Future Climate Change Scenarios Research Articles

Deepening our understanding of the environmental influences on the reproductive dynamics of the main fishery stock of Argentine hake, Merluccius hubbsi, in the southwestern Atlantic Ocean

AbstractThis study analyzed the inter‐annual variability in the reproductive dynamics of the Argentine hake from Patagonian waters during the last 20 years concerning the environmental conditions and the nutritional status of females. Macroscopic and histological information on gonadal maturity, female condition factor (K), and oceanographic data at different sampling sites throughout the studied region were obtained from research surveys carried out during the main spawning season of this species. Four stages, according to the maturity ovarian phases composition, were assigned annually at each sampling site to assess reproductive dynamics: vitellogenesis, ovulation, regression, and resting. The spatial pattern of inter‐annual variability in reproductive dynamics was described, and the influence of temperature and female condition on the probability of ovulation and regression was assessed using generalized linear models. The area with the lowest inter‐annual variability in the hake reproductive dynamics was observed between 43 and 45°S (50 to 80 m depth) in relation to ovulation events. The vitellogenesis stage was more frequently found adjacent to the reproductive area, whereas the regression was mainly observed in deeper waters. Both bottom and surface temperatures explained the ovulation and regression stages, showing a positive and negative relationship, respectively. Lower values of the K factor, associated with low food availability, were further linked to the occurrence of regression. Finally, it is worth noting that the relationship observed between the ovulation/spawning dynamics of Argentine hake and water temperature suggests that the reproductive success of this species could be affected in the future scenario of climate change.

Effects of the nitrification inhibitor nitrapyrin on N2O emissions under elevated CO2 and rising temperature in a wheat cropping system

Nitrogen (N) fertilizer input will likely increase to meet the food demands of a growing population under climate change conditions, characterized by increasing atmospheric CO2 concentration and temperature. Nitrification inhibitors have the potential to reduce N2O emissions from N fertilized croplands. However, it remains unclear whether future climate change scenarios could affect the effectiveness of nitrification inhibitors. In a two-year study, winter wheat (Triticum aestivum L.) was cultivated in climate-controlled growth chambers with an elevated CO2 concentration (ambient +200 μmol mol−1) and increased temperature (ambient +2 °C). Urea was applied with or without nitrapyrin (0.5 % of urea-N). In this study, we measured nitrous oxide (N2O) fluxes, soil ammonium and nitrate levels, and the abundance of five nitrogen-cycling genes related to nitrification (amoA of ammonia-oxidizing bacteria (AOB) and ammonia-oxidizing archaea (AOA)) and denitrification (nirS, nirK and nosZ). Key findings included the following: 1) without nitrapyrin, cumulative N2O emissions were not significantly altered by increased temperature, but decreased 24.9 % by the combination of elevated CO2 and temperature treatment and 17.5 % by the elevated CO2 alone. NO3−-N accumulation occurred in soils under increased CO2 and temperature, both individual and in combination; 2) nitrapyrin effectively reduced AOB abundance, inhibiting NO3−-N accumulation and N2O emission, irrespective of CO2 concentrations and temperature. However, under the combination of elevated CO2 and temperature conditions, the efficiency of nitrapyrin in reducing N2O emission was lower (−13 % to −49 %) than that in the control (−28 % to −65 %) and elevated CO2 (−32 % to −71 %) conditions. This reduced effectiveness of the combined treatment can be attributed to the inability of nitrapyrin to inhibit the AOA, nirS and nirK genes. Thus, nitrapyrin is expected to reduce N2O emissions under future climate change scenarios, but the efficacy may be lower than previously expected when CO2 concentration and temperature increase simultaneously. The indirect effects of nitrapyrin on denitrifiers under climate change scenarios should be considered in future research.

