Projected Climate Scenarios Research Articles

Influence of irrigation strategy and mycorrhizal inoculation on fruit quality in different clones of Tempranillo grown under elevated temperatures

The projected climate scenario for South Mediterranean Europe predicts lower precipitation and higher temperatures that will negatively affect viticulture in the region. The application of moderate deficit irrigation at crucial moments of berry ripening has been found to improve berry quality. Furthermore, grapevine association with arbuscular mycorrhizal fungi (AMF) may improve grapevine’s ability to cope with abiotic stresses. Therefore, the aims of this research were: (1) to characterize the response of three clones of Vitis vinifera L. cv. Tempranillo to the combination of different water deficit programs and AMF inoculation under elevated temperatures, and (2) to determine whether AMF inoculation can improve berry antioxidant properties under these conditions. The study was carried out on three fruit-bearing cuttings clones of cv. Tempranillo (CL-260, CL-1089 and CL-843) inoculated (+M) or not (−M) with AMF and subjected to two temperature regimes (24/14°C and 28/18°C (day/night)) combined with three irrigation regimes during berry ripening. Irrigation treatments were: (i) water deficit from fruit set to veraison (early deficit, ED); (ii) water deficit from veraison to maturity (late deficit, LD); and (iii) full irrigation (FI). Although each Tempranillo clone seemed to have different abilities to respond to elevated temperatures and water supply, in general, at 24/14°C the LD treatment performed better than ED. Differences among clones were attenuated at 28/18°C. In addition, potential benefits of the LD treatment were improved by AMF inoculation. Thus, in all clones the loss of anthocyanins at 28/18°C detected in −M plants after applying LD did not occur in the +M plants. Moreover, AMF inoculation increased must antioxidant capacity in CL-843 under these environmental conditions. Our results suggest that the implementation of measures to promote the association of grapevines with appropriate AMF for each variety could contribute to optimize effects of irrigation strategy on berry properties under future warming conditions.

Climate change impacts on hard red spring wheat yield and production risk: evidence from Manitoba, Canada

A Just–Pope production function is employed to investigate the effects of historic weather changes on hard red spring wheat yield variability in Manitoba. Field-level data on wheat yield, proportion of wheat seeded area, and fertilizer inputs from the Manitoba Agricultural Services Corporation were employed to determine how temperature and precipitation affect mean wheat yield and production risk, and how projected climate scenarios impact yield variability in heterogeneous risk areas of Manitoba. Variety richness increases average yield and reduces yield variance while varieties protected by plant breeders’ rights increase yield variance. Phosphorus fertilizer is positively associated with average wheat yield while total precipitation is shown to negatively affect mean yield and positively impact yield variability. June precipitation matters while June and July temperatures negatively affect yield. Projected climate change is expected to increase yield variability in both the medium (2034–2050) and long term (2079–2095), both under low- and high-carbon scenarios with production variance effects differing across crop districts. Adaptation strategies may be required to mitigate yield risk effects of climate change resulting in late seeding decisions from increased spring precipitation.

Shrub growth rate and bark responses to soil warming and nutrient addition – A dendroecological approach in a field experiment

Tundra shrubs are slow-growing species limited by low air temperature and scarce nutrient availability. However, shrub expansion has been widely observed in the Arctic during the last decades and attributed to climate warming. Shift in shrub growth, wood structure and abundance affects the surface albedo and permafrost thawing and these changes may feedback to climate. Despite the importance of shrub–climate feedbacks, uncertainties about shrub growth sensitivity to climate remain. Here, we explored the indirect effects of climate warming on shrub growth (vertical and radial), bark thickness, and bark investment in four arctic shrub species. We combined a field experiment addressing two suggested growth drivers – thawing depth and nutrient availability – with dendroecology in a Siberian tundra ecosystem. We used heating cables to increase the thawing depth. To enhance the nutrient availability, we fertilized the surface soil layers. We found that shrub growth was mainly limited by nutrient availability, as indicated by the fertilization treatment effects on shrub growth ring widths. We also found a bark thickness decrease with the combined soil heating and nutrient addition treatment and a negative correlation between bark investment and growth rate for two of the species. These findings suggest that tundra shrubs, especially deciduous species, will grow faster and taller driven by an increasing nutrient availability in the surface soil layers. However, shrubs might become more vulnerable to pests, herbivory, and climate extremes, such as frost or drought events, due to thinner bark and lower bark investment. Using dendroecological approaches in field experiments simulating projected climate scenarios for the Arctic, and an increasing number of study species and locations will reduce uncertainties related to shrub growth sensitivity to climate and other processes driving shrub dynamics.

