Climate-induced Changes Research Articles

Late Holocene cooling drove drastic decreases in cladoceran diversity in a subarctic lake

Subarctic lakes are sentinels of climate change, showing responses in their physical, chemical, and biological properties. However, climate-induced changes in invertebrate diversity and their underlying mechanisms are not fully understood. We explored the relationship between past climate change and taxonomic composition of subfossil cladocerans in a subarctic lake during the last ca. 5700 years. The Cladocera community shifted from specialist to generalist species at ca. 3500 cal years BP, corresponding to the long-term cooling period between the Holocene Thermal Maximum and the Late Holocene. Taxonomic diversity declined driven by the collapse of the keystone herbivorous Daphnia longispina group, pelagic and littoral predators, and phytophilous benthic species, therefore resulting in a simplification of the food web and a reduction of trophic levels. Furthermore, the shift in cladoceran composition was associated with the decline of aquatic primary producers and the development of birch forest, suggesting a potential causal link between dissolved organic carbon dynamics and cladoceran community composition. This study provides empirical evidence of the response of cladocerans to climatic fluctuations and their underlying mechanisms through catchment-mediated processes and direct temperature-induced changes.

Edge Computing Architecture for the Management of Underwater Cultural Heritage

Underwater cultural heritage (UCH) is a valuable resource that preserves humanity’s historical legacy, offering insights into traditions and civilisations. Despite its significance, UCH faces threats from inadequate regulatory frameworks, insufficient conservation technologies, and climate-induced environmental changes. This paper proposes an innovative platform combining the internet of underwater things and edge computing technologies to enhance UCH’s real-time monitoring, localisation, and management. The platform processes data through a central unit installed on a buoy near heritage sites, enabling efficient data analysis and decision making without relying on cloud connectivity. Integrating acoustic communication systems, LoRa technology, and nonterrestrial networks supports a robust multilayered communication infrastructure for continuous operation, even in remote maritime areas. The platform’s edge node deploys artificial intelligence models for real-time risk assessment, focusing on key environmental parameters to predict and mitigate corrosion rates and climate-related threats. A case study illustrates the system’s capabilities in underwater localisation, demonstrating how edge computing and acoustic triangulation techniques enable precise tracking.

Coastal vertical land motion across Southeast Asia derived from combining tide gauge and satellite altimetry observations

Vertical land motion (VLM) is complex in Southeast Asia because this region is subject to a range of natural processes (e.g., earthquakes) and anthropogenic activities (e.g., groundwater withdrawal) that can change land heights. To aid in coastal management, long-term observations of VLM are as crucial as observations for climate-induced sea surface height changes; however, such long-term observations are sparse for Southeast Asian coasts. To fill this observational gap, here we derive monthly VLM time series from 1993 to 2020 at 50 coastal sites across Southeast Asia by combining tide-gauge records and newly generated satellite altimetry observations. These altimetry observations are reproduced sea-level products using new altimetry standards and more accurate geophysical corrections. Our 27-year-long VLM dataset shows high spatial variability and non-linear temporal changes in VLM across Southeast Asia. We identify several major sources that dominate the regional land-height changes, which include large subsidence due to groundwater extraction in Manila and Bangkok, land uplift in Indonesia and subsidence in Thailand from postseismic deformation resulting from the sequence of large Sumatran earthquakes since 2004, and land subsidence as a result of sediment compaction in Malaysia. Those signals are quantitatively or qualitatively consistent with observations from other sources. This VLM dataset can be used to advance our understanding of the physical mechanisms behind land-height changes and to improve sea level projections in the region.

