A spatial modelling framework for assessing climate change impacts on freshwater ecosystems: Response of brown trout (Salmo trutta L.) biomass to warming water temperature

Mountain regions worldwide are particularly sensitive to on-going climate change. Specifically in the Alps in Switzerland, the temperature has increased twice as fast than in the rest of the Northern hemisphere. Water temperature closely follows the annual air temperature cycle, severely impacting streams and freshwater ecosystems. In the last 20 years, brown trout (Salmo trutta L) catch has declined by approximately 40-50% in many rivers in Switzerland. Increasing water temperature has been suggested as one of the most likely cause of this decline. Temperature has a direct effect on trout population dynamics through developmental and disease control but can also indirectly impact dynamics via food-web interactions such as resource availability. We developed a spatially explicit modelling framework that allows spatial and temporal projections of trout biomass using the Aare river catchment as a model system, in order to assess the spatial and seasonal patterns of trout biomass variation. Given that biomass has a seasonal variation depending on trout life history stage, we developed seasonal biomass variation models for three periods of the year (Autumn-Winter, Spring and Summer). Because stream water temperature is a critical parameter for brown trout development, we first calibrated a model to predict water temperature as a function of air temperature to be able to further apply climate change scenarios. We then built a model of trout biomass variation by linking water temperature to trout biomass measurements collected by electro-fishing in 21 stations from 2009 to 2011. The different modelling components of our framework had overall a good predictive ability and we could show a seasonal effect of water temperature affecting trout biomass variation. Our statistical framework uses a minimum set of input variables that make it easily transferable to other study areas or fish species but could be improved by including effects of the biotic environment and the evolution of demographical parameters over time. However, our framework still remains informative to spatially highlight where potential changes of water temperature could affect trout biomass. (C) 2015 Elsevier B.V. All rights reserved.-

Impact of different irrigation strategies on grapes and wine quality of four grapevine cultivars (Vitis sp.) in cool climate conditions. An investigation into the relationships among ABA, water status, grape cultivar and wine quality