The challenge of closing the climate adaptation gap for water supply utilities

Many drinking water utilities face immense challenges in supplying sustainable, drought-resilient services to households. Here we propose a quantified framework to perform drought risk analysis on ~5600 potable water supply utilities and evaluate the benefit of adaptation actions. We identify global hotspots of present-day and mid-century drought risk under future scenarios of climate change and demand growth (namely, SSP1-2.6, SSP3-7.0, SSP5-8.5). We estimate the mean rate of unsustainable or disrupted utility supply at 15% (interquartile range, 0–26%) and project a global increase in risk of between 30–45% under future scenarios. Implementing the most cost-effective adaptation action identified per utility would mitigate additional future risk by 75–80%. However, implementing the subset of cost-effective options that generate sufficient tariff revenue to provide a benefit-cost ratio that is greater than 1 would only achieve 5–20% of this benefit. The results underline the challenge of attracting the financing required to close the climate adaptation gap for water supply utilities.

MaxEnt-Based Potential Distribution Mapping and Range Shift under Future Climatic Scenarios for an Alpine Bamboo Thamnocalamus spathiflorus in Northwestern Himalayas

Thamnocalamus spathiflorus is a shrubby woody bamboo invigorating at the alpine and sub-alpine region of the northwestern Himalayas. The present investigation was conducted to map the potential distribution of Th. spathiflorus in the western Himalayas for current and future climate scenario using Ecological Niche Modelling (ENM). In total, 125 geo-coordinates were collected for the species presence from Himachal Pradesh (HP) and Uttarakhand (UK) states of India and modelled to predict the current distribution using the Maximum Entropy (MaxEnt) model, along with 13 bioclimatic variables selected after multi-collinearity test. Model output was supported with a significant value of the Area Under the “Receiver Operating Characteristics” Curve (AUC = 0.975 ± 0.019), and other confusion matrix-derived accuracy measures. The variables, namely precipitation seasonality (Bio 15), precipitation (Prec), annual temperature range (Bio 7), and altitude (Alt) showed highest level of percentage contribution (72.2%) and permutation importance (60.9%) in predicting the habitat suitability of Th. spathiflorus. The actual (1 km2 buffer zone) and predicted estimates of species cover were ~136 km2 and ~982 km2, respectively. The predicted range was extended from Chamba (HP) in the north to Pithoragarh (UK) in southeast, which further protracted to Nepal. Furthermore, the distribution modelling under future climate change scenarios (RCP 8.5) for year 2050 and 2070 showed an eastern centroidal shift with slight decline of the species area by ~16 km2 and ~46 km2, respectively. This investigation employed the Model for Interdisciplinary Research on Climate (MIROC6)–shared socio-economics pathways (SSP245) for cross-validation purposes. The model was used to determine the habitat suitability and potential distribution of Th. spathiflorus in relation to the current distribution and RCP 8.5 future scenarios for the years 2021–2040 and 2061–2080, respectively. It showed a significant decline in the distribution area of the species between year 2030 and 2070. Overall, this is the pioneer study revealing the eco-distribution prediction modelling of this important high-altitude bamboo species.

Predicting trajectories of temperate forest understorey vegetation responses to global change

Predicting forest understorey community responses to global change and forest management is vital given the importance of the understorey for biodiversity conservation and forest functioning. Though substantial effort has gone into disentangling the impact of global change on understorey communities, scarcity of information on site-specific environmental drivers across large temporal-spatial scales has limited our ability to predict global change effects at specific forest sites. In this study, using vegetation resurvey and soil data from 1363 plots across temperate Europe, we applied a machine learning approach (gradient boosting regression, GBR) to model and predict site-specific responses of four understorey properties to global change. We applied our final GBR models at 8 forest sites in Austria to validate the model performance, predict understorey trajectories, and evaluate the effect of alternative scenarios for future nitrogen(N) deposition, climate change and forest management on the projected trajectories. Our results showed that the R² value of the four final GBR models on the independent testing dataset ranged between 0.611 and 0.723 and the most important environmental drivers in predicting the trajectory of understorey properties at specific forest sites were soil pH, soil total carbon-to-nitrogen ratio, overstorey shade-casting ability and regional-scale mean annual precipitation. The out-of-sample R2 value of the four final GBR models on the Austrian data ranged between 0.224 and 0.561. The forecasted trajectories for the Austrian forest sites showed that site-specific understorey responses to near-future climate warming were expected to be weak. Under N deposition decreases, the proportion of woody species was predicted to increase, while species richness and total vegetation cover were predicted to decrease. Furthermore, under a closed canopy, the understorey community was predicted to shift towards more woody species and more forest specialists, albeit with reduced species richness and vegetation cover. Given expected warming and declining N pollution pressures, our presented GBR models allow the prediction of trajectories of understorey vegetation responses to global change and management interventions at specific forest sites. Such projections could aid forest management in addressing challenges posed by global change.

