Impacts of climate change on lakes and reservoirs dynamics and restoration policies

Meteorological-driven processes exert large and diverse impacts on lakes and their water quality; these impacts can be hydrologic, thermal, hydraulic, chemical, biochemical, or ecological. The impact of climate change on Lake Tahoe (California–Nevada) was investigated here as a case study of climate change effects on the physical processes occurring within lakes. The already published trends of meteorological variables were used to assess the effects of global warming on Lake Tahoe dynamics. Records from the period 1969–2002 show that Lake Tahoe has became warmer and more stable. A series of simulation years into the future (i.e., 2000–2040) was established using flows, loads, and meteorology data sets for the period 1994–2004. Results of 40-year simulations show that the lake continues to become warmer and more stable, and mixing is reduced. Possible changes in water quality because of global warming are discussed through inference, although these are not specifically simulated. Many existing problems may be exacerbated due to climate change, yet extreme uncertainty depends on the rate and magnitude of climate change. Therefore, shifts in water quality and quantity due to climate change should be integrated into contemporary planning and management in an adaptive manner, and the research and development of impact assessment methodology should focus on approaches that can handle extreme uncertainty. The general alternatives for lake management due to climate change are discussed. Depending on the specific case, further intensive research is suggested to restore lake water quality.     

Climate change and climate-induced hot spots in forest shifts in central Siberia from observed data

Regional Siberian studies have already registered climate warming over the last several decades. We evaluated ongoing climate change in central Siberia between 1991 and 2010 and a baseline period, 1961–1990, and between 1991 and 2010 and Hadley 2020 climate change projections, represented by the moderate B1 and severe A2 scenarios. Our analysis showed that winters are already 2–3°C warmer in the north and 1–2°C warmer in the south by 2010. Summer temperatures increased by 1°C in the north and by 1–2°C in the south. Change in precipitation is more complicated, increasing on average 10% in middle latitudes and decreasing 10–20% in the south, promoting local drying in already dry landscapes. Hot spots of possible forest shifts are modeled using our Siberian bioclimatic vegetation model and mountain vegetation model with respect to climate anomalies observed pre-2010 and predicted 2020 Hadley scenarios. Forests are predicted to shift northwards along the central Siberian Plateau and upslope in both the northern and southern mountains. South of the central Siberian Plateau, steppe advancement is predicted that was previously non-existent north of 56°N latitude. South of 56°N, steppe expansion is predicted in the dry environments of Khakasiya and Tyva. In the southern mountains, it is predicted that the lower tree line will migrate upslope due to increased dryness in the intermontane Tyvan basins. The hot spots of vegetation change that are predicted by our models are confirmed by regional literature data.     

Impact changes of climatic extremes on arable farming in the north of the Netherlands

Agriculture is vulnerable to climate change in multiple ways. Here, we use the northern region of the Netherlands as a case study to explore how risk assessments for climate change impacts on crop production can address multiple vulnerabilities. We present a methodology, which we call agro climate calendar (ACC) that (i) includes potential yield losses, as well as loss of product quality, and (ii) assesses the risks of a variety of climate factors including weather extremes and the emergence and abundance of pests and diseases. Climate factors are defined for two time slices: 1990 (1976–2005) and 2040 (2026–2055); the frequency of occurrence of the factors is compared for the two periods, and the resulting frequency shifts are presented in a crop calendar on a monthly basis. This yields an indication of the magnitude and direction of changes in climatic conditions that can lead to damage by extreme events and pests and diseases. We present results for the two most important crops in the region, seed potato, and winter wheat. The results provide a good overview of risks from climate factors, and the most important threats and opportunities are identified. This semi-quantitative approach is firmly rooted in farm management, which is the level where operational and strategic decisions are made. Thus, the approach is well suited to assist local stakeholders such as farmers and policy makers to explore farm-level adaptation. This work is complementary to previous modeling work that focused mainly on the relation between mean climate change factors (i.e., temperature) and crop yield.     

