies on five continents using a range of data sources and assumptions. This paper highlights a number of solutions that can be employed to facilitate additional research at the intersection of these fields. Primary among these is the transparent documentation and use of open source models, methods, and data. Future research should also focus on communication among different stakeholders, particularly in ensuring definitions, assumptions, and data requirements are clear. These partnerships can facilitate effective application of robust strategies such as green infrastructure for urban adaptation to the effects of climate change.

Abstract Environmental factors such as climate change are now underway, which have substantial impacts on health and well‐being of human kind, but still imprecisely quantified, implications for human health. At present, one of the most significant discussions among scientists worldwide is interdependency of escalating environmental risk factors and the increasing rates of noncommunicable diseases (NCDs), which are the leading cause of death and disability worldwide. Climate change also triggers the occurrence of NCDs through a variety of direct and indirect pathways. Therefore, it is likely that the interdependence of climate change, environmental risk factors, and NCDs as a whole poses great threat to global health. Hence, this paper aims to review the latest evidence on impacts of environmental risk factors on NCDs and methods used in establishing the cause or correlation of environmental risk factors and NCDs. The literature review leveraged online databases such as PubMed and Google Scholar with articles that matched keywords “climate change”, “environmental risk factors,” and “noncommunicable diseases”. This review shows that the burden of NCDs is increasing globally and attribution of environmental risk factors such as climate change is significant. Understanding the nature of the relation between NCDs and the environment is complex and has relied on evidence generated from multiple study designs. This paper reviews eight types of study designs that can be used to identify and measure causal and correlational nature between environment and NCDs. Future projections suggest that increases in temperatures will continue and also increase the public health burden of NCDs.

Abstract Human‐induced climate change poses a pervasive threat to the world. Human activities, such as deforestation, farming livestock, and burning fossil fuels, are key drivers of climate change. Like other regions, the Southeast Asian region is greatly impacted by climate change. The article focuses on examining the current landscape of climate change adaptation and health preparedness among indigenous populations in Southeast Asia (SEA). Climate change will affect the indigenous populations disproportionately. Over the years, indigenous people living in SEA have faced increasing challenges. For instance, air pollution resulting from forest fires causes respiratory conditions, skin irritations, and other significant health risks. The article also highlights climate change–related health system preparedness in ASEAN and indigenous strategies in navigating climate change adaption. As the saying goes, “actions speak louder than words.” To develop sustainable regional climate change adaptation strategies, representation and voices of indigenous peoples matter. At ASEAN level, although the ASEAN Working Group on Climate Change was convened to develop policies and coordinate action plans among its member states, it is now key to include and learn from the instrumental strategies of indigenous communities in conserving, protecting, and restoring forests. Beyond acknowledging the efforts of indigenous communities on paper, it is now time to translate scientific knowledge into practical actions. It is necessary for us to value and recognize indigenous peoples, particularly in SEA as valued agents in co‐creating sustainable solutions for climate agenda. Centering indigenous peoples’ knowledge in climate adaptation is crucial for strengthening collective resilience in climate action strategies. Conclusively, the article advocates for the prioritization of indigenous communities’ leadership efforts in ASEAN‐wide climate action initiatives and climate action policy.

Abstract Accelerating sea‐level rise combined with the stresses of human land use threatens the persistence of tidal marshes. The proper management of existing marshes and the conservation of lands for marsh migration require a synthesis of factors affecting future marsh evolution. There are a number of existing marsh models, with different parameters and run at different scales, that can assist in this type of assessment. However, as with many models forecasting future conditions, there is no clearly identified ‘best’ model and they all perform slightly differently across different scenarios and with different suites of available data inputs. In this paper, we worked with local and regional managers to inform the development of an ensemble methodology that uses results from multiple marsh models in conjunction with social, land use and environmental data to inform marsh management, conservation and restoration under sea‐level rise. The methodology was developed and tested in three locations in the Virginia portion of the Chesapeake Bay, United States, using existing marsh migration models already run throughout the Bay. Stakeholder groups of local decision makers and a steering committee composed of regional managers were engaged in the process to ensure that the resulting methodology met current management needs. The need for a multimodel approach to identifying marsh migration pathways was supported by the marsh migration comparison done during methodology development which showed disparate results from multiple marsh migration models. Five existing marsh model outputs were combined into a single Marsh Migration Corridor Envelope (MMCE), which encompasses the potential area of current upland expected to become marsh under a selected sea‐level rise scenario. Within the identified MMCE, land covers were assessed for suitability for marsh support and the socio‐economic context of the parcels of land was considered. Last, the current condition of existing marsh on the properties was assessed to determine preservation activities that can increase their longevity. Together, these pieces of information inform a physical and sociological understanding of tidal marshes that can allow for a management framework that incorporates both current and future concerns.

This special issue, brought together during a time of unprecedented global change, represents a unique collection of papers that shed light on the current and future significance of mycorrhiza‐forming fungi in the human world. Across this selection of papers, we explore the significance and potential of mycorrhizal fungi to contribute towards our achievement of global change goals of improved sustainability, food security and conservation as well as how we might best implement mycorrhizal knowledge and technologies to achieve these outcomes in modern societies.

Abstract Natural history collections are invaluable resources for understanding biotic response to global change. Museums around the world are currently imaging specimens, capturing specimen data and making them freely available online. In parallel to the digitisation effort, there have been great advancements in computer vision: the computer trained automated recognition/detection, and measurement of features in digital images. Applying computer vision to digitised natural history collections has the potential to greatly accelerate the use of these collections for biotic response to global change research. In this paper, we apply computer vision to a very large, digitised collection to test hypotheses in an established area of biotic response to climate change research: temperature‐size responses. We develop a computer vision pipeline (Mothra) and apply it to the NHM collection of British butterflies (>180,000 imaged specimens). Mothra automatically detects the specimen and other objects in the image, sets the scale, measures wing features (e.g. forewing length), determines the orientation of the specimen (pinned ventrally or dorsally) and identifies the sex. We pair these measurements and specimen collection data with temperature records for 17,726 specimens across a subset of 24 species to test how adult size varies with temperature during the immature stages of species. We also assess patterns of sexual size dimorphism across species and families for 32 species trained for automated sex ID. Mothra accurately measures the forewing lengths of butterfly specimens compared to manual measurements and accurately determines the sex of specimens, with females as the larger sex in most species. An increase in adult body size with warmer monthly temperatures during the late larval stages is the most common temperature‐size response. These results confirm suspected patterns and support hypotheses based on recent studies using a smaller dataset of manually measured specimens. We show that computer vision can be a powerful tool to efficiently and accurately extract phenotypic data from a very large collection of digital natural history collections. In the future, computer vision will become widely applied to digital collections to advance ecological and evolutionary research and to accelerate their use to investigate biotic response to global change.

