Dynamic assessment of the value of vegetation carbon fixation and oxygen release services in Qinghai Lake basin

Studies on ecosystem service function have an important significance for analyzing and understanding global warming. With the introduction of geographic information system (GIS) and remote sensing (RS) technologies for the evaluation of ecosystem service function, the scope for analysis has been widening. Increasing number of researchers use these technologies to quantify the value of ecosystem service functions and reveal their spatial-temporal variability. By using the data for the interpretation of five RS images and net primary productivity (NPP) in Qinghai Lake basin, we assessed the value of vegetation carbon fixation and oxygen release services and revealed their dynamic variation in this basin. The result suggested that the average values of vegetation carbon fixation and oxygen release services in Qinghai Lake basin between 1987 and 2010 were spatially distributed in a ring shape around the Qinghai Lake and decreased from southeastern to the north and northwestern regions; the northwestern areas had the lowest value. The vegetation carbon fixation value between 1987 and 2010 was on an average 28.87 × 10⁸ yuan/a in Qinghai Lake basin, whereas the oxygen release value was 64.41 × 10⁸ yuan/a. Alpine meadow ecosystem showed the highest value of vegetation carbon fixation and oxygen release services function in Qinghai Lake basin, with average values of 18.28 × 10⁸ yuan/a and 40.79 × 10⁸ yuan/a, respectively, followed by those of temperate steppe and sparse vegetation. The vegetation carbon fixation and oxygen release values in Qinghai Lake basin gradually increased from 1987 to 2010, with the maximum value in 2010. By the end of 2010, the values increased by 7.19 × 10⁸ yuan and 16.04 × 10⁸ yuan, respectively. The values slightly decreased in barren land, lakeside marsh, river valley swamp, and sandy areas, but increased to different degrees in other ecosystems. Among them, the largest increase was noted in alpine meadow (4.38 × 10⁸ yuan and 9.78 × 10⁸ yuan, respectively), followed by those in temperate steppe with increased values of 1.12 × 10⁸ yuan and 2.49 × 10⁸ yuan, respectively.     

The effects of land use change and irrigation water resource on nitrate contamination in shallow groundwater at county scale

The objective of this study was to assess the impacts of land use changes and irrigation water resource on the nitrate contamination in shallow groundwater. 394 water samples were sampled from the same irrigation wells during a period of five years (from 2002 to 2007) in Huantai County in the North China Plain. NO₃-N concentration in irrigation wells was measured. Geostatistical method combined with GIS technique was used to analyze the spatio-temporal distribution of groundwater NO₃-N concentrations in Huantai County. Land use type and irrigation water resource were combined with the variation of NO₃-N concentrations by statistical approach to investigate the relationship between them. The distribution map showed that the percentages of area increased by 13.06%, 14.37%, 12.23% and 3.85% for that had nitrate concentrations of 10–15, 15–20, 20–30 mg L^?1 and greater than 30 mg L^?1 for shallow groundwater, respectively, while decreased by 28.87% and 14.63% for 0–5 and 5–10 mg L^?1. In the well-irrigated field, the NO₃-N concentrations in shallow groundwater had increased for vegetables, wheat–vegetables and wheat–maize rotations. In contrast, fast-growing tree system could act as a buffer to retain shallow groundwater nitrate content which resulted in reduced NO₃-N concentrations. Under the same land use condition, irrigation with sewage, or well and sewage by turns would both enormously add nitrate to groundwater.     

Landuse change impact on sub-watersheds prioritization by analytical hierarchy process (AHP)

Landuse change analysis is considered as elementary in planning and land management of a basin. The present study provides information of change in landuse in 1990, 2000, 2011, and future prediction of the year 2020, 2030, 2040 and 2050 of different sub-watersheds within a basin, which is a part of the Narmada river basin in central India. The major objectives involve landuse prediction by Markov Chain model and sub-watershed prioritization using analytical hierarchy process (AHP) to identify and manage environmentally unstable areas in future. Different landuse categories are used as factors in prioritization analysis. Landuse of 2011 indicates a transition of about 312 km² of forest area to agricultural land and 10.64 km² to settlement in 2020, which increases to 678 km² and 21.29 km² in 2050 respectively. There is also a transition of forest to scattered forest and grasslands and increase in the areas of the rocky surface. AHP is applied to identify sub-watersheds of highest priority, which indicates the sub-watersheds 5 and 6 are of very high priority in 2011 along with 1, 2, 3, 4 and 7 that are in most places plain areas used for agriculture and settlements. Sub-watersheds 8 and 9, which are forest areas, are observed to be of medium to low priority in future. However, 2050 projects high priority for all the sub-watersheds that calls for efficient landuse management and decision. Most of the northern sub-watersheds of 1 to 7 and 12 of south need high priority.     

