Progress and challenges in freshwater conservation planning

• 1. Freshwater ecosystems and their associated biota are among the most endangered in the world. This, combined with escalating human pressure on water resources, demands that urgent measures be taken to conserve freshwater ecosystems and the services they provide. Systematic conservation planning provides a strategic and scientifically defensible framework for doing this.
• 2. Pioneered in the terrestrial realm, there has been some scepticism associated with the applicability of systematic approaches to freshwater conservation planning. Recent studies, however, indicate that it is possible to apply overarching systematic conservation planning goals to the freshwater realm although the specific methods for achieving these will differ, particularly in relation to the strong connectivity inherent to most freshwater systems.
• 3. Progress has been made in establishing surrogates that depict freshwater biodiversity and ecological integrity, developing complementarity‐based algorithms that incorporate directional connectivity, and designing freshwater conservation area networks that take cognizance of both connectivity and implementation practicalities.
• 4. Key research priorities include increased impetus on planning for non‐riverine freshwater systems; evaluating the effectiveness of freshwater biodiversity surrogates; establishing scientifically defensible conservation targets; developing complementarity‐based algorithms that simultaneously consider connectivity issues for both lentic and lotic water bodies; developing integrated conservation plans across freshwater, terrestrial and marine realms; incorporating uncertainty and dynamic threats into freshwater conservation planning; collection and collation of scale‐appropriate primary data; and building an evidence‐base to support improved implementation of freshwater conservation plans.

Copyright © 2008 John Wiley & Sons, Ltd.     

Yield response of sugar beets to water stress under Western European conditions

The average yield of sugar beet has almost doubled within the last 30 years. With the raise in average yields and the increase in sensitivity to water stress of sugar beets, the yield response factor (Ky) derived by Doorenbos and Kassam (1979) needs an update. In this article, the soil water balance model BUDGET (Raes et al., 2006) was calibrated and validated to obtain correct estimations of the evapotranspiration deficit (1 − ETa/ETc, where ETa = actual crop evapotranspiration and ETc = maximum crop evapotranspiration under standard conditions) of sugar beets in two locations in France. Datasets of observed soil water contents of several years and different irrigation treatments were used. The simulated evapotranspiration deficits and observed yields were used to derive a seasonal Ky. The obtained linear and polynomial yield response relation between observed yield decline and evapotranspiration deficit showed a high goodness-of-fit. The coefficient of determination (R²) = 0.83, the Nash-Sutcliffe efficiency (EF) = 0.79, the relative root mean squared error (RRMSE) = 0.26 for linear; the coefficient of determination (R²) = 0.85, the Nash-Sutcliffe efficiency (EF) = 0.79, the relative root mean squared error (RRMSE) = 0.25 for polynomial). The results suggested a more pronounced response of sugar beet to water stress in Europe as compared to the values previously reported by Doorenbos and Kassam (1979). The comparison between the observed and simulated yields (with the updated Ky) for another site in France confirmed the findings.     

Turbine entrainment and passage of potadromous fish through hydropower dams: Developing conceptual frameworks and metrics for moving beyond turbine passage mortality

Potadromous fishes are vulnerable to involuntary entrainment through hydropower turbines. However, turbines can also provide a downstream passage route for potadromous fish. Here, we review evidence for turbine entrainment and passage in potadromous fish, and evaluate the effects of these processes on upstream and downstream populations. We develop conceptual frameworks and metrics to quantify vulnerability to turbine entrainment removals, and to quantify the efficiency of turbines as a downstream passage route. We highlight factors that influence these processes and provide case‐studies demonstrating their applicability. We found that juvenile potadromous fish are being entrained through turbines at rates high enough to impact upstream populations. Given that juvenile passage survival is often high, we argue that turbines provide an important downstream passage route for potadromous fish. We show that entrainment vulnerability is likely a function of interactions between in‐reservoir fish behaviour, habitat configuration and operations and thus not well captured by passage mortality estimates. Similarly, we show that while passage mortality can limit downstream passage efficiency, passage success is also dependent on reservoir and forebay navigation, along with survival and fitness in the downstream river. We advocate for a shift in focus away from estimates of passage mortality and injury, which have previously accounted for the majority of turbine passage research. Instead, we recommend an approach that focusses on quantification of the factors that influence downstream passage efficiency and entrainment vulnerability. Moreover, we highlight the need to better understand the broader scale impacts of these events on upstream and downstream populations.     