Precipitation quantity and timing affect native plant production and growth of a key herbivore, the desert tortoise, in the Mojave Desert

BackgroundDeserts may be disproportionately vulnerable to changes in precipitation that accompany global climate change due to complex evolutionary relationships of species to historical conditions. Based on current and projected climate scenarios for the southwestern United States, we manipulated rainfall timing and quantity and measured the response by plants and the growth and behavior of the desert tortoise (Gopherus agassizii) to precipitation in the eastern Mojave Desert.ResultsWe found that winter-dominant rain – the current prevailing pattern in the eastern Mojave Desert – and greater total rainfall correlated with greater cover and species richness of plants. Winter-dominant rain also correlated with a higher proportion of native plants flowering relative to invasive plants. Juvenile tortoises grew more rapidly when they were subjected to rainfall treatments that associated with increased plant abundance and species richness, while their behavior appeared more driven by water availability.ConclusionsOur results suggest that precipitation timing may be as important as rainfall quantity when considering total effects of climate change on arid-adapted systems. Further research should explore how the timing of rainfall may interact with aridity or temperature to influence total effects due to climate change on arid communities.

Cellular automata approach for modelling climate change impact on water resources

ABSTRACTIn this work, we consider the cellular automata (CA) approach for modelling the climate change impact on water resources. This consists in: constructing a CA model that describes the water cycle dynamics taking into account physical terrain attributes and climatic constraints; coupling the CA model with climate projection scenarios for a considered region as input data; determining and analysing in output the variations of the underground, surface and evaporated water. We present these variations per time interval and per zone of influence. As an application, we consider simulation for a basin in northern Morocco using a simulation software we have designed in Java Object Oriented Programming.We consider cellular automata (CA) approach for modelling climate change impact on water resources. This consists in, first constructing a CA model that describes the water cycle dynamics taking into account physical terrain attributes and climatic constraints, then coupling the CA model with climate projection scenarios for a considered region as input data, and we determine and analyze in output the variations of the water resources (groundwater and surface water). We present these variations per time interval and per zone of influence. The approach application is for a basin in northern Morocco for which we use simulation software that we have designed in Java Object Oriented Programming. Digital terrain model, geological map and satellites image are used for input data.

Growth and cold hardening of European aspen seedlings in response to an altered temperature and soil moisture regime

During the autumn, plants undergo a physiological process of cold hardening to limit damage caused by the low temperatures of winter. Under a warming climate, plants may be less cold hardened and hence more susceptible to the effects of a sudden temperature drop. During the growth season of 2010–2011, growth and cold hardening of European aspen (Populus tremula L.) seedlings from native wild populations were examined under ambient and projected climate scenarios in greenhouses at the Haapastensyrjä research station in Southern Finland. Using locally obtained seedlings, we manipulated temperature and soil moisture during the normal growth period and then subjected them to an artificial freezing treatment during September–November 2010. At the end of the experiment, we determined seedling height, survival and the extent of stem damage, and analysed their variation with mixed effect models.Among the treatments tested, temperature was the main factor affecting survival, cold hardening, and frost damage to seedlings. The higher temperature (4°C increase) of the 2100 future climate regime was associated with a 35% decrease in seedling survival (from 66 to 31%) during the growing period. Increased irrigation had a positive, but considerably weaker effect on seedling survival (improved survival by ca. 8%). Height of seedlings after the first growth season was enhanced by increased soil moisture and temperature, but these effects were negated the following spring by increased frost damage caused by warmer growth conditions. Although cold hardiness increased as the season progressed, increase of temperature by 1 and 4°C severely diminished it, and survival after the freezing dropped from 55% (control) to 48% and 14%, while stem damage increased from 58% (control) to 90% and 96%, respectively. These results suggest that regeneration of north European aspen might become burdened in a warmer climate. Although survival was clearly affected, several seedlings grown under the future climate regimes survived freezing and overwintered with negligible damage, suggesting an adaptive capacity of the local population. The intraspecific competition that occurred as a side effect of the experimental setup also affected cold hardening, suggesting that stand structure might be managed to improve the resilience of aspen to frost damage.