Abstract Ecosystem services are essential for the health of current and future generations and key to the sustainable development of our societies. The role of insects in providing ecosystem services has been increasingly recognized, becoming the focus of several management and conservation initiatives world‐wide. However, ecosystem services framework traditionally overlooks the full range of services that can be provided by insects, largely because services provided by life stages other than the insect adult are often neglected. In this paper, I first review the traditional ecosystem services primarily attributed to insects, namely edible insects and mass‐rearing for biological control. Next, I provide a collection of unconventional ecosystem services provided by insect larvae which highlights the importance of considering life stage‐specific services in a holistic view of the ecosystem services framework. In particular, I discuss recent advances that revealed how insect larvae can degrade plastic, which is one of humanity's greatest environmental pollutants, and how larvae can be used to produce biofuel to help overcome the increasing contribution of the fossil fuel industry to climate change. I then discuss how toxic compounds produced by the larvae of some insects provide potential new medicines for clinical treatment and lastly, I discuss a unique example of how the larval stage of insects is entrenched into the cultural values of Aboriginal communities in Australia. In conclusion, by acknowledging life stage‐specific ecosystem services provided by insects, this paper raises awareness of unconventional services that can underpin innovative solutions to contemporary global challenges, which can ultimately help create more sustainable and culturally diverse societies.

Abstract The influence of climate change on forest condition is noticeable. Forest ecosystem stress caused by climate change has already been manifested in several parts of Europe, including Poland. Thus, the main objective of this paper is to investigate for the entire area of Poland a long‐term trend and variability of forest greenness expressed as the Normalized Difference Vegetation Index (NDVI), derived from two decades (2002–2021) of remote sensing Moderate Resolution Imaging Spectroradiometer (MODIS) data. In the next step, selected meteorological elements – temperature (T), precipitation (P) and evapotranspiration (ETo), derived from ERA5‐Land reanalysis—were used to determine the influence of climatic conditions on the variability of NDVI in forests. The study documents the general greening of forests in Poland in 2002–2021. The greening is mostly visible in central‐eastern Poland, where the annual mean NDVI increased by 0.030 in 20 years, while it is weaker in the Baltic coast and in the southern edges of Poland (increase by 0.009 in 20 years). Overall, the positive, statistically significant trends in annual NDVI prevail over the negative, statistically significant trends and account for 32.5% of forest area, whereas the negative trends account for 3.9%. The study indicates an overall moderate impact of meteorological elements on variability of NDVI in forests in Poland. The most important factors affecting forest condition are P and ETo. The strongest correlations between NDVI and P and ETo reach 0.55 and are located in central Poland, in the form of a belt from western to eastern borders.

Abstract This paper evaluated and compared the performance of a statistical downscaling method and a dynamical downscaling method to simulate the spatial–temporal rainfall distribution. Outputs from RegCM4 Regional Climate Model (RCM) and the CanESM2 Atmosphere–Ocean General Circulation Model (AOGCM) were selected for the data scarce Gwadar‐Ormara basin, Pakistan. The evaluation was based on the climatological average and standard deviation for historic (1971–2000) and future (2041–2070) time periods under Representative Concentration Pathways (RCP) 4.5 and 8.5 scenarios. The performance evaluation showed that statistical downscaling is preferred to simulate and project rainfall patterns in the study area. Additionally, the Statistical DownScaling Model (SDSM) showed low R2 values in calibration and validation of the simulations with respect to observed data for the historic period. Overall, SDSM generated satisfactory results in simulating the monthly rainfall cycle of the entire basin. In this study, RegCM4 showed large rainfall errors and missed one rainfall season in the historic period. This study also explored whether the grid‐based rainfall time series of the Asian Precipitation—Highly Resolved Observational Daily Integration Towards Evaluation (APHRODITE) dataset could be used to enlarge and complement the sample of in situ observed rainfall time series. A spatial correlogram was used for observed and APHRODITE rainfall data to assess the consistency between the two data sources, which resulted in rejecting APHRODITE data. For the future time period (2041–2070) under RCPs 4.5 and 8.5 scenarios, rainfall projections did not show significant difference for both downscaling approaches. This may relate to the driving model (CanESM2 AOGCM) and not necessarily suggests poor performance of downscaling; either statistical or dynamical. Hence, the study recommends evaluating a multi‐model ensemble including other GCMs and RCMs for the same area of study.

Abstract Climate vulnerability could be influenced by transforming demographic, technological, cultural, political and economic factors, which cuts across global, regional, national and local scales. Such social transformations result in positive and negative outcomes, with implications for the adaptive capacities of resource‐poor households, especially those headed by women. However, these transformations are usually not integrated in climate vulnerability assessments. Based on insights from a stakeholders’ brainstorming workshop and the synthesis of information from traditional literature review, this paper contributes to better understanding of the intersections of social transformation with climate vulnerabilities in the Upper West Region of Ghana. The review indicates that the region is experiencing social transformation triggered by technological, demographic and cultural factors, with implications for climate resilience building. For example, compared to the last decade, there is now an increased use of mobile phones, resulting in improved access to e‐extension and climate‐smart agriculture services. At the same time, an emerging trend of land commodification is driving poor households to sell or lease farming lands. Within the context of these transformations, climate vulnerability is still assessed through approaches that mainly focus on a ‘static’ view of the extent of exposure to climate hazards and their impacts on rural livelihoods. A social transformation analysis that promotes a systematic investigation of the transforming factors is proposed as an effective approach for vulnerability assessment in climate adaptation planning. This approach provides critical reflections on, and sustainable resilience interventions for addressing both changing biophysical and social vulnerabilities of rural communities.