Mobile and readily available C and N fractions and their relationship to microbial biomass and selected enzyme activities in a sandy soil under different management systems

Within different land‐use systems such as agriculture, forestry, and fallow, the different morphology and physiology of the plants, together with their specific management, lead to a system‐typical set of ecological conditions in the soil. The response of total, mobile, and easily available C and N fractions, microbial biomass, and enzyme activities involved in C and N cycling to different soil management was investigated in a sandy soil at a field study at Riesa, Northeastern Germany. The management systems included agricultural management (AM), succession fallow (SF), and forest management (FM). Samples of the mineral soil (0—5, 5—10, and 10—30 cm) were taken in spring 1999 and analyzed for their contents on organic C, total N, NH₄⁺‐N and NO₃^—‐N, KCl‐extractable organic C and N fractions (Corg_(KCl) and Norg_(KCl)), microbial biomass C and N, and activities of β‐glucosidase and L‐asparaginase. With the exception of Norg_(KCl), all investigated C and N pools showed a clear relationship to the land‐use system that was most pronounced in the 0—5 cm profile increment. SF resulted in greater contents of readily available C (Corg_(KCl)), NH₄⁺‐N, microbial biomass C and N, and enzyme activities in the uppermost 5 cm of the soil compared to all other systems studied. These differences were significant at P ≤ 0.05 to P ≤ 0.001. Comparably high C_mic:C_org ratios of 2.4 to 3.9 % in the SF plot imply a faster C and N turnover than in AM and FM plots. Forest management led to 1.5‐ to 2‐fold larger organic C contents compared to SF and AM plots, respectively. High organic C contents were coupled with low microbial biomass C (78 μg g^—1) and N contents (10.7 μg g^—1), extremely low C_mic : C_org ratios (0.2—0.6 %) and low β‐glucosidase (81 μg PN g^—1 h^—1) and L‐asparaginase (7.3 μg NH₄‐N g^—1 2 h^—1) activities. These results indicate a severe inhibition of mineralization processes in soils under locust stands. Under agricultural management, chemical and biological parameters expressed medium values with exception for NO₃^—‐N contents which were significantly higher than in SF and FM plots (P ≤ 0.005) and increased with increasing soil depth. Nevertheless, the depth gradient found for all studied parameters was most pronounced in soils under SF. Microbial biomass C and N were correlated to β‐glucosidase and L‐asparaginase activity (r ≥ 0.63; P ≤ 0.001). Furthermore, microbial biomass and enzyme activities were related to the amounts of readily mineralizable organic C (i.e. Corg_(KCl)) with r ≥ 0.41 (P ≤ 0.01), suggesting that (1) KCl‐extractable organic C compounds from field‐fresh prepared soils represent an important C source for soil microbial populations, and (2) that microbial biomass is an important source for enzymes in soil. The Norg_(KCl) pool is not necessarily related to the size of microbial biomass C and N and enzyme activities in soil.<?show $6#>     

Model calculations of water dynamics in lysimeters filled with granular industrial wastes

A three‐year long lysimeter experiment with a fine‐grained aluminum (Al) recycling by‐product and a mixture of this by‐product and a coal combustion waste was conducted. The wastes were proposed as possible soil substitutes in an engineered surface barrier covering a potash mining residue mount. To evaluate the suitability of the wastes as surface barrier material, their hydrological behavior under field conditions must be known. Lysimeter experiments provide one means to study the hydrological behavior of soils or soil‐like materials. However, it is difficult to estimate the long‐term hydrological behavior from short‐term lysimeter studies. The present study was conducted therefore to derive from short‐term lysimeter observations the long‐term hydrological behavior of the two waste materials. The lysimeter data were used to calibrate the one‐dimensional soil water flow model HYDRUS‐1D. With the calibrated model, hydrological simulations for the site of the residue mount were carried out for a period of 31 yr. Calculated long‐term annual seepage from the lysimeters was 237 mm for the pure Al waste and 186 mm for the mixture, or 39% and 24% of the average annual precipitation (764 mm). The average discharge of the bare mount is 482 mm or 63%. We conclude that a soil cover could considerably reduce the discharge and that the mixture is better suited as surface barrier than the pure Al waste.     

Pollen characteristics and stigma receptivity for <Emphasis Type="Italic">Anemone coronaria</Emphasis> L.

To obtain crossing products, an efficient pollination and subsequent fertilization is essential. This efficient pollination is achieved by pollen germination and tube growth. Here, these pollen characteristics of 2 genetically differentiating cultivars of Anemone coronaria L. were investigated in vitro. For the essential components boron, calcium and an osmoticant, only calcium showed to be crucial for pollen germination. Boron concentrations influenced the pollen tube length with a concentration of 100 mg l^?1 H₃BO₃ resulting in the longest pollen tubes. For the osmoticant sucrose, a concentration of 100 g l^?1 caused a significant positive effect on both pollen germination and pollen tube length for the 2 cultivars. The cultivars reacted similarly with respect to the investigated compounds. Next to this, the pollen development was correlated with 8 different flower stages in A. coronaria. As a final point, the germination of an optimized pollen germination medium was compared with in vivo pollen germination in cross-pollinations within the same cultivar (identified by aniline blue staining). For ‘Mistral Wine’, pollen germination percentage was lower in vitro than in vivo, while ‘Wicabri Blue’ pollen showed no significant difference in germination rates in vivo and in vitro. To achieve fertilization a following requisite is that the stigma is receptive. To study this, the most receptive female flower stage of the 8 different flower stages for A. coronaria was characterized by aniline blue staining. A. coronaria clearly showed protogyny.     