Caught out in the cold: Anas platyrhynchos (Mallard) survival decreased during an extreme climatic event

Abstract Extreme climatic events (ECEs) can have profound impacts on individual fitness, affecting survival directly or indirectly. Late winter ECEs may be especially detrimental to fitness due to limited food resources and increased energetic requirements during this time. A polar vortex disruption ECE descended upon the mid-continental United States during February 7–20, 2021 with temperatures as low as −29°C in areas concurrent with ongoing research on Anas platyrhynchos (Mallard) movement ecology and survival in Arkansas, Louisiana, and Tennessee, United States spanning winters 2019–2022. Therefore, we opportunistically evaluated the effects of individual characteristics and latitude on daily survival during the ECE. We extended the survival analysis to March to test for lasting effects of the ECE on survival. We tracked 181 Global Positioning System (GPS)-marked A. platyrhynchos during February 2020, 256 in February 2021, and 324 in February 2022. We documented 22 mortalities during the February 2021 ECE (i.e., 9%), but only 6 mortalities during February 2020 (i.e., 2%) and 2022 (i.e., 1%) when conditions were average. February survival (e.g., 28-day survival) during the ECE was 0.908 (85% CI: 0.879–0.937) but was 0.982 (85% CI: 0.973–0.991) during the 2 non-ECE Februaries. The ECE effect on survival was isolated to February and did not affect March survival. Anas platyrhynchos was 5.4 times more likely to die during the ECE in 2021 compared to non-ECE Februaries. Although large-bodied waterfowl appear cold-tolerant and less sensitive to polar vortex disruptions compared to smaller-bodied passerines, direct mortalities can occur if conditions are severe enough and persist, highlighting the need to consider the influence of ECEs on common, seemingly robust species in future global climate change scenarios.

Modelling the impacts of future droughts and post-droughts on hydrology, crop yields, and their linkages through assessing virtual water trade in agricultural watersheds of high-latitude regions

This study elaborates on the effects of future drought and post-drought conditions on the reliability of global breadbaskets. The study simulates agro-hydrological processes in the Nelson River Basin, a large agricultural watershed in western Canada that supplies food for over 170 countries globally. In temperate zones of higher latitudes, future climate change scenarios suggest that global breadbaskets will likely experience increased precipitation and higher crop yields (Y). This could be perceived as an increased export potential of food from these regions. However, projected drought events in the future can affect agro-hydrological processes, Y, and, therefore, export potentials during and following the drought events. Using a process-based agro-hydrologic model, this research examines the potential impacts of future agricultural droughts and post-drought conditions on hydrological water yield (WYLD), Y, and their linkages through assessing the net virtual water export (NVWE), the water embodied in the production of crops that are destined for export. The results indicate that long-term average Y, NVWE, and WYLD are expected to improve in the future. However, droughts will become more extreme in the future, leading to considerable reductions in Y, NVWE, and WYLD. During the post-drought period, the recovery time for WYLD is considerably longer than Y and NVWE across regions. The slow recovery of WYLD, following an agricultural drought, is related to crop water uptake, which can be controlled by optimization of the cropping pattern. The continuous loss of WYLD during and after prolonged and more frequent droughts in the future can significantly affect not only the environment and several economic sectors but also the irrigated crop production and export potential from these regions. This finding highlights the connections between local hydrology and global trade systems in agricultural watersheds of higher-latitude regions. Future adaptation measures, such as changes in cropping patterns, can preserve WYLD during and after droughts, supporting water and food security.