Climate change impact assessment on hydropower generation using multi-model climate ensemble

Hydropower is the primary renewable source of energy that harnesses the power of the naturally flowing water streams and its potential is strongly impacted by the hydrological regime. The objective of the present research is to carry out a hydrological model based study to assess the impacts of climate change on hydropower generation by using the regional climate model (RCM) data available through coordinated regional downscaling experiment (CORDEX), and subsequently to analyse the effect of using model ensemble in projecting the future hydrology and energy generation scenario. C.H.Corn hydroelectric project located on River Ochlockonee near Tallahassee in Florida, USA, has been considered as a case study. A hydrologic model of the basin, draining into the dam, is developed using a conceptual model HYMOD with the historical climate and flow data extracted from the model parameter estimation experiment (MOPEX) dataset. The future projected climate scenario (2091–2100) is generated following the Representative Concentrated Pathways (RCP) 4.5 with the ensembles of six climate models. The impact of the future climate on water availability indicates a significant seasonal variability among the model ensemble results with an overall annual increase of statistics for the climate variables, corresponding inflows and a marginal increase in the energy generation.

MODELING LAND USE AND THE EFFECTS OF CLIMATE CHANGE IN BRAZIL

This paper discusses the development of a computable general equilibrium (CGE) model with detailed specification for land use. The model considers two aspects of land use: land as a measure of production cost and land as a physical entity that can be used in a variety of ways. To analyze the economic effects of climate change, we integrated the CGE model and an econometric model. The results based on this model, which captures how land allocation responds to changes in temperature and precipitation, are introduced as elasticities in the CGE model to offset the demand curve for land among 13 different land uses in 27 regions of Brazil. The simulations are based on climate data from a benchmark period (1975–2005) and Intergovernmental Panel on Climate Change climate projection scenarios for the periods 2010–2039, 2040–2069, and 2070–2099. The results predict negative changes in real gross domestic product ranging from [Formula: see text]0.0054% to [Formula: see text]0.0198%, depending on the scenario.

Scenario-based runoff prediction for the Kaidu River basin of the Tianshan Mountains, Northwest China

Based on the hydro-meteorological data over the past 50 years (1961–2010), the runoff change of the Kaidu River was predicted for the future 30 years (2011–2040). Two statistical downscaling models, the Statistical DownScaling Model (SDSM) and the Statistical Analog Resampling Scheme (STARS), were used to downscale the HadCM3 outputs for projecting the future climate scenarios of the basin. The Soil and Water Assessment Tool (SWAT) hydrological model was driven by the projected climate scenarios to generate the future runoff. Modeling results suggested that the SWAT model can well duplicate the recorded runoff changes in the basin and thus can be applied to simulation of future runoff changes. Both the SDSM and the STARS models performed well in simulating the temperature but relatively poorly in simulating the precipitation. Under the A2 and B2 scenarios the basin will experience a significant increasing trend in temperature and an indistinctive change trend in precipitation during the entire forecast period. Under the S1–S3 scenarios, both temperature and precipitation do not exhibit distinctive changes. In terms of river runoff, the predicted average annual runoff will be relatively abundant during the period from 2010s to 2020s but obviously short after 2020s under A2 scenario and will be kept relatively steady under B2 scenario. The predicted runoff will fluctuate drastically with no any significant trend under S1–S3 scenarios. The relatively high runoffs under S2–S3 scenarios seem to indicate the importance of temperature increasing in generating runoff. The scenario-based predictions suggest that moderate emission (e.g., B2) or moderate warming (e.g., S2) is beneficial to maintaining the expected level of runoff in the future.

