Future Climate Change Research Articles

Hydrological response to future changes in climate and land use/land cover in the Hanjiang River Basin

Hydrological response to future changes in climate and land use/land cover in the Hanjiang River Basin

Analyzing the Distribution Patterns of Endemic Quercus vulcanica (Boiss. et Heldr. ex) Kotschy in Türkiye Under Climate Change Using Ensemble Modeling

Quercus vulcanica (Boiss. et Heldr. ex) Kotschy (Kasnak oak), one of the 18 Quercus species naturally distributed in Anatolia, is an endemic species with a restricted distribution range. In accordance with the International Union for the Conservation of Nature (IUCN) Red List of Endangered Species classification, Quercus vulcanica is designated as a species of low risk (LC: Least Concern). However, it is predicted that the habitat of Quercus vulcanica will narrow and that the species will become endangered as a result of potential climate change scenarios in the future. The aim of this study was to estimate the temporal and spatial distribution of Quercus vulcanica in Anatolia during the LGM, as well as to examine the impact of present and future climate changes on the species. In this context, principal component analysis was applied to 19 bioclimatic variables of the Community Climate System Model Version 4 (CCSM4) climate model, with nine variables identified for use in modeling. Habitat suitability was estimated using the Biodiversity Modeling (BIOMOD) ensemble modeling method, which combines the results of nine different algorithms through the R package ‘biomod2’, applying both committee averaging and weighted average approaches. To evaluate the performance of the models, the Area Under the Curve (AUC) of Receiver Operating Characteristics (ROC), True Skill Statistics (TSS), KAPPA and Boyce Index were calculated. The contributions of the environmental variables were determined on a per-algorithm-model basis. The results of the analyses show that the bioclimatic variables that contribute the most to the distribution of the species are Bio8. The modeling results show that Quercus vulcanica is capable of occupying suitable habitat areas across the majority of Anatolia during the Last Glacial Maximum (LGM). It is anticipated that future projections will indicate a notable reduction in the extent of suitable habitat for the species, with the remaining areas confined to the vicinity of the Ilgaz Mountains, Köroğlu Mountains and Bolkar Mountains. Given the increasing destruction that Quercus vulcanica, an endemic plant, will be adversely affected by as a result of human impacts and climate change, it is of the highest importance to develop adaptation strategies with a view to protecting the species’ habitat and the sustainability of the species.

Distinct Ecological Habits and Habitat Responses to Future Climate Change in Two Subspecies of Magnolia sieboldii K. Koch, a Tree Endemic to East Asia.

Magnolia sieboldii, an important ornamental tree native to East Asia, comprises two subspecies in distinct regions, with wild populations facing suboptimal survival. This study aimed to understand the potential habitat distribution of these subspecies under future climate-change conditions to support climate-adaptive conservation. The maximum entropy (MaxEnt) model was used with occurrence and environmental data to simulate the current and future suitable habitats under various climate scenarios. Precipitation in the warmest quarter played a crucial role in shaping the potential habitats of both subspecies; however, they exhibited different sensitivities to temperature-related variables and altitude. Magnolia sieboldii subsp. sieboldii is more sensitive to temperature seasonality and annual mean temperature, whereas Magnolia sieboldii subsp. japonica is more affected by altitude, mean temperature in the driest quarter, and isothermality. Currently, the subsp. sieboldii is predicted to have larger, more contiguous suitable habitats across northeastern China, the Korean Peninsula, and Japan, whereas the subsp. japonica occupies smaller, more disjunct habitats scattered in central and western Japan and the southern Chinese mountains. These two subspecies will respond differently to future climate change. Potentially suitable habitats for subsp. sieboldii are expected to expand significantly northward over time, especially under the SSP585 scenario compared with the SSP126 scenario. In contrast, moderately and highly suitable habitats for the subsp. japonica are projected to contract southward significantly. Therefore, we recommend prioritizing the conservation of the subsp. japonica over that of the subsp. sieboldii. Strategies include in situ and ex situ protection, introduction and cultivation, regional hybridization, and international cooperation. Our study offers valuable insights for the development of targeted conservation strategies for both subspecies of M. sieboldii to counteract the effects of climate change.

