Future climate and land-use intensification modify arthropod community structure

Climate change significantly impacted on the survival, development, distribution, and abundance of living organisms. The Chinese serow Capricornis milneedwardsii, known as the "four unlike," is a Class II nationally protected species in China. In this study, we predicted the geographical suitability of C. milneedwardsii under current and future climatic conditions using MaxEnt. The model simulations resulted in area under the receiver operating characteristic curve (AUC) values above 0.9 for both current and future climate scenarios, indicating the excellent performance, high accuracy, and credibility of the MaxEnt model. The results also showed that annual precipitation (Bio12), slope, elevation, and mean temperature of wettest quarter (Bio8) were the key environmental variables affecting the distribution of C. milneedwardsii, with contributions of 31.2%, 26.4%, 11%, and 10.3%, respectively. The moderately and highly suitable habitats were mainly located in the moist area of China, with a total area of 34.56 × 104 and 16.61 × 104 km2, respectively. Under future climate change scenarios, the areas of suitability of C. milneedwardsii showed an increasing trend. The geometric center of the total suitable habitats of C. milneedwardsii would show the trend of northwest expansion and southeast contraction. These findings could provide a theoretical reference for the protection of C. milneedwardsii in the future.

Ecosystem coupling: A unifying framework to understand the functioning and recovery of ecosystems

The great gerbil (Rhombomys opimus) is a gregarious rodent in Central Asia and is one of the major pests found in desert forest and grassland areas. The distribution changes and migration routes of R. opimus in Central Asia under climate change remain unexplored. This study employed multi-model ensemble, correlation analysis, jackknife method, and minimum cumulative resistance (MCR) model to simulate the potential habitat of R. opimus under current and future (2030 and 2050) climate scenarios and estimate its possible migration routes. The results indicate that the ensemble model integrating Random Forest (RF), Gradient Boosting Machine (GBM), and Maximum Entropy Model (MaxEnt) performed best within the present climate context. The model predicted the potential distribution of R. opimus in Central Asia with an area under the curve (AUC) of 0.986 and a True Skill Statistic (TSS) of 0.899, demonstrating excellent statistical accuracy and spatial performance. Under future climate scenarios, northern Xinjiang and southeastern Kazakhstan will remain the core areas of R. opimus distribution. However, the optimal habitat region will expand relative to the current one. This expansion will increase with the rising CO2 emission levels and over time, potentially enlarging the suitable area by up to 39.49 × 104 km2. In terms of spatial distribution, the suitable habitat for R. opimus is shifting toward higher latitudes and elevations. For specific migration routes, R. opimus tends to favor paths through farmland and grassland. This study can provide guidance for managing and controlling R. opimus under future climate change scenarios.

This paper provides a comprehensive overview of the modelling tools available for integrating climate change impacts into pest risk assessments (PRA), elucidating the existing methodologies and models employed to understand the potential distributions of pests based on historical data and under future climate change scenarios. We highlight the strengths and weaknesses of these models and provide commentary on their ability to identify emerging threats due to climate change accurately and adequately, considering pest establishment likelihood, host crop exposure and the distribution of impacts. The simplest methods are based on climate‐matching models, degree‐day development models and Köppen–Geiger climate classification. Correlative species distribution models derive species–environment relationships and have been applied to PRA with mixed success. When fitted models are applied to different continents they are usually challenged to extrapolate climate suitability patterns outside the climate space used to train them. Global climate change is creating novel climates, exacerbating this ‘transferability’ problem. Some tools have been developed to reveal when these models are extrapolating. Process‐oriented models, which focus on mechanisms and processes rather than distribution patterns, are inherently more reliable for extrapolation to novel climates such as new continents and future climate scenarios. These models, however, require more skill and generally more knowledge of the species to craft robust models.

Assessing the impact of climate change on rainwater harvesting in the Oum Zessar watershed in Southeastern Tunisia

In this study we simulated the watershed response according to future climate and land use change scenarios through a hydrological model and predicting future hydroclimate changes by applying the Budyko framework. Future climate change scenarios were derived from the UK Earth system model (UKESM1), and future land use changes were predicted using the future land use simulation (FLUS) model. To understand the overall trend of hydroclimatic conditions, the movements in Budyko space were represented as wind rose plots. Moreover, the impacts of climate and land use changes were separated, and the watersheds’ hydroclimatic conditions were classified into five groups. In future scenarios, both increase and decrease of aridity index were observed depending on the watershed, and land use change generally led to a decrease in the evaporation index. The results indicate that as hydroclimatic movement groups are more diversely distributed by region in future periods, regional adaptation strategies could be required to reduce hydroclimatic changes in each region. The results derived from this study can be used as basic data to establish an appropriate water resource management plan and the governments’ land use plan. As an extension of this study, we can consider more diverse land use characteristics and other global climate model (GCMs) in future papers.