Sensitivity of Portuguese forest fires to climatic, human, and landscape variables: subnational differences between fire drivers in extreme fire years and decadal averages

Within the changing fire regimes of Portugal, the relative importance of humans and climatic variability for regional fire statistics remains poorly understood. This work investigates the statistical relationship between temporal dynamics of fire events in Portugal and a set of socioeconomic, landscape, and climatic variables for the time periods of 1980–1990, 1991–2000, and extreme fires years. For 10 of 15 districts, it was possible to observe moderate shifts in the significance of fire drivers for the first two decadal periods. For others, pronounced changes of the significance of fire drivers were found across time. Results point toward a dynamic (perhaps highly non-linear) behavior of socioeconomic and landscape fire drivers, especially during the occurrence of extreme fire years of 2003 and 2005. At country level, population density alone explained 42% of the inter-annual and inter-district deviance in number of fires. At the same temporal and spatial scale, the explanatory power of temperature anomalies proved to explain 43% of area burnt. We highlight the necessity of including a broad set of socioeconomic and landscape fire drivers in order to account for potential significance shifts. In addition, although climate does trigger broad favorable fire conditions across Portugal mainland, socioeconomic and landscape factors proved to determine much of the complex fire patterns at a subnational scale.     

The impact of climate change and its uncertainty on carbon storage in Switzerland

Projected future climate change will alter carbon storage in forests, which is of pivotal importance for the national carbon balance of most countries. Yet, national-scale assessments are largely lacking. We evaluated climate impacts on vegetation and soil carbon storage for Swiss forests using a dynamic vegetation model. We considered three novel climate scenarios, each featuring a quantification of the inherent uncertainty of the underlying climate models. We evaluated which regions of Switzerland would benefit or lose in terms of carbon storage under different climates, and which abiotic factors determine these patterns. The simulation results showed that the prospective carbon storage ability of forests depends on the current climate, the severity of the change, and the time required for new species to establish. Regions already prone to drought and heat waves under current climate will likely experience a decrease in carbon stocks under prospective ‘extreme’ climate change, while carbon storage in forests close to the upper treeline will increase markedly. Interestingly, when climate change is severe, species shifts can result in increases in carbon stocks, but when there is only slight climate change, climate conditions may reduce growth of extant species while not allowing for species shifts, thus leading to decreases in carbon stocks.     

Forest plantations, water availability, and regional climate change: controversies surrounding Acacia mearnsii plantations in the upper Palnis Hills, southern India

Plantation forests not only impact carbon and water cycles, but also affect biodiversity, livelihoods, and shape regional economies. Each of these impacts differs across varying scales of analysis. This paper illustrates how forest, climate change and hydrology debates play out in the context of the forest plantations of Australian black wattle (Acacia mearnsii) in the upper Palni hills of southern India. We outline the contradictory perspectives of different local groups regarding the impact of plantations on catchment hydrology and water availability, and examine these in relation to changes in the regional economy and rainfall patterns. Our analysis indicates that changes in these two factors have played a more significant role than existing wattle plantations in affecting local and regional water availability. We suggest that ongoing debates regarding forest plantation–hydrology–climate change relationships need to broaden their scope to include changes in regional rainfall patterns and shifts in regional economic activity. This approach is likely to provide a more realistic assessment of plantation forests in a dynamic regional context, and offer more resilient strategies for regional landscape and catchment management under conditions of high variability in rainfall patterns.     

Woody vegetation change in Sahelian West Africa: evidence from local knowledge

Vegetation changes in Sahelian West Africa have been increasingly investigated since 1970 due to the catastrophic droughts in the early 1970s and 1980s and the following decades with below average precipitation. In most cases this was done by remote sensing and vegetation studies. In recent years, local knowledge of farmers and pastoralists about vegetation changes has been increasingly investigated. In this paper, information from different case studies in three West African countries (Burkina Faso, Niger, Senegal) was used to analyse and evaluate vegetation changes in the Sahel. In total, data were analysed from 25 villages, where the local people were asked to mention plant species and qualify their present occurrence compared to the past. In total, 111 woody species were mentioned as having changed compared to the past, of which 79% were classified as having decreased or disappeared. For each single location 8–59 different woody species were mentioned. In most cases, these are valuable species of socio-economic importance. Only 11% of the species was classified as increasing or new (0–12 were mentioned per location), the later being mainly exotic species. Ten percent were categorised differently among villages. A comparison of local knowledge from different locations provide regional scale information on endangered species and thereby crucial information for making insightful priorities for assisted regeneration, reforestation and conservation strategies.     