A GIS-coupled thermal response model for predicting the population growth potential of the red cotton bug, Dysdercus koenigii (Fabricius) (Hemiptera: Pyrrhocoridae) in India under climate change conditions

Recently, the red cotton bug has become a significant menace to cotton in India. With the potential for increased habitat suitability due to predicted temperature rise of 2.5°C under future climate change in India, this pest could become even more severe in certain regions. Addressing the knowledge gap on the temperature-driven population growth of this pest is crucial for developing a climate-resilient pest management strategy. In this study, life history data gathered at various constant temperatures (15°C to 35°C) were used to estimate temperature thresholds and thermal requirements for the red cotton bug development. Stochastic estimation of life table parameters and validation with real-time weather data were performed. The phenology model, integrated into a geographic information system, projected the future pest status based on SSP126 temperature change scenarios for the year 2050. The temperatures between 8.35 – 10.83 °C were estimated as lower developmental thresholds for various immature life stages. The optimum and upper threshold temperatures estimated for different life stages ranged between 22.14 – 28.32°C and 35.80 – 39.08°C, respectively. Thermal requirements of 447.97 degree days for life cycle completion were estimated. The optimum immature survival rates (>70%) were observed at temperatures between 25-30°C. The temperature-dependent decrease in generation times from 90.45 days (15 °C) to 25.44 days (35°C) was observed, whereas maximum fecundity was recorded at 32°C. Simulation at fluctuating temperatures across different cotton growing locations provided reasonably similar results on potential population increase (finite rate of increase: 0.99 - 1.04 females/female/day and a generation time of 44.25 – 83.97 days). Risk mapping highlighted moderate to high suitability (ERI >0.4, GI > 6, and AI >4) of various cotton growing areas under current climate, and projected shifts in suitability under future climate change. The study has generated information valuable for implementing effective and timely pest management strategies for RCB. Integrating the field observations with model outputs can enhance a practical understanding of red cotton bug dynamics.

Analyzing the impact of phosphorous and nitrogen on Castanopsis sclerophylla early growth stages

Plant growth elements, particularly nitrogen (N) and phosphorus (P) are vital for their growth and development, particularly for understory vegetation and their excess limits the net productivity of terrestrial ecosystems. This study focuses on the understory vegetation responds and adaptation to key essential nutrients under changing climate scenarios in subtropical evergreen broad-leaved forests, still needs research attention. this, we set up an experiment taking four treatments in a 50-year-old Castanopsis sclerophylla secondary forest under (a) control (CK), (b) N, (c) P, and (d) combined N and P addition, applied to natural forest regeneration seedlings of C. sclerophylla attained similar growth parameters of diameter of 3 cm and 10 cm height. In addition, carbon, N, P, and non-structural carbohydrates (NSC) were determined through the anthrone colorimetric approach in different parts of seedlings. Results show that the combined N + P application enhanced the N and P by 14.48 %−140.55 % in the seedlings in both dry and wet seasons, respectively. However, during wet season, the content of NSC in the plant leaves significantly exceeded under P addition. Remarkably, CK showed increased P in the growing season but lower during the dry season. Furthermore, the root starch content of seedlings showed a significant increase under the application of N and P compared to combined N + P, ranging between 45.60 % and 58.70 %. Overall, the plant growth is attributed to N and P intake. The nutrient addition and seasonal variations have a coupled effect on seedling growth as proved in the in the natural open forest experiment. The study outcomes emphasize that the alterations in NSC allocation in the roots and leaves of C. sclerophylla seedlings under N + P addition could enhance their adaptation to future global climate changes, drought conditions, and high N concentrations.