A data-driven fuzzy approach to simulate the critical shear stress of mixed cohesive/non-cohesive sediments

Purpose

The critical shear stress of cohesive and mixed cohesive/non-cohesive sediments is affected by multiple interacting physical, chemical and biological parameters. There are various mathematical approaches in the scientific literature for computing critical shear stress. However, processes that influence sediment stability are still not fully understood, and available formulas differ considerably. These discrepancies in the literature arise from random system behaviour (natural variability of the sediments), different definitions of the critical shear stress, different measurement techniques and different model frameworks (scope of the parameters, undisturbed versus artificial sediment samples). While analytical approaches fail to address the involved uncertainties, fuzzy logic-based models integrate uncertainty and imprecision.

Materials and methods

With this in mind, a data-driven neuro-fuzzy model (ANFIS) was used to determine the critical shear stress based on sediment characteristics such as wet bulk density and grain size distribution. In order to select model predictors systematically, an automated stepwise regression algorithm was applied. The database for this analysis consisted of 447 measurements of the critical shear stress originating from 64 undisturbed sediment samples.

Results and discussion

The study identified clay content as the primarily controlling variable for erosion resistance. Depending on the characteristics of the sampling location, the bulk density was also selected as a model predictor. In comparison to analytical models that are available in the scientific literature, the fuzzy model achieved higher correlation coefficients between measured and predicted data.

Conclusions

The neuro-fuzzy-model includes uncertainties of input variables and their interactions directly. Thus, it provides a reliable method for the prediction of erosion thresholds of cohesive/non-cohesive mixtures. It was also shown that this approach requires fewer measured variables as well as fewer assumptions than the models it was compared to.

     

Crop height variability detection in a single field by multi-temporal terrestrial laser scanning

Information on crop height, crop growth and biomass distribution is important for crop management and environmental modelling. For the determination of these parameters, terrestrial laser scanning in combination with real-time kinematic GPS (RTK–GPS) measurements was conducted in a multi-temporal approach in two consecutive years within a single field. Therefore, a time-of-flight laser scanner was mounted on a tripod. For georeferencing of the point clouds, all eight to nine positions of the laser scanner and several reflective targets were measured by RTK–GPS. The surveys were carried out three to four times during the growing periods of 2008 (sugar-beet) and 2009 (mainly winter barley). Crop surface models were established for every survey date with a horizontal resolution of 1 m, which can be used to derive maps of plant height and plant growth. The detected crop heights were consistent with observations from panoramic images and manual measurements (R² = 0.53, RMSE = 0.1 m). Topographic and soil parameters were used for statistical analysis of the detected variability of crop height and significant correlations were found. Regression analysis (R² < 0.31) emphasized the uncertainty of basic relations between the selected parameters and crop height variability within one field. Likewise, these patterns compared with the normalized difference vegetation index (NDVI) derived from satellite imagery show only minor significant correlations (r < 0.44).     

Emerging viral zoonoses: frameworks for spatial and spatiotemporal risk assessment and resource planning

Spatial epidemiological tools are increasingly being applied to emerging viral zoonoses (EVZ), partly because of improving analytical methods and technologies for data capture and management, and partly because the demand is growing for more objective ways of allocating limited resources in the face of the emerging threat posed by these diseases. This review documents applications of geographical information systems (GIS), remote sensing (RS) and spatially-explicit statistical and mathematical models to epidemiological studies of EVZ.Landscape epidemiology uses statistical associations between environmental variables and diseases to study and predict their spatial distributions. Phylogeography augments epidemiological knowledge by studying the evolution of viral genetics through space and time. Cluster detection and early warning systems assist surveillance and can permit timely interventions. Advanced statistical models can accommodate spatial dependence present in epidemiological datasets and can permit assessment of uncertainties in disease data and predictions. Mathematical models are particularly useful for testing and comparing alternative control strategies, whereas spatial decision-support systems integrate a variety of spatial epidemiological tools to facilitate widespread dissemination and interpretation of disease data. Improved spatial data collection systems and greater practical application of spatial epidemiological tools should be applied in real-world scenarios.