Niagara Peninsula of Ontario is the largest viticultural area in Canada. Although it is considered to be a cool and wet region, in the last decade many water stress events occurred during the growing seasons with negative effects on grape and wine quality. This study was initiated to understand and develop the best strategies for water management in vineyards and those that might contribute to grape maturity advancement. The irrigation trials investigated the impact of time of initiation (fruit set, lag phase and veraison), water replacement level based on theoretical loss through crop evapotranspiration (ETc; 100,50 and 25%) and different irrigation strategies [partial root zone drying (PRD) versus regulated deficit irrigation (RD!)] on grape composition and wine sensory profiles. The irrigation experiments were conducted in a commercial vineyard (Lambert Vineyards Inc.) located in Niagara-on-the-Lake, Ontario, from 2005 through 2009. The two experiments that tested the combination of different water regimes and irrigation time initiation were set up in a randomized block design as follows: Baco noir - three replicates x 10 treatments [(25%, 50% and 100% of ETc) x (initiation at fruit set, lag phase and veraison) + control]; Chardonnay - three replicates x seven treatments [(25%, 50% and 100% of ETc) x (initiation at fruit set and veraison) + control]. The experiments that tested different irrigation strategies were set up on two cultivars as follows: Sauvignon blanc - four replicates x four treatments [control, fully irrigated (100% ETc), PRD (100% ETc) and RDI (25% ETc)]; Cabemet Sauvignon - four replicates x five treatments [control, fully irrigated (100% ETc), PRD (100% ETc), RDI (50% ETc) and RDI (25% ETc)]. The controls in each experiment were nonirrigated. The irrigation treatments were compared for many variables related to soil water status, vine physiology, berry composition, wine sensory profile, and hormone composition [(abscisic acid (ABA) and its catabolites]. Soil moisture profile was mostly affected by irrigation treatments between 20 and 60 em depth depending on the grapevine cultivar and the regime of water applied. Overall soil moisture was consistently higher throughout the season in 100 and 50% ETc compare to the control. Transpiration rates and leaf temperature as well as shoot growth rate were the most sensitive variables to soil water status. Drip irrigation associated with RDI treatments (50% ETc and 25% ETc) had the most beneficial effects on vine physiology, fruit composition and wine varietal typicity, mainly by maintaining a balance between vegetative and reproductive parts of the vine. Neither the control nor the 100 ETc had overall a positive effect on grape composition and wine sensory typicity. The time of irrigation initiation affected the vine physiology and grape quality, the most positive effect was found in treatments initiated at lag phase and veraison. RDI treatments were overall more consistent in their positive effect on grape composition and wine varietal typicity comparing to PRD treatment. The greatest difference between non-irrigated and irrigated vines in most of the variables studied was found in 2007, the driest and hottest season of the experimental period. Soil water status had a greater and more consistent effect on red grapevine cultivars rather than on white winegrape cultivars. To understand the relationships among soil and plant water status, plant physiology and the hormonal profiles associated with it, abscisic acid (ABA) and its catabolites [phaseic acid (PA), dihydrophaseic acid (DPA), 7-hydroxy-ABA (TOH-ABA), 8' -hydroxy-ABA, neophaseic acid and abscisic acid glucose ester (ABA-GE)] were analyzed in leaves and berries from the Baco noir and Chardonnay irrigation trials over two growing seasons. ABA and some of its catabolites accurately described the water status in the vines. Endogenous ABA and some of its catabolites were strongly affected in Baco noir and Chardonnay by both the water regime (i.e. ET level) and timing of irrigation initiation. Chardonnay grapevines produced less ABA in both leaves and berries compared to Baco noir, which indicated that ABA synthesis is also cultivar dependant. ABA-GE was the main catabolite in treatments with high water deficits, while PA and DPA were higher in treatments with high water status, suggesting that the vine produced more ABA-GE under water deficits to maintain rapid control of the stomata. These differences between irrigation treatments with respect to ABA and catabolites were particularly noticeable in the dry 2007 season. Two trials using exogenous ABA investigated the effect of different concentrations of ABA and organs targeted for spraying, on grape maturation and berry composition of Cabemet Sauvignon grapevines, in two cool and wet seasons (2008-2009). The fIrst experiment consisted of three replicates x three treatments [(150 and 300 mg/L, both applications only on clusters) + untreated control] while the second experiment consisted in three replicates x four treatments [(full canopy, only clusters, and only leaves sprayed with 300 ppm ABA) + untreated control]. Exogenous ABA was effective in hastening veraison, and improving the composition of Cabemet Sauvignon. Ability of ABA to control the timing of grape berry maturation was dependant on both solution concentration and the target organ. ABA affected not only fruit composition but also yield components. Berries treated with ABA had lower weight and higher skin dry mass, which constitutes qualitative aspects desired in the wine grapes. Temporal advancement of ripening through hormonal control can lead to earlier fruit maturation, which is a distinct advantage in cooler areas or areas with a high risk of early frost occurrence. Exogenous ABA could provide considerable benefits to wine industry in terms of grape composition, wine style and schedule activities in the winery, particularly in wet and cool years. These trials provide the ftrst comprehensive data in eastern North America on the response of important hybrid and Vitis vinifera winegrape cultivars to irrigation management. Results from this study additionally might be a forward step in understanding the ABA metabolism, and its relationship with water status. Future research should be focused on ftnding the ABA threshold required to trigger the ripening process, and how this process could be controlled in cool climates.

Studies on rainfall variability and the influence of orography and land use on the climate of Peninsular India

The present study helped to understand the trend in rainfall patterns at smaller spatial scales and the large regional differences in the variability of rainfall. The effect of land use and orography on the diurnal variability is also understood. But a better understanding on the long term variation in rainfall is possible by using a longer dataset,which may provide insight into the rainfall variation over country during the past century. The basic mechanism behind the interannual rainfall variability would be possible with numerical studies using coupled Ocean-Atmosphere models. The regional difference in the active-break conditions points to the significance of regional studies than considering India as a single unit. The underlying dynamics of diurnal variability need to be studied by making use of a high resolution model as the present study could not simulate the local onshore circulation. Also the land use modification in this study, selected a region, which is surrounded by crop land. This implies the high possibility for the conversion of the remaining region to agricultural land. Therefore the study is useful than considering idealized conditions, but the adverse effect of irrigated crop is more than non-irrigated crop. Therefore, such studies would help to understand the climate changes occurred in the recent period. The large accumulation of rainfall between 300-600 m height of western Ghats has been found but the reason behind this need to be studied, which is possible by utilizing datasets that would better represent the orography and landuse over the region in high resolution model. Similarly a detailed analysis is needed to clearly identify the causative relations of the predictors identified with the predictant and the physical reasons behind them. New approaches that include nonlinear relationships and dynamical variables from model simulations can be included in the existing statistical models to improve the skill of the models. Also the statistical models for the forecasts of monsoon have to be continually updated.