Effects of urban and non-urban land cover on nitrogen and phosphorus runoff to Chesapeake Bay

The aim of this study was to determine the effects of catchment and riparian stream buffer-wide urban and non-urban land cover/land use (LC/LU) on total nitrogen (TN) and total phosphorus (TP) runoff to the Chesapeake Bay. The effects of the composition and configuration of LC/LU patches were explored in particular. A hybrid-statistical-process model, the SPAtially Referenced Regression On Watershed attributes (SPARROW), was calibrated with year 1997 watershed-wide, average annual TN and TP discharges to Chesapeake Bay. Two variables were predicted: (1) yield per unit watershed area and (2) mass delivered to the upper estuary. The 166,534 km² watershed was divided into 2339 catchments averaging 71 km². LC/LU was described using 16 classes applied to both the catchments and also to riparian stream buffers alone. Seven distinct landscape metrics were evaluated. In all, 167 (TN) and 168 (TP) LC/LU class metric combinations were tested in each model calibration run. Runs were made with LC/LU in six fixed riparian buffer widths (31, 62, 125, 250, 500, and 1000 meters (m)) and entire catchments. The significance of the non-point source type (land cover, manure and fertilizer application, and atmospheric deposition) and factors affecting land-to-water delivery (physiographic province and natural or artificial land surfaces) was assessed. The model with a 31 m riparian stream buffer width accounted for the highest variance of mean annual TN (r² = 0.9366) and TP (r² = 0.7503) yield (mass for a specified time normalized by drainage area). TN and TP loadings (mass for a specified time) entering the Chesapeake Bay were estimated to be 1.449 × 10⁸ and 5.367 × 10⁶ kg/yr, respectively. Five of the 167 TN and three of the 168 TP landscape metrics were shown to be significant (p-value ≤ 0.05) either for non-point sources or land-to-water delivery variables. This is the first demonstration of the significance of riparian LC/LU and landscape metrics on water quality simulation in a watershed as large as the Chesapeake Bay. Land cover metrics can therefore be expected to improve the precision of estimated TN and TP annual loadings to the Chesapeake Bay and may also suggest changes in land management that may be beneficial in control of nutrient runoff to the Chesapeake Bay and similar watersheds elsewhere.     

Modelling and simulation of continuous L (+) lactic acid production from sugarcane juice in membrane integrated hybrid-reactor system

Modelling and simulation was done for a two-stage membrane-integrated hybrid reactor system for continuous production of L (+) lactic acid under non-neutralizing conditions. The model captures microbial conversion of sugar cane juice to lactic acid under substrate–product inhibitions with downstream purification by nanofiltration. All the major phenomena and the governing parameters like fluid flow, feed dilution, substrate–product inhibitions, Donnan and steric effects during micro and nanofiltration for cell recycle, product separation and purification have been reflected in the modelling. The model describes a green, integrated continuous process of direct lactic acid production starting with a cheap, renewable carbon source. The highest lactic acid concentration achieved after the final stage of nanofiltration was 66.97 g/L at 13 kg/cm² operating pressure when the overall productivity reached 12.40 g/(L h). The developed model could successfully predict production, purification and transport of lactic acid through two stage membrane modules. Performance of the model was very good as indicated in the high overall correlation coefficient (R² > 0.980) and the low relative error (RE < 0.1).     

