Search

Leptospirosis is a neglected waterborne zoonosis of growing concern in tropical and low-income regions. Endemic in Southeast Asia, its distribution and environmental factors such as climate controlling its dynamics remain poorly documented. In this paper, we investigate for the first time the current and future leptospirosis burden at a local scale in mainland Southeast Asia. We adjusted machine-learning models on incidence reports from the Thai surveillance system to identify environmental determinants of leptospirosis. The explanatory variables tested in our models included climate, topographic, land cover and soil variables. The model performing the best in cross-validation was used to estimate the current incidence regionally in Thailand, Myanmar, Cambodia, Vietnam and Laos. It then allowed to predict the spatial distribution of leptospirosis future burden from 2021 to 2100 based on an ensemble of CMIP6 climate model projections and 4 Shared Socio-economics Pathways ranging from the most optimistic to the no-climate policy outcomes (SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5). Leptospirosis incidence was best estimated by 10 environmental variables: four landscape-, four rainfall-, two temperature-related variables. Of all tested scenario, the worst-case scenario of climate change (SSP5-8.5) surprisingly appeared as the best-case scenario for the future of leptospirosis since it would induce a significant global decline in disease incidence in Southeast Asia mainly driven by the increasing temperatures. These global patterns are however contrasted regionally with some regions showing increased incidence in the future. Our work highlights climate and the environment as major drivers of leptospirosis incidence in Southeast Asia. Applying our model to regions where leptospirosis is not routinely monitored suggests an overlooked burden in the region. As our model focuses on leptospirosis responses to environmental drivers only, some other factors, such as poverty, lifestyle or behavioral changes, could further influence these estimated future patterns., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.)

Determining the drivers of shifting forest disturbance rates remains a pressing global change issue. Large-scale forest dynamics are commonly assumed to be climate driven, but appropriately scaled disturbance histories are rarely available to assess how disturbance legacies alter subsequent disturbance rates and the climate sensitivity of disturbance. We compiled multiple tree ring-based disturbance histories from primary Picea abies forest fragments distributed throughout five European landscapes spanning the Bohemian Forest and the Carpathian Mountains. The regional chronology includes 11,595 tree cores, with ring dates spanning the years 1750-2000, collected from 560 inventory plots in 37 stands distributed across a 1,000 km geographic gradient, amounting to the largest disturbance chronology yet constructed in Europe. Decadal disturbance rates varied significantly through time and declined after 1920, resulting in widespread increases in canopy tree age. Approximately 75% of current canopy area recruited prior to 1900. Long-term disturbance patterns were compared to an historical drought reconstruction, and further linked to spatial variation in stand structure and contemporary disturbance patterns derived from LANDSAT imagery. Historically, decadal Palmer drought severity index minima corresponded to higher rates of canopy removal. The severity of contemporary disturbances increased with each stand's estimated time since last major disturbance, increased with mean diameter, and declined with increasing within-stand structural variability. Reconstructed spatial patterns suggest that high small-scale structural variability has historically acted to reduce large-scale susceptibility and climate sensitivity of disturbance. Reduced disturbance rates since 1920, a potential legacy of high 19th century disturbance rates, have contributed to a recent region-wide increase in disturbance susceptibility. Increasingly common high-severity disturbances throughout primary Picea forests of Central Europe should be reinterpreted in light of both legacy effects (resulting in increased susceptibility) and climate change (resulting in increased exposure to extreme events)., (© 2018 John Wiley & Sons Ltd.)

Climate change is not only likely to improve conditions for crop production in Sweden, but also to increase weed pressure and the need for herbicides. This study aimed at assessing and contrasting the direct and indirect effects of climate change on herbicide leaching to groundwater in a major crop production region in south-west Sweden with the help of the regional pesticide fate and transport model MACRO-SE. We simulated 37 out of the 41 herbicides that are currently approved for use in Sweden on eight major crop types for the 24 most common soil types in the region. The results were aggregated accounting for the fractional coverage of the crop and the area sprayed with a particular herbicide. For simulations of the future, we used projections of five different climate models as model driving data and assessed three different future scenarios: (A) only changes in climate, (B) changes in climate and land-use (altered crop distribution), and (C) changes in climate, land-use, and an increase in herbicide use. The model successfully distinguished between leachable and non-leachable compounds (88% correctly classified) in a qualitative comparison against regional-scale monitoring data. Leaching was dominated by only a few herbicides and crops under current climate and agronomic conditions. The model simulations suggest that the direct effects of an increase in temperature, which enhances degradation, and precipitation which promotes leaching, cancel each other at a regional scale, resulting in a slight decrease in leachate concentrations in a future climate. However, the area at risk of groundwater contamination doubled when indirect effects of changes in land-use and herbicide use, were considered. We therefore concluded that it is important to consider the indirect effects of climate change alongside the direct effects and that effective mitigation strategies and strict regulation are required to secure future (drinking) water resources., (Copyright © 2014 Elsevier B.V. All rights reserved.)

Background and Aims The hart's tongue fern (HTF) complex is a monophyletic group composed of five geographically segregated members with divergent abundance patterns across its broad geographic range. We postulated hierarchical systems of environmental controls in which climatic and land-use change drive abundance patterns at the global scale, while various ecological conditions function as finer scale determinants that further increase geographic disparities at regional to local scales. Methods After quantifying the abundance patterns of the HTF complex, we estimated their correlations with global climate and land-use dynamics. Regional determinants were assessed using boosted regression tree models with 18 potential ecological variables. Moreover, we investigated long-term population trends in the USA to understand the interplay of climate change and anthropogenic activities on a temporal scale. Key Results Latitudinal climate shifts drove latitudinal abundance gradients, and regionally different levels of land-use change resulted in global geographic disparities in population abundance. At a regional scale, population isolation, which accounts for rescue effects, played an important role, particularly in Europe and East Asia where several hot spots occurred. Furthermore, the variables most strongly influencing abundance patterns greatly differed by region: precipitation seasonality in Europe; spatial heterogeneity of temperature and precipitation in East Asia; and magnitudes of past climate change, temperature seasonality and edaphic conditions in North America. In the USA, protected populations showed increasing trends compared with unprotected populations at the same latitude, highlighting the critical role of habitat protection in conservation measures. Conclusions Geographic disparities in the abundance patterns of the HTF complex were determined by hierarchical systems of environmental controls, wherein climatic and land-use dynamics act globally but are modulated by various regional and local determinants operating at increasingly finer scales. We highlighted that fern conservation must be tailored to particular geographic contexts and environmental conditions by incorporating a better understanding of the dynamics acting at different spatiotemporal scales. [ABSTRACT FROM AUTHOR]