Relating ten years of rock temperature monitoring to rockwall weathering processes in steep mountain valleys in western Norway

Most existing studies on rockwall frost regimes and frost weathering at rockwalls focus on permafrost-affected rockwalls. However, a high share of rockwall surface areas in Norway and in many other cold-climate environments is actually free of permafrost. It is therefore of interest how these permafrost-free rockwall systems will respond to future changes in air and rock temperatures. In this study, we report field measurements conducted at rockwalls beneath the current permafrost limit and investigate thermal regimes at rockwalls that include both rockwall areas with and without permafrost. We present a unique dataset of up to ten years of rockwall temperature measurements from ten temperatures sensors installed in two mountain valleys in western Norway. An analysis of the different rockwall thermal regimes with respect to rock weathering and associated rockfall supply for both, permafrost-affected and permafrost-free rockwalls is provided. The highest intensity of recent rockwall weathering including determined rockwall retreat rates and associated rockfall supply is detected for northeast-facing rockwalls followed by south-facing rockwalls in our study area. Frost cracking activity, probably in the form of segregation ice growth, seems to be an important factor particularly for the high weathering intensity on northeast-facing rockwalls whereas solar radiation-induced thermal stresses, which favour incremental subcritical crack growth, is assumed to play a relevant role in the moderate weathering intensity on south- and southwest-facing rockwalls. A mean annual and study area-wide rockwall retreat rate of 0.24 mm yr−1 is estimated for our ten-year investigation period (2010−2020) which is comparable to other published rates in similar lithologies and climates. As it can be assumed that seasonal frost regimes and permafrost will react differently to ongoing and future climate changes, more attention should be paid to analyse these two different thermal regimes with respect to possible varied implications for mechanical rockwall weathering and associated rockfall supply.

Impact of Summer Air Temperature on Water and Solute Transport on a Permafrost‐Affected Slope in West Greenland

AbstractIn Arctic landscapes, the active layer forms a near‐surface aquifer on top of the permafrost where water and nutrients are available for plants or subject to downslope transport. Warmer summer air temperatures can increase the thickness of the active layer and alter the partitioning of water into evapotranspiration and discharge by increasing the potential evapotranspiration, the depth to the water table, and changing the flow paths but the interacting processes are poorly understood. In this study, a numerical model for surface‐ and subsurface cryo‐hydrology is calibrated based on field observations from a discontinue permafrost area in West Greenland considered sensitive to future climate changes. The validated model is used to simulate the effect of three summers with contrasting temperature regimes to quantify the variations in the active layer thickness, the resulting changes in the water balance, and the implications on solute transport. We find that an increase of summer air temperature by1.6°C, under similar precipitation can increase the active layer thickness by 0.25 m, increase evapotranspiration by 5%, and reduce the total discharge compared to a colder summer by 9%. Differences in soil moisture and evapotranspiration between upslope and downslope were amplified in a warm summer. These hydrological differences impact solute transport which is 1.6 times faster in a cold summer. Surprisingly, we note that future warmer summer with increase in permafrost thaw may not necessary lead to an increase in discharge along a hill slope with underlying permafrost.