Quantifying the role of vegetation in slope stability: A case study in Tuscany (Italy)

Vegetation significantly affects hillslope hydrological and mechanical properties related to shallow landslide triggering. In view of the complexity of soil plant hydrological interactions, the quantification of root mechanical reinforcement remains a challenge. Herein we present a back analysis of mechanical stability criteria related to a well-characterized vegetated shallow landslide in Italy, focusing on the quantification of lateral and basal root reinforcement. Lateral root reinforcement is included in slope stability estimates by adding a stabilizing force proportional to the scarp surface and root distribution. This stabilizing force is added to the force balance equation for the infinite slope model for different landslide shapes and dimensions. To quantify root reinforcement, we use the Wu model and the fiber bundle model (WM and FBM, respectively). Implementation of the latter model allows the quantification of the stress–strain behaviour of a bundle of roots for different root distributions and mechanical properties. Results of these models are compared highlighting key differences between the two approaches. Calculations using the FBM can explain the overestimation of lateral root reinforcement using WM and the commonly observed overestimation in the factor of safety. The model also quantifies the displacement-dependent behaviour of root reinforcement on vegetated slopes. Lateral root reinforcement can strongly influence the stability of slopes up to a certain area (1000–2000 m²). The magnitude of this stabilizing effect depends on parameters such as inclination, soil mechanical properties, and root distribution.     

Simulation of land use–soil interactive effects on water and sediment yields at watershed scale

Influences of vegetation management on soil erosion have been extensively studied. However, interactive effects between land use and soil are poorly documented in literature. Given the importance of understanding such effects for successful watershed management, the objective of this study was to examine the land use–soil interactive effects on water and sediment yields for the 117,845-ha drainage area upstream of the U.S. Geological Survey flow gauging station 08101000 in the Cowhouse Creek watershed located in north central Texas. The examination was implemented using the Soil and Water Assessment Tool (SWAT), a distributed watershed model that has been widely used to tackle problems relevant to nonpoint source pollution. A SWAT model was calibrated and validated in accordance with the observed daily streamflows at this gauging station. Subsequently, the calibrated model was used to examine changes of water and sediment yields as a result of the conversion of range brush to range grasses on an individual soil basis. The results indicated that for the study area, the removal of range brush would result in an annual water yield increase of 24 mm ha^?1 treated area. However, the removal on an upland soil with a moderately high permeability was predicted to increase the annual water yield by 80 mm ha^?1 treated area, while it would result in a small increase of annual sediment loading (4.2 t ha^?1 treated area) and a minimal alteration to the existing spatial patterns of sediment sources. The increase of water yield would be larger for the removal of range brush on a soil that is adjacent to the stream channels. For a given soil, the predicted water yield increase was greater for the wetter hydrologic condition than that for the drier one. A reasonable generalization of this study was that the development of best management practices for watershed health and sustainability may need to take into account land use–soil interactive effects on an individual soil basis.     

Planting density influence on fibrous root reinforcement of soils

Reinforcement of soil by fibrous roots is crucial for preventing soil erosion and degradation, yet the underlying mechanisms are poorly understood. We investigated soil reinforcement by roots of barley (Hordeum vulgare) planted at different densities in a controlled glasshouse and a separate field study. Soil shear strength increased with planting density (0–950 m^?2) at 5 weeks with an average 6.7 ± 1.40 kPa increase in strength over the fallow (7.5 ± 0.47 kPa). At 20 weeks, planting density had less of an effect, with on average a 29% increase in strength contributed by roots. In the glasshouse study, roots increased shear strength by an average of 53%, with a positive effect found for the eight planting densities tested ranging from 0 to 1130 plants/m². Detailed measures of root tensile strength, and diameter distributions at the shear plane, allowed us to apply and test two existing root reinforcement models of Wu et al. [Wu, T.H., Mckinnell, W.P., Swanston, D.N., 1979. Strength of tree roots and landslides on Prince-Of-Wales-Island, Alaska. Canadian Geotechnical Journal 16, 19–33] and Pollen and Simon [Pollen, N., Simon, A., 2005. Estimating the mechanical effects of riparian vegetation on stream bank stability using a fiber bundle model. Water Resources Research, 41]. A progressive failure Fibre Bundle Model, developed by Pollen and Simon [Pollen, N., Simon, A., 2005. Estimating the mechanical effects of riparian vegetation on stream bank stability using a fiber bundle model. Water Resources Research, 41], predicted reinforcement better than the catastrophic failure model by Wu et al. [Wu, T.H., Mckinnell, W.P., Swanston, D.N., 1979. Strength of tree roots and landslides on Prince-Of-Wales-Island, Alaska. Canadian Geotechnical Journal 16, 19–33], but neither described reinforcement well for field-grown plants near maturity at 20 weeks.     