Unraveling climate change-induced compound low-solar-low-wind extremes in China

Abstract China's pursuit of carbon neutrality target hinges on a profound shift towards low-carbon energy, primarily reliant on intermittent and variable yet crucial solar and wind power sources. In particular, low-solar-low-wind (LSLW) compound extremes present a critical yet largely ignored threat to the reliability of renewable electricity generation. While existing studies have largely evaluated the impacts of average climate-induced changes in renewable energy resources, comprehensive analyses of the compound extremes and, particularly, the underpinning dynamic mechanisms remain scarce. Here we show the dynamic evolution of compound LSLW extremes and their underlying mechanisms across China via coupling multi-model simulations with diagnostic analysis. Our results unveil a strong topographic dependence in the frequency of compound LSLW extremes, with a national average frequency of 16.4 (10th-90th percentile interval ranges from 5.3 to 32.6) days/yr, when renewable energy resource in eastern China are particularly compromised (∼80% lower than that under average climate). We reveal a striking increase in LSLW extremes frequency, ranging from 12.4% under SSP126 to 60.2% under SSP370, primarily driven by both renewable energy resource declines and increasingly heavy-tailed distributions, resulting from weakened meridional temperature (pressure) gradient, increased frequency of extremely dense cloud cover, and additional distinctive influence of increased aerosols under SSP370. Our study underscores the urgency of preparing for significantly heightened occurrences of LSLW events in a warmer future, emphasizing such climate-induced compound LSLW extreme changes are not simply by chance, but rather projectable, thereby underscoring the need for proactive adaptation strategies. Such insights are crucial for countries globally navigating a similar transition towards renewable energy.

Machine learning prediction of tipping in complex dynamical systems

Anticipating a tipping point, a transition from one stable steady state to another, is a problem of broad relevance due to the ubiquity of the phenomenon in diverse fields. The steady-state nature of the dynamics about a tipping point makes its prediction significantly more challenging than predicting other types of critical transitions from oscillatory or chaotic dynamics. Exploiting the benefits of noise, we develop a general data-driven and machine-learning approach to predicting potential future tipping in nonautonomous dynamical systems and validate the framework using examples from different fields. As an application, we address the problem of predicting the potential collapse of the Atlantic meridional overturning circulation, possibly driven by climate-induced changes in the freshwater input to the North Atlantic. Our predictions based on synthetic and currently available empirical data place a potential collapse window spanning from 2040 to 2065, in consistency with the results in the current literature. Published by the American Physical Society 2024

Mapping the Future: Climate-Induced Changes in Aboveground Live-Biomass Carbon Density Across Mexico’s Coniferous Forests

Climate variations in temperature and precipitation significantly impact forest productivity. Precipitation influences the physiology and growth of species, while temperature regulates photosynthesis, respiration, and transpiration. This study developed bioclimatic models to assess how climate change will affect the carbon density of aboveground biomass (cdAGB) in Mexico’s coniferous forests for 2050 and 2070. We used cdAGB data from the National Forest and Soils Inventory (INFyS) of Mexico and 19 bioclimatic variables from WorldClim ver. 2.0. The best predictors of cdAGB were obtained using machine learning techniques with the “caret” library in R. The model was trained with 80% of the data and validated with the remaining 20% using Generalized Linear Models (GLMs). Current cdAGB prediction maps were generated using the best predictors. Future cdAGB was calculated with the average of three general circulation models (GCMs) of future climate projections from the Coupled Model Intercomparison Project Phase 5 (CMIP5), under four Representative Concentration Pathways (RCPs): 2.6, 4.5, 6.0, and 8.5 W/m2. The results indicate cdAGB losses in all climate scenarios, reaching up to 15 Mg C ha−1, and could occur under the RCP 8.5 scenario by 2070 in the central region of the country. Temperature-related variables are more important than precipitation variables. Bioclimatic variables can explain up to 20% of the total variance in cdAGB. The temperature in the study area is expected to increase by 2.66 °C by 2050 and 3.36 °C by 2070, while precipitation is expected to fluctuate by ±10% relative to the current values, which could geographically redistribute the cdAGB of the country’s coniferous forests. These findings underscore the need for forest management to focus not only on biodiversity conservation but also on the carbon storage capacity of these ecosystems.