Advances in giant clam (Tridacnidae spp.) sclerochronology and sclerochemistry

Understanding past environmental change through high-resolution palaeoenvironmental proxy reconstructions provides crucial baselines for understanding global environmental changes, particularly during the Quaternary Period. Such data are crucial for testing and refining climate models to enable better adaptations to current and future climate changes. Giant clams (Tridacnidae spp.), the largest bivalve mollusc in the Indo-Pacific region, possess distinctive features such as long lifespan, rapid growth, high-resolution growth patterns, wide distribution habitat, and stable shell geochemical composition. These attributes make giant clams a promising and dependable novel palaeoenvironmental archive, offering numerous available geochemical proxies. In this review, we examined preview studies on giant clams conducted for sclerochronology research, spanning publications from 1986 to 2023. The previous studies have proven that isotopic and trace elements proxies of the giant clam, including δ18O, δ13C, Sr/Ca, Mg/Ca, Ba/Ca, and Fe/Ca, can faithfully reconstruct palaeoclimate records including sea surface temperature, dissolved inorganic carbon, insolation, extreme weather events and primary productivity at ultra-high resolution. These proxies have been successfully employed for palaeoclimatic and palaeoenvironmental reconstructions from the Miocene to the present across a range of locations from South Japan to Northern Australia to the Red Sea. These studies have illuminated changes in interannual climate cycles, climate variation, and human migrations over thousands to millions of years. They have generated quantitative records that are valuable for testing and refining numerical climate models, understanding the relationship between past climate cycles and future climate variability, and providing insights into human-environment interactions over time. In the end, the review also addresses the challenges and provided recommendations for future research, highlighting persisting gaps in understanding the influence of microstructure on the shell, age dating of fossil samples, uncertainty in proxies, the need for tank experiments, and access to ultra-high resolution palaeoenvironmental records.

Lineage Differentiation and Genomic Vulnerability in a Relict Tree From Subtropical Forests.

The subtropical forests of East Asia are renowned for their high plant diversity, particularly the abundance of ancient relict species. However, both the evolutionary history of these relict species and their capacity for resilience in the face of impending climatic changes remain unclear. Using whole-genome resequencing data, we investigated the lineage differentiation and demographic history of the relict and endangered tree, Bretschneidera sinensis (Akaniaceae). We employed a combination of population genomic and landscape genomic approaches to evaluate variation in mutation load and genomic offset, aiming to predict how different populations may respond to climate change. Our analysis revealed a profound genomic divergence between the East and West lineages, likely as the result of recurrent bottlenecks due to climatic fluctuations during the glacial period. Furthermore, we identified several genes potentially linked to growth characteristics and hypoxia response that had been subjected to positive selection during the lineage differentiation. Our assessment of genomic vulnerability uncovered a significantly higher mutation load and genomic offset in the edge populations of B. sinensis compared to their core counterparts. This implies that the edge populations are likely to experience the most significant impact from the predicted climate conditions. Overall, our research sheds light on the historical lineage differentiation and contemporary genomic vulnerability of B. sinensis. Broadening our understanding of the speciation history and future resilience of relict and endangered species such as B. sinensis, is crucial in developing effective conservation strategies in anticipation of future climatic changes.

Spatial Distribution Pattern of Aromia bungii Within China and Its Potential Distribution Under Climate Change and Human Activity.

Aromia bungii is a pest that interferes with the health of forests and hinders the development of the fruit tree industry, and its spread is influenced by changes in abiotic factors and human activities. Therefore, exploring their spatial distribution patterns and potential distribution areas under such conditions is crucial for maintaining forest ecosystem security. This study analyzed the spatial differentiation characteristics of the geographic distribution pattern of A. bungii in China using Moran's I and the Getis-Ord General G index. Hot spot distribution areas were identified using Getis-Ord Gi*. An optimized MaxEnt model was used to predict the potential distribution areas of A. bungii within China under four shared economic pathways by combining multivariate environmental data: (1) prediction of natural environmental variables predicted under current climate models; (2) prediction of natural environmental variables + human activities under current climate models; and (3) prediction of natural environmental variables under the future climate models (2050s and 2070s). Meanwhile, MigClim was used to simulate the unoccupied suitable area in the presence of obstacles under future climate change. The results showed that human activities, minimum temperature of the coldest month, and precipitation of the wettest month had positive effects on the distribution of A. bungii. However, in the current period, human activities drastically reduced the survival area of A. bungii, and its suitable distribution area was mainly concentrated in the eastern and central regions of China. Under the influence of climate change in the future, the habitat of A. bungii will gradually increase. Additionally, the MigClim model indicates that the area unoccupied by A. bungii has been on a continuous increasing trend. This study provides a positive reference for the prevention and control of A. bungii and the maintenance of forest health and ecosystem security, and provides important theoretical guidance for researchers, policymakers, and governments.