Creating spatially continuous maps of past land cover from point estimates: A new statistical approach applied to pollen data

Reliable estimates of past land cover are critical for assessing potential effects of anthropogenic land-cover changes on past earth surface-climate feedbacks and landscape complexity. Fossil pollen records from lakes and bogs have provided important information on past natural and human-induced vegetation cover. However, those records provide only point estimates of past land cover, and not the spatially continuous maps at regional and sub-continental scales needed for climate modelling.We propose a set of statistical models that create spatially continuous maps of past land cover by combining two data sets: 1) pollen-based point estimates of past land cover (from the REVEALS model) and 2) spatially continuous estimates of past land cover, obtained by combining simulated potential vegetation (from LPJ-GUESS) with an anthropogenic land-cover change scenario (KK10). The proposed models rely on statistical methodology for compositional data and use Gaussian Markov Random Fields to model spatial dependencies in the data.Land-cover reconstructions are presented for three time windows in Europe: 0.05, 0.2, and 6 ka years before present (BP). The models are evaluated through cross-validation, deviance information criteria and by comparing the reconstruction of the 0.05 ka time window to the present-day land-cover data compiled by the European Forest Institute (EFI). For 0.05 ka, the proposed models provide reconstructions that are closer to the EFI data than either the REVEALS- or LPJ-GUESS/KK10-based estimates; thus the statistical combination of the two estimates improves the reconstruction. The reconstruction by the proposed models for 0.2 ka is also good. For 6 ka, however, the large differences between the REVEALS- and LPJ-GUESS/KK10-based estimates reduce the reliability of the proposed models. Possible reasons for the increased differences between REVEALS and LPJ-GUESS/KK10 for older time periods and further improvement of the proposed models are discussed.     

The influence of rapid urbanization and land use changes on terrestrial carbon sources/sinks in Guangzhou,China

Complex changes in carbon sources and sinks caused by rapid urbanization have been observed with extensive changes in the quantity, structure, and spatial pattern of land use types. Based on the modified Carnegie-Ames-Stanford Approach model and on gray relational analysis, we analyzed the influence of land use changes on carbon sinks and emissions in Guangzhou from 2000 to 2012. The aim was to identify suitable options for built-up land expansion that would allow for minimal carbon losses. The key results were as follows: (1) Built-up land increased by 118.91% in Guangzhou city over the study period, with this expansion taking the form of concentric circles extending around the old Yuexiu district. (2) Carbon emissions over the period of analysis significantly exceeded carbon sink capabilities. The total carbon sink decreased by 30.02%, from 535.40 × 10³ t to 374.6 × 10³ t. Total carbon emissions increased by 1.89 times, from 13.73 × 10⁶ t to 39.67 × 10⁶ t; 80% of carbon emissions were derived from energy consumption. (3) There were large differences in the extent of carbon sink losses at different scales of built-up land expansion and land use change. In Guangzhou, the loss of carbon sink is small when cultivated land (though not prime farmland) and water bodies are converted to built-up land on a small scale. The loss of carbon sink is much smaller when grasslands are converted to built-up land on a large scale. However, forested land, which has excellent carbon sink functions, should not be converted. (4) Changes in carbon sinks were mainly affected by natural factors and land urbanization. Changes in carbon emissions were mainly affected by population urbanization, economic urbanization, and land urbanization. (5) To achieve “economical and intensive use of land”, “urban growth boundary” and “ecological red lines” should be determined for government policies on land use management. These factors have great significance for “increasing carbon sinks and reducing carbon emissions” in urban ecological systems.     