Influence of global warming and human activity on mercury accumulation patterns in wetlands across the Qinghai-Tibet Plateau

Abstract Wetlands in the Qinghai-Tibet Plateau (QTP) are a unique and fragile ecosystem undergoing rapid changes. We show two unique patterns of mercury (Hg, a global pollutant) accumulation in wetland sediments. One is the ‘Surface Peak’ in monsoon-controlled regions, and the other is the ‘Subsurface Peak’ in westerly-controlled regions. The former is attributed to the combined effects of increasing anthropogenic emissions and climate-induced changes in the cryosphere and wetland hydrology in the last 100 − 150 years. The climate changes in westerly-controlled regions in the last 50 − 70 years led to a fluctuation of hydrology and an Hg peak in the sediment subsurface. The increase of legacy Hg input from soil erosion largely enhanced the Hg accumulation rate in wetlands since the 1950s, especially in the proglacial wetlands. We highlight that accelerated glacier melting and permafrost thawing caused by global warming have altered geomorphology and hydrology and affected Hg transport and accumulation in wetlands.

Assessment of non-stationary tree growth responses in the forest-tundra and southern taiga of central Siberia

Anthropogenically induced climate change largely affects the functioning of vegetation communities worldwide. In the world's largest land biome, the boreal forest, a persistent decoupling of tree growth from rising summer temperatures has been recorded in recent decades. This so-called ‘Divergence Problem’ (DP) has been studied over the past 30 years, yet the causes and spatial patterns within the boreal forest zone are not well understood. Here, we present tree-ring evidence on varying DP in Larix gmelinii from the globally northernmost forest island on Taymyr Peninsula and Larix sibirica from the southern taiga in central Siberia. Tree-ring width and maximum latewood density data reveal DP to be substantially stronger in the south indicating that growth-climate relationships in Siberian larch passed beyond a tipping point under warmer climate and increased anthropogenic pressure. In the north, the temperature signal remained strong and temporally stable underscoring the skill of tree-ring chronologies for long-term climate reconstructions. These findings highlight the heterogeneity of tree growth responses to global warming within the boreal forest zone, from which spatially varying consequences for carbon and water cycle dynamics must be expected. Our study emphasizes the importance of updating tree-ring chronologies in remote regions within boreal forest zone to foster understanding of spatiotemporal patterns in biomass allocation, permafrost degradation, and DP across this large biome.

Interdisciplinary Perspectives on Forest Ecosystems and Climate Interplay: A Review

This review comprehensively examines the multifunctional role of forest ecosystems in climate regulation and the consequential impacts of climate change on these critical biomes. A systematic approach was employed, utilizing extensive bibliometric analysis and synthesis of recent literature from databases such as Web of Science, ScienceDirect, and Google Scholar. Key ecological functions of forests, including carbon sequestration, albedo modulation, evapotranspiration, and cloud formation, were scrutinized to elucidate their contributions to the global carbon cycle and local/regional climate dynamics. The analysis highlights significant phenological shifts, species migrations, and increased vulnerabilities to pests, diseases, and fire disturbances as primary indicators of climate-induced ecological changes. Furthermore, the study explores the intricate feedback loops that exacerbate deforestation and alterations in forest structure and function. Predictive models incorporating various climate scenarios are discussed, emphasizing their importance in developing adaptive management strategies for forest conservation. The findings underscore the necessity for interdisciplinary approaches and stakeholder engagement to formulate effective strategies for mitigating climate change impacts and enhancing forest ecosystem resilience. This review advances the field of ecology by providing critical insights into the interplay between forest ecosystems and climate dynamics, offering a foundation for future research and policy development.