Abstract The Acadian Forest Region is a temperate‐boreal transitional zone in eastern North America which provides a unique opportunity for understanding the potential effects of climate change on both forest types. Leaf phenology, the timing of leaf life cycle changes, is an important indicator of the biological effects of climate change, which can be observed with stationary timelapse cameras known as phenocams. Using four growing seasons of observations for the species Acer rubrum (red maple), Betula papyrifera (paper/white birch) and Abies balsamea (balsam fir) from the Acadian Phenocam Network as well as multiple growing season observations from the North American PhenoCam Network we parameterized eight leaf emergence and six leaf senescence models for each species which span a range in process and driver representation. With climate models from the Fifth Phase of the Coupled Model Intercomparison Project (CMIP5) we simulated future leaf emergence, senescence and season length (senescence minus emergence) for these species at sites within the Acadian Phenocam Network. Model performances were similar across models and leaf emergence model RMSE ranged from about 1 to 2 weeks across species and models, while leaf senescence model RMSE ranged from about 2 to 4 weeks. The simulations suggest that by the late 21st century, leaf senescence may become continuously delayed for boreal species like Betula papyrifera and Abies balsamea, though remain relatively stable for temperate species like Acer rubrum. In contrast, the projected advancement in leaf emergence was similar across boreal and temperate species. This has important implications for carbon uptake, nutrient resorption, ecology and ecotourism for the Acadian Forest Region. More work is needed to improve predictions of leaf phenology for the Acadian Forest Region, especially with respect to senescence. Phenocams have the potential to rapidly advance process‐based model development and predictions of leaf phenology in the context of climate change.

Abstract The necessity to achieve global sustainability and renewable energy resources to overcome the threat of climate change has led to unparalleled social and economic alterations ubiquitous throughout the world. The environment surrounding pollution correlated with global warming is essential to technological advances for developing energy resources. Renewable and sustainable energy resources are eco‐friendly energy sources that transform heat directly into electrical energy. The transformation of the global energy system underway in various countries can play a predominant role in power sectors. It helps in establishing a low‐power solution with high performance in advance. This review paper highlights technological feasibility within the economic activity of sustainable resources in various sectors. The sustainable resource would represent the world's most advanced technology and cost‐effective global power transition pathway. The present status, prospects, and updated information about these energy resources have been discussed in detail. This review provides a recommendation on which energy would be suitable for electrical energy generation and would establish a green environment for the next generation to survive in the world.

Abstract Ecosystems across the United States are changing in complex ways that are difficult to predict. Coordinated long‐term research and analysis are required to assess how these changes will affect a diverse array of ecosystem services. This paper is part of a series that is a product of a synthesis effort of the U.S. National Science Foundation’s Long Term Ecological Research (LTER) network. This effort revealed that each LTER site had at least one compelling scientific case study about “what their site would look like” in 50 or 100 yr. As the site results were prepared, themes emerged, and the case studies were grouped into separate papers along five themes: state change, connectivity, resilience, time lags, and cascading effects and compiled into this special issue. This paper addresses the time lags theme with five examples from diverse biomes including tundra (Arctic), coastal upwelling (California Current Ecosystem), montane forests (Coweeta), and Everglades freshwater and coastal wetlands (Florida Coastal Everglades) LTER sites. Its objective is to demonstrate the importance of different types of time lags, in different kinds of ecosystems, as drivers of ecosystem structure and function and how these can effectively be addressed with long‐term studies. The concept that slow, interactive, compounded changes can have dramatic effects on ecosystem structure, function, services, and future scenarios is apparent in many systems, but they are difficult to quantify and predict. The case studies presented here illustrate the expanding scope of thinking about time lags within the LTER network and beyond. Specifically, they examine what variables are best indicators of lagged changes in arctic tundra, how progressive ocean warming can have profound effects on zooplankton and phytoplankton in waters off the California coast, how a series of species changes over many decades can affect Eastern deciduous forests, and how infrequent, extreme cold spells and storms can have enduring effects on fish populations and wetland vegetation along the Southeast coast and the Gulf of Mexico. The case studies highlight the need for a diverse set of LTER (and other research networks) sites to sort out the multiple components of time lag effects in ecosystems.

Abstract Geoengineering is the focus of a large debate over potential solutions to climate change. However, in the midst of geoengineering and other large‐scale proposals, such as reducing emissions at an industrial level, the role of individual actions to reduce emissions is often overlooked. Given the current and fast‐paced changes we have seen as emissions are reduced by COVID‐19 social distancing strategies, it is time to re‐examine the impact that individual actions can have. This paper considers how one individual action (reducing carbon dioxide emissions from gasoline‐fueled private vehicles), when adopted at a global scale, may have an effect that is comparable to the effects of geoengineering. This paper also argues that the role of geoengineering as a safeguard against climate change may be encouraging complacency and reducing motivation for individual action.

Abstract The biological knowledge and associated values and beliefs of Indigenous and other long‐resident Peoples are often overlooked and underrepresented in governance, planning and decision‐making at local, regional, national and international levels. Ethnobiology—the study of the dynamic relationships among peoples, biota and environments—is a field that places Indigenous Peoples' ecological knowledge and ways of knowing at the forefront of research interests, particularly in relation to the importance of biocultural diversity in sustaining the Earth's Ecosystems. In this paper, we examine the nature and significance of Indigenous Peoples' knowledge systems concerning environmental sustainability, as documented in collaborative ethnobiological research. We emphasize the diverse aspects of Indigenous knowledge in conservation, and the role played by ethnobiologists in respectfully highlighting this knowledge, and link these to the Intergovernmental Science‐Policy Platform on Biodiversity and Ecosystem Services Global Assessment's key levers and leverage points for enabling the transformative change required for achieving more sustainable lifeways. Drawing on diverse ways of knowing—respectfully, collaboratively, ethically and reciprocally—can help provide more detailed knowledge of local ecosystems, and guide all humans towards greater sustainability. From environmental monitoring, to building relationships with plants and the land, to ecological restoration, there are many lessons and ways in which the intersections between Indigenous knowledge and ethnobiology can inform and contribute to the future of humanity and other life on earth. Read the free Plain Language Summary for this article on the Journal blog.