SOC storage (SOCS) plays a vital role in global climate change. Understanding the spatial pattern and features of soil organic carbon (SOC) and its influencing factors is important for increasing SOC fixation. However, few studies exist on the organic carbon reserves of farmland on a regional scale. This study revealed the SOCD and SOCS values and distribution using Hubei Province as a sampling region. The results demonstrated that the spatial distributions of farmland system carbon storage and density were uneven, and the spatial heterogeneity was related to geography, cultivated area, and soil type. The SOCD ranged from 0.559 to 10.613 kg/m2, with an average of 3.3710 ± 0.0337 kg/m2, and the soil carbon reserve of the farmland system was ~17.81 Tg. The SOCD varied with topography and soil type: in mountainous cultivated land, it was generally higher than that in hilly land and in the plains. However, the plain cultivated areas contained the highest carbon reserves. Within the farmland system, paddy soil, the dominant soil type, exhibited higher SOCD and larger SOC storage capacity. Soil types with the same physicochemical properties exhibited different organic carbon storage capacity in different geomorphic and regional environments. Specifically, paddy soil was found to have higher SOCD and SOCS than the other soil types, and its soil carbon storage capacity was high; the SOC reserves of wheat-rice tillage were the largest among the main tillage methods. Boosting the soil carbon sink requires fundamental improvement in soil properties by improving soil texture, using conservation tillage to increase soil organic matter, and reducing unnecessary human interference. [ABSTRACT FROM AUTHOR]

The crucial roles of soil carbon (C) and nutrients and their stoichiometric characteristics in indicating the soil interior nutrient cycling and plant nutrient supply of forest ecosystems have been widely verified, whereas it has been less explored when considering the influencing factors regionally, especially for the widely cultivated plantation tree species. In the current study, the patterns of soil organic C (SOC), total nitrogen (TN), and total phosphorus (TP) stoichiometry in Chinese fir [Cunninghamia lanceolata (Lamb.) Hook] plantations across subtropical China were analyzed, and their influencing factors were also investigated. The results showed that the range of SOC: TN (C:N), SOC: TP (C:P), and TN: TP (N:P) ratios were 7.32–18.27, 20.15–230.48, and 2.11–15.05 with a mean value of 13.22, 83.50, and 6.05, respectively. Well-constrained correlations were found in SOC and TN, as well as in TN and TP. Soil TN and TP contents increased with increasing altitude, whereas soil C:N, C:P, and N:P ratios decreased. Soil TP content decreased, and the C:P ratio increased with increasing mean annual temperature (MAT) and annual total solar radiation (ATSR). Soil C:N, C:P, and N:P ratios increased with increased mean annual precipitation (MAP) and mean annual evaporation (MAE). Overall, our findings suggested that the soil nutrient supply is relatively adequate in Chinese fir plantations across subtropical China. Meanwhile, soil C, N, and P stoichiometric characteristics were affected by geographical and climatic variables to different degrees.

Vegetation change can significantly alter evapotranspiration (ET), an important component of the terrestrial water balance, and consequently influences other hydrological processes. With no direct measurement techniques available at large spatial scales, the accurate estimation of ET under changing forest landscapes and climate is challenging. In this study, we used an improved method based on Fuh's equation (a functional form of the Budyko framework) to investigate ET responses to cumulative forest disturbance and climate in the snow‐dominated interior of British Columbia, Canada. First, we divided the study region into three distinct climate groups, and then related the watershed parameter m in Fuh's equation to vegetation change (represented by cumulative equivalent clearcut area (CECA)) and watershed properties, with independent calibration and validation watersheds. The validated relationships were used to examine regional ET variations (∼380,000 km2). Our results showed that ET in moderate climates had the highest sensitivity to CECA, characterized by wetness index between 1 and 2 (the ratio of precipitation to potential evapotranspiration). ET in dry climates (wetness index <1) was also significantly related to CECA, but with reduced sensitivity compared to the moderate climates. Wetter climates (wetness index >2) did not show a significant relationship with CECA, suggesting an insensitivity of ET to forest change. Simulations under future climate and vegetation disturbance scenarios demonstrated that ET would be further decreased in most of the study region. Forest management should consider reducing disturbance in the dry to moderate climate areas to mitigate negative impacts on hydrological processes and functions. Key Points: We related the watershed parameter m in Fuh's equation to forest disturbance for estimating evapotranspiration (ET) under changing vegetation and climateForest disturbance significantly decreased ET in most parts of the study regionET was most sensitive to forest disturbance in moderate climates, with reduced sensitivity in dry areas, and no sensitivity in wet areas [ABSTRACT FROM AUTHOR]

Climate change adaptation has become the current focus of research due to the remarkable potential of climate change to alter the spatial and temporal distribution of global water availability. Although reservoir operation is a potential adaptation option, earlier studies explicitly demonstrated only its historical quantitative effects. Therefore, this article evaluated the possibility of reservoir operation from an adaptation viewpoint for regulating the future flow using the H08 global hydrological model with the Chao Phraya River basin as a case study. This basin is the largest river system in Thailand and has often been affected by extreme weather challenges in the past. Future climate scenarios were constructed from the bias‐corrected outputs of three general circulation models from 2080 to 2099 under RCP4.5 and RCP8.5. The important conclusions that can be drawn from this study are as follows: (i) the operation of existing and hypothetical (i.e., construction under planning) reservoirs cannot reduce the future high flows below the channel carrying capacity, although it can increase low flows in the basin. This indicates that changes in the magnitude of future high flow due to climate change are likely to be larger than those achieved by reservoir operation and there is a need for other adaptation options. (ii) A combination of reservoir operation and afforestation was considered as an adaptation strategy, but the magnitude of the discharge reduction in the wet season was still smaller than the increase caused by warming. This further signifies the necessity of combining other structural, as well as non‐structural, measures. Overall, this adaptation approach for assessing the effect of reservoir operation in reducing the climate change impacts using H08 model can be applied not only in the study area but also in other places where climate change signals are robust. [ABSTRACT FROM AUTHOR]

Identifying the main controlling factors of the stream temperature (Tw) variability is important to target streams sensitive to climate and other drivers of change. The thermal sensitivity (TS), based on relationship between air temperature (Ta) and Tw, of a given stream can be used for quantifying the streams sensitivity to future climate change. This study aims to compare TS for a wide range of temperate streams located within a large French catchment (110,000 km2) using 4 years of hourly data (2008–2012) and to cluster stations sharing similar thermal variabilities and thereby identify environmental key drivers that modify TS at the regional scale. Two successive classifications were carried out: (a) first based on Ta–Tw relationship metrics including TS and (b) second to establish a link between a selection of environmental variables and clusters of stations. Based on weekly Ta–Tw relationships, the first classification identified four thermal regimes with differing annual Tw in terms of magnitude and amplitudes in comparison with Ta. The second classification, based on classification and regression tree method, succeeded to link each thermal regime to different environmental controlling factors. Streams influenced by both groundwater inflows and shading are the most moderated with the lowest TS and an annual amplitude of Tw around half of the annual amplitude of Ta. Inversely, stations located on large streams with a high distance from source and not (or slightly) influenced by groundwater inflows nor shading showed the highest TS, and so, they are very climate sensitive. These findings have implications for guiding river basin managers and other stakeholders in implementing thermal moderation measures in the context of a warming climate and global change. [ABSTRACT FROM AUTHOR]