Comparative assessment of empirical random forest family's model in simulating future streamflow in different basin of Sarawak, Malaysia

In Sarawak, a region highly vulnerable to climate change, the translation of climate-induced changes in rainfall to river flow is non-linear, presenting a challenge for water resource managers. This research investigates the impact of climate change on hydrological processes in Sarawak, Malaysia, with a specific focus on assessing future spatiotemporal variations in streamflow. The families of Random Forest (RF) empirical models based on data mining techniques were compared and utilized to develop a continuous hydrologic model. Then, by incorporating rainfall and evapotranspiration future projection prepared based on RF past performance statistical downscaling, the top performing RF empirical hydrological model was used for future streamflow projection. The results showed that despite an expected increase in rainfall, the RFR (Random Forest by Randomization) empirical hydrological model demonstrated a potential decrease in river runoff due to heightened evapotranspiration demands associated with rising temperatures. The examination of climate-induced alterations in both rainfall and evapotranspiration patterns revealed a consistent decrease in river discharges during the early to middle period across Sarawak, followed by a shift towards an increasing trend by the end of the 21st century. The central region along the Rajang basin exhibited a prevailing decrease in river discharge, with contrasting patterns in the last part of the century. The northern region displayed diverse trends, with some basins experiencing decreases in river runoff despite augmented rainfall, emphasizing the heterogeneity in response. By employing empirical models, and projecting future scenarios, the study contributes to a better understanding of climate change impacts on hydrology in the region, essential for effective water resource management and environmental conservation.

Climate change and staple grain acreage: Regional adaptation in China's agricultural cluster

The regionally adaptative use of cropland for staple grain production forms a critical foundation for agricultural clustering, however, the effects of climate change on grain acreage across regions have received insufficient attention. This study uses recent county-level data from 2000 to 2019 in China and employs an empirical framework that incorporates 10-year averages of weather variables to analyze regional variations in grain acreage in response to changes in temperature and precipitation. Our findings reveal significant regional heterogeneity: increases in temperature and precipitation generally lead to an expansion of staple grain acreage in initially colder or drier regions. These findings remain robust after accounting for a range of confounding factors. Mechanism analysis indicates that these climate-induced changes in grain acreage stem from variations in land productivity. Furthermore, the study identifies shifts in comparative advantages among staple grains across regions: rising temperatures favor paddy over corn in colder regions and corn over wheat in warmer areas, while increased precipitation enhances corn's advantage over wheat in arid regions. These findings have important implications for designing effective adaptation policies to sustain grain productivity in China's agricultural clusters and ensure food security targets.

Parent-Specific Transgenerational Immune Priming Enhances Offspring Defense-Unless Heat Stress Negates It All.

Transgenerational immune priming (TGIP) adjusts offspring's immune responses based on parental immunological experiences. It is predicted to be adaptive when parent-offspring environmental conditions match, while mismatches negate those advantages, rendering TGIP potentially costly. We tested these cost-benefit dynamics in the pipefish Syngnathus typhle (Syngnathidae). Because of their unique male pregnancy, egg production and rearing occur in different sexes, providing both parents multiple avenues for TGIP. Parental bacteria exposure in our pipefish was simulated through vaccinations with heat-killed Vibrio aestuarianus before mating the fish to each other or to controls. The resulting offspring were exposed to V. aestuarianus in control or heat stress environments, after which transcriptome and microbiome compositions were investigated. Transcriptomic TGIP effects were only observed in Vibrio-exposed offspring at control temperatures, arguing for low costs of TGIP in non-matching microbiota environments. Transcriptomic phenotypes elicited by maternal and paternal TGIP had limited overlap and were not additive. Parentally induced transcriptomic responses were associated with immune functions, and specifically, the paternal response to the innate immune branch, possibly hinting at trained immunity. TGIP of both parents reduced the relative abundance of the experimental Vibrio in exposed offspring, showcasing its ecological benefits. Despite TGIP's significance in matching biotic environments, no TGIP-associated phenotypes were observed for heat-treated offspring, illustrating its limitations. Heat spikes caused by climate change thus threaten TGIP benefits, potentially increasing susceptibility to emerging marine diseases. We demonstrate the urgent need to understand how animals cope with climate-induced changes in microbial assemblages to assess their vulnerability in light of climate change.

