Habitat Use by Nekton along a Stream-Order Gradient in a Louisiana Estuary

We examined patterns of habitat use by fishes and decapod crustaceans in a seemingly pristine tidal stream system that drains into southeastern coastal Louisiana, northern Gulf of Mexico. The study area centered on a relatively unaltered mesohaline saltmarsh nested within more heavily degraded conditions. Monthly sampling (February–November 2004) stratified along a stream-order gradient examined changes in nekton abundance, species richness, and community structure. Analyses were based on a microhabitat approach used to characterize nekton responses to spatial gradients of water depth, temperature, dissolved oxygen, salinity, turbidity, bottom slope, stream width, and distance to mouth. Thirty taxa were identified from 3,757 individuals collected in 82 seine samples. Seven fishes and three decapods constituted >95% of the community structure. Analyses detected the effects of stream order on fish community structure and associated environmental variables. Spatial differences of environmental variables across stream order were attributed to the geomorphology and hydrology of the study area. A factor analysis resolved eight environmental variables into four orthogonal axes that explained 80% of environmental variation. We interpreted factor 1 as a stream-order axis, factor 2 as a morphological axis, factor 3 as a seasonal axis, and factor 4 as a salinity axis. Differences in use of four-dimensional factor space by dominant species reflected habitat selection and species residency status.     

Analysis of physical factors of climate and bioclimate and their effects on almonds production to increase the economy in Hebron area of Palestine

For the 1993–2009 period, we analyzed the relationship between almond yield and three climatic variables (mean annual temperature, soil water reserve, and precipitation), and four bioclimatic variables (annual ombrothermic index, water deficit, simple continentality index, and compensated thermicity index), for one major Hebron crop (soft and hard almonds). Moreover, we obtained data almond production from the Palestinian Central Bureau of Statistics, while the climate data from the Palestinian meteorological station during the study period from 1993 to 2009, and analysis is it by using bioclimatic classification of the Earth of Salvador Rivas-Martinez to study the relationship between the almond yield and climate and bioclimate factors (variables). The climatic and bioclimate variables of greatest importance to almond were used to develop regressions analysis relating yield to climatic conditions. Hebron was positively affected by annual ombrothermic index, simple continentality index, precipitation, water soil reserve, and mean annual temperature, but negatively affected by water deficit, with a large proportion of the variance explained by axis F1 (72.48%), F2 (22.38%), and axes F1and F2 (94. 86%). However, in order to produce a high amount of almonds and quality, it can be grown in the regions of the mesomediterranean region, with the value of annual ombrothemic index more than 3, compensated thermicity index between 220/220 to 350/350, simple continentality index between 14 and 20, and in areas where the average annual temperature is between 15 and 20 °C.     

Impacts of climate change on groundwater in Australia: a sensitivity analysis of recharge

Groundwater recharge is a complex process reflecting many interactions between climate, vegetation and soils. Climate change will impact upon groundwater recharge but it is not clear which climate variables have the greatest influence over recharge. This study used a sensitivity analysis of climate variables using a modified version of WAVES, a soil-vegetation-atmosphere-transfer model (unsaturated zone), to determine the importance of each climate variable in the change in groundwater recharge for three points in Australia. This study found that change in recharge is most sensitive to change in rainfall. Increases in temperature and changes in rainfall intensity also led to significant changes in recharge. Although not as significant as other climate variables, some changes in recharge were observed due to changes in solar radiation and carbon dioxide concentration. When these variables were altered simultaneously, changes in recharge appeared to be closely related to changes in rainfall; however, in nearly all cases, recharge was greater than would have been predicted if only rainfall had been considered. These findings have implications for how recharge is projected to change due to climate change.     