• Regional assessment of natural regeneration occurrence in Mediterranean forests. • Regeneration occurrence depends on climatic and stand variables. • According climate predictions suitable conditions for regeneration will decreases. • Regeneration benefited from the presence of mixture in the overstory. The generation of projections under different climate scenarios and stand conditions provides a useful tool to explore the consequences of climate change on ecosystem dynamics and to define possible interventions to ensure their persistence over time. Over recent decades, climate change has been particularly severe in the Mediterranean basin, where a lack of natural regeneration is one of the main limitations threatening Mediterranean forests. In this context, in order to define the main drivers affecting this process, we evaluated the occurrence of regeneration in P. pinea and P. pinaster forests, taking into account the stand-structure as well as climate conditions. The regeneration data is taken from a network of 1703 plots located on the Northern Plateau of Spain and monitored over 15 years. Through survival analysis we modeled the probability of regeneration occurrence after a time t (years since regeneration fellings were carried out) at regional level. The model was then used to simulate regeneration success under two climatic scenarios. According to the modeling results, the ability of P. pinaster to regenerate was always lower than that of P. pinea , regardless of the scenario and stand conditions. The relationship between regeneration success and presence of adult trees varies depending on the species composition. Higher probabilities of regeneration occurrence were positively associated with mixed species composition in adult trees for both species, while P. pinaster exhibited significantly lower regeneration under monospecific P. pinea adult trees. Regeneration probability was negatively associated with increasing levels of grass cover on soils. The results also pointed to the existence of climate-mediated annual regeneration occurrence, reflecting the complex interaction which exists between environmental factors and the optimum conditions for natural regeneration. The findings obtained in the present study could help us to identify problematic areas with regard to natural regeneration so that appropriate management can be defined to favor the different species in future stands. [ABSTRACT FROM AUTHOR]

Soil erosion represents a major environmental threat to ecosystems. Effective sediment trapping relies on the cooperation of multiple soil erosion control measures. However, findings on the synergistic effects of multiple soil erosion control measures are still lacking, in particular on a large spatial scale. This study provides a first attempt to analyze four decades of data from the 1980s to the 2010s on the Loess Plateau. The analysis combines the spatial investigation of check‐dam construction in gullies, afforestation on hillslopes, and station‐observed sediment yield within the evaluation framework of the Water and Tillage Erosion Model/Sediment Delivery Model. The results indicate two periods of effective sediment trapping on the Loess Plateau in the last four decades: 1980s–1990s and 2000s–2010s. Check‐dam construction was the main driver of reduced sediment yields before the 1990s. Massive afforestation played an increasingly important role beginning in 1999. The synergistic effects of afforestation and the construction of check‐dams in the period from the 2000s to the 2015 include not only the effective trapping of sediment but also the improvements in the resistance of ecosystems to climate change. These results improve our understanding of the synergistic effects of multiple soil erosion control measures on sediment trapping. The findings support a rational collocation of different soil erosion control measures to support comprehensive management in erosion‐prone regions. [ABSTRACT FROM AUTHOR]

Modelling river temperature at the catchment scale is needed to understand how aquatic communities may adapt to current and projected climate change. In small and medium rivers, riparian vegetation can greatly reduce maximum water temperature by providing shade. It is thus important that river temperature models are able to correctly characterise the impact of this riparian shading. In this study, we describe the use of a spatially-explicit method using LiDAR-derived data for computing the riparian shading on direct and diffuse solar radiation. The resulting data are used in the T-NET one-dimensional stream temperature model to simulate water temperature from August 2007 to July 2014 for 270 km of the Loir River, an indirect tributary of the Loire River (France). Validation is achieved with 4 temperature monitoring stations spread along the Loir River. The vegetation characterised with the LiDAR approach provides a cooling effect on maximum daily temperature ( T max ) ranging from 3.0 °C (upstream) to 1.3 °C (downstream) in late August 2009. Compared to two other riparian shading routines that are less computationally-intensive, the use of our LiDAR-based methodology improves the bias of T max simulated by the T-NET model by 0.62 °C on average between April and September. However, difference between the shading routines reaches up to 2 °C (monthly average) at the upstream-most station. Standard deviation of errors on T max is not improved. Computing the impact of riparian vegetation at the hourly timescale using reach-averaged parameters provides results close to the LiDAR-based approach, as long as it is supplied with accurate vegetation cover data. Improving the quality of riparian vegetation data should therefore be a priority to increase the accuracy of stream temperature modelling at the regional scale. [ABSTRACT FROM AUTHOR]

Abstract: Determining the drivers of shifting forest disturbance rates remains a pressing global change issue. Large‐scale forest dynamics are commonly assumed to be climate driven, but appropriately scaled disturbance histories are rarely available to assess how disturbance legacies alter subsequent disturbance rates and the climate sensitivity of disturbance. We compiled multiple tree ring‐based disturbance histories from primary Picea abies forest fragments distributed throughout five European landscapes spanning the Bohemian Forest and the Carpathian Mountains. The regional chronology includes 11,595 tree cores, with ring dates spanning the years 1750–2000, collected from 560 inventory plots in 37 stands distributed across a 1,000 km geographic gradient, amounting to the largest disturbance chronology yet constructed in Europe. Decadal disturbance rates varied significantly through time and declined after 1920, resulting in widespread increases in canopy tree age. Approximately 75% of current canopy area recruited prior to 1900. Long‐term disturbance patterns were compared to an historical drought reconstruction, and further linked to spatial variation in stand structure and contemporary disturbance patterns derived from LANDSAT imagery. Historically, decadal Palmer drought severity index minima corresponded to higher rates of canopy removal. The severity of contemporary disturbances increased with each stand's estimated time since last major disturbance, increased with mean diameter, and declined with increasing within‐stand structural variability. Reconstructed spatial patterns suggest that high small‐scale structural variability has historically acted to reduce large‐scale susceptibility and climate sensitivity of disturbance. Reduced disturbance rates since 1920, a potential legacy of high 19th century disturbance rates, have contributed to a recent region‐wide increase in disturbance susceptibility. Increasingly common high‐severity disturbances throughout primary Picea forests of Central Europe should be reinterpreted in light of both legacy effects (resulting in increased susceptibility) and climate change (resulting in increased exposure to extreme events). [ABSTRACT FROM AUTHOR]