Vegetation and climate

Over the last two centuries, man's activities have caused a 30% increase in the atmospheric concentration of CO₂, with continued increases seeming inevitable. This change in CO₂ concentration will act on vegetation, both directly and indirectly through global climatic change. It is well established that, on a global scale, patterns of vegetation and climate are closely correlated. Such correlations indicate that climatic change will cause the distribution of vegetation to change. However, the use of correlations for predicting vegetation responses to climatic change is fundamentally unreliable because correlations have no mechanistic underpinning of causation. This paper outlines a mechanistic model for predicting the equilibrium state between current climate and vegetation. It is also used to indicate the sensitivity of global vegetation to the changed climate associated with a doubled CO₂—greenhouse scenario. The interpretation of this static model is discussed in terms of rates and patterns of vegetation change.     

Climate change vulnerability and resilience: current status and trends for Mexico

Climate change alters different localities on the planet in different ways. The impact on each region depends mainly on the degree of vulnerability that natural ecosystems and human-made infrastructure have to changes in climate and extreme meteorological events, as well as on the coping and adaptation capacity toward new environmental conditions. This study assesses the current resilience of Mexico and Mexican states to such changes, as well as how this resilience will look in the future. In recent studies (Moss et al. in Vulnerability to climate change: a quantitative approach. Pacific Northwest National Laboratory, Washington DC, 2001; Brenkert and Malone in Clim Change 72:57–102, 2005; Malone and Brenkert in Clim Change 91:451–476, 2008), the Vulnerability–Resilience Indicators Model (VRIM) is used to integrate a set of proxy variables that determine the resilience of a region to climate change. Resilience, or the ability of a region to respond to climate variations and natural events that result from climate change, is given by its adaptation and coping capacity and its sensitivity. On the one hand, the sensitivity of a region to climate change is assessed, emphasizing its infrastructure, food security, water resources, and the health of the population and regional ecosystems. On the other hand, coping and adaptation capacity is based on the availability of human resources, economic capacity, and environmental capacity. This paper presents two sets of results. First, we show the application of the VRIM to determine state-level resilience for Mexico, building the baseline that reflects the current status. The second part of the paper makes projections of resilience under socioeconomic and climate change and examines the varying sources and consequences of those changes. We used three tools to examine Mexico’s resilience in the face of climate change, i.e., the baseline calculations regarding resilience indices made by the VRIM, the projected short-term rates of socioeconomic change from the Boyd–Ibarrarán computable general equilibrium model, and rates of the IPCC-SRES scenario projections from the integrated assessment MiniCAM model. This allows us to have available change rates for VRIM variables through the end of the twenty-first century.     

Synthesis of ecosystem vulnerability to climate change in the Netherlands shows the need to consider environmental fluctuations in adaptation measures

Climate change impacts on individual species are various and range from shifts in phenology and functional properties to changes in productivity and dispersal. The combination of impacts determines future biodiversity and species composition, but is difficult to evaluate with a single method. Instead, a comparison of mutually independent approaches provides information and confidence in patterns observed beyond what may be achieved in individual approaches. Here, we carried out such comparison to assess which ecosystem types in the Netherlands appear most vulnerable to climate change impacts, as arising from changes in hydrology, nutrient conditions and dispersal limitations. We thus combined meta-analyses of species range shifts with species distribution modelling and ecohydrological modelling with expert knowledge in two respective impact studies. Both impact studies showed that nutrient-poor ecosystems and ecosystem types with fluctuating water tables—like hay meadows, moist heathlands and moorlands—seem to be most at risk upon climate change. A subsequent meta-analysis of species–environmental stress relations indicated that particularly endangered species are adversely affected by the combination of drought and oxygen stress, caused by fluctuating moisture conditions. This implies that adaptation measures should not only aim to optimise mean environmental conditions but should also buffer environmental extremes. Major uncertainties in the assessment included the quantitative impacts of vegetation-hydrology feedbacks, vegetation adaptation and interactions between dispersal capacity and traits linked to environmental selection. Once such quantifications become feasible, adaptation measures may be tailor-made and optimised to conserve vulnerable ecosystem types.     