Lignin impedes access to cellulose during biofuel production and pulping but trees can be genetically modified to improve processing efficiency. Modification of lignin may have nontarget effects on mechanical and chemical resistance and subsequent arthropod community responses with respect to pest susceptibility and arthropod biodiversity. We quantified foliar mechanical and chemical resistance traits in lignin-modified and wild-type (WT) poplar (Populus alba × Populus tremula) grown in a plantation and censused arthropods present on these trees to determine total abundance, as well as species richness, diversity and community composition. Our results indicate that mechanical resistance was not affected by lignin modification and only one genetic construct resulted in a (modest) change in chemical resistance. Arthropod abundance and community composition were consistent across modified and WT trees, but transgenics produced using one construct exhibited higher species richness and diversity relative to the WT. Our findings indicate that modification of lignin in poplar does not negatively affect herbivore resistance traits or arthropod community response, and may even result in a source of increased genetic diversity in trees and arthropod communities.

Simple SummaryAdopting deficit irrigation (DI) to improve crop production and safeguard groundwater resources is of great importance in water scarce regions, e.g., the North China Plain (NCP). Under the background of global warming, it is worth investigating whether DI continues to play such a key role under future climate change scenarios. Thus, we studied the effect of DI on wheat yield and water use efficiency under future climate change scenarios. We found that moderate deficit irrigation (DI3, ≤0.4 PAWC at sowing to flowering stage) under the N3 (150 kg N ha−1) condition was identified as the optimum irrigation schedule for the study site under future climate change scenarios. However, the compensation effect of DI3 on yield and water use efficiency (WUE) became weak in the future. To conclude, in water scarce regions of NCP, DI remains an effective strategy to maintain higher yield and enhance water use under future climate scenarios.Background. Deficit irrigation (DI) is a feasible strategy to enhance crop WUE and also has significant compensation effects on yield. Previous studies have found that DI has great potential to maintain crop production as full irrigation (FI) does. Therefore, adopting DI to improve crop production and safeguard groundwater resources is of great importance in water scarce regions, e.g., the North China Plain (NCP). Under the background of global warming, it is worth investigating whether DI continues to play such a key role under future climate scenarios. Methods. We studied the response of winter wheat yield and WUE to different DI levels at pre-anthesis under two Shared Socioeconomic Pathways (SSPs) scenarios (SSP245 and SSP585) using the Agricultural Production Systems Simulator (APSIM) model driven by 21 general circulation models (GCMs) from the Coupled Model Inter-Comparison Project phase 6 (CMIP6). Additionally, we explored the effects of different nitrogen (N) fertilizer application rates on DI. Results. We found that simulated wheat yield would increase by 3.5–45.0%, with WUE increasing by 8.8–46.4% across all treatments under future climate change. Moderate deficit irrigation (DI3, ≤0.4 PAWC at the sowing to flowering stage) under the N3 (150 kg N ha−1) condition was identified as the optimum irrigation schedule for the study site under future climate change. However, compensation effects of DI3 on yield and WUE became weak in the future, which was mainly due to increased growing season rainfall projected by GCMs. In addition, we found that N fertilizer application could mitigate the effect of DI3. Conclusions. We highlight that in water scarce regions of NCP, DI remains an effective strategy to maintain higher yield and enhance water use under future climate scenarios. Results strongly suggest that moderate deficit irrigation under a 150 kg N ha−1 condition could mitigate the contradiction between production and water consumption and ensure food safety in the NCP.