Reconstruction of Holocene sea-surface salinity in the Skagerrak–Kattegat: a climatic and environmental record of Scandinavia

Holocene sea-surface salinity in the Skagerrak–Kattegat is reconstructed using weighted averaging regression and calibration (WA) of diatom data from core Skagen 3. Diatom data from surface sediments together with 10-yr mean values of salinity and water temperature were used as a modern training set. Canonical correspondence analysis (CCA) was used to identify statistically significant directions of variation within the training set. The results of forward selection of the environmental variables and associated Monte Carlo permutation tests of the statistical significance of each variable, the canonical coefficients, and the intraset correlations of the environmental variables with the CCA axes suggest that summer and winter sea-surface salinities (SSS, WSS) are potentially reconstructable from fossil diatom assemblages. The changes in sea-surface salinity during the Holocene can be correlated with changes in climate of the circum-Baltic area, the current patterns of the Skagerrak–Kattegat, and the development of the Baltic Sea. Generally low SSS and large differences between WSS and SSS (ΔSw-s) during 9000–6000 yr BP might have resulted from a climate with higher precipitation than today in the circum-Baltic area and its catchment, or a climate with maximum precipitation in late spring or early summer. The mechanism behind these patterns may be the combination of the northward shift of the jet stream and a stronger surface westerly penetration into the continent caused by a reduced latitudinal insolation gradient and enhanced land–sea contrast in the early to middle Holocene. It was, however, complicated by local events such as changes in the strength of various currents in the Skagerrak–Kattegat, successions of Baltic brackish and freshwater phases, and hydrodynamic conditions in the circum-Baltic area. © 1998 John Wiley & Sons, Ltd.     

Climate change impacts on water demand and availability using CMIP5 models in the Jaguaribe basin,semi-arid Brazil

The objective of this study was to analyze climate change impacts on irrigation water demand and availability in the Jaguaribe River basin, Brazil. For northeastern Brazil, five global circulation models were selected using a rainfall seasonal evaluation screening technique from the Intergovernmental Panel on Climate Change named Coupled Model Intercomparison Project Phase 5. The climate variables were generated for the base period of 1971–2000, as were projections for the 2025–2055 future time slice. Removal of maximum and minimum temperature and rainfall output bias was used to estimate reference evapotranspiration, irrigation water needs, and river flow using the rainfall—river flow hydrological model Soil Moisture Accounting Procedure for the baseline and future climate (Representative Concentration Pathways 4.5 and 8.5 scenarios). In addition, by applying improved irrigation efficiency, a scenario was evaluated in comparison with field observed performance. The water-deficit index was used as a water availability performance indicator. Future climate projections by all five models resulted in increases in future reference evapotranspiration (2.3–6.3%) and irrigation water needs (2.8–16.7%) for all scenarios. Regarding rainfall projections, both positive (4.8–12.5%) and negative (??2.3 to ??15.2%) signals were observed. Most models and scenarios project that annual river flow will decrease. Lower future water availability was detected by the less positive water-deficit index. Improved irrigation efficiency is a key measure for the adaptation to higher future levels of water demand, as climate change impacts could be compensated by gains in irrigation efficiency (water demand changes varying from ??1.7 to ??35.2%).     

Mollusc assemblages in palaeoecological reconstructions: an investigation of their predictive power using transfer function models

Horsák, M. 2010: Mollusc assemblages in palaeoecological reconstructions: an investigation of their predictive power using transfer function models. Boreas, Vol. 40, pp. 459–467. 10.1111/j.1502‐3885.2010.00195.x. ISSN 0300‐9483. Fossil mollusc assemblages are commonly used to reconstruct past environments, as their shells are abundant in various types of calcium‐rich deposits. However, it is impossible to exactly evaluate estimates derived from fossil data using directly measured factors. To assess the accuracy of environmental variables derived from mollusc species composition, two modern data sets (training and test), each consisting of 73 samples of treeless fen communities, were constructed along with known local and climatic variables. The main predictors of species composition were isolated using canonical correspondence analysis and forward selection with the Monte Carlo permutation test. The accuracy of prediction for those factors that were significant in the forward selection was studied via four commonly used transfer function models. Three independent gradients of species composition driven by calcium content, moisture and temperature were detected. The best predictions were found for variables that correlated with the main changes in species composition. The strongest correlation between the predicted and measured values of the test data set was observed for water conductivity (r=0.86), a good proxy of calcium content. The locally weighted–weighted averaging transfer function model performed best out of all the models for the majority of variables tested. Mollusc assemblages were found to be useful for estimating local environmental variables based on a given species composition. Along with the specific advantages of mollusc fossil material, there is much potential for the use of their fossil assemblages to reconstruct palaeoenvironmental variables using transfer function models calibrated from recent compositional data and directly measured factors.     