A methodology for assessing multiple hazards applied to Sweden

Despite extensive efforts through various international initiatives to reduce global warming, it has been determined that human induced climate change is here, that the present scale of disruption of the climate is unprecedented and will continue. Increasing weather volatility can be expected, which will most likely increase exposure to weather related hazards, e.g. wildfires, flooding. The aim of this paper is to present an index-based multi-hazard risk assessment method to assess wildfires and flooding hazard for two municipalities within Sweden. The method is designed to be used by the Fire and Rescue Service (FRS) for planning purposes and can be modified to take the local FRS's capabilities and local conditions into account, thereby improving hazard preparedness at a local level. The analysis presented indicates that, while the frequency of multi-hazard overlap from wildfires and flooding is greatest in more northern parts of Sweden, the method provides important information even when applied to areas with limited overlap. A variation of the hazard assessment using a box kernel sliding window was studied to investigate the sensitivity of the model for rapid variations of an individual hazard level. Given that resource needs will typically spread over several days for large scale natural hazards, the box kernel approach is valuable in helping to identify a span of days when resources associated with incident response might be needed. In the future, the model should be expanded to include additional single hazards, the application to additional municipalities and extension to FRS planning exercises for natural hazards.

Phenological trends and associated climate drivers of a tree community in lowland dipterocarp forest, Western Ghats, India.

Understanding phenological responses of tropical forest plant communities is crucial for identifying climate-induced changes in ecosystem dynamics. Monitoring phenology across diverse species in natural habitats provides cost-effective insights for conserving both species and forests. We studied tree phenology in a lowland evergreen dipterocarp forest in the Western Ghats, India. About 719 tree individuals representing 95 species were monitored for their vegetative and reproductive phenology from April 2021 to September 2023. Circular statistics detected seasonality in phenological events and Generalized Linear Mixed Modelling (GLMM) identified influence of climate variables on the phenological responses of the tree community. We also assessed how the activity and intensity of phenophases vary over the study period. Our results showed that leaf flushing and flowering peaked during the dry season, with mass flowering observed in two dominant dipterocarps. Fruit production peaked before the monsoon. We also observed diversity in vegetative and reproductive phenodynamics across species groups (forest strata, sexual system, and seed size). Leaf flushing was positively correlated with maximum relative humidity and negatively correlated with maximum temperature and the number of rainy days. Flowering had negative correlations with maximum relative humidity, rainfall days, and maximum temperature but showed a positive correlation with minimum temperature. Fruiting was positively correlated with maximum temperature and negatively correlated with rainy days. This detailed phenological information provides critical knowledge on resource availability and insights into how climate and seasonal changes affect plant growth cycles thereby aiding reforestation and biodiversity conservation strategies in vulnerable forest areas.

Optimization of vegetation carbon content parameters and their application in carbon storage estimation in China

As a key parameter for C pool and flux assessments, vegetation carbon (C) content can be used in ecological models to predict climate-induced changes in the C sequestration capacity of vegetation. However, the differences in methods for upscaling C content from the organ to the community scale and their impact on regional C stock estimates have been ignored. Based on a comprehensive community structure survey of 72 typical natural ecosystems in China and 27,905 measured samples of plant organs (leaves, twigs, trunks, and roots), we first quantified the differences among scaling-up methods for vegetation C content. These methods included the community or dominant species-weighted mean, geometric mean, arithmetic mean, and traditional empirical coefficients (45 % and 50 %), and their impact on C storage estimation at the regional scale. Comparing the accuracy, variability, and response patterns of the different scaling-up methods, the dominant C species biomass-weighted mean (CDWM) method had the highest similarity to the community-weighted C mean (CCWM) method. Concerning vegetation C storage estimation in China's natural terrestrial ecosystems, the relative errors of the other methods ranged from −2.6 % to 8.22 % compared with that of the CCWM method (18.39 Pg C). The empirical coefficients had the highest uncertainty, with a 45 % empirical coefficient underestimating the vegetation C stock by 2.60 %, and a 50 % empirical coefficient overestimating it by 8.22 %. The CDWM method proposed here has high reliability for C storage estimation (overestimated by only 0.44 %), making it a preferable sampling and scaling-up method for regional C content and stock assessment. Additionally, our study provided the C content of plant organs for China's provinces and typical vegetation types based on the CCWM, which could be used for regional C stock assessment and C cycle models.