Abstract A comprehensive and accurate estimation of water quality in lakes and reservoirs is vital for the protection of the aquatic biota. Research on the spatiotemporal variations of nitrogen (N) and phosphorus (P) concentrations in lacustrine systems is typically plagued, however, by a lack of long‐term, spatially continuous monitoring data. This paper assembled a 30‐year (1989–2018) data set of water quality in 586 lakes and reservoirs in China, along with basin characteristics and climate conditions, forming the comprehensive data set available. These data were then used in a stacking model (based on random forest, support vector regression, and K‐nearest neighbor models) to identify the relationships between nutrient concentrations and their influencing factors, including net anthropogenic N/P inputs, geographical position, climate, land use pattern, and soil type. The stacking models were developed using data collected over multiple time scales (annual, seasonal, and monthly), which were then applied to reconstruct TN and TP concentrations during the periods of 1980–2018 and 2020s–2050s under the climate scenarios of RCP 4.5 and RCP 8.5. The accuracy of the stacking models was 99.1% and 98.3% for TN and TP concentrations using ensembled data, respectively. The interannual variations in TN and TP contents in the 586 lakes and reservoirs during 1980–2018 exhibited a non‐monotonic pattern with a peak of 1.12 and 0.049 mg/L in 2007, respectively. This study demonstrates that stacking machine learning models represent a new effective approach for estimating nutrient concentrations in unmonitored lakes and reservoirs across broad spatiotemporal scales.

Abstract With global estimates showing an increasing trend in flooding and its adverse effects on communities and population health, resilience is presented as a concept with potential to help integrate disaster risk management, sustainable development, and climate change adaptation concerns. Resilience research and practice have conceptual and empirical challenges of how to understand, characterize and measure resilience, particularly at community level. Using a multidimensional framework, this paper takes a systems approach to understanding, characterizing, and measuring community flood resilience. Through cluster analysis, bivariate methods and multivariable‐adjusted binary logistic regression modeling, we developed a context and hazard specific construct of community flood resilience and investigated its predictor variables. The factors defining the community flood resilience construct captured the community needs to withstand disasters through purpose‐built infrastructure, early warning systems for preparedness and utilization of local human capacity for adaptation. These results strengthen the previous arguments for utilizing a comprehensive multidimensional framework for resilience analysis. Access to services for improved health and psychosocial well‐being was significantly associated with the three‐item measure of being more flood resilient. Additionally, a strong sense of place and resistance to relocation were presented as key elements of resilience, maintaining community system function, and preserving livelihoods. The study further found that these key factors would not be adequate to guarantee community flood resilience outside the transformative capacity of a well‐resourced village civil protection committee that can prepare and mobilize stakeholders in response to flood emergencies. Our results suggest that, in the context where policymakers seek to strengthen resilience of communities without relocating them, a focus on public health and on strengthening and utilizing local capacities as adaptation, are key in disaster risk management policymaking and implementation. For the international research community, this study demonstrated the importance of utilizing context and hazard specific measures for defining, characterizing, and measuring resilience to inform policy.

Abstract Ranges of species around the world are expected to contract in response to climate change. Species distribution models (SDMs) are a powerful tool for predicting changes in habitat availability, but the variables selected to create SDMs influence their performance. In addition to climate, habitat characteristics and species traits can play a role in predicting species distribution. In this paper, we consider how variable selection influences the accuracy of SDMs when applied to isolated subpopulations of two widely distributed bird species: great gray owl (Strix nebulosa) and willow flycatcher (Empidonax traillii). In the Sierra Nevada of California, these species are restricted largely to discrete patches of meadow habitat within a forest matrix, providing the potential to identify specific locations to target conservation efforts. We contrast predictions made by SDMs that consider climatic variables alone with those that incorporate both climate and geophysical variables. Adding geophysical variables resulted in differing model predictions. For willow flycatchers, adding geophysical variables improved predictive performance. In the case of great gray owls, models with and without geophysical variables had nearly identical performance under historical conditions but differed starkly in their predictions. The full model (climatic and geophysical variables) predicted habitat availability to decrease moderately, whereas the climate‐only model predicted nearly complete loss of favorable habitat by 2099. The climate‐only model is consistent with expectations based on previous SDMs of birds across North America, but previous studies also assumed homogeneity in species traits and range‐wide habitat requirements. The full model appears more consistent with recent trends in great gray owl numbers in the Sierra Nevada specifically, where the population has remained relatively stable over recent decades. Given contradictions in our model predictions, care should be taken when trying to apply similar SDMs to other systems.