Up to 80% of threatened and commercial species across European marine protected areas face novel climates under high emission scenario

Marine protected areas (MPAs) are a critical tool for safeguarding marine species and habitats for the future, though the effects of projected climate change raise concerns about their long-term success. Assessing the degree to which MPAs may be exposed to future novel climatic conditions is, therefore, crucial for informing conservation and management actions aimed at ensuring a resilient and thriving ocean in the years to come. Here, we evaluate the future exposure of 398 threatened and commercially important species to novel and extremely novel climatic conditions within European MPAs. We estimated climate novelty through multivariate analyses considering biologically meaningful distribution drivers of temperature, oxygen, pH, and primary productivity from present-day to the end of the 21st-century conditions under contrasting shared socioeconomic pathways (SSP) scenarios—low emission scenario (SSP1–1.9) and high emission scenario (SSP5–8.5). Our findings suggest that, under SSP1–1.9, ~6.5% of species and 0.5% of European MPAs will be at risk due to future novel conditions. In contrast, under SSP5–8.5, 87% of MPAs and 80% of species are projected to be at risk. Notably, up to 100% of species currently located in the MPAs of enclosed and semi-enclosed seas like the Baltic Sea and the Black Sea are projected to be exposed to novel or even extremely novel conditions. Virtually all species in most of those regions will be at risk, suggesting that even new MPAs might not be able to adequately protect them. Comparatively, the Norwegian Sea, North-East Atlantic, and western parts of the Mediterranean and North Seas are expected to be less impacted even under the high emission scenario. Overall, our study advances the understanding of the potential impacts of future climate change scenarios on threatened and commercially important marine species in European MPAs and reinforces the urgent need to meet the Paris Agreement. Our results suggest that existing approaches to marine governance in Europe may be insufficient for ensuring the success of MPAs in light of future impacts and that novel anticipatory forms of governance are needed.

Predicting the Impact of Climate Change on the Future Distribution of Paederus fuscipes Curtis, 1826, in China Based on the MaxEnt Model.

Paederus fuscipes Curtis, 1826, belongs to the Coleoptera order, Staphylinidae family, and Paederus genus (Fabricius, 1775). It has a wide distribution and strong invasive and environmental adaptation capabilities. As a predatory natural enemy of agricultural and forestry pests, understanding its suitable habitat is crucial for the control of other pests. This study, for the first time, uses the MaxEnt model and ArcGIS software, combining known distribution information of P. fuscipes and climate environmental factors to predict the current and future suitable habitat distribution of this insect. The key environmental variables affecting the distribution of P. fuscipes have been identified as mean diurnal range (mean of monthly (max temp-min temp)) (bio2), isothermality (Bio2/Bio7) (*100) (bio3), minimum temperature of the coldest month (bio6), temperature annual range (bio5-bio6) (bio7), mean temperature of the driest quarter (bio9), mean temperature of the coldest quarter (bio11), precipitation of the wettest month (bio13), precipitation of the driest month (bio14), and precipitation seasonality (coefficient of variation) (bio15). The highly suitable areas for P. fuscipes in China are mainly distributed in the hilly regions of Shandong, the North China Plain, and the middle and lower reaches of the Yangtze River Plain, with a total suitable area of 118.96 × 104 km2, accounting for 12.35% of China's total area. According to future climate change scenarios, it is predicted that the area of highly and lowly suitable regions will significantly decrease, while moderately suitable regions will increase (except for the 2090s, SSP2-4.5 scenario). These research findings provide important theoretical support for pest control and ecological conservation applications.