Estimating potential vegetation distribution and restoration in a biodiversity hotspot region under future climate change

Estimating potential vegetation distribution and restoration in a biodiversity hotspot region under future climate change

Root physiological and morphology processes co-regulate the growth of Chinese-fir saplings in response to warming and precipitation reduction in the sub-tropical regions

Subtropical China is projected to experience elevated temperature greater than the mean global temperature increase and is accompanied by reduced precipitation. The plasticity of roots to changing environment strongly influences ecosystem feedbacks to climate change. However, knowledge gaps on the individual and combined effects of warming and precipitation reduction on root systems hinder our ability to accurately predict the growth and adaptability of forests under future climate change. To examine the effects of warming (W) and precipitation reduction (P) on roots physiology and morphology of Chinese-fir saplings, we used a randomized complete block design with factorial soil warming (ambient, ambient + 5℃) and precipitation reduction (ambient, ambient-50%) treatments. A full excavation method was adopted to obtain roots, then we measured the root physiology (osmoregulatory substances, oxidant substances, protective enzymes, endogenous hormones), morphology (specific root length, SRL; surface root area, SRA; root tissue density, RTD). The content of carbon and nitrogen, isotopes (δ13C and δ15N); soil temperature, soil moisture and sapling growth were also measured. We found that compared with the control, W decreased the abscisic acid (IAA) content; P increased the contents of hydrogen peroxide (H2O2) and proline (Pro), and decreased the contents of IAA and cytokinin (CTK); warming plus precipitation reduction (WP) increased the Pro content, and decreased the contents of IAA and CTK. In addition, the effects of W and P on root morphology varied with soil depth and root diameter class. W, P, and WP all increased fine root SRL and SRA in deep soil. Warming and precipitation reduction could affect physiological traits (e.g. non-enzymatic substances and antioxidant enzymes) and subsequently morphological traits via influencing soil environment and root tissue chemistry. Collectively, the results indicated that Chinese-fir saplings responded to warming and precipitation reduction by comprehensive regulation of the non-enzymatic substances (e.g., osmotic substances and endogenous hormones) of fine roots and changing root morphological characteristics in deep soil.

Balancing Water Yield and Water Use Efficiency Between Planted and Natural Forests: A Global Analysis.

Climate warming is projected to affect hydrological cycle in forest ecosystems and makes the forest-water relationship more controversial. Currently, planted forests are gaining more public attention due to their role in carbon sequestration and wood production relative to natural forests. However, little is known about how the global patterns and drivers of water yield and water-use efficiency (WUE) differ between planted and natural forests. Here, we conduct a global analysis to compare water yield and WUE in planted and natural forests using 946 observations from 112 published studies. The results showed that global average water yield coefficient was 0.29 for planted forests and 0.34 for natural forests. Planted forests exhibited lower water yield coefficient (p < 0.05) in three climatic regions (arid, dry subhumid, and humid regions), but higher (p < 0.01) WUE only in arid region, compared with natural forests. Both water yield coefficient and WUE in planted forests were significantly lower (p < 0.05) than that in natural forests for stand characteristic groups (stand density, average tree height, leaf area index [LAI], and basal area). Additionally, stand density within the ranging between 1000 to 2000 stem ha-1 can maximize the water yield and WUE in planted and natural forests. Water yield coefficient in planted forests was primarily controlled by the factors related to tree growth (i.e., tree height, DBH), while that of natural forest mainly affected by stand structure (i.e., LAI, stand density, DBH). WUE in planted forest was more sensitive to climate than in natural forests. This work highlights the critical role of natural forests in water supply and the importance of tree species selection and stand management (e.g., stand density adjustment) in plantations in future forest restoration policies and climate change mitigation.