Assessing the impact of future climate change on groundwater recharge in Galicia-Costa, Spain

Climate change can impact the hydrological processes of a watershed and may result in problems with future water supply for large sections of the population. Results from the FP5 PRUDENCE project suggest significant changes in temperature and precipitation over Europe. In this study, the Soil and Water Assessment Tool (SWAT) model was used to assess the potential impacts of climate change on groundwater recharge in the hydrological district of Galicia-Costa, Spain. Climate projections from two general circulation models and eight different regional climate models were used for the assessment and two climate-change scenarios were evaluated. Calibration and validation of the model were performed using a daily time-step in four representative catchments in the district. The effects on modeled mean annual groundwater recharge are small, partly due to the greater stomatal efficiency of plants in response to increased CO₂ concentration. However, climate change strongly influences the temporal variability of modeled groundwater recharge. Recharge may concentrate in the winter season and dramatically decrease in the summer–autumn season. As a result, the dry-season duration may be increased on average by almost 30 % for the A2 emission scenario, exacerbating the current problems in water supply.     

全新世中期中国气候和东亚季风:PMIP4模式结果

利用国际古气候模拟比较计划(PMIP)最新第四阶段(PMIP4)中14个气候模式的试验数据,集中研究了距今约6 000年的全新世中期中国气候和东亚季风。与早期PMIP第三阶段(PMIP3)多模式结果类似,全新世中期中国年、冬季和春季地表气温较工业革命前期偏冷,而夏季和秋季偏暖,其中年和冬季模拟偏冷与大部分地质记录显示的偏暖不符;所有14个PMIP4模式集合的中国区域平均年和季节温度变化绝对值为0.08~1.69 ℃,较PMIP3多模式平均结果额外偏小0.01~0.45 ℃,这部分源于大气二氧化碳浓度的减少。在用于分析的11个PMIP4模式平均结果中,全新世中期中国年平均降水、蒸发和有效降水(即降水量减蒸发量)相对于工业革命前期分别增加2%、减少1%和增加7%,所有3个物理量在季节上均表现为冬春季减少,夏秋季增加。对比PMIP4模式和PMIP3多模式平均结果,上述3个物理量的中国区域平均值和区域变化差异均在夏、秋季大于年和冬、春季;相比于PMIP3模式,PMIP4模式模拟的年有效降水变化与地质记录更为接近。全新世中期东亚冬、夏季风在14个PMIP4模式中均模拟加强,所有模式平均较工业革命前期分别增强11%和32%;在区域尺度上,与早期PMIP3模式相比,当前PMIP4模式模拟的季风环流增强幅度在东亚北部更强,南部偏弱。     

The influence of climate on mechanistic pathways that affect lower food web production in Northern San Francisco Bay estuary

Significant coherence among time series of environmental and biological production variables suggested mechanistic pathways through which climate contributed to the downward shift in estuarine production (biomass) in northern San Francisco Bay estuary, 1975–1993. Climate directly and indirectly affected physical processes in the estuary through precipitation and its subsequent impact on streamflow and physical variables affected by streamflow. Climate also directly influenced air temperature and wind velocity. The influence if climate was evaluated through a climate index based on sea level pressure. A shift in this climate index in the early 1980s coincided with changes in many environmental variables including water transparency, water temperature, wind velocity, and rainfall. These physical changes were accompanied by a decrease in diatom, total zooplankton, andNeomysis mercedis carbon at the base of the food web throughout the estuary. Box-Jenkins time series coherence analysis was used to quantify associations among these physical, chemical, and biological time series for nine regions of the estuary. These associations were used to develop a conceptual model of mechanistic pathways that directly linked food web carbon production to climate. Strong coherence among diatom, zooplankton, andN. mercedis carbon time series suggested climate also had an indirect impact on food web production through trophic cascade. Differing mechanistic pathways among the nine regions of the estuary suggested climate was an important contributor to the spatial variability in total food web production and trophic structure.     