Hydropower Production in Future Climate Scenarios; the Case for the Zambezi River

Climate change remains a threat to water resources projects in southern Africa where impacts resulting from changes in climate are projected to be negative and worse than in most other regions of the world. This work presents an assessment of the impacts of climate change on water resources and hydropower production potential in the Zambezi River Basin. Future climate scenarios projected through the five General Circulation Model (GCM) outputs are used as input in the impact assessment. The future projected climate scenarios are downscaled to find local and regional changes, and used in the Hydrologiska Byråns Vattenbalansavdelning (HBV) hydrological model to assess climate change impacts on water resources in the river basin. According to the simulations, air temperature and potential evaporation are projected to increase, while rainfall is projected to decrease. The Zambezi hydropower system is likely to be affected negatively as a result of future climate changes. Increasing air temperature leading to increased evaporation, and reduced rainfall, both contribute to a decrease in resulting river flows and increased reservoir evaporation. Consequently, the decrease in water resources will lead to decreased hydropower production potential, by 9% in 2020s, 18% in 2050s and 28% in 2080s in the hydropower system, for a medium emission scenario, A1B.

Tradeoffs between Maize Silage Yield and Nitrate Leaching in a Mediterranean Nitrate-Vulnerable Zone under Current and Projected Climate Scenarios.

Future climatic changes may have profound impacts on cropping systems and affect the agronomic and environmental sustainability of current N management practices. The objectives of this work were to i) evaluate the ability of the SALUS crop model to reproduce experimental crop yield and soil nitrate dynamics results under different N fertilizer treatments in a farmer’s field, ii) use the SALUS model to estimate the impacts of different N fertilizer treatments on NO3- leaching under future climate scenarios generated by twenty nine different global circulation models, and iii) identify the management system that best minimizes NO3- leaching and maximizes yield under projected future climate conditions. A field experiment (maize-triticale rotation) was conducted in a nitrate vulnerable zone on the west coast of Sardinia, Italy to evaluate N management strategies that include urea fertilization (NMIN), conventional fertilization with dairy slurry and urea (CONV), and no fertilization (N0). An ensemble of 29 global circulation models (GCM) was used to simulate different climate scenarios for two Representative Circulation Pathways (RCP6.0 and RCP8.5) and evaluate potential nitrate leaching and biomass production in this region over the next 50 years. Data collected from two growing seasons showed that the SALUS model adequately simulated both nitrate leaching and crop yield, with a relative error that ranged between 0.4% and 13%. Nitrate losses under RCP8.5 were lower than under RCP6.0 only for NMIN. Accordingly, levels of plant N uptake, N use efficiency and biomass production were higher under RCP8.5 than RCP6.0. Simulations under both RCP scenarios indicated that the NMIN treatment demonstrated both the highest biomass production and NO3- losses. The newly proposed best management practice (BMP), developed from crop N uptake data, was identified as the optimal N fertilizer management practice since it minimized NO3- leaching and maximized biomass production over the long term.