Impact of climate change on hetrotrophic bacterial communities in the water and sediment of kongsfjord in norwegian artic

Considering the extent of warming in the artic region and the resultant changes in the dynamic marine enviornments there is a need to monitor the bacterial diversity in the fjord enviornments especially in terms of cultivable bacteria. The present study reports the diversity of cultivable hetrotrophic bacteria from the water and sediment samples of kongsfjord their growth responses to important enviornmental variables and ability to produce industrially important hydrolytic enzymes.

Development and Validation of the Family Motivational Climate Questionnaire (FMC-Q)

Resumen tomado de la publicación

The Influence of Summer Climate on Avian Community Composition in the Eastern Boreal Forest of Canada

Understanding the relative influence of environmental variables, especially climate, in driving variation in species diversity is becoming increasingly important for the conservation of biodiversity. The objective of this study was to determine to what extent climate can explain the structure and diversity of forest bird communities by sampling bird abundance in homogenous mature spruce stands in the boreal forest of the Québec-Labrador peninsula using variance partitioning techniques. We also quantified the relationship among two climatic gradients, summer temperature and precipitation, and bird species richness, migratory strategy, and spring arrival phenology. For the bird community, climate factors appear to be most important in explaining species distribution and abundance because nearly 15% of the variation in the distribution of the 44 breeding birds selected for the analysis can be explained by climate. The vegetation variables we selected were responsible for a much smaller amount of the explained variation (4%). Breeding season temperature seems to be more important than precipitation in driving variation in bird species diversity at the scale of our analysis. Partial correlation analysis indicated that bird species richness distribution was determined by the temperature gradient, because the number of species increased with increasing breeding season temperature. Similar results were observed between breeding season temperature and the number of residents, short-distance and long-distance migrants, and early and late spring migrants. Our results suggest that the northern and southern range boundaries of species are not equally sensitive to the temperature gradient across the region.

An observing system simulation experiment for climate monitoring with GNSS radio occulation data: setup and testbed study

The long-term stability, high accuracy, all-weather capability, high vertical resolution, and global coverage of Global Navigation Satellite System (GNSS) radio occultation (RO) suggests it as a promising tool for global monitoring of atmospheric temperature change. With the aim to investigate and quantify how well a GNSS RO observing system is able to detect climate trends, we are currently performing an (climate) observing system simulation experiment over the 25-year period 2001 to 2025, which involves quasi-realistic modeling of the neutral atmosphere and the ionosphere. We carried out two climate simulations with the general circulation model MAECHAM5 (Middle Atmosphere European Centre/Hamburg Model Version 5) of the MPI-M Hamburg, covering the period 2001–2025: One control run with natural variability only and one run also including anthropogenic forcings due to greenhouse gases, sulfate aerosols, and tropospheric ozone. On the basis of this, we perform quasi-realistic simulations of RO observables for a small GNSS receiver constellation (six satellites), state-of-the-art data processing for atmospheric profiles retrieval, and a statistical analysis of temperature trends in both the “observed” climatology and the “true” climatology. Here we describe the setup of the experiment and results from a test bed study conducted to obtain a basic set of realistic estimates of observational errors (instrument- and retrieval processing-related errors) and sampling errors (due to spatial-temporal undersampling). The test bed results, obtained for a typical summer season and compared to the climatic 2001–2025 trends from the MAECHAM5 simulation including anthropogenic forcing, were found encouraging for performing the full 25-year experiment. They indicated that observational and sampling errors (both contributing about 0.2 K) are consistent with recent estimates of these errors from real RO data and that they should be sufficiently small for monitoring expected temperature trends in the global atmosphere over the next 10 to 20 years in most regions of the upper troposphere and lower stratosphere (UTLS). Inspection of the MAECHAM5 trends in different RO-accessible atmospheric parameters (microwave refractivity and pressure/geopotential height in addition to temperature) indicates complementary climate change sensitivity in different regions of the UTLS so that optimized climate monitoring shall combine information from all climatic key variables retrievable from GNSS RO data.