Abstract Human impact is noticeable around the globe, indicating that a new era might have begun: the Anthropocene. Continuing human activities, including land‐use changes, introduction of non‐native species and rapid climate change, are altering the distributions of countless species, often giving rise to human‐mediated hybridization events. While the interbreeding of different populations or species can have detrimental effects, such as genetic extinction, it can be beneficial in terms of adaptive introgression or an increase in genetic diversity. In this paper, I first review the different mechanisms and outcomes of anthropogenic hybridization based on literature from the last five years (2016–2020). The most common mechanisms leading to the interbreeding of previously isolated taxa include habitat change (51% of the studies) and introduction of non‐native species (34% intentional and 19% unintentional). These human‐induced hybridization events most often result in introgression (80%). The high incidence of genetic exchange between the hybridizing taxa indicates that the application of a genic view of speciation (and introgression) can provide crucial insights on how to address hybridization events in the Anthropocene. This perspective considers the genome as a dynamic collection of genetic loci with distinct evolutionary histories, giving rise to a heterogenous genomic landscape in terms of genetic differentiation and introgression. First, understanding this genomic landscape can lead to a better selection of diagnostic genetic markers to characterize hybrid populations. Second, describing how introgression patterns vary across the genome can help to predict the likelihood of negative processes, such as demographic and genetic swamping, as well as positive outcomes, such as adaptive introgression. It is especially important to not only quantify how much genetic material introgressed, but also what has been exchanged. Third, comparing introgression patterns in pre‐Anthropocene hybridization events with current human‐induced cases might provide novel insights into the likelihood of genetic swamping or species collapse during an anthropogenic hybridization event. However, this comparative approach remains to be tested before it can be applied in practice. Finally, the genic view of introgression can be combined with conservation genomic studies to determine the legal status of hybrids and take appropriate measures to manage anthropogenic hybridization events. The interplay between evolutionary and conservation genomics will result in the constant exchange of ideas between these fields which will not only improve our knowledge on the origin of species, but also how to conserve and protect them.

Abstract A growing body of work examines the direct and indirect effects of climate change on ecosystems, typically by using manipulative experiments at a single site or performing meta‐analyses across many independent experiments. However, results from single‐site studies tend to have limited generality. Although meta‐analytic approaches can help overcome this by exploring trends across sites, the inherent limitations in combining disparate datasets from independent approaches remain a major challenge. In this paper, we present a globally distributed experimental network that can be used to disentangle the direct and indirect effects of climate change. We discuss how natural gradients, experimental approaches, and statistical techniques can be combined to best inform predictions about responses to climate change, and we present a globally distributed experiment that utilizes natural environmental gradients to better understand long‐term community and ecosystem responses to environmental change. The warming and (species) removal in mountains (WaRM) network employs experimental warming and plant species removals at high‐ and low‐elevation sites in a factorial design to examine the combined and relative effects of climatic warming and the loss of dominant species on community structure and ecosystem function, both above‐ and belowground. The experimental design of the network allows for increasingly common statistical approaches to further elucidate the direct and indirect effects of warming. We argue that combining ecological observations and experiments along gradients is a powerful approach to make stronger predictions of how ecosystems will function in a warming world as species are lost, or gained, in local communities.

Abstract For the safety assessment and design of levees in the Netherlands probabilistic tools are used, which account for both statistical and model uncertainties in the determination of hydraulic loads. However, climate change induced uncertainties in extreme wind climate or storminess are not yet accounted for. This paper presents a first assessment of the effect of uncertainties in storminess on Dutch levee design. An expert panel was consulted to define a range of plausible trends and uncertainties in extreme wind climate. Three scenarios were defined with variations of the current wind climate, including changes in wind speed high percentiles and in wind direction. For the defined scenarios probabilistic computations were carried out to determine the effect of the wind statistics variations on the water level, wave loads, and required levee height along the Dutch lakes and coast. In the case of an increase in wind percentiles (mean + 5%, standard deviation 12%), the required levee height increases significantly: up to 1.5–4 m along the Dutch coast and up to 1–2 m along the Dutch lakes. Given the large impact of the considered changes, it is first recommended to carry out a more robust assessment of the uncertainties in future storm climate and to measure and monitor evolution of future wind speeds.

Abstract Geography, like many other disciplines, is reckoning with the carbon intensity of its practices and rethinking how activities such as annual meetings are held. The Climate Action Task Force of the American Association of Geographers (AAG), for example, was set up in 2019 and seeks to transform the annual conference in light of environmental justice concerns. Mirroring shifts in geographic practice across the globe, these efforts point to a need to understand how new opportunities for knowledge production, such as online events, can operate effectively. In this paper, we offer suggestions for best practice in virtual spaces arising from our Material Life of Time conference held in March 2021, a two‐day global event that ran synchronously across 15 time zones. Given concerns about lack of opportunities for informal exchanges at virtual conferences, or the ‘coffee break problem’, we designed the event to focus particularly on opportunities for conviviality. This was accomplished through a focus on three key design issues: the spatial, the temporal, and the social. We review previous work on the benefits and drawbacks of synchronous and asynchronous online conference methods and the kinds of geographic communities they might support. We then describe our design approach and reflect on its effectiveness via a variety of feedback materials. We show that our design enabled high delegate satisfaction, a sense of conviviality, and strong connections with new colleagues. However, we also discuss the problems with attendance levels and external commitments that hampered shared time together. We thus call for collective efforts to support the ‘event time’ of online meetings, rather than expectations to fit them around everyday tasks. Even so, our results suggest that synchronous online events need not result in geographical exclusions linked to time‐zone differences, and we outline further recommendations for reworking the spacetimes of the conference.

Abstract Extreme rain events have caused numerous issues and have had a significant impact on agriculture, human activities, ecology, infrastructure, and casualties. The theory of extreme values has been widely applied in extreme precipitation modelling and a variety of other fields. This paper employs the generalized Pareto distribution, which has been widely used to analyse extreme climates, in conjunction with the peak over thresholds approach to investigate exceedances. The occurrence of intense rainfall events in Kigali city causes severe damage to human properties, infrastructure damage, people injuries, loss of life, and other various harmful consequences. Early detection of extreme rainfall in Kigali aids in the development and implementation of strategies and measures to mitigate the negative effects of extreme rainfall before it occurs. The aim of this research is to estimate the frequency and magnitude of intense rainfall events in Kigali. The daily rainfall data from Kigali Airport station collected by Rwanda Meteorological Agency from 1990 to 2019 were applied. The results showed that as the return periods increased, so did the return levels, implying that the intensity and frequency of rainfall in Kigali will increase in the future. The model's goodness was tested, and the study suggests a model that has a non‐negative shape parameter (ξ) to be good. The study's findings are extremely important for understanding the occurrence of these events and also serve as a tool for decision‐making and the development of policies aimed at mitigating the effects of such events.