Modeling of Hydrological Extremes Under Climate Change Scenarios in The Upper Blue Nile River Basin, Ethiopia

The impact of climate change on modeling of hydrological extremes is needed to asses at regional and local scales since these vicissitudes are not uniform over the globe. This work stresses on climate change impact on the hydrological extremes (MMAX, CMAX, NNHF, Q10, MMIX, CMIX, MIN7, and Q90) and precipitation extremes (MLWD, MLDD, ADMT, ADMP) during the far future (2071-2100) period over the selected sites across the upper Blue Nile River basin (UBNRB), Ethiopia. The change in extreme indices were calculated based on daily precipitation and temperature data derived from the most recent CMIP5 climate projection scenarios compared to the reference period (1971-2000). The raw outputs from the climate models were corrected in order to reduce biases using distribution based quantile mapping technique. The validation and calibration demonstrates that the seasonal maximum cycle of precipitation and temperature in the reference period is reproduced reasonably in the bias-corrected climate results. The projections of climate change impacts on the hydrological extremes were evaluated using three generalize lump conceptual hydrological models: GR4J; HBV; HMETS and two objective functions: NSE and LogNSE. These hydrological models are calibrated in the period of 1971-2000 and validated in 2001-2010 period. The optimized hydrological parameters are adopted for the future hydrological simulations (2071-2100). The results indicate that the wet/dry spell will significantly decrease/increase due to climate change in some sites of the region (sites 2 and 6), while in sites 1 and 5, there is increase/decrease in wet/dry spell but not significant, respectively. Far future maximum river flows in the study area will be less extreme and more variable in terms of magnitude, and more irregular in terms of seasonal occurrence, than they are at present. Low flows may become less extreme and variable in terms of magnitude, and more irregular in terms of seasonal occurrence. Most areas of northern, western, and northeastern part of the river basin will likely become wetter in the wet season and drier in dry season. Whereas, indices that related to low flows are projected to increase most prominently for lowland sites, due to the combined effects of projected decreases in summer precipitation, and projected increases in evapotranspiration that reduce residual soil moisture in late summer. Whereas the indices related to the high flows are projected slight increase in the central and upper part of the basin. According to the evaluated scenarios, climate change may have favorable impacts on the distribution of hydrological extremes in the study area.

Future Changes in Drought Characteristics: Regional Analysis for South Korea under CMIP5 Projections

Abstract The future changes in drought characteristics were examined on a regional scale for South Korea, in northeastern Asia, using 17 bias-corrected projections from phase 5 of the Coupled Model Intercomparison Project (CMIP5) of representative concentration pathway (RCP) scenarios 4.5 and 8.5. The frequency of severe or extreme drought, based on the standardized precipitation index (SPI) and standardized precipitation evapotranspiration index (SPEI), with time scales of 1, 3, and 12 months (i.e., SPI1, SPI3, SPI12, SPEI1, SPEI3, and SPEI12), was considered, as well as the average duration based on SPEI1. A multimodel ensemble (MME) was produced using selected models, and future changes were investigated in terms of both drought frequency and the average duration for the entire area and four river basins. The changes in drought frequency largely depend on the selection of a drought index, rather than climate projection scenarios. SPEI3 mostly projected future increases in drought frequency, while SPI3 showed varied projections. SPI12 projected decreases in drought frequency for both scenarios in the study area, while differences between river basins were observed for SPEI12. Increases in the average duration of droughts were projected based on SPEI1, indicating an increase in persistent short-term droughts in the future. The results emphasize the importance of regional- and subregional-scale analysis in northeastern Asia. The findings of the study provide valuable information that can be used for drought-related decision-making, which could not be obtained from studies on a global spatial scale.

Predicting the distribution of rubber trees (Hevea brasiliensis) through ecological niche modelling with climate, soil, topography and socioeconomic factors

AbstractIdentifying the factors that contribute to species distribution will help determine the impact of the changing climate on species’ range contraction and expansion. Ecological niche modelling is used to analyze the present and potential future distribution of rubber trees (Hevea brasiliensis) in two biogeographically distinct regions of India i.e., the Western Ghats (WG) and Northeast (NE). The rubber tree is an economically important plantation species, and therefore factors other than climate may play a significant role in determining its occurrence. To assist in future planning, we used the maximum entropy model to predict plausible areas for the expansion of rubber tree plantations under a changing climate scenario. Inclusion of elevation, soil and socioeconomic factors into the model did not result in a significant increase in the model accuracy estimates over the bioclimatic model (AUC > 0.92), but their effect was pronounced in the predicted probability scoring of species occurrence. Among various factors, elevation, rooting condition, village population and agricultural labour availability contributed substantially to the model in the NE region, whereas for the WG region, climate was the most important contributing factor for rubber tree distribution. We found that more areas would be suitable for rubber tree plantation in the NE region, whereas further expansion would be limited in the WG region under the projected climate scenario for 2050.