Climate change and emissions rates of contaminants are expected to affect distribution and fate of Persistent Organic Pollutants (POPs) in the environment, however, studies on these combined factors are rare. In this study, Perfluorooctane Sulfonate (PFOS) is used as an example to assess how those two factors synthetically affect fate and disposition of POPs in the Bohai Rim of China by using the Berkeley-Trent-Urban-Rural (BETR-Urban-Rural) model. We set up three climate change scenarios and four emission scenarios to conduct the simulations. The results show that climate change could have significant effects on the transport and fate of PFOS mainly including advection, inter-compartmental transfer under the “worst case” emission scenario. For most grids, a remarkable decrease in concentrations of PFOS are predicted for fresh water and urban soil in the future, with precipitation and temperature being predominant factors, whilst for coastal water and rural soil, an increasing trend is predicted. Additionally, predicted sum of sources to the Bohai Sea increases greater than removals from the Bohai Sea in the future, adding evidence that concentrations of PFOS in coastal water will increase more in the future. Under scenarios of reduced emissions and climate change, concentrations of PFOS in each compartment decreased more rapidly over time. We suggest that assessment of future climate change impacts on fate of PFOS could take emission reductions into consideration. [ABSTRACT FROM AUTHOR]

This study presents a comprehensive methodology that addresses climate change–induced coastal erosion at the regional scale O (100 km). The use of climate data with high space-time resolution enabled the reconstruction of the shoreline response to cross-shore forcing both historically and throughout the twenty-first century. Cross section–based equilibrium models were combined to assess beach erosion induced by local waves, storm surge, astronomical tide and mean sea-level rise. The approach incorporates the potential impacts that tidal inlets could have on the long-term evolution of adjacent beaches as sink terms in the beaches’ budget. The methodology provides probabilistic estimates of coastline recession while accounting for sea level rise uncertainty, both of which are essential aspects for establishing adaptation priorities and efficient fund allocation. The outlined assessment was undertaken on 57 sandy beaches along a 345 km coastline stretch in Asturias, a region in the northwest of Spain open to the Atlantic. [ABSTRACT FROM AUTHOR]

Soil moisture is an important state variable in terrestrial water cycles; however, only few studies are available on regional soil moisture spatial variability (SMSV), which yielded inconsistent findings about regional controls on SMSV. Here, long-term soil moisture data were obtained from the Automated Weather Data Network and Soil Climate Analysis Network in three regions with different climate regimes across the continental U.S. Comprehensive data sets were compiled to examine regional controls on SMSV using the method of Empirical Orthogonal Function. One dominant spatial structure (EOF1) of soil moisture was found in the study regions, which explained over 75%, 67%, and 86% of the spatial variance in soil moisture in Nebraska, Utah, and the Southeast U.S., respectively. Despite the significant spatial variability in precipitation and potential evapotranspiration in all the study regions, the results showed that meteorological forcings had limited effects on regional SMSV in those regions with different climatic conditions, which differed from the traditional notion that SMSV is mainly controlled by meteorological forcings at the scale from 50 to 400 km. Instead, local factors related to soil (e.g., sand and clay fractions) were found to have significant correlations with EOF1, although the effects of other local factors (e.g., topography and vegetation) were generally negligible. This study provides strong field evidence that soil can exert much stronger impacts on regional SMSV than previously thought, which can override the effects of meteorological forcings. Future studies are still needed to elaborate on the relative roles of climate and soil in affecting regional SMSV. [ABSTRACT FROM AUTHOR]

Increased intensity and duration of droughts and high-temperature events have been associated with forest decline in many parts of the world, and these decline events are expected to become more common under climate change. There is, therefore, a need for monitoring and modeling of forest decline. We used a regional forest condition monitoring program (DEBOSCAT) to study the spatial distribution of decline events in 2012 in Catalonia (Northeastern Spain) and their relationship with climatic factors. In 2012, this dataset was collected after an extraordinarily dry summer, and allowed the study of decline events in eight dominant tree species. We fitted a logistic model to predict forest decline probability as a function of species, precipitation and temperature anomalies, solar radiation, and remotely sensed soil moisture data from the Soil Moisture and Ocean Salinity Mission (SMOS). Broadleaved species were more affected by decline events than conifers. The statistical model explained almost 40% of forest decline occurrence, wherein almost 50% of this variability was explained by species effect, with broadleaved trees being generally more sensitive to the studied factors than conifers. Climatically wetter areas and those more exposed to radiation were more likely to be affected, suggesting better adaptation of forests in dry areas. In general, more damaged forests were characterized by high-positive temperature anomalies, lower than average rainfall, and low soil moisture in summer 2012. The most vulnerable species was Fagus sylvatica, a Euro-Siberian species, contrasting with Pinus halepensis, a typically Mediterranean species, which showed low sensitivity to drought. [ABSTRACT FROM PUBLISHER]

The elaboration of conservation strategies at regional scale, dealing with the potential effects of climate change on the abundance and distribution of tree species, should be supported by models produced at the appropriate scale. We used a bioclimatic model aimed at analysing the large-scale effects of climate change on the abundance and distribution of tree species with respect to their chorological and ecological characteristics. Abundance data for 16 species, sampled in 912 plots, distributed on a 3x3 km grid were used. A climatic model provided high resolution current climatic surfaces and a climatic scenario for 2080 was obtained using the A1FI emission scenario of HadCM3 GCM. A deterministic Regression Tree Analysis (RTA) and Multiple Linear Regression (MLR) were applied in order to define the realised niche of the species in relation to the chosen environmental variables. The comparison between RMSE values showed that RTA always outperforms MLR, in terms of predicting species distribution. Zonal species were better predicted than rare species (extrazonal or with specific habitat requirements). Climate change is expected to determine a general increase of the average potential altitude. Only the Mediterranean species are likely to be favoured by the predicted climate change, while for the two other chorological types (Sub-Mediterranean and Eurosiberian) the response seems to be species-specific, depending on the ecological characteristic of each species: the more thermophilous and xerophilous species should benefit from the predicted drought in terms of area and mean abundance, while mesophilous species should suffer a strong reduction.

Participatory modeling (PM) has become an essential concept in environmental impact assessment and planning in the field of water resources. In this paper, we focus on the use of PM to support the development of the integrated regional modeling system DANUBIA as a scientific concept to analyze the previously unknown impacts of global change, i.e., the combined effects of climate, demographic, economic, social and ecological change, on the Upper Danube Catchment (Germany). We use this case study to examine the specific conditions for PM in the field of complex integrated models on a regional scale. We describe the stepwise PM process and discuss the respective results, focusing on (1) the stakeholder dialogue's contribution in supporting the development of new, complex modeling systems, particularly on a regional scale, (2) conditions of stakeholder involvement in issues related to the distant future, such as climate change impacts on regional water availability, and (3) limitations of PM and scientists' motivation to carry out participatory research at all. We conclude that the PM process was not entirely successful in improving the scientific quality and practical applicability of the developed models because the process goals were manifold and overambitious, and the definition of the problem of 'global change impacts on a regional scale' was too weak and uncertain to allow for a clear common objective of modelers and stakeholders. We claim that there is a lack of incentives for scientists, particularly natural scientists, to commit to PM activities. [ABSTRACT FROM AUTHOR]