Evaluation of the Pacific oyster marine aquaculture suitability in Shandong, China based on GIS and remote sensing

The Pacific oyster (Crassostrea gigas) is a marine aquaculture species with rapid production growth in recent years. China accounts for nearly 90% of global production by 2021, especially in Shandong province. Evaluating suitability is crucial for ensuring the sustainable growth of Pacific oyster marine aquaculture and achieving a blue transition. This study developed a suitability evaluation model for Pacific oyster marine aquaculture using a Geographic Information System (GIS), Maximum Entropy (MaxEnt) model, remote sensing, and reanalysis data. A literature review and Analytic Hierarchy Process (AHP) were used to establish an evaluation model encompassing water quality, hydrology, climate and meteorology, and socioeconomic factors. The results showed that within a 20 km range of the Shandong coast, 49% of the area was highly suitable, 51% was moderately suitable, and the overall annual high score proportion (HSP) fluctuated around 50%, with higher suitability observed in the spring and autumn. The inner bays of the coastal areas (Laizhou, Rongcheng, Jimo) exhibited high suitability (HSP over 80%); in contrast, the offshore areas (Changdao, Rushan) farther from the coast had lower suitability and showed significant monthly variations. The result was consistent with the spatial distribution and temporal variation of Shandong’s existing Pacific oyster marine aquaculture areas. The study also found that El Niño significantly impacts Rongcheng, Rushan, and Jimo during summer. We predicted an overall increase of suitability in the Shandong offshore areas under future climate change scenarios, with a more significant increase of suitability in the north. El Niño-Southern Oscillation (ENSO) influenced the concentration of parameters such as chlorophyll-a (Chl-a) and total suspended sediment (TSS) in the coastal waters through its impact on precipitation (Pr), resulting in suitability fluctuations.

Prediction of Potential Suitable Distribution of Liriodendron chinense (Hemsl.) Sarg. in China Based on Future Climate Change Using the Optimized MaxEnt Model

Liriodendron chinense (Hemsl.) Sarg. (Magnoliales: Magnoliaceae), valued for its medicinal properties and timber and as an ornamental plant, is now classified as an endangered species. Investigating how future climate-change scenarios might affect the potential geographic distribution of L. chinense will provide a crucial scientific basis for its protection and management strategies. The MaxEnt model was calibrated using the ENMeval optimization package, and then it was coupled with ArcGIS 10.8 to forecast the possible distribution areas of L. chinense in China, utilizing elevation data, bioclimatic factors, and human footprint as environmental variables. The results indicate: (1) The optimal model parameters were set as follows: FC = LQ, RM = 0.5, the MaxEnt model demonstrated high predictive accuracy and minimal overfitting; (2) The total suitable habitat area for the potential geographical distribution of L. chinense during the current period is estimated at 151.55 × 104 km2, predominantly located in central, eastern, and southwestern regions of China; (3) The minimum temperature of the coldest month (bio6), precipitation of the driest month (bio14), precipitation of the driest quarter (bio17), precipitation of the warmest quarter (bio18), elevation (alt), and human footprint (hf) are the main environmental variables determining the suitable habitat distribution of L. chinense; (4) During the period from 2041 to 2060, under the carbon emission scenarios of SSP126, SSP245, and SSP370, the suitable habitat for L. chinense shows varying degrees of increase compared to the current period. However, under the highest concentration scenario of SSP585, the suitable habitat area decreases to some extent; (5) The distribution of L. chinense is likely to move towards higher latitudes and elevations in the future due to changes in the climate. This research provides a comprehensive analysis of the potential impacts of climate change on L. chinense, offering valuable information for its protection and management under future climatic conditions.