Reconstructing Turbidity in a Glacially Influenced Lake Using the Landsat TM and ETM+ Surface Reflectance Climate Data Record Archive, Lake Clark, Alaska

Lake Clark is an important nursery lake for sockeye salmon (Oncorhynchus nerka) in the headwaters of Bristol Bay, Alaska, the most productive wild salmon fishery in the world. Reductions in water clarity within Alaska lake systems as a result of increased glacial runoff have been shown to reduce salmon production via reduced abundance of zooplankton and macroinvertebrates. In this study, we reconstruct long-term, lake-wide water clarity for Lake Clark using the Landsat TM and ETM+ surface reflectance products (1985–2014) and in situ water clarity data collected between 2009 and 2013. Analysis of a Landsat scene acquired in 2009, coincident with in situ measurements in the lake, and uncertainty analysis with four scenes acquired within two weeks of field data collection showed that Band 3 surface reflectance was the best indicator of turbidity (r2 = 0.55, RMSE << 0.01). We then processed 151 (98 partial- and 53 whole-lake) Landsat scenes using this relation and detected no significant long-term trend in mean turbidity for Lake Clark between 1991 and 2014. We did, however, detect interannual variation that exhibited a non-significant (r2 = 0.20) but positive correlation (r = 0.20) with regional mean summer air temperature and found the month of May exhibited a significant positive trend (r2 = 0.68, p = 0.02) in turbidity between 2000 and 2014. This study demonstrates the utility of hindcasting turbidity in a glacially influenced lake using the Landsat surface reflectance products. It may also help land and resource managers reconstruct turbidity records for lakes that lack in situ monitoring, and may be useful in predicting future water clarity conditions based on projected climate scenarios.

Disentangling the effects of competition and climate on individual tree growth: A retrospective and dynamic approach in Scots pine

Understanding the relative contributions of competition and climate on individual tree growth is critical to project realistic forest dynamics under projected climate scenarios. Furthermore, present competition levels may reflect legacies of past use. Here, we analyze the effects of climate, site conditions and competition on radial growth in three Scots pine stands located along an altitudinal gradient in central Spain. Current stand structure and retrospective analyses of radial growth (basal area increment, BAI) were used to model changes in tree growth as a function of a spatially-explicit competition index (CI) and climate. Linear mixed-effects models were employed to model BAI and to quantify the growth responses to climate of trees under low and high competition levels. Competition effects on growth were steady over time regardless of tree age. High competition levels negatively affected growth since negative exponential functions characterized the CI–BAI relationships. Tree growth sensitivity to climate increased with decreasing competition intensity. Growth at high elevations was mainly limited by low winter temperatures, whereas warm spring enhanced growth at middle elevations and warm late summer temperatures constrained growth at low elevation. Growth responsiveness to climate is enhanced under low competition levels. Overall, current competition is a more relevant driver of recent growth than climate. Proactive forest management should be adopted to reduce the vulnerability of Scots pine forests currently subjected to higher competition levels and warmer and drier conditions.

