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Despite the importance of marine megafauna on ecosystem functioning, their contribution to the oceanic carbon cycle is still poorly known. Here, we explored the role of baleen whales in the biological carbon pump across the southern hemisphere based on the historical and forecasted abundance of five baleen whale species. We modelled whale-mediated carbon sequestration through the sinking of their carcasses after natural death. We provide the first temporal dynamics of this carbon pump from 1890 to 2100, considering both the effects of exploitation and climate change on whale populations. We reveal that at their pre-exploitation abundance, the five species of southern whales could sequester 4.0 × 10 5 tonnes of carbon per year (tC yr −1 ). This estimate dropped to 0.6 × 10 5 tC yr −1 by 1972 following commercial whaling. However, with the projected restoration of whale populations under a RCP8.5 climate scenario, the sequestration would reach 1.7 × 10 5 tC yr −1 by 2100, while without climate change, recovered whale populations could sequester nearly twice as much (3.2 × 10 5 tC yr −1 ) by 2100. This highlights the persistence of whaling damages on whale populations and associated services as well as the predicted harmful impacts of climate change on whale ecosystem services.

Little Ruaha catchment has been recognized for its potential to support multi-projects including irrigated schemes, urban water supply and providing significant inflow to Mtera reservoir for hydropower generation and ultimately Julius Nyerere Hydropower Plant (JNHPP). Despite the potential, the catchment has experienced declining flows in the recent years. This study assessed the likely changes in streamflow due to future climate change in the Little Ruaha catchment for the period 2025-2060. General Circulation Model (GCM) datasets from ACCESS1.0, CNRM-CM5 and BCC-CSM1 models and RCP4.5 and RCP8.5 greenhouse gas concentration scenarios were selected as the representative scenarios. Impact of climate change on stream flows was assessed using the calibrated NAM hydrological model. The impact assessment results show that under the climate change scenario (2025–2060), the monthly maximum and minimum temperatures will increase in the range of 0.8 °C to 2 °C for both RCP4.5 and RCP8.5 scenarios. For the case of rainfall, average annual rainfall is expected to increase by about 10% compared to the baseline. However, the inter-annual variability of rainfall for the period between 2025 and 2060 shows the decreasing trend for RCP 8.5. The simulation results show that streamflow will decrease by about 30% and 6% for RCP4.5 and RCP8.5, respectively. Keywords: Hydrological modelling; climate change scenarios; hydrological impacts; Little Ruaha.

Anthropocene is characterised by significant, and in many ways outcompeting natural processes, the impact of human activities on natural ecosystems. The excessive emission of greenhouse gases caused by global-scale use of fossil fuels, anthropogenic land-use change, and drastic decrease in pristine areas, have all contributed to global climate change. Although the Earth’s climate has historically fluctuated, the current situation is novel as climatic change is occurring at an unprecedented rate and has mainly been driven by human behaviour. The rapid pace of environmental change forces living organisms to respond fast in order to survive and reproduce. The magnitude of such responses might be especially prominent in migratory species due to their diverse and dispersed habitat requirements. Migratory species connect habitats across the globe, coupling biodiversity and ecosystem services. By travelling long distances, migratory species move biomass between habitats; transporting energy, nutrients, and other organisms. Also, migratory species alter the dynamics of resident communities that they connect on their journeys by foraging and becoming prey in numerous habitats during their annual cycle. Therefore environmental alteration leading to disruption of long-distance migratory behaviour will have far-reaching consequences which may drastically affect synchrony and unity in natural ecosystems. The aim of this dissertation was to reveal climate-driven changes to populations of migratory bats, from a historical overview through to future perspectives. To understand the magnitude of ongoing changes in populations of bats, we require adequate reference points from the past. Here, I had a unique opportunity to study recent changes in migratory behaviour and distribution of common European migratory bat species, Nyctalus noctula, based on long term dataset. In the presented work, I combined different approaches such as stable hydrogen isotopes to reveal migratory destinations; analysis of demographic data to evaluate sex and age population dynamics; respirometry measurements to establish physiological parameters and environmental modelling to predict suitable for hibernation areas under three climate change scenarios. This variety of applied technics allowed for complex investigation of animal responses to climate change. The obtained results are reported in two peer-reviewed publications and one manuscript, which is in preparation for submission. The research outcome aims to bridge the most demanding gaps in knowledge related to climate-driven changes in populations of migratory animals. The first chapter contributed to the improvement of the method for studying migratory animals by using stable isotopes. The second chapter was dedicated to climate change responses, particularly to an investigation of the mechanism of climate-driven range changes in populations of migratory bats. The third chapter described and evaluated the novel mechanistic approach in environmental modelling of species distribution under the impact of climate change. In chapter one, I have contributed to the validation of the assumptions for stable hydrogen analysis. Stable isotopes are broadly applied for the identification of the geographical origin of bats via transfer function, which is consists of the isotope signature of animals of know origin. However, there was no age validation performed before for stable isotope signatures in bat tissues. The stable isotopes approach was planned as the main method for the assignment of migratory bats in a long-term dataset. Therefore, in chapter one, I presented a validation approach for age differences in stable isotope signatures to better understand variation around the transfer function and increase the precision in the prediction of the geographic origin. In chapter two using a transfer function, which included individuals of both age classes, I investigated migratory behaviour and demographic structure of N. noctula under the distribution shift. The common noctule bats increased their winter range by more than 500 km during several decades. Apart from the observed biogeographic pattern little was known regarding the mechanism relevant for the range change. I hypothesized that the generation shift is the mechanism relevant to the range change in migratory bats. To test the hypothesis, I looked at the long-term data set regarding the demographic structure of winter colonies in the recently occupied winter range and I used stable hydrogen analysis to establish the geographic origin of bats. My finding supported the hypothesis regarding the generational shift in migratory behaviour of bats which resulted in winter range change. Obtained results, for the first time, demonstrated the relevance of generation shift in the regulation of species distribution in mammals. Chapter three was dedicated to the elaboration of a mechanistic physiologically-based model for the evaluation and forecasting of suitable hibernation areas in migratory bats. Climate change is expected to affect the cost of hibernation in a given area and might ultimately modify species winter distribution. With a novel approach, I aimed to combine fine-scale thermoregulation data of noctule bats with environmental variables from their past and present winter ranges to model species occurrence dynamics. Firstly, this joint approach improved our understanding of species physiological requirements to external conditions. Secondly, it enabled us to refine the modelling of future species distribution under different climate change scenarios. The presented work had revealed climate-driven changes in migratory behaviour and distribution of common noctule bats. By incorporation various technics and methodological approaches, I could tackle the magnitude of responses to climate change on different levels of ecological organisation: from an organismal physiological response to environmental conditions; to change in migratory behaviour on a population level and change in geographic distribution on a species level. The main findings elaborate on physiological and behavioural mechanisms underlying climate-driven range change and provide evidence for migratory bats being able to respond fast to the rapid pace of climate change. However, the consistency of responses is conditioned by species-specific traits such as physiological flexibility, high mobility and dispersion rate, short generation life, and diversity of migratory strategies; and climate velocity, as a metric of speed, and direction of climate displacement.