Assessing spatiotemporal variations of soil organic carbon and its vulnerability to climate change: A bottom-up machine learning approach

Soil organic carbon (SOC) is a crucial component of the terrestrial carbon cycle and essential for agricultural productivity. Quantifying its sensitivity to future climate change is vital for sustaining agricultural practices and mitigating greenhouse gas emissions. However, this remains a challenge as long-term SOC data are scarce and substantial uncertainties regarding future climate scenarios. This study presents a bottom-up machine learning framework to assess the spatiotemporal variations of SOC and its vulnerability to climate change in the Jinghe River Basin, a typical loess hilly and gully watershed. Firstly, the long-term (2000–2023) dynamics of SOC was estimated by integrating in-situ measurements with machine learning techniques. Results show that the high SOC values are primarily distributed in the farmland of the mountain-loess transition zone, while the low-value areas are mainly found in the loess region. During the study period, the SOC content exhibited a slight increasing trend with a rate of 0.02 ​g ​kg−1 ​yr−1 (p ​= ​0.449). The vulnerability of farmland surface SOC to future climate change was then evaluated by combining a robust machine learning model with the bottom-up framework. To this end, the study explored a wide range of possible future climates to identify critical climate thresholds and their spatial variation across the basin’s farmlands. Based on this analysis, this research found that the farmland in the northern basin is generally more susceptible to changing climate with even marginal rises in temperature could lead to severe loss in SOC. These results highlight the need for proactive climate adaptation strategies to safeguard SOC in vulnerable agricultural landscapes, ensuring soil health and resilience in the face of climate change.

Mowing mitigates the negative impacts of long-term warming on community composition and niche characteristics of alpine meadow on the Tibetan Plateau

Climate warming and human disturbance are supposed to have significantly impacted the alpine grasslands. However, it is still unclear how human activity affects the community composition and niche characteristics in response to warming. We conducted a two-factorial experiment in an alpine meadow, and set up four treatments: warming, mowing, warming with mowing, and control. Based on the investigation of community composition and niche characteristics, we evaluated the impacts of soil carbon, nitrogen, and phosphorus on species niche overlap. The results showed that mowing significantly increased species richness of Grass, Sedge, Forbs and the importance value of Sedge compared to warming (P < 0.05). The niche breadth of species (>50%) was reduced by warming, but increased under mowing. The niche overlap mainly occurred between Grass and Forbs in warming, while it was evenly distributed among species after mowing, which alleviated the negative effects of warming on interspecific competitiveness. Warming increased the number of species pairs with a niche overlap value >0.9 by 24.15%, while warming with mowing decreased it by 2.7%. The number of species pairs with niche overlap was significantly correlated with soil total nitrogen and soil available nitrogen (P < 0.05). In particular, the species pairs with highly competitive showed a greater dependency on soil nitrogen. Our work highlights that moderate utilization and soil nitrogen are two crucial factors influencing the response of community structure in alpine meadows to future climate change. The study provides an important reference for predicting and addressing the impact of global climate change on adaptive management and grassland protection.

Decline in Coupling Between Vegetation Photosynthesis and Greening in Northern Ecosystems During the Photosynthesis-Up Period.

The maximum seasonal vegetation photosynthesis (Phomax) is crucial to regulating the global carbon dynamics. Of particular importance are the seasonal increments in vegetation photosynthesis (ΔPho), which provide key insights into understanding Phomax. However, the interannual variability of ΔPho within the photosynthesis-up period (PUP) and its influencing factors remain unclear. To address this gap, we identified PUP and quantified the multi-year characteristics of ΔPho using satellite-derived solar-induced chlorophyll fluorescence. We further investigated the response of ΔPho in northern ecosystems to climate change and vegetation greening by integrating climate data and the normalized difference vegetation index. In the northern ecosystems, longer PUP often spatially correlated with a higher ΔPho. An increasing trend was evident regarding the multi-year variations in ΔPho, suggesting enhanced vegetation photosynthesis within the PUP. This phenomenon is primarily driven by increased solar radiation and intensified vegetation greening. Additionally, based on the results derived from satellite data, we found three pieces of evidence for the decoupling trend between vegetation photosynthesis and greening under the influence of climate change: first, the inconsistent trends between ΔPho and greening; second, the declining moving trend in the correlation coefficient between ΔPho and greening, approximately 9.17 × 10-4; and third, the weakened dominant role of greening on ΔPho. These findings were further supported by results from ecosystem model simulations. In summary, this study provides insights into the interannual variability of ΔPho and its influencing factors and indicates that vegetation dynamics and terrestrial carbon cycle are likely to become more complex under future climate change scenarios.