Evaluation of the sea ice simulation in a new coupled atmosphere-ocean climate model (HadGEM1)

[ 1] A rapid increase in the variety, quality, and quantity of observations in polar regions is leading to a significant improvement in the understanding of sea ice dynamic and thermodynamic processes and their representation in global climate models. We assess the simulation of sea ice in the new Hadley Centre Global Environmental Model (HadGEM1) against the latest available observations. The HadGEM1 sea ice component uses elastic-viscous-plastic dynamics, multiple ice thickness categories, and zero-layer thermodynamics. The model evaluation is focused on the mean state of the key variables of ice concentration, thickness, velocity, and albedo. The model shows good agreement with observational data sets. The variability of the ice forced by the North Atlantic Oscillation is also found to agree with observations.

Impact of land cover changes on the South African climate

The Joint UK Land Environmental Simulator (JULES) was run offline to investigate the sensitivity of land surface type changes over South Africa. Sensitivity tests were made in idealised experiments where the actual land surface cover is replaced by a single homogeneous surface type. The vegetation surface types on which some of the experiments were made are static. Experimental tests were evaluated against the control. The model results show among others that the change of the surface cover results in changes of other variables such as soil moisture, albedo, net radiation and etc. These changes are also visible in the spin up process. The model shows different surfaces spinning up at different cycles. Because JULES is the land surface model of Unified Model, the results could be more physically meaningful if it is coupled to the Unified Model.

Translating climate forecasts into agricultural terms: advances and challenges

Seasonal climate prediction offers the potential to anticipate variations in crop production early enough to adjust critical decisions. Until recently, interest in exploiting seasonal forecasts from dynamic climate models (e.g. general circulation models, GCMs) for applications that involve crop simulation models has been hampered by the difference in spatial and temporal scale of GCMs and crop models, and by the dynamic, nonlinear relationship between meteorological variables and crop response. Although GCMs simulate the atmosphere on a sub-daily time step, their coarse spatial resolution and resulting distortion of day-to-day variability limits the use of their daily output. Crop models have used daily GCM output with some success by either calibrating simulated yields or correcting the daily rainfall output of the GCM to approximate the statistical properties of historic observations. Stochastic weather generators are used to disaggregate seasonal forecasts either by adjusting input parameters in a manner that captures the predictable components of climate, or by constraining synthetic weather sequences to match predicted values. Predicting crop yields, simulated with historic weather data, as a statistical function of seasonal climatic predictors, eliminates the need for daily weather data conditioned on the forecast, but must often address poor statistical properties of the crop-climate relationship. Most of the work on using crop simulation with seasonal climate forecasts has employed historic analogs based on categorical ENSO indices. Other methods based on classification of predictors or weather types can provide daily weather inputs to crop models conditioned on forecasts. Advances in climate-based crop forecasting in the coming decade are likely to include more robust evaluation of the methods reviewed here, dynamically embedding crop models within climate models to account for crop influence on regional climate, enhanced use of remote sensing, and research in the emerging area of 'weather within climate'.

Translating climate forecasts into agricultural terms: advances and challenges

Seasonal climate prediction offers the potential to anticipate variations in crop production early enough to adjust critical decisions. Until recently, interest in exploiting seasonal forecasts from dynamic climate models (e.g. general circulation models, GCMs) for applications that involve crop simulation models has been hampered by the difference in spatial and temporal scale of GCMs and crop models, and by the dynamic, nonlinear relationship between meteorological variables and crop response. Although GCMs simulate the atmosphere on a sub-daily time step, their coarse spatial resolution and resulting distortion of day-to-day variability limits the use of their daily output. Crop models have used daily GCM output with some success by either calibrating simulated yields or correcting the daily rainfall output of the GCM to approximate the statistical properties of historic observations. Stochastic weather generators are used to disaggregate seasonal forecasts either by adjusting input parameters in a manner that captures the predictable components of climate, or by constraining synthetic weather sequences to match predicted values. Predicting crop yields, simulated with historic weather data, as a statistical function of seasonal climatic predictors, eliminates the need for daily weather data conditioned on the forecast, but must often address poor statistical properties of the crop-climate relationship. Most of the work on using crop simulation with seasonal climate forecasts has employed historic analogs based on categorical ENSO indices. Other methods based on classification of predictors or weather types can provide daily weather inputs to crop models conditioned on forecasts. Advances in climate-based crop forecasting in the coming decade are likely to include more robust evaluation of the methods reviewed here, dynamically embedding crop models within climate models to account for crop influence on regional climate, enhanced use of remote sensing, and research in the emerging area of 'weather within climate'.