Chelmos-Vouraikos National Park is a floristic diversity and endemism hotspot in Greece and one of the main areas where Greek endemic taxa, preliminary assessed as critically endangered and threatened under the IUCN Criteria A and B, are mainly concentrated. The climate and land-cover change impacts on rare and endemic species distributions is more prominent in regional biodiversity hotspots. The main aims of the current study were: (a) to investigate how climate and land-cover change may alter the distribution of four single mountain endemics and three very rare Peloponnesian endemic taxa of the National Park via a species distribution modelling approach, and (b) to estimate the current and future extinction risk of the aforementioned taxa based on the IUCN Criteria A and B, in order to investigate the need for designing an effective plant micro-reserve network and to support decision making on spatial planning efforts and conservation research for a sustainable, integrated management. Most of the taxa analyzed are expected to continue to be considered as critically endangered based on both Criteria A and B under all land-cover/land-use scenarios, GCM/RCP and time-period combinations, while two, namely Alchemilla aroanica and Silene conglomeratica, are projected to become extinct in most future climate change scenarios. When land-cover/land-use data were included in the analyses, these negative effects were less pronounced. However, Silene conglomeratica, the rarest mountain endemic found in the study area, is still expected to face substantial range decline. Our results highlight the urgent need for the establishment of micro-reserves for these taxa.

Summarization: Crete is a Mediterranean, karst-dominated island, characterized by long drought periods. The Karst-SWAT model, combined with 11 climate change scenarios, was run to assess climate change impacts on the island under two set-ups, both using the auto-irrigation function of the model: (1) with water drawn from the shallow or deep aquifer, and (2) with irrigated water derived from an unlimited outside source. The first set-up provided insight into the fluctuation of future irrigation needs, and when compared to the second set-up, enabled quantification of the future water deficit. The Water Exploitation Index was used to describe the spatial variability of future water stress on Crete. A decrease in both surface and karstic spring flows is foreseen, especially after 2060 (24.2 and 16.5%, respectively). Simulated irrigation water demand and water deficit show continuous increase throughout the projection period (2020–2098). Παρουσιάστηκε στο: Hydrological Sciences Journal

Resumen Introducción. El cambio climático puede alterar las reservas de carbono (C) almacenado en los sistemas agroforestales con café. Objetivo. Simular las reservas de C en la biomasa aérea (ABOC) y suelo (COS) a una proyección de cincuenta años bajo la línea base y con escenarios de cambio climático en sistemas agroforestales con café, mediante el modelo CO2Fix. Materiales y métodos. En el año 2020, se estableció la línea base de C total (ABOC + COS) en veinticinco parcelas de café orgánico de la Sociedad Catuaí Amarillo S. de S.S, Chocamán, Veracruz, México. Las parcelas se clasificaron en tres diseños agroforestales: D1 (árboles de sombra-café en laderas), D2 (árboles de sombra-café-plátano en laderas) y D3 (árboles de sombra-café-plátano en el valle). Se utilizó el modelo CO2Fix para simular las reservas de C total a una proyección de cincuenta años bajo la línea base y con escenarios de cambio climático en los tres diseños agroforestales con café. Resultados. El C total en la línea base fue de 124,59, 107,43 y 102,320 t ha-1, para D1, D2 y D3, respectivamente. Se presentaron disminuciones entre 0,77 y 8,75 t ha-1 en las reservas de C total bajo escenarios de cambio climático en los tres diseños agroforestales evaluados. No hubo diferencias estadísticamente significativas entre los diseños agroforestales en la línea base y bajo escenarios de cambio climático. Aunque se constataron variaciones, las reservas de C total se mantuvieron a lo largo del tiempo. La cohorte de árboles fue la principal fuente de almacenaje del C total. Conclusión. Fue posible simular, en una proyección de cincuenta años, las reservas de carbono en la biomasa aérea y suelo en la línea base, bajo los diferentes escenarios de cambio climático, mediante el uso del modelo CO2Fix, en sistemas agroforestales con café de la Sociedad Catuaí Amarillo S. de S.S. Abstract Introduction. Climate change can alter carbon (C) stocks stored in coffee agroforestry systems. Objective. To simulate C stocks in the aboveground biomass (ABOS) and soil (COS) at a fifty-years projection under the baseline and climate change scenarios in agroforestry systems with coffee, using the CO2Fix model. Materials and methods. In 2020, the baseline total C (ABOC + COS) was established in twenty-five organic coffee plots of the Catuai Amarillo S. de SS Society, Chcaman, Veracruz, Mexico. The plots were classified into three agroforestry designs: D1 (shade trees -coffee on slopes), D2 (shade trees -coffee-banana on slopes), and D3 (shade trees -coffee-banana in the valley). The CO2Fix model was used to simulate the total C stocks at a fifty-years projection under the baseline and climate change scenarios in the three agroforestry designs with coffee. Results. The total C in the baseline was 124.59, 107.43, and 102.320 t ha-1 for D1, D2, and D3, respectively. There were decreases between 0,77 and 8,75 t ha-1 in the low total C stocks under climate change scenarios in the three agroforestry designs evaluated. There were no statistically significant differences between agroforestry designs in the baseline and under climate change scenarios. Although variations were found, total C stocks were maintained over time. The tree cohort was the main storage source of total C storage. Conclusion. It was possible to simulate, in a fifty-year projection, the carbon stocks in aboveground biomass and soil in the baseline, under different climate change scenarios, using the CO2Fix model, in agroforestry systems with coffee from the Catuai Amarillo S. de S.S. Society.