This paper assesses the relative importance of socioeconomic factors linked to fire occurrence through the simulation of future land use/land cover (LULC) change scenarios in the Madrid region (Spain). This region is a clear example of the socioeconomic changes that have been occurring over recent decades in the European Mediterranean as well as their impact on LULC and fire occurrence. Using the LULC changes observed between 1990 and 2006 as a reference, future scenarios were run up to 2025 with the conversion of land use and its effects model. Simultaneously, the relationship between LULC arrangement (interfaces) and historical fire occurrence was calculated using logistic regression analysis and used to quantify changes in future fire occurrence due to projected changes in LULC interfaces. The results revealed that it is possible to explain the probability of fire occurrence using only variables obtained from LULC maps, although the explanatory power of the model is low. In this context, border areas between some LULC types are of particular interest (i.e., urban/forest, grassland/forest and agricultural/forest interfaces). Results indicated that expected LULC changes in Euro-Mediterranean regions, particularly given the foreseeable increase in the wildland-urban interface, will substantially increase fire occurrence (up to 155 %). This underlines the importance of future LULC scenarios when planning fire prevention measures. [ABSTRACT FROM AUTHOR]

Alpine regions represent an interesting biome for studying local adaptation in forest trees. Strong genetic differentiation is expected along elevational gradients in spite of extensive gene flow. We sampled 18 and 20 natural populations of Pinus cembra and Pinus mugo, in two subregions and four elevational gradients. To investigate the effects of elevation on genetic diversity and adaptation, 768 and 1152 single nucleotide polymorphisms (SNPs) were genotyped in P. cembra and P. mugo. We found low but significant genetic differentiation among populations in both species. To discover outliers, we applied Bayesian simulation and hierarchical island model analyses. A larger number of outliers were found using the first method. Some SNPs were detected with both analyses: one SNP in P. cembra and three in P. mugo when using two subregions and four SNPs in P. cembra and one in P. mugo when using four elevational gradients. The association between environmental and genetic variation was tested with Bayesian simulation (Bayenv) and a latent factor mixed model (LFMM). The first method, using all populations, detected 6 and 20 SNPs associated to temperature in P. cembra and in P. mugo, respectively, 3 SNPs associated to precipitation in P. cembra, and 14 SNPs to elevation in P. mugo. The LFMM found a higher number of SNPs associated to temperature in P. mugo than in P. cembra (37 vs. 27), with a stronger association with maximum temperature (April–June). In P. cembra, the majority of associations (51 SNPs) were found with precipitation (January–March). Five SNPs in common between species were found on genes potentially involved in plant response to abiotic stress. Using these results, we confirmed that temperature was an important driver of adaptive potential for each species so that continued changes to global temperatures will likely involve continued adaptation as ranges shift upwards. [ABSTRACT FROM AUTHOR]

This paper evaluates soil loss due to water erosion in an area of 32,362 ha with a predominant land use of vineyards (Alt Penedès-Anoia region, Catalonia, Spain). The Soil and Water Assessment Tool (SWAT) was used incorporating daily climatic data for the period 2000-2010 and also detailed soil and land use maps. Particular attention was given to the universal soil loss equation cover and management factor (C factor) of vineyards, with a minimum value of 0·15 being determined for this crop. The model was calibrated using daily flow data for the year 2010, which yielded satisfactory results. Even so, significant differences were obtained on days with high-intensity rainfall events, when the model overestimated runoff and peak discharge. In these vineyards, the simulated average soil losses per sub-basin ranged between 0·13 and 9·73 Mg ha−1 y−1, with maximum values of between 26·32 and 42·60 Mg ha−1 y−1 registered in fine-loamy soils developed on unconsolidated Tertiary marls. Other findings were related to problems associated with SWAT calibration under Mediterranean conditions characterised by major climate variability and high-intensity rainfall events. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Stakeholder participation in environmental management has become widespread globally while the normative benefits of multi-stakeholder processes in governing natural resources are promoted by academics and policy makers. As projections indicate more frequent and intense flood events with future climate change, this article examines one stakeholder participation process within UK flood risk management to evaluate whether it contributes to enhancing effective engagement, through social learning. Evidence is derived from multiple interviews conducted within the England's Regional Flood and Coastal Committees (RFCCs), which were specifically introduced to better integrate local level interests in regional flood defence decision-making. In testing a modified ‘individual-community interaction’ learning framework, it is apparent that personal and group learning outcomes were evident to varying degrees, suggesting that stakeholder participation was relatively successful. However, our analysis suggests that flexibility exists within such structures, allowing reflexive reconstitution to further increase social learning. Recommendations for future stakeholder participation are proposed, providing lessons for both UK flood governance and similar flood risk management processes in other countries. [ABSTRACT FROM AUTHOR]

How can debris flow occurrences be modelled at regional scale and take both environmental and climatic conditions into account? And, of the two, which has the most influence on debris flow activity? In this paper, we try to answer these questions with an innovative Bayesian hierarchical probabilistic model that simultaneously accounts for how debris flows respond to environmental and climatic variables. In it, full decomposition of space and time effects in occurrence probabilities is assumed, revealing an environmental and a climatic trend shared by all years/catchments, respectively, clearly distinguished from residual “random” effects. The resulting regional and annual occurrence probabilities evaluated as functions of the covariates make it possible to weight the respective contribution of the different terms and, more generally, to check the model performances at different spatio-temporal scales. After suitable validation, the model can be used to make predictions at undocumented sites and could be used in further studies for predictions under future climate conditions. Also, the Bayesian paradigm easily copes with missing data, thus making it possible to account for events that may have been missed during surveys. As a case study, we extract 124 debris flow event triggered between 1970 and 2005 in 27 catchments located in the French Alps from the French national natural hazard survey and model their variability of occurrence considering environmental and climatic predictors at the same time. We document the environmental characteristics of each debris flow catchment (morphometry, lithology, land cover, and the presence of permafrost). We also compute 15 climate variables including mean temperature and precipitation between May and October and the number of rainy days with daily cumulative rainfall greater than 10/15/20/25/30/40 mm day − 1 . Application of our model shows that the combination of environmental and climatic predictors explained 77% of the overall variability of debris flow occurrences in this data set. Occurrence probabilities depend mainly on climatic variables, which explain 44% of the overall variability through the number of rainy days and maximum daily temperature. This important time component in the variability of overall debris flow occurrence is shown to be responsible for a significant increase in debris flow activity between 1970 and 2005 at regional scale. Environmental variables, which account for 33% of the overall variability, includes mostly the morphometric variables of the debris flow catchments. [ABSTRACT FROM AUTHOR]