Conserving marginal populations of the foodplant (Impatiens noli-tangere) of an endangered moth (Eustroma reticulatum) in a changing climate

Impatiens noli-tangere is scarce in the UK and probably only native to the Lake District and Wales. It is the sole food plant for the endangered moth Eustroma reticulattum. Significant annual fluctuations in the size of I. noli-tangere populations endanger the continued presence of E. reticulatum in the UK. In this study, variation in population size was monitored across native populations of L noli-tangere in the English Lake District and Wales. In 1998, there was a crash in the population size of all metapopulations in the Lake District but not of those found in Wales. A molecular survey of the genetic affinities of samples in 1999 from both regions and a reference population from Switzerland was performed using AFLP and ISSR analyses. The consensus UPGMA dendrogram and a PCO scatter plot revealed clear differentiation between the populations of L noli-tangere in Wales and those in the Lake District. Most of the genetic variation in the UK (H-T= 0.064) was partitioned between (G(ST) = 0.455) rather than within (H-S = 0.034) regions, inferring little gene flow occurs between regions. There was similar bias towards differentiation between metapopulations in Wales, again consistent with low levels of interpopulation gene flow. This contrasts with far lower levels of differentiation in the Lake District which suggests modest rates of gene flow may occur between populations. It is concluded that in the event of local extinction of sites or populations, reintroductions should be restricted to samples collected from the same region. We then surveyed climatic variables to identify those most likely to cause local extinctions. Climatic correlates of population size were sought from two Lake District metapopulations situated close to a meteorological station. A combination of three climatic variables common to both sites explained 81-84% of the variation in plant number between 1990 and 2001. Projected trends for these climatic variables were used in a Monte Carlo simulation which suggested an increased risk of I. noli-tangere population crashes by 2050 at Coniston Water. but not at Derwentwater. Implications of these findings for practical conservation strategies are explored. (C) 2003 Elsevier Ltd. All rights reserved.

The Namib Sand Sea digital database of aeolian dunes and key forcing variables

A new digital atlas of the geomorphology of the Namib Sand Sea in southern Africa has been developed. This atlas incorporates a number of databases including a digital elevation model (ASTER and SRTM) and other remote sensing databases that cover climate (ERA-40) and vegetation (PAL and GIMMS). A map of dune types in the Namib Sand Sea has been derived from Landsat and CNES/SPOT imagery. The atlas also includes a collation of geochronometric dates, largely derived from luminescence techniques, and a bibliographic survey of the research literature on the geomorphology of the Namib dune system. Together these databases provide valuable information that can be used as a starting point for tackling important questions about the development of the Namib and other sand seas in the past, present and future.

Cosmic rays, clouds, and climate

It has been proposed that Earth's climate could be affected by changes in cloudiness caused by variations in the intensity of galactic cosmic rays in the atmosphere. This proposal stems from an observed correlation between cosmic ray intensity and Earth's average cloud cover over the course of one solar cycle. Some scientists question the reliability of the observations, whereas others, who accept them as reliable, suggest that the correlation may be caused by other physical phenomena with decadal periods or by a response to volcanic activity or El Niño. Nevertheless, the observation has raised the intriguing possibility that a cosmic ray–cloud interaction may help explain how a relatively small change in solar output can produce much larger changes in Earth's climate. Physical mechanisms have been proposed to explain how cosmic rays could affect clouds, but they need to be investigated further if the observation is to become more than just another correlation among geophysical variables.

A sensitivity study for water availability in the Northern Caucasus based on climate projections

A strong climatic warming is currently observed in the Caucasus mountains, which has profound impact on runoff generation in the glaciated Glavny (Main) Range and on water availability in the whole region. To assess future changes in the hydrological cycle, the output of a general circulation model was downscaled statistically. For the 21st century, a further warming by 4–7 °C and a slight precipitation increase is predicted. Measured and simulated meteorological variables were used as input into a runoff model to transfer climate signals into a hydrological response under both present and future climate forcings. Runoff scenarios for the mid and the end of the 21st century were generated for different steps of deglaciation. The results show a satisfactory model performance for periods with observed runoff. Future water availability strongly depends on the velocity of glacier retreat. In a first phase, a surplus of water will increase flood risk in hot years and after continuing glacier reduction, annual runoff will again approximate current values. However, the seasonal distribution of streamflow will change towards runoff increase in spring and lower flows in summer.