In order to prepare for floods and droughts that occur as a result of climate change, various studies in water-related fields are being carried out in various countries around the world. Among them, special attention is being paid to the low-impact development (LID) technique. This study measured the annual maximum daily rainfall data from 2019 to 2100 by climate change scenario, which is the annual maximum daily rainfall series observed for rainfall stations, and tested the hydrological data using statistical analysis. After determining whether the data could be analyzed, the probability distribution was selected, and the parameters of the selected probability distribution were calculated using the L-moment method for each rainfall station. The probabilities of rainfall data were derived using GEV distribution, and the United States Environmental Protection Agency Storm Water Management Model (SWMM), a runoff simulation program, was used to compare and analyze the runoff reduction rate before and after the installation of a permeable pavement as an LID facility. The results of the analysis showed that representative concentration pathway (RCP) 4.5 and RCP 8.5 had the effect of reducing the runoff for more than 100 years at a 30% reduction rate compared with before installation.

The inundation of urban areas has frequently occurred as a result of the localized heavy precipitation and flash floods in both South Korea and globally. Metropolitan areas with higher property value and population density than rural areas need practical strategies to reduce flood damage. Therefore, this study aims to perform an inundation analysis of coastal urban areas under a climate change scenario. Changwon city is one of the typical coastal metropolitan regions in South Korea. Severe flooding has occurred in this area caused by a combination of precipitation and sea-level rise enhanced by the typhoon, Sanba, in September 2012. At that time, daily precipitation was 65.5 mm, which is lower than the capable amount of rainfall of the drainage system. However, the river stage combined with the tidal wave caused by a typhoon and heavy precipitation exceeded the flood warning level. This study performed the flood inundation analysis for a part of Changwon city using the SWMM model, a two-dimensional urban flood analysis model. Furthermore, we considered the climate change scenarios to predict the potential flood damage that may occur in the future. As a result, as the future target period increases, both the flooding area and the inundation depth increase compared to the results of the inundation simulation according to the current precipitation and sea-level conditions. The inundation area increased by 2.6–16.2% compared to the current state, and the flooded depths would be higher than 1 m or more. We suggest a structural method to reduce inundation damages to consider extreme precipitation and tidal wave effects.

Vanillaplanifolia is the most widely cultivated species for obtaining natural vanilla. In Mexico, vanilla production has decreased due to negative effects of climate change. We evaluate the current, potential, and future of vanilla cultivation areas in Mexico using bioclimatic models with distinct climate change scenarios (intermediate emissions, temperature rise of 1.1 to 2.6 °C, and high emissions from 2.6 to 4.8 °C, to 2050 and 2070), in order to understand the magnitude of future distribution changes and propose future management strategies. We found that the areas with greatest potential for establishment of V. planifolia are northern Veracruz state bordering the state of Puebla (the Totonacapan region) and northeast Oaxaca state. In the models, the most relevant environmental variable were mean temperature and precipitation of the driest quarter. The average projections for 2050 and 2070 show a progressive reduction in the potential area for the species (−1.6 and −17.3%). However, the Totonacapan region maintains the largest ideal cultivation area, while that of northeast Oaxaca is reduced by 50%. These results show the need to redesign the strategies of agricultural production of vanilla, through sustainable and climate-smart agricultural production strategies as well as a national strategy for conservation of genetic diversity.

Assessing and managing cumulative impacts produced by interactive anthropogenic and natural drivers is a major challenge to achieve the sustainable use of marine spaces in line with the objectives of relevant EU acquis. However, the complexity of the marine environment and the uncertainty linked to future climate and socio-economic scenarios, represent major obstacles for understanding the multiplicity of impacts on the marine ecosystems and to identify appropriate management strategies to be implemented. Going beyond the traditional additive approach for cumulative impact appraisal, the Cumulative Impact Index (CI-Index) proposed in this paper applies advanced Multi-Criteria Decision Analysis techniques to spatially model relationships between interactive climate and anthropogenic pressures, the environmental exposure and vulnerability patterns and the potential cumulative impacts for the marine ecosystems at risk. The assessment was performed based on spatial data characterizing location and vulnerability of 5 relevant marine targets (e.g. seagrasses and coral beds), and the distribution of 17 human activities (e.g. trawling, maritime traffic) during a reference scenario 2000-2015. Moreover, projections for selected physical and biogeochemical parameters (temperature and chlorophyll 'a') for the 2035-2050 timeframe under RCP8.5 scenario, were integrated in the assessment to evaluate index variations due to changing climate conditions. The application of the CI-Index in the Adriatic Sea, showed higher cumulative impacts in the Northern part of the basin and along the Italian continental shelf, where the high concentration of human activities, the seawater temperature conditions and the presence of vulnerable benthic habitats, contribute to increase the overall impact estimate. Moreover, the CI-Index allowed understanding which are the phenomena contributing to synergic pressures creating potential pathways of environmental disturbance for marine ecosystems. Finally, the application in the Adriatic case showed how the output of the CI-Index can provide support to evaluate multi-risk scenarios and to drive sustainable maritime spatial planning and management.