Review: Regional groundwater flow modeling in heavily irrigated basins of selected states in the western United States

Water resources in agriculture-dominated basins of the arid western United States are stressed due to long-term impacts from pumping. A review of 88 regional groundwater-flow modeling applications from seven intensively irrigated western states (Arizona, California, Colorado, Idaho, Kansas, Nebraska and Texas) was conducted to provide hydrogeologists, modelers, water managers, and decision makers insight about past modeling studies that will aid future model development. Groundwater models were classified into three types: resource evaluation models (39 %), which quantify water budgets and act as preliminary models intended to be updated later, or constitute re-calibrations of older models; management/planning models (55 %), used to explore and identify management plans based on the response of the groundwater system to water-development or climate scenarios, sometimes under water-use constraints; and water rights models (7 %), used to make water administration decisions based on model output and to quantify water shortages incurred by water users or climate changes. Results for 27 model characteristics are summarized by state and model type, and important comparisons and contrasts are highlighted. Consideration of modeling uncertainty and the management focus toward sustainability, adaptive management and resilience are discussed, and future modeling recommendations, in light of the reviewed models and other published works, are presented.     

Environmental fragility evaluation and guidelines for environmental zoning: a study case on Ibiuna (the Southeastern Brazilian region)

Environmental fragility models are important decision tools for policy makers as they help quantify environmental sensitivity and understand the relationship between human activities and environmental quality. The objective of this study was to evaluate three different environmental fragility models within the Brazilian rainforest region and to use the results to develop environmental zone classes. Two rural river basins located in Ibiuna, Sao Paulo state, Brazil, were studied. Input variables, including slope class, relief dissection rate, soil class, lithology, land cover, and climate data, were used to compute environmental fragility classes using three standard models. The model outputs were evaluated on their ability to accurately predict the most sensitive and least sensitive areas. The best models for each region were used to derive environmental zoning maps, including restoration priorities, best regions for agriculture, and areas with high needs for soil management. These maps will help support land use strategies for environmental restoration. This study provides insight into territorial ordering and management of environmental services with a regional perspective.     

Evaluating the accuracy of ANN and LR models to estimate the water quality in Zarivar International Wetland,Iran

One of the most important qualitative aspects of wetland ecosystem management is preserving the natural quality of water in such environments. This would not be achievable unless continuous water quality monitoring is implemented. With the recent advances in remote sensing technology, this technology could assist us to produce accurate models for estimating water quality variables in the ecosystem of wetlands. The present study was carried out to evaluate the capability of remote sensing data to estimate the water quality variables [pH, total suspended solids (TSS), total dissolved solids (TDS), turbidity, nitrate, sulfate, phosphate, chloride and the concentration of chlorophyll a] in Zarivar International Wetland using linear regression (LR) and artificial neural network (ANN) models. For this purpose, spectral reflectance of bands 2, 3, 4 and 5 of the OLI sensor of Landsat 8 was utilized as the input data and the collected chemical and physical data of water samples were selected as the objective data for both ANN and LR models. Based on our results overall, ANN model was the proper model compared with LR model. The spectral reflectance in bands 5 and 4 of OLI sensor revealed the best results to estimate TDS, TSS, turbidity and chlorophyll in comparison with other used bands in ANN model, respectively. We conclude that OLI sensor data are an excellent means for studying physical properties of water quality and comparing its chemical properties.     

Phytoplankton, nutrients, and transparency in Danish coastal waters

We present a comparative analysis of 1400 data series of water chemistry (particularly nitrogen and phosphorus concentrations), phytoplankton biomass as chlorophylla (chla) concentrations, concentrations of suspended matter and Secchi depth transparency collected from the mid-1980s to the mid-1990s from 162 stations in 27 Danish fjords and coastal waters. The results demonstrate that Danish coastal waters were heavily eutrophied and had high particle concentrations and turbid waters. Median values were 5.1 μg chla 1⁻¹, 10.0 mg DW 1⁻¹ of suspended particles, and Secchi depth of 3.6 m. Chlorophyll concentration was strongly linked to the total-nitrogen concentration. The strength of this relationship increased from spring to summer as the concentration of total nitrogen declined. During summer, total nitrogen concentrations accounted for about 60% of the variability in chlorophyll concentrations among the different coastal systems. The relationship between chlorophyll and total phosphorus was more consistant over the year and correlations were much weaker than encountered for total nitrogen. Secchi depth could be predicted with good precision from measurements of chlorophyll and suspended matter. In a multiple stepwise regression model with In-transformed values the two variables accounted for most of the variability in water transparency for the different seasons and the period March–October as a whole (c. 80%). We were able to demonstrate a significant relationship between total nitrogen and Secchi depth, with important implications for management purposes.     