Abstract Citizen science can facilitate in‐depth learning for pupils and students, contribute to scientific research, and permit civic participation. Here, we describe the development of the transnational school‐based citizen science project Phenology of the North Calotte. Its primary goal is to introduce pupils (age 12–15; grades 7–10) in northern Norway, Russia, and Finland to the local and global challenges of climate change resulting in life cycle changes at different trophic and ecosystem levels in their backyards. Partnerships between regional scientists and staff from NIBIO Svanhovd, State nature reserves, national parks, and teachers and pupils from regional schools aim to engage pupils in project‐based learning. The project uses standardized protocols, translated into the different languages of participating schools. The phenological observations are centered around documenting clearly defined life cycle phases (e.g., first appearance of species, flowering, ripening, leaf yellowing, snow fall, and melt). The observations are collected either on paper and are subsequently submitted manually to an open‐source online database or submitted directly via a newly developed mobile app. In the long term, the database is anticipated to contribute to research studying changes in phenology at different trophic levels. In principle, guided school‐based citizen science projects have the potential to contribute to increased environmental awareness and education and thereby to transformative learning at the societal level while contributing to scientific progress of understudied biomes, like the northern taiga and (sub)arctic tundra. However, differences in school systems and funding insecurity for some schools have been major prohibiting factors for long‐term retention of pupils/schools in the program. Project‐based and multidisciplinary learning, although pedagogically desired, has been partially difficult to implement in participating schools, pointing to the need of structural changes in national school curricula and funding schemes as well as continuous offers for training and networking for teachers.

Abstract Maximising resource‐use efficiency, productivity and environmental sustainability are all fundamental requirements to raise global food production by ~70 per cent in order to feed a world population of ~9.7 billion people by 2050. Perhaps the most vital resource within our capacity to achieve this goal is our soil. Broadly, the fundamental question concerns whether or not satisfying this production demand will accelerate soil degradation, climate change, and the loss of soil carbon stocks. This paper builds upon the outputs of the UK Charity ‘Food & Farming Futures’ (chaired by Lord Curry of Kirkharle) virtual workshop held on 23 March 2021, entitled ‘Capturing the Potential of Soil’. The event focussed on the link between soil health, primarily soil organic carbon (SOC), and agricultural productivity. Supported with commentaries by Professor Pete Smith (University of Aberdeen and Science Director of the Scottish Climate Change Centre of Expertise) and Professor Steve McGrath (Head of Sustainable Agricultural Sciences at Rothamsted Research), specific focus will be given to the research challenges within the UK’s ability to improve soil health and functionality, the implementation priorities that must be held in order to improve soil management by 2050 and what the potential co‐benefits could be. These co‐benefits were scattered across environmental, economic, social and political issues, yet they may be summarised into six primary co‐benefits: developing natural capital, climate change mitigation, carbon trading, improvements in crop yield, animal performance and human health (nutrition). Additionally, the main barriers to improved soil management practices are centred on knowledge exchange‐regarding agri‐environmental techniques—whilst the most impactful solutions rely on soil monitoring, reporting and verification.

Abstract Climate change and human activities have already caused degradation in a large fraction of vegetation on the Qinghai‐Tibetan Plateau (QTP). Many studies report that climate variability instead of overgrazing has been the primary cause for large‐scale vegetation cover changes on the QTP, for example, Lehnert et al., 2016, https://doi.org/10.1038/srep24367. However, it remains unclear how human activities (mainly livestock grazing) regulate vegetation dynamics under climate change. This paper takes the AVHRR/GIMMS Normalized Difference Vegetation Index (NDVI) as an indicator to analyze the growth status of vegetation zones in the QTP, which has highly sensitive to climate change. The spatiotemporal dynamics of vegetation growth between 1981 and 2015 were analyzed. The dual effects of climate change and human activities were examined by correlation analyses of data from 87 meteorological stations and economic statistical data of the QTP. Results show that: (a) The vegetation in central and southwestern QTP with high altitudes was improving due to the warm‐humid climate trend. An increase in temperature and a reduction in the harsh frigid climate at high altitudes due to global warming has resulted in expansions of the vegetated areas, with the NDVI showing a concordant increase. (b) The degraded areas were mainly confined to the northern and eastern QTP, which have high human and livestock population densities. In comparison to gently changing climate regimes, anthropogenic activities such as chronic concentration of population and livestock in the valleys with a less harsh climate exerts a much stronger pressure on vegetation. The study indicates that the anthropogenic pressures are much more intensive than the impact of climate change and are critical for the conservation and sustainable management of the QTP vegetation.

Abstract The Yangtze River Basin (YRB), a key biodiversity area and a major economic zone in China, the biodiversity of the area is confronted with severe challenges. In this paper, we analyzed species distribution patterns based on a dataset with 18,538 seed plant species to identify hotspots and evaluate conservation effectiveness and gaps of the YRB. We calculated distribution patterns of species richness with the top 5% richness algorithm and complementarity algorithm, and reconstructed a phylogenetic tree and elucidated spatial phylogenetics. There were 214 hotspot grid cells covering only 6.8% of the study region, but containing 88% seed plant species. Then, we conducted correlation analysis on distribution patterns of different algorithms and species categories, which showed moderate or weak correlations between the top 5% richness algorithm and complementary algorithm. Conservation effectiveness analysis indicated there were 116 hotspot grid cells (accounting for 73.6% of the total species) protected by current conservation networks and there are many conservation gaps remaining. Finally, we used the maximum entropy model (MaxEnt) to predict suitable habitat areas of threatened species under current and future climate scenarios. Prediction analysis results indicated future expansion of suitable habitat to the southeast, and reduction in the central and western portions of the study area. When we considered anthropogenic areas, the suitable habitat was severely decreased, indicating the importance of optimizing the layout of conservation networks and comprehensive biodiversity conservation planning in the YRB.