Development of a surrogate model based on patient weight,bone mass and geometry to predict femoral neck strains and fracture loads

Osteoporosis and related bone fractures are an increasing global burden in our ageing society. Areal bone mineral density assessed through dual energy X-ray absorptiometry (DEXA), the clinically accepted and most used method, is not sufficient to assess fracture risk individually. Finite element (FE) modelling has shown improvements in prediction of fracture risk, better than aBMD from DEXA, but is not practical for widespread clinical use. The aim of this study was to develop an adaptive neural network (ANN)-based surrogate model to predict femoral neck strains and fracture loads obtained from a previously developed population-based FE model. The surrogate model performance was assessed in simulating two loading conditions: the stance phase of gait and a fall.The surrogate model successfully predicted strains estimated by FE (r² = 0.90–0.98 for level gait load case, r² = 0.92–0.96 for the fall load case). Moreover, an ANN model based on three measurements obtainable in clinics (femoral neck length (level gait) or maximum femoral neck diameter (fall), femoral neck bone mass, body weight) was able to give reasonable predictions (r² = 0.84–0.94) for all of the strain metrics and the estimated femoral neck fracture load. Overall, the surrogate model has potential for clinical applications as they are based on simple measures of geometry and bone mass which can be derived from DEXA images, accurately predicting FE model outcomes, with advantages over FE models as they are quicker and easier to perform.     

Nitrate removal in surface-flow constructed wetlands treating dilute agricultural runoff in the lower Yakima Basin,Washington

Constructed treatment wetlands (CTWs) have been used effectively to treat a range of wastewaters and non-point sources contaminated with nitrogen (N). But documented long-term case studies of CTWs treating dilute nitrate-dominated agricultural runoff are limited. This study presents an analysis of four years of water quality data for a 1.6-ha surface-flow CTW treating irrigation return flows in Yakima Basin in central Washington. The CTW consisted of a sedimentation basin followed by two surface-flow wetlands in parallel, each with three cells. Inflow typically contained 1–3 mg-N/L nitrate and <0.4 mg-N/L total Kjeldahl N (TKN). Hydraulic loading was fairly constant, ranging from around 125 cm/d in the sedimentation basin to 12 cm/d in the treatment wetlands. Concentration removal efficiencies for nitrate averaged 34% in the sedimentation basin and 90–93% in the treatment wetlands. Total N removal efficiencies averaged 21% and 57–63% in the sedimentation basin and treatment wetlands, respectively. Area-based first-order removal rate constants for nitrate in the wetlands averaged 142–149 m/yr. Areal removal rates for nitrate in treatment wetlands averaged 139–146 mg-N/m²/d. Outflow from the CTW typically contained <0.1 mg-N/L nitrate and <0.6 mg-N/L TKN. Rates of nitrate loss in wetlands were highly seasonal, generally peaking in the summer months (June–August). Nitrate loss rates also correlated significantly with water temperature (positively) and dissolved oxygen (negatively). Based on the modified Arrhenius relationship, θ for nitrate loss in the wetlands was 1.05–1.09. The CTW also significantly affected temperature and dissolved oxygen concentration in waters flowing through the system. On average, the sedimentation basin caused an increase in temperature (+1.7 °C) and dissolved oxygen (+1.5 mg/L); in contrast the wetlands caused a decrease in temperature (?1.6 °C) and dissolved oxygen (?5.0 mg/L). Results show that CTWs with surface-flow wetlands can be extremely effective at polishing dilute non-point sources, particularly in semi-arid environments where warm temperatures and low oxygen levels in treatment wetland water promote biological denitrification.     

Nitrate-nitrogen retention in wetlands in the Mississippi River Basin

Nitrate-nitrogen retention as a result of river water diversions is compared in experimental wetland basins in Ohio for 18 wetland-years (9 years × 2 wetland basins) and a large wetland complex in Louisiana (1 wetland basin × 4 years). The Ohio wetlands had an average nitrate-nitrogen retention of 39 g-N m⁻² year⁻¹, while the Louisiana wetland had a slightly higher retention of 46 g-N m⁻² year⁻¹ for a similar loading rate area. When annual nitrate retention data from these sites are combined with 26 additional wetland-years of data from other wetland sites in the Basin Mississippi River (Ohio, Illinois, and Louisiana), a robust regression model of nitrate retention versus nitrate loading is developed. The model provides an estimate of 22,000 km² of wetland creation and restoration needed in the Mississippi River Basin to remove 40% of the nitrogen estimated to discharge into the Gulf of Mexico from the river basin. This estimated wetland restoration is 65 times the published net gain of wetlands in the entire USA over the past 10 years as enforced by the Clean Water Act and is four times the cumulative total of the USDA Wetland Reserve Program wetland protection and restoration activity for the entire USA.     