[EN] In the last decades, a global warming trend was observed. Along with the temperature increase, modifications in the humidity and wind regime amplify the regional and local impacts on livestock husbandry. Direct impacts include the occurrence of climatic stress conditions. In Europe, cows are economically highly relevant and are mainly kept in naturally ventilated buildings that are most susceptible to climate change. The high-yielding cows are particularly vulnerable to heat stress. Modifications in housing management are the main measures taken to improve the ability of livestock to cope with these conditions. Measures are typically taken in direct reaction to uncomfortable conditions instead of in anticipation of a long-term risk for climatic stress. Measures that balance welfare, environmental and economic issues are barely investigated in the context of climate change and are thus almost not available for commercial farms. Quantitative analysis of the climate change impacts on animal welfare and linked economic and environmental factors is rare. Therefore, we used a numerical modeling approach to estimate the future heat stress risk in such dairy cattle husbandry systems. The indoor climate was monitored inside three reference barns in central Europe and the Mediterranean regions. An artificial neuronal network (ANN) was trained to relate the outdoor weather conditions provided by official meteorological weather stations to the measured indoor microclimate. Subsequently, this ANN model was driven by an ensemble of regional climate model projections with three different greenhouse gas concentration scenarios. For the evaluation of the heat stress risk, we considered the number and duration of heat stress events. Based on the changes in the heat stress events, various economic and environmental impacts were estimated. The impacts of the projected increase in heat stress risk varied among the barns due to different locations and designs as well as the anticipated climate change (considering different climate models and future greenhouse gas concentrations). There was an overall increasing trend in number and duration of heat stress events. At the end of the century, the number of annual stress events can be expected to increase by up to 2000, while the average duration of the events increases by up to 22 h compared to the end of the last century. This implies strong impacts on economics, environment and animal welfare and an urgent need for mid-term adaptation strategies. We anticipated that up to one-tenth of all hours of a year, correspondingly one-third of all days, will be classified as critical heat stress conditions. Due to heat stress, milk yield may decrease by about 2.8 % relative to the present European milk yield, and farmers may expect financial losses in the summer season of about 5.4 % of their monthly income. In addition, an increasing demand for emission reduction measures must be expected, as an emission increase of about 16 Gg of ammonia and 0.1 Gg of methane per year can be expected under the anticipated heat stress conditions. The cattle respiration rate increases by up to 60 %, and the standing time may be prolonged by 1 h. This causes health issues and increases the probability of medical treatments. The various impacts imply feedback loops in the climate system which are presently underexplored. Hence, future in-depth studies on the different impacts and adaptation options at different stress levels are highly recommended., This research has been supported by the German Federal Ministry of Food and Agriculture (BMEL) through the Federal Office for Agriculture and Food (BLE) (grant nos. 2814ERA02C and 2814ERA03C), the Instituto Nacional de Investigacion Tecnologia Agraria y Alimentaria (INIA) (grant no. 618105), the Basque Government (grant no. BERC 2018-2021), the Spanish Ministry of Economy, Industry and Competitiveness MINECO (grant nos. MDM-2017-0714, FJCI-2016-30263, and RYC-2017-22143), and the Innovation Foundation Denmark (grant no. 4215-00004B).

Precise agricultural predictions of climate change effects on crop water productivity are essential to ensure food security and alleviate water scarcity. In this regard, the present study provides an overview of the future impacts of climate change on the irrigation of agricultural products such as rice, millet, maize, cassava, sorghum, and sugar cane. These crops are some of the most-consumed foodstuffs in countries of the Niger River basin. This study is realized throughout 2020 to 2080, and three Global Climate Models (GCMs) (CSIRO, MIROC5, and ECHAM. MPI-ESM-LR) have been used. The GCMs data have been provided by the IPCC5 database. The irrigation water requirement for each crop was calculated using Smith’s CROPWAT approach. The Penman–Monteith equation recommended by the FAO was used to calculate the potential evapotranspiration. The inter-annual results of the IWR, according to the set of models selected, illustrate that the largest quantities of water used for irrigation are generally observed between January and March, and the lowest quantities are the most often seen between July and September. The majority of models also illustrate a peak in the IWR between March and April. Sorghum and millet are the crops consuming the least amount of water for irrigation, followed by cassava, then rice and corn, and finally sugar cane. The most significant IWRs, which have been predicted, will be between 16.3 mm/day (MIROC5 model, RCP 4.5) and 45.9 mm/day (CSIRO model, RCP 4.5), particularly in Mali, Niger, Algeria, and rarely in Burkina-Faso (CSIRO model, RCP4.5 and 8.5). The lowest IWRs predicted by the models will be from 1.29 mm/day (MIROC5 model, RCP 4.5) to 33.4 mm/day (CSIRO model, RCP 4.5), they will be observed according to the models in Guinea, southern Mali, Ivory Coast, center and southern Nigeria, and Cameroon. However, models predict sugarcane to be the plant with the highest IWR, between 0.25 mm/day (Benin in 2020–2040) and 25.66 mm/day (Chad in 2060–2080). According to the models’ predictions, millet is the crop with the most IWR, between 0.20 mm/day (Benin from 2020 to 2060) and 19.37 mm/day (Chad in 2060–2080). With the results of this study, the countries belonging to the Niger River basin can put in place robust policies in the water resources and agriculture sectors, thus ensuring food security and high-quality production of staple crops, and avoiding water scarcity while facing the negative impacts of climate change.

The extreme cycles of flood and drought in the Poyang Lake catchment (China) place immense pressure on the region's water users and ecosystems. This study examines potential impacts of future climate change in the Poyang Lake catchment using the popular regional climate model, COSMO-CLM, and a distributed hydrological model, WATLAC. Near-future projections (2016–2035) indicate that the mean annual precipitation and temperature are expected to increase over the catchment, with the exception of some northern regions. Relative to the baseline period (1986–2005), the monthly mean precipitation is projected to increase in spring, summer and autumn (March-October), and to decrease in winter (November-February), with the most significant changes in September (62%) and January (−39%). Projected increases in monthly mean temperatures range from 0.3 to 1.4 °C, 0.2 to 0.7 °C, and 0.2 to 1.2 °C for Representative Concentration Pathways (RCP) climate scenarios RCP2.6, 4.5 and 8.5, respectively. Winter temperatures are expected to increase significantly regardless of the climate scenarios. WATLAC simulations indicate that future climate changes will lead to increased high flows in summer and reduced low flows in winter, in terms of both frequency and magnitude, suggesting a high likelihood of an increase in frequency and severity of flooding and droughts in the Poyang Lake catchment.