Nonlinear Radiative Response to Patterned Global Warming due to Convection Aggregation and Nonlinear Tropical Dynamics

Abstract Climate responses to global warming exhibit large dependence on the spatial pattern of sea surface temperature (SST) changes. A Green’s function (GF) approach—predicting the global climate response to a complex SST pattern change as the linear superposition of the response to finite-area SST perturbations evaluated in isolation—has been used to systematically evaluate and understand the top of atmosphere (TOA) radiation response to patterned warming. However, in general, the linear GF approach fails for TOA radiation reconstruction under future global warming scenarios in coupled models. Here, we show that the linear superposition of global mean TOA radiation responses to large SST warming perturbations at multiple patches (the GF approach prediction) overestimates the actual response to simultaneous multipatch perturbation. This is because the linear superposition overestimates tropical large-scale convection aggregation strengthening upon localized heating that enhances longwave radiative cooling, which is further explained by the overestimation of circulation response and associated horizontal water vapor transport. The nonadditivity of TOA radiation response is caused by the nonadditivity of convection aggregation, ultimately rooted in nonlinear tropical dynamics. We also demonstrate that the prediction error of the GF approach grows with decreasing patch size (equivalently, increasing patch number). We conclude that using the GF approach to predict future climate change could overestimate longwave radiative cooling and underestimate (effective) climate sensitivity. Numerical experiments may be used to identify specific perturbation patterns where the errors are smaller than the signal. Our research also highlights that an increase in the degree of large-scale convection aggregation has a nonlinear and negative feedback for mean warming.

Seagrass Tolerance to Simulated Herbivory Along a Latitudinal Gradient: Predicting the Potential Effects of Tropicalisation

ABSTRACTThe polewards range expansion of tropical herbivorous fish into temperate latitudes is leading to overgrazing of marine habitats and community phase shifts in some regions. Here, we test the potential effects of increased herbivory on the temperate habitat‐forming seagrass Posidonia australis. We used a series of simulated herbivory experiments to predict the potential impacts of climate‐mediated increases in seagrass consumption along P. australis entire latitudinal range (~9° latitude) in eastern Australia (1700 km of coastline). We subjected treatment plots to two levels of simulated herbivory (10% or 80% of leaves clipped) and compared them to unclipped controls. We measured seagrass leaf growth rates and tissue chemical traits: carbohydrates in rhizomes, leaf phenolics, and nutrients (carbon, nitrogen, and C:N ratio) in leaves and rhizomes. At the warmest range‐edge population, we also tested how responses to increased herbivory may vary between summer and winter, or with repeated clipping events. Clipped shoots maintained growth rates similar to unclipped controls despite losing up to 80% of leaf biomass. This was consistent along the full latitudinal range and after repeated simulated herbivory at the northernmost location. One‐off clipping events impacted plant architecture, increasing the number of subdividing shoots. At the species range edge, leaves grew more in winter than in summer, and clipping tended to lower seagrass growth only in winter; however, higher levels of shoot subdivision were produced over summer than in winter. Plant chemical traits could not explain consistently the growth patterns observed despite some traits varying with latitude (e.g., leaf nitrogen content decreased with latitude and C:N ratio increased) and/or simulated herbivory. Synthesis: P. australis growth is not affected by increases in simulated herbivory and may be relatively resilient to future increases in seagrass consumption, suggesting that this species could be a relative ‘winner’ under future climate change conditions that lead to enhanced herbivory.