The narrow-skulled vole (<Emphasis Type="Italic">Microtus gregalis</Emphasis> Pall.) in the dynamics of zonal rodent communities of northern Eurasia

On the basis of abundant fossil and subfossil bone remains, the ecological and faunal role of the narrow-skulled vole in zonal rodent communities of northern Eurasia is analyzed over the period from the Late Pleistocene to the present time. Special attention is given to the correlated dynamics of relative abundance of Microtus gregalis and other rodent species in the course of transition from one zonal type to another and to specific features of this correlation in the southern, middle, and northern parts of the species range. It is shown that distinctive dimensional and morphotypic features of the two currently existing subspecies, Microtus gregalis major Ogn. and M. g. gregalis Pall., are the product of concordant development of the species and environmental conditions in the past 3000–4000 years (transition from the Holocene optimum to the present-day climate and state of the natural environment). Published in Russian in Ekologiya, 2007, Vol. 38, No. 2, pp. 117–123. The article was translated by the authors.     

Mid-21st century climate and weather extremes in Cyprus as projected by six regional climate models

We present climate change projections and apply indices of weather extremes for the Mediterranean island Cyprus using data from regional climate model (RCM) simulations driven by the IPCC A1B scenario within the ENSEMBLES project. Daily time-series of temperature and precipitation were used from six RCMs for a reference period 1976–2000 and for 2026–2050 (‘future‘) for representative locations, applying a performance selection among neighboring model grid-boxes. The annual average temperatures of the model ensemble have a ±1.5°C bias from the observations (negative for maximum and positive for minimum temperature), and the models underestimate annual precipitation totals by 4–17%. The climatological annual cycles for the observations fall within the 1σ range of the 6-model average, highlighting the strength of using multi-model output. We obtain reasonable agreement between models and observations for the temperature-related indices of extremes for the recent past, while the comparison is less good for the precipitation-related extremes. For the future, the RCM ensemble shows significant warming of 1°C in winter to 2°C in the summer for both maximum and minimum temperatures. Rainfall is projected to decrease by 2–8%, although this is not statistically significant. Our results indicate the shift of the mean climate to a warmer state, with a relatively strong increase in the warm extremes. The precipitation frequency is projected to decrease at the inland Nicosia and at the coastal Limassol, while the mountainous Saittas could experience more frequent 5–15 mm/day rainfall. In future, very hot days are expected to increase by more than 2 weeks/year and tropical nights by 1 month/year. The annual number of consecutive dry days shows a statistically significant increase (of 9 days) in Limassol. These projected changes of the Cyprus climate may adversely affect ecosystems and the economy of the island and emphasize the need for adaptation strategies.     

Modeling thermoelectric power generation in view of climate change

In this study we investigate how thermal power plants with once-through cooling could be affected by future climate change impacts on river water temperatures and stream flow. We introduce a model of a steam turbine power plant with once-through cooling at a river site and simulate how its production could be constrained in scenarios ranging from a one degree to a five degree increase of river temperature and a 10–50% decrease of stream flow. We apply the model to simulate a large nuclear power plant in Central Europe. We calculate annual average load reductions, which can be up to 11.8%, assuming unchanged stream flow, which leads to average annual income losses of up to 80 million €. Considering simultaneous changes in stream flow will exacerbate the problem and may increase average annual costs to 111 million € in a worst-case scenario. The model demonstrates that power generation could be severely constrained by typical climate impacts, such as increasing river temperatures and decreasing stream flow.     