Kinetic modelling and performance prediction of a hybrid anaerobic baffled reactor treating synthetic wastewater at mesophilic temperature

A modelling study on the anaerobic digestion process of a synthetic medium-strength wastewater containing molasses as a carbon source was carried out at different influent conditions. The digestion was conducted in a laboratory-scale hybrid anaerobic baffled reactor with three compartments and a working volume of 54 L, which operated at mesophilic temperature (35 °C). Two different kinetic models (one model was based on completely stirred tank reactors (CSTR) in series and the other an axial diffusion or dispersion model typical of deviations of plug-flow reactors), were assessed and compared to simulate the organic matter removal or fractional conversion. The kinetic constant (k) obtained by using the CSTR in series model was 0.60 ± 0.07 h⁻¹, while the kinetic parameter achieved with the dispersion model was 0.67 ± 0.06 h⁻¹, the dispersion coefficient (D) being 46. The flow pattern observed in the reactor studied was intermediate between plug-flow and CSTR in series systems, although the plug-flow system was somewhat predominant. The dispersion model allowed for a better fit of the experimental results of fractional conversions with deviations lower than 8% between the experimental and theoretical values. By contrast, the CSTR in series model predicted the behaviour of the reactor somewhat less accurately showing deviations lower than 10% between the experimental and theoretical values of the fractional conversion.     

Estimation of the long-term nutrient budget and thresholds of regime shift for a large shallow lake in China

In this study, we apply an integrated empirical and mechanism approach to estimate a comprehensive long-term (1953–2012) total nitrogen (TN) and total phosphorus (TP) loading budget for the eutrophic Lake Chaohu in China. This budget is subsequently validated, firstly, by comparing with the available measured data in several years, and secondly, by model simulations for long-term nutrient dynamics using both Vollenweider (VW) model and dynamic nonlinear (DyN) model. Results show that the estimated nutrient budget is applicable for further evaluations. Surprisingly, nutrient loading from non-point sources (85% for TN and 77% for TP on average) is higher than expectation, suggesting the importance of nutrient flux from the soil in the basin. In addition, DyN model performs relatively better than VW model, which is attributed to both the additional sediment recycling process and the parameters adjusted by the Bayesian-based Markov Chain Monte Carlo (MCMC) method. DyN model further shows that the TP loading thresholds from the clear to turbid state (631.8 ± 290.16 t y⁻¹) and from the turbid to clear state (546.0 ± 319.80 t y⁻¹) are significantly different (p < 0.01). Nevertheless, the uncertainty ranges of the thresholds are largely overlapped, which is consistent with the results that the eutrophication of Lake Chaohu is more likely to be reversible (74.12%) than hysteretic (25.53%). The ecosystem of Lake Chaohu shifted from the clear to turbid state during late 1970s. For managers, approximately two-thirds of the current TP loading must be reduced for a shift back with substantial improvement in water quality. Because in practice the reduction of loading from a non-point source is very difficult and costly, additional methods beyond nutrient reduction, such as water level regulation, should be considered for the lake restoration.     

Kinetics of organic carbon removal by a mixed culture in a membrane bioreactor

The aim of this work was to model the biological activity and anticipate the kinetic behaviour of microorganisms and the overall performance of the process according to a specific model and running parameters. The bacterial inoculum used in these experiments was a mixture of cultures taken from the wastewater treatment plant in Montpellier. The fermentor, used in association with an ultrafiltration separation stage (with a filtration area of 0.2 m²) had a working volume of 15.8 l. For various working conditions (different solid retention times, different hydraulic retention times and substrate concentrations), the biomass concentration and the residual substrate concentration, expressed in terms of dry weight and chemical oxygen demand, respectively, were measured. The basic idea of modelling was related to the concept of maintenance. The coefficient of maintenance, E, and the theoretical conversion yield, y, were therefore calculated. The values of E and y, measured for total cell recycling experiments and for experiments with various solid retention times, remained similar and were found to equal 0.040 mgCOD mgVSS h⁻¹ and 0.36 mgVSS mgCOD⁻¹, respectively. Determining these two constants and modelling the treatment process made it possible to anticipate the optimal biomass concentration for a defined removal efficiency under different steady-state operating conditions.     