Planning for a future of changes: Prioritising areas for conservation of small mammals in the Caatinga, Brazil

AbstractAimHuman land‐use and climate change are two of the main threats affecting biodiversity, especially in arid/semiarid regions. The most effective way to protect the species in these ecosystems against these threats is through the delimitation of protected areas (PAs). However, such PAs need to be targeted cost‐efficiently and consider future climate change. We identify priority areas to preserve small mammal species in the Caatinga in the present and in a future of climate changes. We also evaluate how well these priority areas are protected by currently PAs and identify ways forward to improve their protection.LocationThe Caatinga Dry Forest, Northeast Brazil.MethodsWe use ecological niche models and Zonation spatial prioritisation software to identify the top 30% priority areas to preserve small mammal species under current climate and land use scenarios, besides considering optimistic and pessimistic scenarios of future climate change. We also evaluate how much these priority areas are covered by current PAs, identify ways to further improve their protection using hierarchical mask analysis, and by evaluating species mean distribution coverage.ResultsThe consequences of climate change will not hugely impact the distribution of priority areas for species conservation in the Caatinga. Around 13% of the identified priority areas overlap with current PAs, and planning the expansion of PAs considering integral protection areas increases the coverage of priority areas to more than 18% and captures more than 72% of species suitable area.Main ConclusionsOur prioritisations take into account climate change and provide low risk if conducted as a ‘no‐regrets’ conservation action. These priority areas are poorly supported by the Brazilian PA system, and need of further protection. One cost‐effective option could be to upgrade some sustainable use PAs into more restrictive ones. Securing these priority areas helps preserve the long‐term ecosystem functioning and to prevent biodiversity loss in a changing world.

Brown algae (Phaeophyceae) stressors and illnesses: a review for a sustainable aquaculture under climate change

Brown algae (Phaeophyceae) dominate intertidal and shallow subtidal areas globally, where larger species form extensive underwater forests. These structurally complex and highly productive habitats enhance local biodiversity and support food webs in coastal areas through secondary production, thereby shaping local oceanography and ecology. Macroalgal aquaculture is an important and growing sector, where approximately 40% of all cultivated algae belong to Phaeophyceae. However, both cultured and natural brown algae have been under increasing pressure due to climate-driven factors, such as ocean warming, eutrophication, and herbivore outbreaks. We conducted a comprehensive literature review on abiotic (temperature, light intensity, and UV radiation, nutrients, water motion, salinity, and substrata and sediment) and biotic (bacteria, viruses, fungi, eukaryotic endophytes and endoparasites, epiphytes, and grazers) stressors and illnesses in marine brown macroalgae, as well as brown algae defense mechanisms, and discuss how these parameters may affect the production of a sustainable crop for the aquaculture industry under future climate change scenarios.

Potential impact of climate change on the distribution of Capricornis milneedwardsii, a vulnerable mammal in China.

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.

English

The present study is to understand how climatic variables such as precipitation and temperature vary over time and how those changes affect stream flow in the Jhelum River basin in Pakistan under different emission scenarios A2 and B2. The simulation results of HadCM3 were employed to create potential climate change scenarios with the Statistically Downscale Model (SDSM). The calibrated model Soil and Water Assessment Tool (SWAT) was used to forecast imminent stream flow to develop a proposed future climate change scenario. Results indicated that cooling patterns were identified in the north portion of the study area whereas warming patterns were detected in the south portion. The projected mean annual maximum temperature (Tmax) of 2020’s 2050’s and 2080’s would be 0.3 oC, 0.8 oC, and 0.99 oC, respectively, under the A2 scenario. The changes in mean annual minimum temperature (Tmin) were also observed as it would be 0.4 oC, 0.7 oC, and 1.4 oC during 2020’s (2021-2040), 2050’s (2041-2070) and 2080’s (2071-2100), respectively. Similarly, it was observed that average annual rainfall would rise by 14%, 10%, and 20% during the 2020s, 2050s, and 2080s, respectively, in the Mangla basin. The results showed an increase in annual stream flows of 100% (1545 m3/sec), with increases in the winter and autumn seasons of up to 409% and 211%, respectively, and a drop in the spring and summer seasons of up to 29% and 25%, respectively, in the 2080’s compared to baseline. Water managers should consider the current trends and variability brought on by climate change to improve water management where water is scarce.