The response of fishes to physicochemical changes in the mangroves of northeast Florida Bay

Historically, large volumes of fresh water from the Everglades reached Florida Bay in the form of overland sheet flow. South Florida's extensive canal system has diverted fresh water from its historic course, resulting in shorter hydroperiods and higher salinities than would have occurred in an unaltered system. The mixing zone between the freshwater Everglades and euryhaline Florida Bay is primarily characterized as a dwarf red mangrove forest. The small, demersal fishes found in this habitat are an important food source for a variety of predators and are excellent bioindicators for both short-term and long-term perturbations in the system. I examine the effect of fluctuating water level, salinity, and temperature on this fish community in order to better understand the impact water diversion has had on the ecotone. Fish were collected at four sites within the ecotone over a t-yr period using a 9-m² drop trap. Principal components analysis was used to generate 10 composite variables (PCs) from a temporal array of 59 physicochemical variables. These composite variables were used in regression analyses to evaluate spatial and temporal changes in the fish community. Regression analysis indicated fish density was significantly related to short-term and long-term changes in water level and with long-term temperature variation (r²=0.50). An ANOVA of density between sites supports the regression results, indicating that sites with longer hydroperiod had higher density than sites with shorter hydroperiod. The impact of changes in density on biomass was reflected by regression analysis, which indicated that increased water level and decreased variability in depth were correlated with higher biomass (r²=0.61). Biomass was also influenced by changes in the salinity regime, presumably through increases in individual fish body size or through a shift in the community toward heavier-bodied fish species. An ANOVA of biomass between sites indicates sites with longer freshwater periods had higher biomass than sites with shorer freshwater periods. The first two axes of a detrended correspondence analysis on community biomass explained 59.2% of the variance in the community and supported the hypothesis that salinity was a primary determinant of community structure. These results indicate historic changes in water deliver could have altered the mangrove fish community, thereby lowering prey availability for higher trophic levels.     

Identification of algal blooms based on support vector machine classification in Haizhou Bay, East China Sea

Harmful algal blooms commonly known as red tides have been observed at increasing frequencies, which are causing serious economic and ecologic problems in Haizhou Bay off the eastern coast of China. It is important to study the inducing factors of red tides including a wide variety of environmental variables and the complex interactions between them. This study explores the possibility of predicting the occurrence of red tides using support vector machine (SVM) with environmental variables. Seventeen in situ environmental variables which are known to affect the occurrence of red tides were collected between May and October of 2004–2006. Seven characteristic factors were extracted from these variables via factorial analysis to reduce computation complexity. Three of them are related to nutrients, others are contributed by temperature, oxygen depletion, pH, hydrodynamics, and precipitation, respectively. The classification models based on SVM were constructed to identify the red tides samples using the seven factors as independent variables and radial basis function as the kernel function. The model with the combination parameters of C = 10, γ = 0.7, and ζ = 0.1 has the highest accuracy of 92.06 %. It indicates that the model is highly valuable in predicting the occurrence of red tides by environmental variables in this region for its conservative threshold of surface algae concentration.     

Climate change and groundwater conditions in the Mekong Region–A review

Changes in the climatic system introduce uncertainties in the supply and management of water resources. The Intergovernmental Panel on Climate Change(IPCC) predicts an increase of 2 to 4 °C over the next 100 years. Temperature increases will impact the hydrologic cycle by directly increasing the evaporation of surface water sources. Consequently, changes in precipitation will indirectly impact the flux and storage of water in surface and subsurface reservoirs(i.e., lakes, soil moisture, groundwater, etc.). In addition, increases in temperature contribute to increases in the sea level, which may lead to sea water intrusions, water quality deterioration, potable water shortages, etc. Climate change has direct impacts on the surface water and the control of storage in rivers, lakes and reservoirs, which indirectly controls the groundwater recharge process. The main and direct impact of climate change on groundwater is changes in the volume and distribution of groundwater recharge. The impact of climate change on groundwater resources requires reliable forecasting of changes in the major climatic variables and accurate estimations of groundwater recharge. A number of Global Climate Models(GCMs) are available for understanding climate and projecting climate change.These GCMs can be downscaled to a basin scale, and when they are coupled with relevant hydrological models, the output of these coupled models can be used to quantify the groundwater recharge, which will facilitate the adoption of appropriate adaptation strategies under the impact of climate change.     