On the global scale, there is a robust observational evidence that, over the last decades, the frequency and intensity of extreme events significantly changed, even if regional and local studies have highlighted complex and non-uniform spatial patterns. Climate change can cause increased rainfall intensities which leads to an additional impact on drainage systems, due to the alteration of magnitude and frequency of peak flows over their service life. For this reason, the design criteria of urban drainage infrastructures need to be revised and updated, in order to take into account the possible variations of extreme rainfall. In particular, the Depth-Duration-Frequency (DDF) curves, widely used in engineering to assess the return periods of rainfall events, require an adjustment for climate change. The main purpose of this study is to provide a methodology to assess the DDF curves parameters in climate change scenarios, once the evidence of a statistically significant trend in extreme rainfall was verified. Specifically, a Bayesian procedure has been applied for two cases of study located in the Sicily (Southern Italy), in order to incorporate the effects of extreme rainfall variations on the definition of DDF curve for a future climate condition and to evaluate the uncertainty related to such projection. The climate projection has been compared with a baseline scenario representative of current climate conditions. Finally, the implications of the uncertainty related to the DDF parameters estimation on the design of real detention tanks were analyzed, thus providing an evaluation of their hydraulic performance under the assumption of climate change. Results showed that the assessment of DDF parameters from historical extreme rainfall series could not be adequate to provide reliable estimations of future design storm. Therefore, the occurring climate change cannot be neglected in the design procedure based on extreme rainfall estimation.

Climate change is a well-known phenomenon all over the globe. The influence of projected climate change on agricultural production, either positive or negative, can be assessed for various locations. The present study was conducted to investigate the impact of projected climate change on rice&rsquo, s production, water demand and phenology for the state of Bihar, India. Furthermore, this study assessed the irrigation water requirement to increase the rice production by 60%, for the existing current climate scenario and all the four IPCC climate change scenarios (RCP 2.6, RCP 4.5, RCP 6.0 and RCP 8.5) by the 2050s (2050&ndash, 2059). Various management practices were used as adaptation methods to analyze the requirement of irrigation water for a 60% increase in rice production. The climate data obtained from the four General Circulation Models (GCMs) (bcc_csm1.1, csiro_mk3_6_0, ipsl_cm5a_mr and miroc_miroc5) were used in the crop growth model, with the Decision Support System for Agrotechnology Transfer (DSSAT) used to simulate the rice yield, phenological days and water demand under all four climate change scenarios. The results obtained from the CERES-Rice model in the DSSAT, corresponding to all four GCMs, were ensembled together to obtain the overall change in yield, phenology and water demand for the 10 years from 2020 to 2059. We investigated several strategies: increasing the rice yield by 60% with current agronomic practice, increasing the yield by 60% with conservation agricultural practice, and increasing the rice yield by 30% with current agronomic practice as well as with conservation agricultural practices (assuming that the other 30% increase in yield would be achieved by reducing post-harvest losses by 30%). The average increase in precipitation between 2020 and 2059 was observed to be 5.23%, 13.96%, 9.30% and 9.29%, respectively, for RCP 2.6, RCP 4.5, RCP 6.0 and RCP 8.5. The decrease in yield during the 2050s, from the baseline period (1980&ndash, 2004), was observed to be 2.94%, 3.87%, 4.02% and 5.84% for RCP 2.6, RCP 4.5, RCP 6.0 and RCP 8.5, respectively. The irrigation requirement was predicted to increase by a range of 39% to 45% for a 60% increase in yield using the current agronomic practice in the current climate scenario by the 2050s, for all four climate change scenarios from the baseline period (1980&ndash, 2004). We found that if we combine both conservation agriculture and removal of 30% of the post-harvest losses, the irrigation requirement would be reduced by 26% (45 to 19%), 20% (44 to 24%), 21% (43 to 22%), 22% (39 to 17%) and 20% (41 to 21%) with the current climate scenarios, namely, the RCP 2.6, RCP 4.5, RCP 6.0 and RCP 8.5 conditions, respectively. This combination of conservation practices suggests that the irrigation water requirement can be reduced by a large percentage, even if we produce 60% more food under the projected climate change conditions.

Species ecological envelope maps were obtained for the two main Portuguese wood-production species (Eucalyptus globulus Labill. and Pinus pinaster Aiton) and projected future climate change scenarios. A machine learning approach was used to understand the most influential environmental variables that may explain current species distribution and productivity. Background and Objectives: The aims of the study were: (1) to map species potential suitability areas using ecological envelopes in the present and to project them in the future under climate change scenarios, (2) to map species current distributions, (3) to map species current productivity, and (4) to explore the most influential environmental variables on species current distribution and productivity. Materials and Methods: Climate, elevation data, and soil data sets were used to obtain present and future species ecological envelopes under two climate change scenarios. The official land cover maps were used to map species distributions. Forest inventory data were used to map the species productivity by geostatistical techniques. A Bayesian machine learning approach, supported by species distributions and productivity data, was used to explore the most influential environmental variables on species distribution and productivity and to validate species ecological envelopes. Results: The species ecological envelope methodology was found to be robust. Species&rsquo, ecological envelopes showed a high potential for both species&rsquo, afforestation. In the future, a decrease in the country&rsquo, s area potentiality was forecasted for both species. The distribution of maritime pine was found to be mainly determined by precipitation-related variables, but the elevation and temperature-related variables were very important to differentiate species productivity. For eucalypts, species distribution was mainly explained by temperature-related variables, as well as the species productivity. Conclusions: These findings are key to support recommendations for future afforestation and will bring value to policy-makers and environmental authorities in policy formulation under climate change scenarios.