This paper makes a case for spiritualising climate change, outlining the importance of bringing diverse religious understandings into climate change responses, particularly in the Pacific Island region. It situates this as part of a wider geographical project of rendering climate change locally meaningful, and story‐telling multiple climate change narratives, including Christian ones. It identifies one of the major obstacles to this spiritualisation: the treatment of religious thought as a barrier to climate change action by much of the existing social science research in the Pacific Islands. Rather than attempting to purify scientific and religious knowledge, this paper proposes an alternative approach, tufala save: the balancing of multiple epistemologies of climate change, exploring their convergences and tensions. This paper draws on four months of ethnographic fieldwork in Vanuatu, and over 60 semi‐structured interviews with religious figures and individuals engaged in climate change adaptation and advocacy across the Pacific Island region. It applies the tufala save approach in order to explore one recurring narrative, the biblical story of Noah and the flood, due to the contentious associations between this story and climate change denial in Oceania. The paper traces three discursive manifestations of the Noah story within the Pacific Islands: rainbow covenant as a basis for denial, Noah as an icon of preparation, and Islanders as unjustly outside of the ark. The contrasts between these three articulations – in terms of the relations between the different knowledges and the possibilities for climate change action they encourage and foreclose – demonstrate the heterogeneity of religious responses to climate change and the potential for fruitful connections between religious and scientific knowledges. They highlight the potential for more‐than‐scientific yet not anti‐scientific responses to climate change that are locally meaningful and morally compelling.

Abstract A new data set of Night Marine Air Temperature (NMAT) is presented that builds on the HadNMAT2 data set, which was released in 2013. In a similar manner to HadNMAT2, the new data set (CLASSnmat) provides uninterpolated, monthly global values at a 5° resolution back to 1880. In addition to being extended to the end of 2019, four main developments are made in CLASSnmat: (1) the NMAT values are extracted from the most recent version of the International Comprehensive Ocean‐Atmosphere Data Set (ICOADS Release 3) and a revised method of eliminating duplicated observations is used; (2) values of NMAT are adjusted to 2m and 20m heights in addition to the 10 m height used in HadNMAT2; (3) a refinement is made to the corrections necessary during World War 2, which uses more of the NMAT observations and hence results in a more extensive spatial coverage for this period than was possible in HadNMAT2; (4) an updated gridding method is used that allows for an improved propagation of uncertainty from the individual NMAT values through to the gridded estimates. In this paper, the method used to construct CLASSnmat (version 1.0.0.0) is described.

Abstract Norway spruce (Picea abies) is a dominant conifer species of major economic importance in northern Europe. Extensive breeding programs were established to improve phenotypic traits of economic interest. In southern Sweden, seeds used to create progeny tests were collected on about 3,000 trees of outstanding phenotype (‘plus’ trees) across the region. In a companion paper, we showed that some were of local origin but many were recent introductions from the rest of the natural range. The mixed origin of the trees together with partial sequencing of the exome of >1,500 of these trees and phenotypic data retrieved from the Swedish breeding program offered a unique opportunity to dissect the genetic basis of local adaptation of three quantitative traits (height, diameter and bud‐burst) and assess the potential of assisted gene flow. Through a combination of multivariate analyses and genome‐wide association studies, we showed that there was a very strong effect of geographical origin on growth (height and diameter) and phenology (bud‐burst) with trees from southern origins outperforming local provenances. Association studies revealed that growth traits were highly polygenic and bud‐burst somewhat less. Hence, our results suggest that assisted gene flow and genomic selection approaches could help to alleviate the effect of climate change on P. abies breeding programs in Sweden.

Abstract. Risk of climate‐related impacts results from the interaction of climate‐related hazards (including hazardous events and trends) with the vulnerability and exposure of human and natural systems. Despite the commitment of the Paris Agreement, the integrate research on climate change risk combining risk‐causing factors and risk‐bearing bodies, the regional differences in climate impacts are still missing. In this paper we provide a quantitative assessment of hazards and socioeconomic risks of extreme events, risks of risk‐bearing bodies in China under global warming of 1.5 and 2.0 °C based on future climate scenarios, and quantitative evaluation theory for climate change risk. For severe heat waves, hazards might significantly intensify. Affected population under 2.0 °C warming might increase by more than 60% compared to that of 1.5 °C. Hazards of severe droughts and floods might strengthen under Representative Concentration Pathway 8.5 scenario. Economic losses might double between warming levels of 1.5 and 2.0 °C, and the population affected by severe floods might continuously increase. Under the integrate effects of multiple disasters, the regions with high population and economic risks would be concentrated in eastern China. The scope would gradually expand to the west with socioeconomic development and intensification of extreme events. High ecological risks might be concentrated in the southern regions of the Yangtze River Basin, while the ecological risk in northern China would expand. High agriculture yield risks might be distributed mainly in south of the North China Plain, the Sichuan Basin, south of the Yangtze River, and west of Northwest China, and the risk levels might continuously increase.

Societal Impact Statement Trees play a critical role for people and the planet. Numerous studies have demonstrated that the presence of trees and urban nature can improve people's mental and physical health, children's attention and test scores, the property values in a neighborhood, and beyond. Trees cool our urban centers. Trees are essential for healthy communities and people. The benefits that trees provide can help cities and countries meet 15 of the 17 internationally supported United Nations Sustainable Development Goals. This critical review provides a comprehensive argument that trees should be considered an important part of the equation by project managers and civic leaders as we collectively work toward reaching these sustainability goals. Summary We live in an era influenced by humans to the point that the Earth's systems are now altered. In addition, a majority of the world's population live in cities. To meet the needs of people in a changing world, The United Nations General Assembly created the United Nations Sustainable Development Goals (UN SDG) to improve the quality of life for people. These broad goals outline the greatest challenges of our time. An effective strategy to assist in meeting these goals is to plant and protect trees, especially in cities where the majority of people live. This paper serves as a critical review of the benefits of trees. Trees promote health and social well‐being by removing air pollution, reducing stress, encouraging physical activity, and promoting social ties and community. Children with views of trees are more likely to succeed in school. Trees promote a strong economy and can provide numerous resources to the people that need them. While cities are getting hotter, trees can reduce urban temperatures. They provide habitat and food for animals. Finally, trees are valuable green infrastructure to manage stormwater. Money spent on urban forestry has a high return on investment. As we navigate this human‐dominated era, we need skilled people who understand the nuances of the built environment and trees as we strategically plan the cities of the future. The overwhelming evidence from the scientific literature suggests that investing in trees is an investment in meeting the UN SDG, and ultimately an investment for a better world.