Assessment of impact of climate change on water resources in a hilly river basin

The sensitivity of Sutlej river sub-basin (middle catchment) which is located in N-W Himalaya is investigated for its hydrologic response to potential changes in climate variability. The predictors of two global climate models (GCMs) that are found to perform well over Indian sub-continents are downscaled, and future time series of temperature (maximum and minimum) and precipitation is generated using statistical downscaling model (SDSM) under A1B, A2, and B2 emission scenarios. An overall increase in mean annual temperature and precipitation is predicted under both the models for future periods. The predicted increase in temperature is relatively higher for HadCM3 model compares to CGCM3 model whereas it is opposite for precipitation. The model also predicts considerable shift in monthly pattern of temperature and precipitation. Further, soil and water assessment tool (SWAT) is employed to appraise future changes in stream flow and water balance of the sub-basin under projected climate scenarios. The simulation results show that in future, increase in mean annual stream flow are likely to range from 1.3 to 7.8 % for CGCM3 model and 0.3 to 3.4 % for HadCM3 model, respectively. However, decrease in mean monthly stream flow is predicted under scenarios of CGCM3 model (from January to May and from November to December) and HadCM3 model (from January to April and from October to December), respectively.

Yield and duration of potato crop in Bihar under projected climate scenarios

The impact of projected climate during 2020-2080 on the potential yield of potato in Bihar has been analysed using InfoCrop model. Data from field experiments conducted at Patna, with popular potato variety Kufri Ashoka grown in rabi season of 2008-09 through 2010-11, was used for calibration and validation of model. It is indicated that increased minimum and maximum temperature projected for future time periods, however, almost no change in rainfall is projected for the stations under studied. The crop planted on 2nd December, showed projected decline in yield ranging from 3.3-5.9% for 2020, 12.5-15% for 2050 and 19.3-24.8% for 2080 time period across the locations studied. Delayed planting by 10 days successively from 2nd December through 22nd December showed a progressively lower decline in the projected yield at different locations. However, advancing the planting time by 10 days resulted inhigher decline in projected yield. Weather data analysis performed for the crop season (November-February).

Integrated SASSCAL research to assess and secure current and future water resources in Southern Africa

Climate change will affect current water resources and food security in sub-Saharan Africa. Considering ongoing changes in land management and population growth as well as projected climate scenarios, the overall challenge in the southern African region is to secure water at sufficient quality and quantity for both the stability of ecosystems, with their functions, and services and for human well-being (potable water, irrigation water, and water for industrial use). Thus, improved understanding of the linkages between hydrological (including hydrogeological) components of ecosystems and society is needed as a precondition to develop sustainable management strategies for integrated water resources management in this data scarce region. With initial funding through the Federal Ministry of Education and Research (BMBF) of Germany, 88 research projects of the SASSCAL Initiative (Southern African Science Service Centre for Climate Change and Adaptive Land Management; www.sasscal.org) focus on providing information and services allowing for a better understanding and assessment of the impact of climate and land management changes in five thematic areas: climate, water, agriculture, forestry and biodiversity.

Plants on the move: Assisted migration of forest trees in the face of climate change

Climate change is impacting distributions of both fauna and flora, including many crops. In order to ensure the health and vigor of the species we depend upon for food and fiber, assisted migration strategies may need to be implemented. This is especially true for long-lived forest trees. Multinomial logit regression was used to develop a Categorical Universal Response Function (CURF) to delineate deployment zones for loblolly pine (Pinus taeda L.) using 15-year measurements from the Western Gulf Forest Tree Improvement Program (WGFTIP) Geographic Seed Source Study (GSSS). The CURF uses performance categories for the response variable, and the model assigns the probabilities with which the performance for a given seed source will fall into these various categories. First and second powers of minimum temperature of the coldest month, summer precipitation, and variation measures of these two metrics at both the seed source site of origin and the test location were used as independent variables. Planted tree volume, accounting for both survival and growth, was used as the response variable. Model performance was good, with the AUC score ranging from 0.785 to 0.808, depending on (1) whether or not the variable interactions were included and (2) the variable selection criterion used (AIC or BIC). Resulting models were then applied to historic weather patterns to illustrate inferred deployment zones for three seed sources. The projected performance generally agreed with the current consensus on loblolly pine seed movement guidelines. The models developed here can be readily implemented in a Decision Support System as they (1) suggest sets of adapted loblolly pine families from which foresters can choose based on local knowledge, (2) can be easily expanded to include other variables, and (3) can be applied to outputs from projected climate scenarios to extrapolate into the future.