Predicting the Potential Risk Area of the Invasive Plant Galinsoga parviflora in Tibet Using the MaxEnt Model

The Tibetan plateau, with complex and diverse ecosystems, is an important ecological security barrier to China. However, climate change and the spread of invasive plant species have imperiled the once pristine and diverse ecosystem of the region. To prevent the further spread and control of invasive plants, it is important to delineate the potential distribution patterns of alien invasive plants at the regional scale across Tibet and understand their responses to climate change. Galinsoga parviflora Cav., a member of the family Asteraceae, is an annual herbaceous plant distributed globally as an invasive weed and possesses characteristics that make it highly invasive, such as a strong ability to proliferate and disperse. The species is also known to have an allelopathic effect. There has been no report on the spatial distribution of G. parviflora in Tibet. Using field survey data, we investigated the risk of G. parviflora invasion and its impacts on the ecological safety of Tibet. We employed the MaxEnt model using the R language and SPSS software to optimize and select model parameters and data. We acquired various environmental variables along with current and future climate change scenarios (two carbon emission scenarios, SSP126 and SSP585, for the years 2050 and 2090) to predict the geographic distribution and potential risk areas in Tibet that G. parviflora can invade. The MaxEnt model accurately predicted the distribution of G. parviflora in Tibet with an average AUC of 0.985. The most suitable environmental conditions in which G. parviflora performed the best in Tibet included a mean annual temperature of 6.2–10.0 °C and an elevation range of 2672–3744 m above sea level. Our results indicate that low precipitation during the coldest quarter of the year (mean temperature −2–3 °C) was the most important variable predicting G. parviflora distribution. The results also showed that the species was hardly found when precipitation in the coldest quarter exceeded 155 mm. The current potential invasion risk areas for G. parviflora included the river valleys of central, southeastern, and eastern Tibet. With future climate change scenarios (i.e., SSP126, SSP585), the suitable habitats for G. parviflora distribution will likely shift to northwest regions from the southeast. Particularly under the highest carbon emission scenario (i.e., SSP585), the potential risk area expands more rapidly, and the center of distribution shifts to northwest regions. These findings provide useful information about the current and future changes in G. parviflora distribution in Tibet, which is crucial for the comprehensive and proactive management and control of G. parviflora under future climate change.

Molecular evidence for a new endemic species of Acartia (Copepoda, Calanoida) from the Southeast Pacific coast

The loss of biodiversity in marine populations is one of the consequences of the increased events of extreme environmental conditions in the oceans, which can condition the persistence of populations to future scenarios of climate change. Therefore, it is extremely necessary to explore and monitor the genetic diversity of natural populations. In the Southeast Pacific Ocean (SEPO), specifically on the coast of Chile, the presence of the copepod Acartia tonsa has been indicated solely using morphological evidence, due to the absence of genetic information. In the present work, the genetic diversity, population structure and phylogenetic position within the genus Acartia, of populations identified morphologically as A. tonsa, was evaluated by amplification of the mitochondrial cytochrome c oxidase subunit I and nuclear marker 18 s. Our results showed that the populations identified as A. tonsa correspond to a new monophyletic group endemic to SEPO (GMYC = 1.00; PTP = 0.95). The populations showed moderate to high genetic diversity with an incipient structuring between populations and biogeographic zones. Our results suggest that despite the homogenizing effect of the Humboldt Current, isolation by distance and contrasting environmental conditions at different geographic scales have an important influence on the genetic diversity of zooplankton in the SEPO region.

On Predicting Offshore Hub Height Wind Speed and Wind Power Density in the Northeast US Coast Using High-Resolution WRF Model Configurations during Anticyclones Coinciding with Wind Drought