Spatiotemporal modeling of watershed nutrient transport dynamics: Implications for eutrophication abatement

The main objective of this study was to quantify nutrient transport dynamics of a previously ungauged, temperate watershed (145 km²) surrounding a shallow eutrophic lake and discern lake response to external nutrient loading, based on soil water assessment tool (SWAT) and the Organization of Economic Cooperation and Development (OECD) empirical lake models, respectively. A SWAT model was used to simulate baseline nutrient dynamics after its calibration and validation against daily tributary flow, total dissolved phosphorus (TDP), total phosphorus (TP), and nitrate (NO₃) loads. On the watershed scale, median annual TDP, TP, and NO₃ losses were 0.4, 1.1, and 2.0 kg ha^− 1, respectively. The highest median annual TP and NO₃ losses were estimated at 3.7 and 7.7 kg ha^− 1 for pastureland and 1.7 and 3.8 kg ha^− 1 for cropland and mixed forests, respectively. Baseflow was the major nutrient transport pathway over a wide range of precipitation events (450 to 900 mm yr^− 1). Erosion was the predominant surface process exporting P across the watershed. Critical source areas (CSAs) of TP and NO₃ comprised 17% and 4% of the watershed, respectively. Annual mean TP, and mean and maximum chlorophyll content indicated a hyper-eutrophication risk for the lake. An external P load reduction by excess of 80% could be necessary to restore mesotrophy in the lake. Our results suggested that subsurface P transport should not be overlooked a priori when groundwater-dependent and extensively farmed watersheds are managed for eutrophication abatement.     

Modelling potential impacts of climate change on the bioclimatic envelope and conservation of the Maned Wolf (Chrysocyon brachyurus)

Forecasting the influence of climatic changes on the distribution of the Maned Wolf (Chrysocyon brachyurus) is important for the conservation of the species. We explored the environmental characteristics than best explain the current distribution of the species, modelled the past and present distribution, projected the niche model into the future, and identified suitable areas for conservation. Niche modelling was performed using Maxent and 21 environmental variables. For past conditions, we considered the Last Glacial Maximum (LGM) and the mid-Holocene (MH) climates. For future conditions, we used the A2a greenhouse gas emission scenario for 2050. Four General Circulation Models (FGOALS 1.0, HADCM3, IPSL-CM4 and MIROC 3.2) were used. The resulting niche model (AUC = 0.89 ± 0.02) predicts maximum probability of presence at precipitation of 106 mm during the coldest quarter, of 396 mm during the warmest quarter, and in totally flat areas. The suitable area for the Maned Wolf currently covers 4,320,364 km². For the LGM, there were inter-model differences in predicted areas (from 819,324 km² to 6,395,886 km²) and in geographic location. The MH models showed drastic changes with respect to the present and considerable inter-model variation. Predictions for 2050 show significant (at least 33%) reductions in distribution. Only a minor fraction (39%) of the current distribution can be considered stable for the period LGM-2050. The FGOALS model was the best option for projecting species occurrence into the future because it included the three localities known for the Maned Wolf from the late Pleistocene and predicts stable areas that coincide with spatial patterns of genetic diversity. The FGOALS projection for 2050 predicts a 33% reduction in suitable habitats, indicating some stable areas (central South America) that will probably be key sites for the conservation of the species.     

Modelling biomass of mountainous grasslands by including a species composition map