Aspalathus linearis (Burm. f.) R. Dahlgren (rooibos) is endemic to the Fynbos Biome of South Africa, which is an internationally recognized biodiversity hot spot. Rooibos is both an invaluable wild resource and commercially cultivated crop in suitable areas. Climate change predictions for the region indicate a significant warming scenario coupled with a decline in winter rainfall. First estimates of possible consequences for biodiversity point to species extinctions of 23% in the long term in the Fynbos Biome. Bioclimatic modelling using the maximum entropy method was used to develop an estimate of the realized niche of wild rooibos and the current geographic distribution of areas suitable for commercially production. The distribution modelling provided a good match to the known distribution and production area of A. linearis. An ensemble of global climate models that assume the A2 emissions scenario of high energy requirements was applied to develop possible scenarios of range/suitability shift under future climate conditions. When these were extrapolated to a future climate (2041–2070) both wild and cultivated tea exhibited substantial range contraction with some range shifts southeastwards and upslope. Most of the areas where range expansion was indicated are located in existing conservation areas or include conservation worthy vegetation. These findings will be critical in directing conservation efforts as well as developing strategies for farmers to cope with and adapt to climate change.

Systems biology promises to revolutionize medicine, yet human wellbeing is also inherently linked to healthy societies and environments (sustainability). The IDEA Consortium is a systems ecology open science initiative to conduct the basic scientific research needed to build use-oriented simulations (avatars) of entire social-ecological systems. Islands are the most scientifically tractable places for these studies and we begin with one of the best known: Moorea, French Polynesia. The Moorea IDEA will be a sustainability simulator modeling links and feedbacks between climate, environment, biodiversity, and human activities across a coupled marine–terrestrial landscape. As a model system, the resulting knowledge and tools will improve our ability to predict human and natural change on Moorea and elsewhere at scales relevant to management/conservation actions., GigaScience, 5 (1), ISSN:2047-217X

is work focuses on evaluating the climate change projected by the end of the 21st century under the SRES A2 emission scenario over southern South America using the regional model MM5. e model projects: (i) an increase of precipitation over central Argentina, Uruguay and southern Brazil during summer and fall; (ii) a decrease in precipitation over most of the study domain during winter and spring; (iii) an important decrease in precipitation over central and southern Chile, through the year. In general, the projected temperature increase depends on the season and the examined area; particularly, it is highest over tropical and subtropical latitudes in spring and over high latitudes in summer. e MM5 model projects: (i) an increase of the interanual precipitation variability of precipitation over central Argentina and Uruguay regardless the season; (ii) a slight decrease in interannual temperature variability over large extents of Argentina for summer and winter; (iii) a slight increase in interannual temperature variability at transition seasons; with highest values over central Chile in autumn and over north central Argentina in spring. From the reliability assessment of regional climate projections, it can be concluded that signal-to-noise ratio is high for temperature and low for precipitation. erefore, the MM5 model is a useful tool in the generation of regional climate change scenarios of high resolution over southern South America, particularly for temperature, and is a starting point to perform studies related to impacts of climate change. Este trabajo evalúa las proyecciones de cambio climático del modelo regional MM5 para fines del siglo veintiuno en el escenario de emisión SRES A2 en el sur de Sudamérica. El modelo proyecta: (i) aumento de la precipitación en el centro de Argentina, Uruguay y sur de Brasil en verano y otoño; (ii) disminución de la precipitación en la mayor parte de la región de estudio en invierno y primavera; (iii) marcada reducción de la precipitación en el centro y sur de Chile durante todo el año. En general, el aumento de temperatura proyectado depende de la época y la región examinada; particularmente es máximo en latitudes tropicales y subtropicales en primavera y en altas latitudes en verano. El modelo MM5 proyecta: (i) aumento de la variabilidad interanual de la precipitación en el centro de Argentina y Uruguay independientemente de la época del año; (ii) una leve disminución de la variabilidad interanual de la temperatura en la mayor parte de territorio argentino para verano e invierno; (iii) un leve aumento de la variabilidad interanual de la temperatura en las estaciones intermedias; con valores mayores en el centro de Chile en otoño y en el centro norte de Argentina en primavera. De la evaluación de cuán robustas son las proyecciones climáticas regionales, puede concluirse que la relación señal-ruido es alta para la temperatura y baja para la precipitación. Por lo tanto, el modelo MM5 es una herramienta de mucha utilidad para la generación y evaluación de escenarios regionales de cambio climático en el sur de Sudamérica, en especial para la temperatura. Esto constituye un punto de partida para realizar estudios relacionados con el impacto del cambio climático. Fil: Cabre, Maria Fernanda. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; Argentina. Centre National de la Recherche Scientifique; Francia Fil: Solman, Silvina Alicia. Centre National de la Recherche Scientifique; Francia. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Ciencias de la Atmósfera y los Océanos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; Argentina Fil: Nuñez, Mario Nestor. Centre National de la Recherche Scientifique; Francia. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Ciencias de la Atmósfera y los Océanos; Argentina

Esta comunicación presenta los resultados de la investigación llevada a cabo para el desarrollo de un geovisor diseñado para la explotación y difusión de los datos de escenarios regionales de cambio climático para Andalucía. Este geovisor está basado en la generación de servicios interoperables OGC (Open Geospatial Consortium) de visualización. Este trabajo es fruto de la colaboración entre el Grupo de Climatología del Departamento de Geografía Física de la Universidad de Sevilla y la Consejería de Medio y Ordenación del Territorio (CMAOT) de la Junta de Andalucía. El conocimiento generado en términos de técnicas de geovisualización de BIG DATA espaciales ha sido transferido a la Red de Información Ambiental de Andalucía (REDIAM), con el objeto de poder ser aplicado a otros ámbitos de la información climatológica y ambiental. Los datos de partida proceden de los escenarios regionalizados para Andalucía a partir de técnicas de downscalling estadístico, a partir de la modelización (3 modelos CNMC3, ECHAM5 y EGMAN) y de los escenarios del IV Informe del IPCC (a1b, a2 y b1). Este trabajo ha supuesto la implementación de una base de datos espacial de gran volumen y difícil manejo que ha requerido el desarrollo de una nueva línea de investigación y desarrollos que permitiera el análisis y tratamiento de los datos acumulados para su explotación y difusión. El resultado de esta colaboración es un geovisor que permite consultar para la región, a una resolución de 200 metros, escenarios de temperatura media y precipitación para tres horizontes temporales (2011-2040, 2041-2070, 2071-2100) combinando modelos, escenarios y sus correspondientes indicadores de cambio. This paper presents the results of research carried out for the development of a GeoVisor designed for exploitation and dissemination of data of regional climate change scenarios for Andalusia. This GeoVisor is based on the generation of interoperable OGC display. This work is the result of collaboration between the Group of Climatology Department of Physical Geography of the University of Seville and the Environment and Spatial Planning Administration of the Andalusian Government. The knowledge generated in terms of techniques geovisualization BIG DATA space has been transferred to the Environmental Information Network of Andalusia (REDIAM), in order to be able to be applied to other areas of the climatological and environmental information. The input data come from the regionalized scenarios for Andalusia from techniques of statistical downscalling, from modeling (3 models CNMC3, ECHAM5 and EGMAN) and scenarios IV Report of the IPCC (A1B, A2 and B1). This work has involved the implementation of a spatial database of high volume and difficult handling has required the development of a new line of research and development that would allow the analysis and processing of data accumulated for exploitation and dissemination. The result of this collaboration is a GeoVisor that provides access to the region, at a resolution of 200 meters, scenarios average temperature and precipitation for three time horizons (2011-2040, 2041-2070, 2071-2100) combining models, scenarios and corresponding indicators of change.