Net primary productivity of paleo-peatlands linked to deep-time glacial periods in the late Carboniferous and early Permian icehouse interval

Peatlands, an important organic carbon reservoir, play a crucial role in the global carbon cycle. The carbon accumulation of peatlands, reflected by net primary productivity (NPP), can have an impact on global carbon cycling and climate change. The late Carboniferous - early Permian is an icehouse period, during which numerous thick coal beds were accumulated in the North China Block (NCB) located within a low-latitude area, providing an opportunity for studying the carbon cycling under the glacial and interglacial climates. In this study, spectral analysis was performed on the natural gamma-ray (GR) logs of the Benxi, Taiyuan and Shanxi formations of the late Carboniferous to early Permian in a borehole section located within the Ordos Basin in western NCB. Cyclic signals related to astronomical orbital parameters were identified, including long eccentricity (~405 kyr), short eccentricity (~125 kyr and ~ 95 kyr), and obliquity (~35.5kyr). A floating astronomical time scale was established by using the long eccentricity signal, and this time scale was further used to constrain the durations of the accumulation of coal-forming paleo-peatlands. The paleo-peatland for the C8 + 9 coal seam (9 m thick) of the Taiyuan Formation lasted approximately 203 kyr, and the paleo-peatland for the C5 coal seam (4 m thick) of the Shanxi Formation lasted approximately 46 kyr. Using this timeframe and an estimation of carbon loss during coalification, the carbon accumulation rates of the late Carboniferous - early Permian low-latitude peatlands are calculated to be 104.7 ± 14.9 g·C·m−2·a−1for the C8+9 coal seam and 192.6 ± 11.6 g·C·m−2·a−1for the C5 coal seam. The NPP of the paleo-peatlands, which deducts a part of carbon loss caused by the loss of CO2 and CH4, can be calculated from the carbon accumulation rates. The calculated average NPP of the paleo-peatlands for the C8+9 seam was 199 ± 28 g·C·m−2·a−1, and that of the C5 seam was 366 ± 22 g·C·m−2·a−1. In combination of the absolute time scale calibrated by high-precision UPb dates from Palougou section in western NCB, the depositional time of the investigated strata was constrained to be from 300.1 ± 0.5 Ma to 294.3 ± 0.5 Ma. The coal seams of the late Carboniferous to early Permian in the NCB corresponds to interglacial interval around ~298 Ma. The peatland with a lower NPP corresponds to the warming stage and the peatland with a higher NPP corresponds to the cooling stage. This implies that a lower NPP of paleo-peatland tend to be less efficient in carbon storage, and could not reduce the atmospheric CO2 substantially. In contrast, a higher NPP of paleo-peatland tend to accelerate carbon fixation, leading to temperature decrease and the termination of interglacial interval in early Permian. The results of this study could provide insights into the relationship between the development of paleo-peatlands and the record of the paleoclimates during the same period, and could be helpful for the prediction of future climate change.

Multi-Omics Inform Invasion Risks Under Global Climate Change.

Global climate change is exacerbating biological invasions; however, the roles of genomic and epigenomic variations and their interactions in future climate adaptation remain underexplored. Using the model invasive ascidian Botryllus schlosseri across the Northern Hemisphere, we investigated genomic and epigenomic responses to future climates and developed a framework to assess future invasion risks. We employed generalized dissimilarity modeling and gradient forest analyses to assess genomic and epigenomic offsets under climate change. Our results showed that populations with genomic maladaptation did not geographically overlap with those experiencing epigenomic maladaptation, suggesting that genomic and epigenomic variations play complementary roles in adaptation to future climate conditions. By integrating genomic and epigenomic offsets into the genome-epigenomic index, we predicted that populations with lower index values were less maladapted, indicating a higher risk of future invasions. Native populations exhibited lower offsets than invasive populations, suggesting greater adaptive potentials and higher invasion risks under future climate change scenarios. These results highlight the importance of incorporating multi-omics data into predictive models to study future climate (mal)adaptation and assess invasion risks under global climate change.