Increasing temperature threatens post‐fire auto‐successional dynamics of a Mediterranean obligate seeder

Abstract Reproductive traits influence plant auto‐successional dynamics in post‐fire regeneration. Obligate seeding species rely on their seedbank and on the climatic conditions following the fire to ensure a successful recovery, defining the window of opportunity for seedling emergence. In the Mediterranean basin, emergence opportunities generally begin with autumnal rains. However, climate change‐induced increases in temperature and drought could jeopardise the regeneration capacity of seeding species by causing temporal shifts in emergence opportunities or by modifying wildfire seasonality. This study aimed to explore the impact of experimentally induced climate change on regeneration dynamics of Aleppo pine (Pinus halepensis), a serotinous Mediterranean obligate seeder. In March 2021, we set up an 18‐month climate change simulation experiment with 15 open‐top chambers (OTC), each paired with a control subplot (CON) on top of Aleppo pines that were naturally regenerating after a stand‐replacing wildfire in SW Catalonia (June 2019). We tagged 178 young Aleppo pine recruits in OTC and CON subplots (98 and 81 respectively), classified according to their initial size, to periodically measure height growth and survival throughout the experiment duration. Furthermore, Aleppo pine seeds were seasonally sown (7900 total seeds) in 10 subplot pairs between May 2021 and April 2022, to monthly monitor temporal patterns of seedling emergence and survival. We found that OTCs reduced overall emergence rates and caused the loss of the autumnal window of opportunity for the emergence of Aleppo pine seedlings. Furthermore, seedlings which emerged within OTCs faced higher mortality rates in all seasons, with only 1% of seedlings surviving compared with 21.1% of seedlings in control plots. The OTC‐induced conditions were also detrimental to the survival of recruited seedlings, especially those with a smaller initial size, although no significant effects of temperature increase were found on growth. Synthesis. Climate change is likely to interfere with the post‐fire regeneration dynamics of obligate seeders by shortening the temporal window of opportunities for emergence and by enhancing the bottleneck effects throughout the recruitment process in the early phases of pine demographic recovery. Altogether, it could threaten post‐fire regeneration by increasing the hazard of a demographic collapse of Aleppo pine.

Reassessing water resource challenges in a changing climate in the Kagera transboundary river basin, Tanzania

The dynamic shifts in climatic patterns, particularly alterations in precipitation, have significantly impacted water resource availability and accessibility. These climate-induced changes affect hydrological processes, encompassing runoff, groundwater replenishment, water demand, and biophysical patterns within river basins. This study seeks to unravel the multifaceted implications encountered and challenges in water resource management within the river basin. It employed a survey-based approach for data collection, including Key informant interviews (KI), consultation methods and documentary reviews. The study utilized Statistical Package for the Social Sciences (SPSS) and Microsoft Excel for quantitative analysis and thematic synthesis for qualitative insights, including local community perspectives. The findings reveal substantial fluctuations in precipitation, protracted droughts, severe flooding, and other climatic extremes. The observed annual mean rainfall of 832 mm, with a standard deviation of 248, a standard error of 361, and a skewness of −945, accentuates the pronounced variability in mean precipitation, exhibiting a declining trend indicative of climatic shifts (R2 = 0.1797 and P = 0.002). The challenges are limited access to hydrological and meteorological data, undermining prediction accuracy, infrastructure planning, and response strategies for water resource allocation and management. The absence of unified approaches, influenced by the politics of riparian states, feeble coordination, conflicting sectoral policies, and ambiguous priorities, hinders effective transboundary water resource management. The study addresses these complexities and advocates for institutionalizing robust water management strategies that capitalize on existing resources and foster innovative capacities among critical stakeholders. Central to these efforts is harmonizing and enforcing policies, regulations, and laws governing water use, coupled with a concerted focus on inclusive governance to ensure the sustainability of water resource management. Such effort entails synchronized strategies, programs, plans, and livelihood practices underpinned by active stakeholder involvement in pivotal facets of water resources management.