High mountain grasslands offer multiple goods and services to society but are severely threatened by improper land use practices such as abandonment or rapid intensification. In order to reduce abandonment and strengthen the common extensive agricultural practice a sustainable land use management of high mountain grasslands is needed. A spatially detailed yield assessment helps to identify possible meadows or, on the contrary, areas with a low carrying capacity in a region, making it easier to manage these sites. Such assessments are rarely available for remote and inaccessible areas. Remotely sensed vegetation indices are able to provide valuable information on grassland properties. These indices tend, however, to saturate for high biomass. This affects their applicability to assessments of high-yield grasslands.The main aim of this study was to model a spatially explicit grassland yield map and to test whether saturation issues can be tackled by consideration of plant species composition in the modelling process. The high mountain grassland of the subalpine belt (1800 – 2500 m a.s.l.) in the Kazbegi region, Greater Caucasus, Georgia, was chosen as test site for its strong species composition and yield gradients.We first modelled the species composition of the grassland described as metrically scaled gradients in the form of ordination axes by random forest regression. We then derived vegetation indices from Rapid Eye imagery, and topographic variables from a digital elevation model, which we used together with the multispectral bands as predictive variables. For comparison, we performed two yield models, one excluding the species composition maps and one including the species composition map as predictors. Moreover, we performed a third individual model, with species composition as predictors and a split dataset, to produce the final yield map.Three main grassland types were found in the vegetation analysis: Hordeum violaceum-meadows, Gentianella caucasea-grassland and Astragalus captiosus-grassland. The three random forest regression models for the ordination axes explained 64%, 33% and 46% of the variance in species composition. Independent validation of modelled ordination scores against a validation data set resulted in an R² of 0.64, 0.32 and 0.46 for the first, second and third axes, respectively. The model based on species composition resulted in a R² = 0.55, whereas the benchmark model showed weaker relationships between yield and the multispectral reflectance, vegetation indices, and topographical parameters (R² = 0.42). The final random forest yield model used to derive the yield map resulted in 62% variance explained and an R² = 0.64 between predicted and observed biomass. The results further indicate that high yields are generally difficult to predict with both models.The benefit of including a species composition map as a predictor variable for grassland yield lies in the preservation of ecologically meaningful features, especially the occurrence of high yielding vegetation type of Hordeum violaceum meadows is depicted accurately in the map. Even though we used a gradient based design, sharp boundaries or immediate changes in productivity were visible, especially in small structures such as arable fields or roads (Fig. 6b), making it a valuable tool for sustainable land use management. The saturation effect however, was mitigated by using species composition as predictor variables but is still present at high yields.     

An ozone response relationship for four Phleum pratense genotypes based on modelling of the phytotoxic ozone dose (POD)

In the last decade extensive research has focused on the development of dose–response relationships based on stomatal plant ozone uptake (phytotoxic ozone dose, POD). So far most work has concentrated on crops and forest trees. This study provides a flux-based dose–response function for timothy (Phleum pratense), a widespread grassland species, which can be used in risk assessment for ground-level ozone. In 1996 and 2001 timothy was exposed in open-top chambers to ozone concentrations ranging from around 10 nmol mol⁻¹ in the charcoal filtered treatments up to 60 nmol mol⁻¹ in the fumigated treatments (08:00–20:00) in. In 1996 there was a negative effect of ozone on biomass production in the non-filtered treatment while in 2001 no such ozone effect in the non-filtered treatment could be seen. Measurements of stomatal conductance on four timothy genotypes in 2001 were used to calibrate a Jarvis-type multiplicative stomatal conductance model. The maximum conductance varied between the genotypes, from 477 to 589 mmol O₃ m⁻² s⁻¹ (projected leaf area). The model includes functions describing the reduction of stomatal conductance of senescing leaves and the direct effects on stomatal conductance by light, temperature and water vapour pressure deficit. A function describing ozone induced senescence of the leaves was included since exposure to ozone is known to cause premature senescence. The function for ozone was applied when it suggested ozone to be more limiting to stomatal conductance than phenology. To avoid overestimation of stomatal conductance in days with high VPD, a function reflecting the effect on leaf water potential on stomatal conductance was included. Comparison between modelled and measured conductance for the four timothy genotypes resulted in an r² value at 0.57 and a very small average deviation of observed from modelled values. The calibrated stomatal conductance model was used to estimate the accumulated POD, i.e. the accumulated stomatal flux of ozone, of the plants in the 1996 and 2001 experiments. The strongest relationship between ozone relative effects on biomass was obtained when POD was accumulated from 105 degree days after emergence to 1000 degree days after emergence, and integrated using an uptake rate threshold of 7 nmol m⁻² s⁻¹ (POD₇). The response relationship between biomass and POD₇ resulted in an r² value of 0.71 over all four genotypes. This r² value was somewhat higher than for the corresponding relationship based on the accumulated ozone exposure over 40 nmol mol⁻¹ (AOT40; r² = 0.66). With an uptake rate threshold at 7 nmol m⁻² s⁻¹, ozone concentrations above ∼20 nmol mol⁻¹, contribute to reduce the biomass production of timothy if meteorological conditions promote maximum stomatal conductance.