Abstract Arctic tundra consists of diverse habitats that differ in dominant vegetation, soil moisture regimes, and relative importance of organic vs. inorganic nutrient cycling. The Arctic is also the most rapidly warming global area, with winter warming dominating. This warming is expected to have dramatic effects on tundra carbon and nutrient dynamics. We completed a meta‐analysis of 166 experimental warming study papers to evaluate the hypotheses that warming changes tundra biogeochemical cycles in a habitat‐ and seasonally specific manner and that the carbon (C), nitrogen (N), and phosphorus (P) cycles will be differentially accelerated, leading to decoupling of elemental cycles. We found that nutrient availability and plant leaf stoichiometry responses to experimental warming were variable and overall weak, but that both gross primary productivity and the plant C pool tended to increase with growing season warming. The effects of winter warming on C fluxes did not extend into the growing season. Overall, although warming led to more consistent increases in C fluxes compared to N or P fluxes, evidence for decoupling of biogeochemical cycles is weak and any effect appears limited to heath habitats. However, data on many habitats are too sparse to be able to generalize how warming might decouple biogeochemical cycles, and too few year‐round warming studies exist to ascertain whether the season under which warming occurs alters how ecosystems respond to warming. Coordinated field campaigns are necessary to more robustly document tundra habitat‐specific responses to realistic climate warming scenarios in order to better understand the mechanisms driving this heterogeneity and identify the tundra habitats, communities, and soil pools most susceptible to warming.

The assessment and implementation of structural or financial instruments for climate risk mitigation requires projections of future climate risk over the operational life of each proposed instrument. A point often neglected in the climate adaptation literature is that the physical sources of predictability differ between projects with long and short planning periods: While historical and paleo climate records emphasize low‐frequency modes of variability, anthropogenic climate change is expected to alter their occurrence at longer time scales. In this paper we present a set of stylized experiments to assess the uncertainties and biases involved in estimating future climate risk over a finite future period, given a limited observational record. These experiments consider both quasi‐periodic and secular change for the underlying risk, as well as statistical models for estimating this risk from an N‐year historical record. The uncertainty of IPCC‐like future scenarios is considered through an equivalent sample size N. The relative importance of estimating short‐ or long‐term risk depends on the investment life M. Shorter design lives are preferred for situations where interannual to decadal variability can be successfully identified and predicted, highlighting the importance of sequential investment strategies for adaptation.

Abstract Over the past decade, Vietnam has emerged as one of the world's fastest growing economies. Fossil fuel use, which is a dominant energy source and vital for economic growth, have been increasing considerably. Undoubtedly, the projection of fossil fuel demand is essential for a better understanding of energy needs, fuel mix, and Vietnam's strategic development. This paper provides an outlook for coal, oil, and gas demand in Vietnam to 2050. The projection is based on the calibrated results from a hybrid model (that combines a GTAP‐ R version for resources, and a micro simulation approach) and an energy database. Under the baseline scenario (business as usual), from 2018 to 2050, the demand for coal, oil products, and gas are expected to increase by a factor of 2.47‐fold, 2.14‐fold, and 1.67‐fold, respectively. Emissions are also projected to increase. Because fossil fuels are the dominant source of carbon emissions in Vietnam, it follows, going forward, that an effective fuel‐mix strategy that encourages the development of renewables and energy efficiency is essential.

Abstract We thank the Comment's authors for their considered critique of our paper. We respond to their main criticisms and hope that this discussion motivates further consideration of communication strategies for event attribution analyses.

Abstract Climate is an essential element in agricultural production, and climate change inevitably have an impact on agriculture. Assessing the economic consequences of climate change requires comprehensive assessments of the impact chain from climate to crops and the economy. In our previous study, we derived a dose‐response function to estimate the response of crop yields to climate variables through a systematic review. In this paper, a dynamic multiregional input‐output model is established to assess the economic consequences of changes in agricultural production on China's regional and sectoral levels. The results show that (1) the direct economic damage is equivalent to 1% of gross domestic product (GDP) which implies the resulting economic cascade effect (ECE) that amounts to 17.8% of China's GDP. At the end of 21st century, the ECE is −0.1% to 13.6% of GDP (negative values indicate economic gains) without considering CO2 fertilization effect, of which the ECE in the most pessimistic pathway are equivalent to the total agricultural output in China today. (2) Regional‐level results show an uneven distribution of economic impact in China, which is related to the regional economic development. The least developed region in China experiences 2.8 to 8.5 times more ECE caused by climate change than the most developed region. (3) Sector‐level results show that agriculture is still the main affected sector, but in developed regions, manufacturing and services also bear part of the ECE.

Abstract As global mean sea level continues to rise, thresholds corresponding to coastal inundation impacts are exceeded more frequently. This paper aims to relate sea level rise (SLR) observations and projections to their physical on‐the‐ground impacts. Using a large coastal city as an example, we show that in Sydney, Australia, frequencies of minor coastal inundation have increased from 1.6 to 7.8 days per year between 1914 and present day. We attribute over 80% of the observed coastal inundation events between 1970 and 2015 to the predominantly anthropogenic increases in global mean sea level. Further, we find that impact‐producing coastal inundation will occur weekly by 2050 under high‐ and medium‐emission/SLR scenarios and daily by 2100 under high emissions. The proportion of tide‐only coastal inundation events (i.e., where no storm surge is required to exceed flood thresholds) will increase with SLR, such that most coastal inundation events, including those considered historically severe, will become a predictable consequence of SLR and astronomical tides. These findings are important for coastal managers as frequency, severity, and predictability of inundation impacts can all now be related to the amount of SLR (e.g., a planning allowance or SLR projection). By incorporating known historical inundation events, this allows contextualization, visualization, and localization of global SLR and the changing nature of future coastal inundation risk.