Research on Climate Feedback of Human Water Use and Its Impact on Terrestrial Water Cycles —Advances and Challenges

The terrestrial water cycle is the mutual transformation of surface and near-surface water, which controls the supply of fresh water resources. It is affected by human activities, solar radiation and gravity, as well as climate and environmental conditions. Inter-basin water transfer, irrigation, crop cultivation and harvesting, exploitation of groundwater water and other human activities lead to the change of spatial and temporal distribution of soil moisture, the underground water level, surface albedo, surface evaporation, as well as water and energy exchange between land surface and atmosphere. Human water use generates important feedback on the climate and changes the processes of the terrestrial water cycle significantly. The spatial and temporal distribution of precipitation in China is uneven. In addition, human activities further exacerbate the fragility of water resources and the contradiction between supply and demand, posing a serious challenge to the sustainable development of social economy. Therefore, understanding the laws and mechanisms of terrestrial water cycle change is very important for water resources utilization and human sustainable development. From the perspective of climate change and human activities, this paper summarized the impact of human activities on terrestrial water cycle and the progress of climate feedback research. It is urgent to consider the evolution of terrestrial water cycle and its climate under the dual impact of natural and human activities, and develop the large-scale land surface hydrological models and climate models with human water use, crop planting and irrigation, lateral groundwater flow. From the perspective of a fully coupled system, we need quantitatively to assess the climate feedback of human water use and its impact on the terrestrial water cycle process, and to explore its mechanism. We need to distinguish the contribution of human water activities and global climate change to the evolution of terrestrial water cycle in the context of climate change, and to propose water resources management strategies to address climate change.     

Assessing groundwater vulnerability to nitrate pollution using statistical approaches: a case study of Sidi Bouzid shallow aquifer,Central Tunisia

The study region comprises the Sidi Bouzid shallow aquifer, which is located in the western part of Central Tunisia. It is mainly occupied by agricultural land with intensive use of chemical fertilizers especially nitrates. For this reason, nitrate measurement was performed in 38 water samples to evaluate and calibrate the obtained models. Several environmental parameters were analyzed using groundwater nitrate concentrations, and different statistical approaches were applied to assess and validate the groundwater vulnerability to nitrate pollution in the Sidi Bouzid shallow aquifer. Multiple linear regression (MLR), analyses of covariance (ANCOVA), and logistic regression (LR) were carried out for studying the nitrate effects on groundwater pollution. Statistical analyses were used to identify major environmental factors that control the groundwater nitrate concentration in this region. Correlation and statistical analyses were conducted to examine the relationship between the nitrate (dependent variable) and various environmental variables (independent variables). All methods show that “groundwater depth” and “land use” parameters are statistically significant at 95% level of confidence. Groundwater vulnerability map was obtained by overlaying these two thematic layers which were obtained in the GIS environment. It shows that the high vulnerability area coincides with the likelihood that nitrate concentration exceeds 24.5 mg/l in groundwater. The relationship between the groundwater vulnerability classes and the nitrate concentrations provides satisfactory results; it showed an Eta-squared correlation coefficient of 64%. So, the groundwater vulnerability map can be used as a synthetic document for realistic management of groundwater quality.     

Contribution of multivariate statistical techniques in the hydrochemical evaluation of groundwater from the Ouargla phreatic aquifer in Algeria

A hydrochemical evaluation of the hydrogeological surface aquifer of Ouargla was conducted using 17 samples of water. The analysis of the samples focused on the determination of calcium, magnesium, sodium, potassium, chloride, sulfate, bicarbonate, and nitrate, while electrical conductivity, temperature, and pH were measured on the ground. The obtained data are processed by multivariate techniques with a varimax rotation approach after standardization. The chemical data follow four factorial axes that provide a cumulative total variance explained by 67 %. Considering the EC as an additional variable, the matrix components after varimax rotation have identified a first axis related to NaCl, a second axis associated with CaSO₄, a third axis of HCO₃ and a fourth axis of NO₃. These variables control a significant part of the chemistry of the groundwater in the region of Ouargla.