Arthropods play key roles in ecosystems as pollinators or as food resources for many birds. The decline in arthropods in farmland due to agricultural intensification is related to negative population trends in farmland birds. Semi‐natural areas such as fallow land are valuable habitats for arthropod communities in farmland, but the potential of these areas to boost biodiversity greatly depends on their management. We used a field experiment to explore the mechanisms behind the effects of mechanical management on arthropod communities in high conservation value fallow land. We used GLMMs to explore changes in arthropod abundance after treatment application, and pSEM to discriminate direct effects of treatments from indirect effects mediated by changes in vegetation structure. Tillage had stronger negative effects than vegetation shredding on total arthropod, spider and bee abundance, which were mediated by a reduction in vegetation height, green cover and flowering. Coleoptera biomass did not vary between treatments. The differences between treatments disappeared from 2 to 3 months after treatment application for total arthropod and spider biomass, but not for Orthoptera and bees. Synthesis and applications. Low‐intensity mechanical management of fallows has short‐term negative effects on arthropod abundance. For conservation purposes, fallow management should combine untreated fallow fields (or strips within fields) to boost arthropod communities, with low‐intensity management to create suitable breeding habitats for steppe birds.

Trophic rewilding, the (re)introduction of species to promote self-regulating biodiverse ecosystems, is a future-oriented approach to ecological restoration. In the twenty-first century and beyond, human-mediated climate change looms as a major threat to global biodiversity and ecosystem function. A critical aspect in planning trophic rewilding projects is the selection of suitable sites that match the needs of the focal species under both current and future climates. Species distribution models (SDMs) are currently the main tools to derive spatially explicit predictions of environmental suitability for species, but the extent of their adoption for trophic rewilding projects has been limited. Here, we provide an overview of applications of SDMs to trophic rewilding projects, outline methodological choices and issues, and provide a synthesis and outlook. We then predict the potential distribution of 17 large-bodied taxa proposed as trophic rewilding candidates and which represent different continents and habitats. We identified widespread climatic suitability for these species in the discussed (re)introduction regions under current climates. Climatic conditions generally remain suitable in the future, although some species will experience reduced suitability in parts of these regions. We conclude that climate change is not a major barrier to trophic rewilding as currently discussed in the literature.This article is part of the theme issue 'Trophic rewilding: consequences for ecosystems under global change'.

The cultivation of grapevines in the UK and many other cool climate regions is expected to benefit from the higher growing season temperatures predicted under future climate scenarios. Yet the effects of climate change on the risk of adverse weather conditions or events at key stages of crop development are not always captured by aggregated measures of seasonal or yearly climates, or by downscaling techniques that assume climate variability will remain unchanged under future scenarios. Using fine resolution projections of future climate scenarios for south-west England and grapevine phenology models we explore how risks to cool-climate vineyard harvests vary under future climate conditions. Results indicate that the risk of adverse conditions during flowering declines under all future climate scenarios. In contrast, the risk of late spring frosts increases under many future climate projections due to advancement in the timing of budbreak. Estimates of frost risk, however, were highly sensitive to the choice of phenology model, and future frost exposure declined when budbreak was calculated using models that included a winter chill requirement for dormancy break. The lack of robust phenological models is a major source of uncertainty concerning the impacts of future climate change on the development of cool-climate viticulture in historically marginal climatic regions.

Climate change exerts profound influences on the ecological environments on a global scale, leading to habitat destruction and altering distribution patterns for numerous plant species. Traditional Chinese medicinal plants, such as those belonging to the Sambucus genus, have been extensively utilized for several centuries to treat fractures, rheumatism, and inflammation. However, our understanding of their geographic distribution and climatic adaptation within China still needs to be improved. In this study, we screened the optimal predictive model (random forest model) to predict the potential suitable distribution of three Sambucus species (Sambucus adnata, Sambucus javanica, and Sambucus williamsii) across China under both current and future climate scenarios. Moreover, we identified key climate factors that influence their potential distributions. Our findings revealed that S. adnata and S. javanica are predominantly shaped by temperature seasonality and mean diurnal range, respectively, whereas S. williamsii is significantly affected by the precipitation of the wettest month. Currently, S. williamsii is primarily distributed in north and central south China (covering 9.57 × 105 km2), S. javanica is prevalent in the south and east regions (covering 6.41×105 km2), and S. adnata predominantly thrives in the southwest China (covering 1.99×105 km2). Under future climate change scenarios, it is anticipated that S. adnata may migrate to higher latitudes while S. javanica may shift to lower latitudes. However, potentially suitable areas for S. williamsii may contract under certain scenarios for the years 2050 and 2090, with an expansion trend under the SSP585 scenario for the year 2090. Our study emphasizes the importance of climatic variables in influencing the potential geographic distribution of Sambucus species. These findings provide valuable theoretical insights for the preservation, cultivation, and utilization of Sambucus medicinal plant resources in the context of ongoing climate change.