The assessment of uncertainties in satellite-derived global surface albedo products is a critical aspect for studying the climate, ecosystem change, hydrology or the Earth's radiant energy budget. However, it is challenged by the spatial scaling errors between satellite and field measurements. This study aims at evaluating the forthcoming MODerate Resolution Imaging Spectroradiometer (MODIS) (Collection V006) Bidirectional Reflectance Distribution Function (BRDF)/albedo product MCD43D over a Mediterranean agricultural area. Here, we present the results from the accuracy assessment of the MODIS blue-sky albedo. The analysis is based on collocated comparisons with higher spatial resolution estimates from Formosat-2 that were first evaluated against local in situ measurements. The inter-sensor comparison is achieved by taking into account the effective point spread function (PSF) for MODIS albedo, modeled as Gaussian functions in the North–South and East–West directions. The equivalent PSF is estimated by correlation analysis between MODIS albedo and Formosat-2 convolved albedo. Results show that it is 1.2 to 2.0 times larger in the East–West direction as compared to the North–South direction. We characterized the equivalent PSF by a full width at half maximum size of 1920 m in East–West, 1200 m in North–South. This provided a very good correlation between the products, showing absolute (relative) Root Mean Square Errors from 0.004 to 0.013 (2% to 7%), and almost no bias. By inspecting 1-km plots homogeneous in land cover type, we found poorer performances over rice and marshes (i.e., relative Root Mean Square Error of about 11% and 7%, and accuracy of 0.011 and − 0.008, respectively), and higher accuracy over dry and irrigated pastures, as well as orchards (i.e., relative uncertainty < 3.8% and accuracy < 0.003). The study demonstrates that neglecting the MODIS PSF when comparing the Formosat-2 albedo against the MODIS one induces an additional uncertainty up to 0.02 (10%) in albedo. The consistency between fine and coarse spatial resolution albedo estimates indicates the ability of the daily MCD43D product to reproduce reasonably well the dynamics of albedo. [ABSTRACT FROM AUTHOR]

• There is a growing need for Decision Support Systems in forestry that focus on the understorey. • This paper presents a first prototype of such an understorey Decision Support System. • We developed General Additive Models to predict understorey responses to global change. • Climate warming will shift understorey composition towards more woody species and forest generalists. • Keeping the canopy close can help mitigating this shift by increasing the proportion of forest specialists. • Understorey responses to global change were found to be context-dependent. The temperate forest understorey is rich in terms of vascular plant diversity and plays a vital functional role. Given the sensitivity of this forest layer to forest management and global environmental change and the limited knowledge on its long-term dynamics, there is a need for decision support systems that can guide temperate forest managers to optimize their management in terms of understorey outcomes. In this study, using understorey resurvey data collected from across temperate Europe, we developed Generalized Additive Models (GAM) to predict four understorey properties based on forest management and environmental change data, and implemented this model in a web-based tool as a prototype understorey Decision Support System (DSS). Using seventy-two combined climate change, nitrogen(N) deposition and forest management scenarios, applied to two case study regions in Europe, we predicted temperate forest understorey biodiversity dynamics between 2020 and 2050. A sensitivity analysis subsequently allowed to quantify the relative importance of canopy opening, N deposition and climate change on understorey dynamics. Our study showed that, regardless of regions, understorey richness and the proportion of forest specialists generally decreased among most scenarios, but the proportion of woody species and the understorey vegetation total cover increased. Climate warming, N deposition, and increases in canopy openness all influenced understorey dynamics. Climate warming will shift composition towards a selection of forest generalists and woody species, but a less open canopy could mitigate this shift by increasing the proportion of forest specialists. The case studies also showed that these responses can be context-dependent, especially in terms of responses to N deposition. [ABSTRACT FROM AUTHOR]

Vegetation plays an important role in regulating the terrestrial carbon balance and the climate system, and also overwhelmingly dominates the provisioning of ecosystem services. In this study, a non-stationary 1982–2012 AVHRR NDVI 3g time series, the newest dataset, were used to evaluate spatio-temporal patterns of seasonal vegetation changes in Xinjiang province of China at regional, biome and pixel scales over progressively longer periods from 18 to 31 years, starting in 1982, and their linkages to climatic factors and human activities were analyzed. At regional scale, the increases were statistically significant for autumn NDVI during fourteen periods, for growing season and summer NDVI during the most periods, and for spring only during the first four periods. The rates of NDVI increase in growing season and all seasons significantly decreased over fourteen periods. At pixel scale, areas with significant browning rapidly increased over fourteen periods for growing season and all seasons, and these areas were mainly concentrated in northern desert of Xinjiang. Vegetation growth in Xinjiang was regulated by both moisture and thermal conditions: the response of NDVI in spring and autumn was more sensitive to thermal factors, such as temperature and potential evapotranspiration, and correlations between NDVI and precipitation and between NDVI and humidity index were stronger in summer and growing season. Extensive use of fertilizers and expanded farmland irrigated area increased vegetation growth for cropland. However, the rapid increase in the proportion of cotton cultivation and use of drip irrigation may reduce spring NDVI in the part of farmlands. Trend analysis during the multiple nested time series may contribute to a better and deep understanding of NDVI dynamic and foreseeing changes in the future. Accordingly, NDVI in Xinjiang will continuously increase at regional scale and the areas showing significant browning will also furthermore grow. [ABSTRACT FROM AUTHOR]

A letter to the editor is presented related to the challenges associated with the implementation of forest adaptation strategies in the wake of climate change.

Highlights: [•] Biome boundary shifts in India. [•] Assessment of impact of climate change. [•] First records of biome shifts from India. [•] Impacts and vulnerabilities of projected climate change on forest ecosystems (life zones). [•] A nation-wide study at regional scale. [ABSTRACT FROM AUTHOR]

In order to assess the performance of two versions of the IAP/LASG Flexible Global Ocean-Atmosphere-Land System (FGOALS) model, simulated changes in surface air temperature (SAT), from natural and anthropogenic forcings, were compared to observations for the period 1850-2005 at global, hemispheric, continental and regional scales. The global and hemispheric averages of SAT and their land and ocean components during 1850-2005 were well reproduced by FGOALS-g2, as evidenced by significant correlation coefficients and small RMSEs. The significant positive correlations were firstly determined by the warming trends, and secondly by interdecadal fluctuations. The abilities of the models to reproduce interdecadal SAT variations were demonstrated by both wavelet analysis and significant positive correlations for detrended data. The observed land-sea thermal contrast change was poorly simulated. The major weakness of FGOALS-s2 was an exaggerated warming response to anthropogenic forcing, with the simulation showing results that were far removed from observations prior to the 1950s. The observations featured warming trends (1906-2005) of 0.71, 0.68 and 0.79°C (100 yr) for global, Northern and Southern Hemispheric averages, which were overestimated by FGOALS-s2 [1.42, 1.52 and 1.13°C (100 yr)] but underestimated by FGOALS-g2 [0.69, 0.68 and 0.73°C (100 yr)]. The polar amplification of the warming trend was exaggerated in FGOALSs2 but weakly reproduced in FGOALS-g2. The stronger response of FGOALS-s2 to anthropogenic forcing was caused by strong sea-ice albedo feedback and water vapor feedback. Examination of model results in 15 selected subcontinental-scale regions showed reasonable performance for FGOALS-g2 over most regions. However, the observed warming trends were overestimated by FGOALS-s2 in most regions. Over East Asia, the meridional gradient of the warming trend simulated by FGOALS-s2 (FGOALS-g2) was stronger (weaker) than observed. [ABSTRACT FROM AUTHOR]