Droughts reshape apex predator space use and intraguild overlap.

Droughts are increasing in frequency and severity globally due to climate change, leading to changes in resource availability that may have cascading effects on animal ecology. Resource availability is a key driver of animal space use, which in turn influences interspecific interactions like intraguild competition. Understanding how climate-induced changes in resource availability influence animal space use, and how species-specific responses scale up to affect intraguild dynamics, is necessary for predicting broader community-level responses to climatic changes. Although several studies have demonstrated the ecological impacts of drought, the behavioural responses of individuals that scale up to these broader-scale effects are not well known, particularly among animals in top trophic levels like large carnivores. Furthermore, we currently lack understanding of how the impacts of climate variability on individual carnivore behaviour are linked to intraguild dynamics, in part because multi-species datasets collected at timescales relevant to climatic changes are rare. Using 11 years of GPS data from four sympatric large carnivore species in southern Africa-lions (Panthera leo), leopards (Panthera pardus), African wild dogs (Lycaon pictus) and cheetahs (Acinonyx jubatus)-spanning 4 severe drought events, we test whether drought conditions impact (1) large carnivore space use, (2) broad-scale intraguild spatial overlap and (3) fine-scale intraguild interactions. Drought conditions expanded space use across species, with carnivores increasing their monthly home range sizes by 35% (wild dogs) to 66% (leopards). Drought conditions increased the amount of spatial overlap between lions and subordinate felids (cheetahs and leopards) by up to 119%, but only lion-cheetah encounter rates were affected by these changes, declining in response to drought. Our findings reveal that drought has a clear signature on the space use of multiple sympatric large carnivore species, which can alter spatiotemporal partitioning between competing species. Our study thereby illuminates the links between environmental change, animal behaviour and intraguild dynamics. While fine-scale avoidance strategies may facilitate intraguild coexistence during periodic droughts, large carnivore conservation may require considerable expansion of protected areas or revised human-carnivore coexistence strategies to accommodate the likely long-term increased space demands of large carnivores under projected increases in drought intensity.

The potential for evolutionary rescue in an Arctic seashore plant threatened by climate change.

The impacts of climate change may be particularly severe for geographically isolated populations, which must adjust through plastic responses or evolve. Here, we study an endangered Arctic plant, Primula nutans ssp. finmarchica, confined to Fennoscandian seashores and showing indications of maladaptation to warming climate. We evaluate the potential of these populations to evolve to facilitate survival in the rapidly warming Arctic (i.e. evolutionary rescue) by utilizing manual crossing experiments in a nested half-sibling breeding design. We estimate G-matrices, evolvability and genetic constraints in traits with potentially conflicting selection pressures. To explicitly evaluate the potential for climate change adaptation, we infer the expected time to evolve from a northern to a southern phenotype under different selection scenarios, using demographic and climatic data to relate expected evolutionary rates to projected rates of climate change. Our results indicate that, given the nearly 10-fold greater evolvability of vegetative than of floral traits, adaptation in these traits may take place nearly in concert with changing climate, given effective climate mitigation. However, the comparatively slow expected evolutionary modification of floral traits may hamper the evolution of floral traits to track climate-induced changes in pollination environment, compromising sexual reproduction and thus reducing the likelihood of evolutionary rescue.

Climate Change Induced Saltwater Intrusion and Migration Intentions in the Mekong Delta

Climate Change Induced Saltwater Intrusion and Migration Intentions in the Mekong Delta