This study provides an up-to-date analysis of climate change over the Salento area (southeast Italy) using both historical data and multi-model projections of Regional Climate Models (RCMs). The accumulated anomalies of monthly precipitation and temperature records were analyzed and the trends in the climate variables were identified and quantified for two historical periods. The precipitation trends are in almost all cases not significant while the temperature shows statistically significant increasing tendencies especially in summer. A clear changing point around the 80s and at the end of the 90s was identified by the accumulated anomalies of the minimum and maximum temperature, respectively. The gradual increase of the temperature over the area is confirmed by the climate model projections, at short&mdash, (2016&ndash, 2035), medium&mdash, (2046&ndash, 2065) and long-term (2081&ndash, 2100), provided by an ensemble of 13 RCMs, under two Representative Concentration Pathways (RCP4.5 and RCP8.5). All the models agree that the mean temperature will rise over this century, with the highest increases in the warm season. The total annual rainfall is not expected to significantly vary in the future although systematic changes are present in some months: a decrease in April and July and an increase in November. The daily temperature projections of the RCMs were used to identify potential variations in the characteristics of the heat waves, an increase of their frequency is expected over this century.

Many major questions in earth science research today are not matters of the behavior of physical systems alone, but of the interaction of physical and social systems. Information and assumptions about human behavior, human institutions and infrastructures, and human reactions and responses, as well as consideration of social and monetary costs, play a role in climate prediction, hydrological research, and earthquake risk assessment. The incorporation of social factors into “physical” models by scientists with little or no training in the humanities or social sciences creates ground for concern as to how well such factors are represented, and thus how reliable the resulting knowledge claims might be. Yet science studies scholars have scarcely noticed this shift, let alone analyzed it, despite its potentially profound epistemic – and potentially social – consequences.

The regional effects of climate change on forest ecosystems in the temperate climate zone of Europe can be modelled as shifts of forest vegetation zones in the landscape, northward and to higher elevations. This study applies a biogeographical model of climate conditions in the forest vegetation zones of the Central European landscape, in order to predict the impact of future climate change on the most widespread tree species in European deciduous forests-the European beech (Fagus sylvatica L.). The biogeographical model is supported by a suite of software applications in the GIS environment. The model outputs are defined as a set of conditions - climate scenario A1B by the Special Report on Emission Scenarios (SRES) for a forecast period, for a specified geographical area and with ecological conditions appropriate for the European beech, which provide regional scenarios for predicted future climatic conditions in the context of the European beech's environmental requirements. These predicted changes can be graphically visualized. The results of the model scenarios for regional climate change show that in the Czech Republic from 2070 onwards, optimal growing conditions for the European beech will only exist in some parts of those areas where it currently occurs naturally. Based on these results, it is highly recommended that the national strategy for sustainable forest management in the Czech Republic be partly re-evaluated. Thus, the presented biogeographical model of climate conditions in forest vegetation zones can be applied, not only to generate regional scenarios of climate change in the landscape, but also as a support tool for the development of a sustainable forest management strategy.

The scenario forecasting technique for assessing changes of water balance components of the northern river basins due to possible climate change was developed. Three IPCC global emission scenarios corresponding to different possible scenarios for economic, technological, political and demographic development of the human civilization in the 21st century were chosen for generating climate change projections by an ensemble of 16 General Circulation Models with a high spatial resolution. The projections representing increments of monthly values of meteorological characteristics were used for creating 3-hour meteorological time series up to 2063 for the Northern Dvina River basin, which belongs to the pan-Arctic basin and locates at the north of the European part of Russia. The obtained time series were applied as forcing data to drive the land surface model SWAP to simulate possible changes in the water balance components due to different scenarios of climate change for the Northern Dvina River basin

Waiting author review, in this status since: 1 Jul 2008 for Journal: Environmental Modelling and & Software., The demand for high-resolution seasonal and climate change forecasts is continuously increasing in a variety of socio-economic impact sectors, including agriculture, energy, health, and insurance. To fill the gap between the coarse-resolution outputs available from Global Circulation Models (GCMs) and the regional needs of the impact applications used in the above sectors, a number of statistical downscaling techniques have been developed. Statistical downscaling is nowadays a mature and complex multi-disciplinary discipline involving a cascade of different scientific applications to access and process large amounts of heterogeneous data. Therefore, interactive user-friendly tools are necessary in order to ease the downscaling process for end users, thus maximizing the exploitation of the available predictions. The Statistical Downscaling Portal (SD Portal) described in this paper has been designed following an end-to-end approach in order to transparently connect data providers and end users. To this aim, Internet and distributed computing technologies have been combined together with statistical tools to directly downscale GCM outputs to the regional or local scale required by impact applications. Thus, users can test and validate online di®erent methods (regression, neural networks, analogs, weather typing, etc.) using a Web browser, not worrying about the details of the techniques used or the different formats of the data accessed. The portal is part of the ENSEMBLES EU-funded project., The authors are grateful to the 6th FP EU project ENSEMBLES (GOCE-CT-2003-505539) and to the CICYT project CGL2005-06966-C07-02/CLI for partial support of this work.