Abstract: We present a regional inventory of rock glaciers (n =1514) and protalus ramparts (228) for the Lombardy region, central Italian Alps. To identify and classify the landforms we inspect three sequential air-orthophoto mosaics and a 2m-DSM, and conduct confirmatory field work. The inventory forms an empirical basis to analyze: (i) the relative contribution of hillslope (i.e., talus slopes) and glacial (i.e., moraines) sediment stores to rock glacier sediment supply; (ii) linkages between the landforms inventoried and local topographic attributes; (iii) the spatial variability of periglacial activity in relation to a parsimonious set of environmental variables (i.e., elevation, precipitation, and lithology); and (iv) the effects of the Pleistocene–Holocene climatic transition on the distribution of intact and relict landforms. This analysis reveals that the elevation of rock glacier termini can vary over 200m as a function of slope aspect. In turn, the distribution of rock glaciers among aspect categories is controlled by the structure of the valley network that promotes NW and SE exposures. Talus rock glaciers prevail numerically over the glacier-related typology, even though the latter population appears to have increased during the Holocene. Relict and intact rock glaciers have distinct spatial patterns in that the former display, on average, a 400-m elevation drop and a less clustered distribution towards northern aspects, suggesting that they have developed in more “permafrost-prone” climatic conditions. Analyzing the study region through a 27.5km-grid has been instrumental for showing that the rock glacier specific area and terminus elevation are: (i) positively correlated with terrain elevation; and (ii) negatively correlated with mean annual precipitation. As a consequence, in relation to Holocene generalized atmospheric temperature rise, intact rock glaciers have progressively disappeared from the wetter and milder portions of the central Italian Alps. Analysis of rock glacier occurrence across litho-tectonic sectors does not provide conclusive dependences and requires further analysis. This inventory, which represents a necessary preliminary step for modelling the spatial distribution of discontinuous permafrost at the regional scale, fills a critical geographic gap in the context of ongoing permafrost research in the European Alps (e.g., PermaNET). [Copyright &y& Elsevier]

Summary: The classification of small catchments with respect to low flow risk is needed by water and environmental managers to plan adaptation measures for freshwater streams. In this study a new approach is presented to assess the risk of seasonal low flow in the Pleistocene landscape of the Federal State of Brandenburg in Germany. Seasonal low flow and drought in small streams is very common in this region and is predicted to increase due to climate change within the next decades. Data of 15years (1991–2006) of daily discharge at 37 small catchments (<500km2) and rainfall data from the same region were used. Principal component analyses were applied to the two data sets separately. The first five principal components of the discharge data, principal components of a precipitation data set covering the same catchments and catchment characteristics were used to explain the patterns found. The first five discharge components explained 72.9% of the total variance in the data set. The first component reflected the general regional discharge pattern. Components 2 and 3 of the discharge data could be related to spatial patterns of precipitation. Components 4 and 5 of the discharge data reflected geohydrologic processes within the catchments. In order to identify catchments with high risk with respect to low flows, component three and five were important as they both identified catchments with faster decrease of flows during summer. These components were used to estimate low flow risk. Catchments located in the northeast of Brandenburg, especially those in the Barnim highlands north and east of Berlin, were identified to be prone to seasonal low flow. There water management measures to adapt to climate change are needed the most. [Copyright &y& Elsevier]

As important marine mesopredators and sensitive indicators of Antarctic ecosystem change, penguins have been a major focus of long-term biological research in the Antarctic. However, the vast majority of such studies have been constrained by logistics and relate mostly to the temporal dynamics of individual breeding populations from which regional trends have been inferred, often without regard for the complex spatial heterogeneity of population processes and the underlying environmental conditions. Integrating diverse census data from 70 breeding sites across 31 years in a robust, hierarchical analysis, we find that trends from intensely studied populations may poorly reflect regional dynamics and confuse interpretation of environmental drivers. Results from integrated analyses confirm that Pygoscelis adeliae (Adélie Penguins) are decreasing at almost all locations on the Antarctic Peninsula. Results also resolve previously contradictory studies and unambiguously establish that P. antarctica (Chinstrap Penguins), thought to benefit from decreasing sea ice, are instead declining regionally. In contrast, another open-water species, P. papua (Gentoo Penguin), is increasing in abundance and expanding southward. These disparate population trends accord with recent mechanistic hypotheses of biological change in the Southern Ocean and highlight limitations of the influential but oversimplified "sea ice" hypothesis. Aggregating population data at the regional scale also allows us to quantify rates of regional population change in a way not previously possible. [ABSTRACT FROM AUTHOR]

Abstract: Matching supply and demand for knowledge in the fields of global change and sustainability is a daunting task. Science and public policy differ in their timeframes, epistemologies, objectives, process-cycles and criteria for judging the quality of knowledge, while global change and sustainability issues involve value pluralities and large uncertainties. In literature and in practice, it is argued that joint knowledge production in projects through collaboration between (and within) science and policy serves as a means to bridge the gap between the two domains. However, an assessment framework for analysing the merits and limitations of such projects, identifying good practices and enabling adaptive management as well as social learning had not yet been developed. This paper aims to develop such a framework. We portray joint knowledge production projects as policy arrangements in which the degree of success depends on the actors involved, contents of dominant discourses, presence of rules and the availability of resources. Literature was discussed to specify these four dimensions into seven success conditions for joint knowledge production. Scholars, boundary organizations and actors in projects can use the framework for retrospective analyses of projects, providing joint knowledge production with the empirical basis it still requires. The framework can also be used for promoting reflection in action as well as for formative assessments enabling social learning. [Copyright &y& Elsevier]

The article offers the trends in and tree phylogenetic diversity in 7,000 forested plots in eastern United States. It mentions that testing of three hypothesis including phylogenetic diversity changes in forest communities, the difference of phylogenetic diversity from species richness and the consistency of patterns with climate change effects. It finds that species richnesss and phylogenetic diversity are decoupled at medium and small scales.