We investigated the predictive capability of various configurations of the Weather Research and Forecasting (WRF) model version 4.4, to predict hub height offshore wind speed and wind power density in the Northeast US wind farm lease areas. The selected atmospheric conditions were high-pressure systems (anticyclones) coinciding with wind speed below the cut-in wind turbine threshold. There are many factors affecting the potential of offshore wind power generation, one of them being low winds, namely wind droughts, that have been present in future climate change scenarios. The efficiency of high-resolution hub height wind prediction for such events has not been extensively investigated, even though the anticipation of such events will be important in our increased reliance on wind and solar power resources in the near future. We used offshore wind observations from the Woods Hole Oceanographic Institution’s (WHOI) Air–Sea Interaction Tower (ASIT) located south of Martha’s Vineyard to assess the impact of the initial and boundary conditions, number of model vertical levels, and inclusion of high-resolution sea surface temperature (SST) fields. Our focus has been on the influence of the initial and boundary conditions (ICBCs), SST, and model vertical layers. Our findings showed that the ICBCs exhibited the strongest influence on hub height wind predictions above all other factors. The NAM/WRF and HRRR/WRF were able to capture the decreased wind speed, and there was no single configuration that systematically produced better results. However, when using the predicted wind speed to estimate the wind power density, the HRRR/WRF had statistically improved results, with lower errors than the NAM/WRF. Our work underscored that for predicting offshore wind resources, it is important to evaluate not only the WRF predictive wind speed, but also the connection of wind speed to wind power.

Global insect herbivory and its response to climate change

Herbivorous insects consume a large proportion of the energy flow in terrestrial ecosystems and play a major role in the dynamics of plant populations and communities. However, high-resolution, quantitative predictions of the global patterns of insect herbivory and their potential underlying drivers remain elusive. Here, we compiled and analyzed a dataset consisting of 9,682 records of the severity of insect herbivory from across natural communities worldwide to quantify its global patterns and environmental determinants. Global mapping revealed strong spatial variation in insect herbivory at the global scale, showing that insect herbivory did not significantly vary with latitude for herbaceous plants but increased with latitude for woody plants. We found that the cation-exchange capacity in soil was a main predictor of levels of herbivory on herbaceous plants, while climate largely determined herbivory on woody plants. We next used well-established scenarios for future climate change to forecast how spatial patterns of insect herbivory may be expected to change with climate change across the world. We project that herbivore pressure will intensify on herbaceous plants worldwide but would likely only increase in certain biomes (e.g., northern coniferous forests) for woody plants. Our assessment provides quantitative evidence of how environmental conditions shape the spatial pattern of insect herbivory, which enables a more accurate prediction of the vulnerabilities of plant communities and ecosystem functions in the Anthropocene.

Deforestation limits evolutionary rescue under climate change in Amazonian lizards

AbstractAimThe impact of climate change on biodiversity is often analysed under a stable evolutionary perspective focused on whether species can currently tolerate warmer climates. However, species may adapt to changes, and particularly under conditions of low habitat fragmentation, standing adaptive genetic variation can spread across populations tracking changing climates, increasing the potential for evolutionary rescue. Here, our aim is to integrate genomic data, niche modelling and landscape ecology to predict range shifts and the potential for evolutionary rescue.LocationThe megadiverse Amazonian rainforest.MethodsWe use genome–environment association analyses to search for candidate loci under environmental selection, while accounting for neutral genetic variation in a widespread Amazonian whiptail lizard (Teiidae: Kentropyx calcarata). We then model the distribution of individuals with genotypes adapted to different climate conditions. We predict range shifts for each genotype in distinct future climate change scenarios by integrating this information with dispersal constraints based on predicted scenarios of forest cover across Amazonia. The predicted ranges of each genotype were then overlapped to infer the potential for evolutionary rescue.ResultsWe find that the potential for evolutionary rescue and, therefore, a smaller degree of range loss buffering extinction risk in the future is considerably high, provided that current forest cover is retained and climate change is not extreme. However, under extreme environmental change scenarios, range loss will be high in central and southern Amazonia, irrespective of the degree of deforestation.Main ConclusionsOur results suggest that protecting the Amazonian rainforest against further deforestation and mitigating climate change to moderate scenarios until 2070 could foster evolutionary rescue of ectothermic organisms. These actions could prevent substantial biodiversity loss in Amazonia, emphasizing the importance of understanding species adaptability in maintaining biodiversity.