International audience; An overview is presented of the phenological models relevant for boreal coniferous, temperate-zone deciduous and Mediterranean coniferous forest ecosystems. The phenology of the boreal forests is mainly driven by temperature, affecting the timing of the start of the growing season and thereby its duration, and the level of frost hardiness and thereby the reduction of foliage area and photosynthetic capacity by severe frost events. The phenology of temperate-zone forests is also mainly driven by temperature. Since temperate-zone forests are mostly mixed-species deciduous forests, differences in phenological response may affect competition between tree species. The phenology of Mediterranean coniferous forests is mainly driven by water availability, affecting the development of leaf area, rather than the timing of phenological events. These phenological models were subsequently coupled to the process-based forest model FORGRO to evaluate the effect of different climate change scenarios on growth. The results indicate that the phenology of each of the forest types significantly affects the growth response to a given climate change scenario. The absolute responses presented in this study should, however, be used with caution as there are still uncertainties in the phenological models, the growth models, the parameter values obtained and the climate change scenarios used. Future research should attempt to reduce these uncertainties. It is recommended that phenological models that describe the mechanisms by which seasonality in climatic drivers affects the phenological aspects of trees should be developed and carefully tested. Only by using such models may we make an assessment of the impact of climate change on the functioning and productivity of different forest ecosystems.

The necessity to combine forest resource management with regional development is a social requirement. The halting of the forestry marginalization trend is the result, among other things, of the lack of strong links between forest management and local communities’ development, as well as the lack of a holistic approach to the space management principles. The paper analyses the causes and possibilities of solving forest, forestry and regional development problems.

In the last decades, a global warming trend was observed. Along with the temperature increase, modifications in the humidity and wind regime amplify the regional and local impacts on livestock husbandry. Direct impacts include the occurrence of climatic stress conditions. In Europe, cows are economically highly relevant and are mainly kept in naturally ventilated buildings that are most susceptible to climate change. The high-yielding cows are particularly vulnerable to heat stress. Modifications in housing management are the main measures taken to improve the ability of livestock to cope with these conditions. Measures are typically taken in direct reaction to uncomfortable conditions instead of in anticipation of a long-term risk for climatic stress. Measures that balance welfare, environmental and economic issues are barely investigated in the context of climate change and are thus almost not available for commercial farms. Quantitative analysis of the climate change impacts on animal welfare and linked economic and environmental factors is rare. Therefore, we used a numerical modeling approach to estimate the future heat stress risk in such dairy cattle husbandry systems. The indoor climate was monitored inside three reference barns in central Europe and the Mediterranean regions. An artificial neuronal network (ANN) was trained to relate the outdoor weather conditions provided by official meteorological weather stations to the measured indoor microclimate. Subsequently, this ANN model was driven by an ensemble of regional climate model projections with three different greenhouse gas concentration scenarios. For the evaluation of the heat stress risk, we considered the number and duration of heat stress events. Based on the changes in the heat stress events, various economic and environmental impacts were estimated. The impacts of the projected increase in heat stress risk varied among the barns due to different locations and designs as well as the anticipated climate change (considering different climate models and future greenhouse gas concentrations). There was an overall increasing trend in number and duration of heat stress events. At the end of the century, the number of annual stress events can be expected to increase by up to 2000, while the average duration of the events increases by up to 22 h compared to the end of the last century. This implies strong impacts on economics, environment and animal welfare and an urgent need for mid-term adaptation strategies. We anticipated that up to one-tenth of all hours of a year, correspondingly one-third of all days, will be classified as critical heat stress conditions. Due to heat stress, milk yield may decrease by about 2.8 % relative to the present European milk yield, and farmers may expect financial losses in the summer season of about 5.4 % of their monthly income. In addition, an increasing demand for emission reduction measures must be expected, as an emission increase of about 16 Gg of ammonia and 0.1 Gg of methane per year can be expected under the anticipated heat stress conditions. The cattle respiration rate increases by up to 60 %, and the standing time may be prolonged by 1 h. This causes health issues and increases the probability of medical treatments. The various impacts imply feedback loops in the climate system which are presently underexplored. Hence, future in-depth studies on the different impacts and adaptation options at different stress levels are highly recommended.

The European grapevine moth (Lobesia botrana) is one of the major pests of the grapevine (Vitis vinifera) in Europe. The phenology of both the insect pest and the plant has already changed over the last decades in response to rising temperatures, with a tendency towards an earlier development. The impact of a warming climate, among other factors, could alter matches in phenology between two trophic levels, being either beneficial or detrimental to V. vinifera. As a consequence, when considering a European latitudinal transect, the changes toward synchrony or a mismatch are not fully understood. In this study, we applied the results of sequential models to simulate the phenological development of V. vinifera from dormancy to physiological maturity of Chardonnay or a similar grape variety. Likewise, we simulated the phenology of L. botrana with a process-based voltinism model. Both models were calibrated and validated in previous studies. The present study aims at simulating the future evolution of both trophic levels under changing climatic conditions at four representative European locations by using quasi-transient climate scenarios up to the year 2100 that consider the RCP4.5 and RCP8.5 greenhouse-gas forcing pathways. Although some physiological adaptations could alter these results, simulations of synchrony under climate change are crucial for the adaptation of grape cultivation and varieties. This modelling work seeks to improve our understanding of the probable shifts in the timing and spatial distribution of the plant-insect interactions in a warmer climate and how this may impact their synchrony. A risk index of damage has been implemented for the different sites and greenhouse gas forcing trajectories. Results suggest an increasing damage risk for V. vinifera close to the timing of harvests in northern Europe. They also point to increasing mortality rates of the fourth generation of L. botrana in southern Europe, where temperatures will increasingly reach the upper thermal limit for insect development.