Copyright of Hydrogeology Journal is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Ecoscience (Ecoscience) is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

• Predictions of physiological process depends on climate model, species and region. • Predictions were improved after correction for the three models considered. • Processes simulated exhibited large variability at the plot scale. • This variability faded out at larger scales, owing to an aggregation effect. • Process predictions were more variable during the driest years. Climate change affects various aspects of ecosystem functioning, especially photosynthesis, respiration and carbon storage. We need accurate modelling approaches (impact models) to simulate forest functioning and vitality in a warmer world so that forest models can estimate multiple changes in ecosystem service provisions (e.g., productivity and carbon storage) and test management strategies to promote forest resilience. Here, we aimed to quantify the bias in these models, addressing three questions: (1) Do the predictions of impact models vary when forcing them with different climate models, and how do the predictions differ under climate model vs. observational climate forcings? (2) Does the climate impact simulation variability caused by climate forcings fade out at large spatial scales? (3) How does using simulated climate data affect process-based model predictions in stressful drought events? To answer these questions, we present historical results for 1960-2010 from the CASTANEA ecophysiological forest model and use the data from three climate models. Our analysis focuses on monospecific stands of European beech (Fagus sylvatica), temperate deciduous oaks (Quercus robur and Q. petraea), Scots pine (Pinus sylvestris) and spruce (Picea abies) in French forests. We show that prediction of photosynthesis, respiration and wood growth highly depends on the climate model used and species and region considered. Predictions were improved after a monthly mean bias or monthly quantile mapping correction for the three models considered. The processes simulated by the impact model exhibited large variability under different climate forcings at the plot scale (i.e., a few hectares). This variability faded out at larger scales (i.e., an ecological region, 100 km²), owing to an aggregation effect. Moreover, process predictions obtained under different climate forcings were more variable during the driest years. These results highlight the necessity of quantifying the bias correction effect on process predictions before predicting flux dynamics with a process-based model. [ABSTRACT FROM AUTHOR]

Recent concerns about potential climate-change effects on coastal systems require the application of vulnerability assessment tools in order to define suitable adaptation strategies and improve coastal zone management effectiveness. In fact, while various research efforts were devoted to evaluate coastal vulnerability to climate change on a national to global level, fewer applications were carried out so far to develop more comprehensive and site-specific vulnerability assessments suitable to plan possible adaptation measures at the regional scale. In this respect, specific indicators are needed to address climate-change-related issues for coastal zones and to identify vulnerable areas at the regional level. Two sets of coastal vulnerability indicators were selected, one for regional and one for global studies, respectively, concerning the same features of coastal systems, including topography and slope, geomorphological characteristics, presence and distribution of wetlands and vegetation cover, density of coastal population and number of coastal inhabitants. The proposed set of indicators for the regional scale was chosen taking into account the availability of environmental and territorial data for the whole coastal area of the Veneto region and was based on site-specific datasets characterized by a spatial resolution appropriate for a regional analysis. Moreover, a GIS-based segmentation procedure was applied to divide the coastline into linear segments, homogeneous in terms of vulnerability to climate change and sea-level rise at the regional scale. This approach allowed to divide the Veneto shoreline into 140 segments with an average length of about 1 km, while the global scale approach identified four coastal segments with an average length of about 66 km. The performed comparison indicated how the more detailed approach adopted at the regional scale is essential to understand and manage the complexities of the specific study area. In fact, the 25-m DEM employed at the regional scale provided a more accurate differentiation of the coastal area's elevation and thus of coastal susceptibility to the inundation risks, compared to the 1-km DEM used at the global level. Moreover, at the regional level the use of a 1:20,000 geomorphological map allowed to differentiate the unique landform class detected at the global level (e.g., fluvial plain) in a variety of more detailed coastal typologies (e.g., open coast eroding sandy shores backed by bedrock) characterized by a different sensitivity to climate change and sea-level rise. Accordingly, the information provided by regional indicators can support decision-makers in improving the management of coastal resources by considering the potential impacts of climate change and in the definition of appropriate actions to reduce inundation risks, to avoid the potential loss of valuable wetlands and vegetation and to plan the nourishment of sandy beaches subject to erosion processes. [ABSTRACT FROM AUTHOR]

Aim We analysed lake-sediment pollen records from eight sites in southern New England to address: (1) regional variation in ecological responses to post-glacial climatic changes, (2) landscape-scale vegetational heterogeneity at different times in the past, and (3) environmental and ecological controls on spatial patterns of vegetation. Location The eight study sites are located in southern New England in the states of Massachusetts and Connecticut. The sites span a climatic and vegetational gradient from the lowland areas of eastern Massachusetts and Connecticut to the uplands of north-central and western Massachusetts. Tsuga canadensis and Fagus grandifolia are abundant in the upland area, while Quercus, Carya and Pinus species have higher abundances in the lowlands. Methods We collected sediment cores from three lakes in eastern and north-central Massachusetts (Berry East, Blood and Little Royalston Ponds). Pollen records from those sites were compared with previously published pollen data from five other sites. Multivariate data analysis (non-metric multi-dimensional scaling) was used to compare the pollen spectra of these sites through time. Results Our analyses revealed a sequence of vegetational responses to climate changes occurring across southern New England during the past 14,000 calibrated radiocarbon years before present (cal yrbp). Pollen assemblages at all sites were dominated by Picea and Pinus banksiana between 14,000 and 11,500 cal yrbp; by Pinus strobus from 11,500 to 10,500 cal yrbp; and by P. strobus and Tsuga between 10,500 and 9500 cal yrbp. At 9500–8000 cal yrbp, however, vegetation composition began to differentiate between lowland and upland sites. Lowland sites had higher percentages of Quercus pollen, whereas Tsuga abundance was higher at the upland sites. This spatial heterogeneity strengthened between 8000 and 5500 cal yrbp, when Fagus became abundant in the uplands and Quercus pollen percentages increased further in the lowland records. The differentiation of upland and lowland vegetation zones remained strong during the mid-Holocene Tsuga decline (5500–3500 cal yrbp), but the pattern weakened during the late-Holocene (3500–300 cal yrbp) and European-settlement intervals. Within-group similarity declined in response to the uneven late-Holocene expansion of Castanea, while between-group similarity increased due to homogenization of the regional vegetation by forest clearance and ongoing disturbances. Main conclusions The regional gradient of vegetation composition across southern New England was first established between 9500 and 8000 cal yrbp. The spatial heterogeneity of the vegetation may have arisen at that time in response to the development or strengthening of the regional climatic gradient. Alternatively, the differentiation of upland and lowland vegetation types may have occurred as the climate ameliorated and an increasing number of species arrived in the region, arranging themselves in progressively more complex vegetation patterns across relatively stationary environmental gradients. The emergence of a regional vegetational gradient in southern New England may be a manifestation of the increasing number of species and more finely divided resource gradient. [ABSTRACT FROM AUTHOR]

The simulation of hydrological consequences of climate change has received increasing attention from the hydrology and land-surface modelling communities. There have been many studies of climate-change effects on hydrology and water resources which usually consist of three steps: (1) use of general circulation models (GCMs) to provide future global climate scenarios under the effect of increasing greenhouse gases, (2) use of downscaling techniques (both nested regional climate models, RCMs, and statistical methods) for “downscaling” the GCM output to the scales compatible with hydrological models, and (3) use of hydrologic models to simulate the effects of climate change on hydrological regimes at various scales. Great progress has been achieved in all three steps during the past few years, however, large uncertainties still exist in every stage of such study. This paper first reviews the present achievements in this field and then discusses the challenges for future studies of the hydrological impacts of climate change. [ABSTRACT FROM AUTHOR]