Spatial assessment of climate change effects on crop suitability for major plantation crops in Sri Lanka

Climate change is the main global challenge of this century; it is therefore imperative to identify its effects on agriculture in developing countries. This research makes spatial assessment of climate change effect on major plantation crops in Sri Lanka, with emphasis on crop suitability of tea, rubber, and coconut. Geo-referenced maps of spatial and temporal changes in crop suitability and production potentials are generated and compared. Data pertaining to six agro-ecological zones under the study area are analyzed for a period of 1980–2007. Crop suitability maps are generated amalgamating yield maps and climatic factors maps using AHP in multi-criteria analysis under two time frames of 1980–1992 and 1993–2007. Percent change in crop suitability and crop yield classes is calculated based on five crop suitability and five crop yield classes during two time frames. Dynamics of climatic parameters and crop yield are recognized using geo-referenced maps. The suitability maps of the two time frames are compared to identify the changes with each crop in conjunction with changes in the prevailing climate and yield. Geographic shift of suitability, yield, and climate classes are examined. Net gain or loss in crop production is quantified. Long-term annual rainfall significantly decreased in mid-country wet zone, whereas the mean temperature of the study area increased by 1.4°C. Results clearly showed that the climate and yield can be meaningfully related to the crop suitability and management.     

Soil organic carbon dynamics of croplands in European Russia: estimates from the “model of humus balance”

The Model of Humus Balance was used to estimate the influence of climate effects and changing agricultural practices on carbon (C) levels in soddy–podzolic soils in the Russian Federation for the years 2000–2050. The model was linked with a spatial database containing soil, climate and farming management layers for identification of spatial change of C sequestration potential. Analysis of relationships between C, soil texture and climate indicated that compared with a business-as-usual scenario, adaptation measures could increase the number of polygons storing soil organic carbon (SOC) by 2010–2020. The rate of possible C loss is sensitive to the different climate scenarios, with a maximum potential for SOC accumulation expected in 2030–2040, thereafter decreasing to 2050. The effect is most pronounced for the arid part of the study area under the emission scenario with the highest rate of increase in atmospheric CO₂ concentration, supporting findings from the dynamic SOC model, RothC. C sequestration during the study period was permanent for clay and clay loam soils with a C content of more than 2%, suggesting that C sequestration should be focused on highly fertile, fine-textured soils. We also show that spatial heterogeneity of soil texture can be a source of uncertainty for estimates of SOC dynamics at the regional scale. Figures in color are available at     

Changes in mineral soil organic carbon stocks in the croplands of European Russia and the Ukraine, 1990–2070; comparison of three models and implications for climate mitigation

Three soil carbon models (RothC, CANDY and the Model of Humus Balance) were used to estimate the impacts of climate change on agricultural mineral soil carbon stocks in European Russia and the Ukraine using detailed spatial data on land-use, future land-use, cropping patterns, agricultural management, climate and soil type. Scenarios of climate were derived from the Hadley Centre climate Version 3 (HadCM3) model; future yields were determined using the Soil–Climate–Yield model, and land use was determined from regional agricultural and economic data and a model of agricultural economics. The models suggest that optimal management, which entails the replacement of row crops with other crops, and the use of extra years of grass in the rotation could reduce Soil organic carbon (SOC) loss in the croplands of European Russia and the Ukraine by 30–44% compared to the business-as-usual management. The environmentally sustainable management scenario (SUS), though applied for a limited area within the total region, suggests that much of this optimisation could be realised without damaging profitability for farmers.     

Modelling bark beetle disturbances in a large scale forest scenario model to assess climate change impacts and evaluate adaptive management strategies

To study potential consequences of climate-induced changes in the biotic disturbance regime at regional to national scale we integrated a model of Ips typographus (L. Scol. Col.) damages into the large-scale forest scenario model EFISCEN. A two-stage multivariate statistical meta-model was used to upscale stand level damages by bark beetles as simulated in the hybrid forest patch model PICUS v1.41. Comparing EFISCEN simulations including the new bark beetle disturbance module against a 15-year damage time series for Austria showed good agreement at province level (R2 between 0.496 and 0.802). A scenario analysis of climate change impacts on bark beetle-induced damages in Austria’s Norway spruce [Picea abies (L.) Karst.] forests resulted in a strong increase in damages (from 1.33 Mm3 a⁻¹, period 1990–2004, to 4.46 Mm3 a⁻¹, period 2095–2099). Studying two adaptive management strategies (species change) revealed a considerable time-lag between the start of adaptation measures and a decrease in simulated damages by bark beetles.     