A particular threat posed by climate change for biodiversity conservation, one which has scarcely been studied, is the overlap of the potential distribution areas in phylogenetically closely related species. In this study, Species Distribution Modelling (SDM) was used to investigate the potential changes in the distribution of Delphinium bolosii and D. fissum subsp. sordidum under future climatic scenarios. These two closely related and endangered endemic species from the Iberian Peninsula do not have complete reproductive barriers between them. The two models selected different predictors with a similar effect in the biological cycle. Both taxa need low winter temperatures to break seed dormancy and sufficient rainfall to complete the flowering and fruiting stages. The current potential distribution areas of both taxa do not currently overlap. However, the results showed that potential changes may take place in the species’ distribution range under future climate scenarios. The models predict a reduction of the potential distribution area of D. bolosii while, conversely, the potential distribution area of D. fissum subsp. sordidum increased. In both cases, the predicted contraction in range is very high, and loss of habitat suitability in some current localities is worrying. Notwithstanding, the models do not predict overlaps of potential areas under climate change scenarios. Our findings can be used to define areas and populations of high priority for conservation or to take action against the impacts of climate change on these endangered species.

Revealing the spatial distribution of adaptive genetic variation is both a challenging and crucial task in evolutionary ecology, essential for understanding local adaptation within species, and in management, for predicting species responses to future climate change. This understanding is particularly important for long-lived tree species, which may not be able to migrate quickly enough to adapt to rapid climate changes and may need to rely on their standing genetic variation. In this study, we focused on Cryptomeria japonica, a major component of Japan's temperate forests and an important forestry species adapted to the humid environment of monsoon Asia. We extracted climate-associated genetic variation from the entire genome and evaluated its distribution and vulnerability under future climate scenarios using spatial modeling techniques. We analyzed 31,676 high-quality SNPs from 249 individuals across 22 natural populations of C. japonica, covering its entire distribution range. We identified 239 candidate climate-associated SNPs and found winter temperature, summer precipitation, and winter precipitation as the most significant factors explaining the genetic variation in these SNPs. The climate-associated genetic variation deviated from non-associated (neutral) genetic variation in the opposite (the Sea of Japan and Pacific Ocean) sides of Japanese archipelago, suggesting natural selection of different climate conditions in these regions. Difference in estimated allele frequency at the climate-associated loci (genetic offset) between the present and future (2090 in the SSP5-8.5 scenario) climate conditions was predicted to be larger in three areas (not only southwestern Japan but also coastal area on the Sea of Japan side and inland area on the Pacific Ocean side in northeastern Japan). This prediction implies the discrepancy between standing genetic variation at the present and that adaptive to the future climate in these areas, which underscores the necessity for proactive management to adjust the adaptive genetic variation.

Changes in land use and climate are the main drivers of change in soil organic matter contents. We investigated the impact of the largest policy-induced land conversion to arable land, the Virgin Lands Campaign (VLC), from 1954 to 1963, of the massive cropland abandonment after 1990 and of climate change on soil organic carbon (SOC) stocks in steppes of Russia and Kazakhstan. We simulated carbon budgets from the pre-VLC period (1900) until 2100 using a dynamic vegetation model to assess the impacts of observed land-use change as well as future climate and land-use change scenarios. The simulations suggest for the entire VLC region (266 million hectares) that the historic cropland expansion resulted in emissions of 1.6⋅ 1015 g (= 1.6 Pg) carbon between 1950 and 1965 compared to 0.6 Pg in a scenario without the expansion. From 1990 to 2100, climate change alone is projected to cause emissions of about 1.8 (± 1.1) Pg carbon. Hypothetical recultivation of the cropland that has been abandoned after the fall of the Soviet Union until 2050 may cause emissions of 3.5 (± 0.9) Pg carbon until 2100, whereas the abandonment of all cropland until 2050 would lead to sequestration of 1.8 (± 1.2) Pg carbon. For the climate scenarios based on SRES (Special Report on Emission Scenarios) emission pathways, SOC declined only moderately for constant land use but substantially with further cropland expansion. The variation of SOC in response to the climate scenarios was smaller than that in response to the land-use scenarios. This suggests that the effects of land-use change on SOC dynamics may become as relevant as those of future climate change in the Eurasian steppes.