Understanding deforestation in the southern Yucatán: insights from a sub-regional, multi-temporal analysis

The southern Yucatán has been identified as a deforestation hot spot. Land-change studies document the extent of forest loss at a regional scale, and case studies provide insights into the drivers of deforestation at the household level. Those studies have paid minimal attention to sub-regional analysis, especially to discrete land-management units above the household level. This analysis of upland forest change addresses the range of variation in deforestation among 96 ejidos (communal lands) and the Calakmul Biosphere Reserve, the two dominant land-tenure and land-management units in the region. Satellite imagery, census, and land-tenure data are used to establish the extent and location of deforestation patterns, and multivariate techniques are employed to identify biophysical and socioeconomic variables that explain such patterns. Results show that, for the 1984–1993 period, deforestation in the southern Yucatán was not as prevalent as implied by its hot spot designation. Three clusters of deforestation are identified. A logistic regression analysis establishes that size of forest holdings, population growth, and location in the precipitation gradient correlate with ejidos that experienced higher deforestation rates than the rest of the land-tenure units. For the 1993–2000 period, conservation programs and changes in the economic context of this “hollow frontier” contributed to reduce deforestation rates and extent. This analysis illustrates the spatio-temporal heterogeneity of much tropical forest change and caution that it should bring to simple formulations of modeling this change and prescribing policies to control it.     

Impact of climate change on human infectious diseases: Empirical evidence and human adaptation

Climate change refers to long-term shifts in weather conditions and patterns of extreme weather events. It may lead to changes in health threat to human beings, multiplying existing health problems. This review examines the scientific evidences on the impact of climate change on human infectious diseases. It identifies research progress and gaps on how human society may respond to, adapt to, and prepare for the related changes. Based on a survey of related publications between 1990 and 2015, the terms used for literature selection reflect three aspects — the components of infectious diseases, climate variables, and selected infectious diseases. Humans' vulnerability to the potential health impacts by climate change is evident in literature. As an active agent, human beings may control the related health effects that may be effectively controlled through adopting proactive measures, including better understanding of the climate change patterns and of the compound disease-specific health effects, and effective allocation of technologies and resources to promote healthy lifestyles and public awareness. The following adaptation measures are recommended: 1) to go beyond empirical observations of the association between climate change and infectious diseases and develop more scientific explanations, 2) to improve the prediction of spatial–temporal process of climate change and the associated shifts in infectious diseases at various spatial and temporal scales, and 3) to establish locally effective early warning systems for the health effects of predicated climate change.     

Nature and fate of Hudson Bay permafrost

Two aspects of the permafrost of the Hudson Bay region are examined. The first is the climatological conditions that support permafrost especially along the southwestern shore of Hudson Bay. The second is the fate of the permafrost using recent climate change scenarios. The continuous permafrost along the shores of southwestern Hudson Bay is examined from a climatological perspective. Two hypotheses are explored to explain the presence of continuous permafrost in this region in spite of the relatively "warm" local climate. Possible errors in the calculation of thawing degree days and the asymmetries in frozen and unfrozen soil thermal conductivities are successively examined. Only the second hypothesis is likely to explain the presence of permafrost in southwestern Hudson Bay. Sophisticated climate models are used to assess the potential change in permafrost distribution in the Hudson Bay region. Nine simulations using three different versions of the Canadian Centre of Climate Modelling and Analysis (CCCma) general circulation model are used to project permafrost distribution. Two surface temperature thresholds, –5 and –10 °C, are used to diagnose permafrost grid points. All simulations, including those that include reduction of CO₂ emissions, showed at least a 50% reduction of permafrost by 2100 using these temperature thresholds. Electronic Publication