What does resilience of a clear-water state in lakes mean for the spatial heterogeneity of submersed macrophyte biovolume?

Short-term variability of spatial heterogeneity of submersed macrophyte biovolume (percent of water column occupied by vegetation) was evaluated over 3 years along a gradient of productivity in four north temperate glacial lakes in Minnesota, USA. We hypothesized we would observe the lowest among-year variability in spatial heterogeneity of biovolume in our undisturbed, moderately productive lake and high variability in our more locally disturbed productive lakes. Our analysis involved three major steps: first, we removed negative trends of biovolume across depth with non-parametric regression smoothers; second, we examined spatial pattern in residuals using variograms; finally, we compared spatial pattern of biovolume among lakes seasonally, over 3 years. Lake productivity negatively correlated with water clarity and the depth range of macrophyte growth, and positively correlated with the variability of spatial patterns. In the least disturbed moderately productive lake, vegetation grew over a large range of depths (up to 7.5 m), and spatial pattern across the littoral zone was similar for each survey. In contrast, in the more turbid, productive lakes, depth and spatial patterns of biovolume varied greatly from survey to survey. Factors that increase productivity and weaken resilience in lakes may lead to unstable spatial patterns of macrophyte biovolume.     

What does resilience of a clear-water state in lakes mean for the spatial heterogeneity of submersed macrophyte biovolume?

Short-term variability of spatial heterogeneity of submersed macrophyte biovolume (percent of water column occupied by vegetation) was evaluated over 3 years along a gradient of productivity in four north temperate glacial lakes in Minnesota, USA. We hypothesized we would observe the lowest among-year variability in spatial heterogeneity of biovolume in our undisturbed, moderately productive lake and high variability in our more locally disturbed productive lakes. Our analysis involved three major steps: first, we removed negative trends of biovolume across depth with non-parametric regression smoothers; second, we examined spatial pattern in residuals using variograms; finally, we compared spatial pattern of biovolume among lakes seasonally, over 3 years. Lake productivity negatively correlated with water clarity and the depth range of macrophyte growth, and positively correlated with the variability of spatial patterns. In the least disturbed moderately productive lake, vegetation grew over a large range of depths (up to 7.5 m), and spatial pattern across the littoral zone was similar for each survey. In contrast, in the more turbid, productive lakes, depth and spatial patterns of biovolume varied greatly from survey to survey. Factors that increase productivity and weaken resilience in lakes may lead to unstable spatial patterns of macrophyte biovolume.     

Development and application of an ecological classification tool for fish in lakes in Ireland

A classification tool suitable for establishing the ecological status of lakes based on fish population parameters has been developed for the Republic of Ireland and Northern Ireland (EU Water Framework Directive Ecoregion 17). A lake typology relevant to fish populations in lakes from Ecoregion 17 was produced as part of the ecological classification tool development. Four lake types were determined based on fish metrics and abiotic variables from 43 “reference” lakes. The specific lake fish typology categorised lakes into low (≤67 CaCO₃ mg L⁻¹) or high (>67 CaCO₃ mg L⁻¹) alkalinity, and shallow (≤17 m) or deep (>17 m) maximum depth. The fish in lakes classification tool (FIL2) follows a novel multimetric predictive approach, assigning ecological status to a lake using two independent methods. FIL2 qualitatively defines a lake's ecological status based on fish metrics using discriminant classification rules and, using a generalised linear model, quantitatively derives an Ecological Quality Ratio (EQR, 0 < EQR < 1), along with associated confidence intervals. It is recommended that both methods are used to validate output and cross-check and highlight potential misclassification.     

Structure and seasonal dynamics of the protozoan community (heterotrophic flagellates,ciliates, amoeboid protozoa) in the plankton of a large river (River Danube,Hungary)

Seasonal dynamics of all major protozoan groups were investigated in the plankton of the River Danube, upstream of Budapest (Hungary), by bi-weekly sampling over a 1-year long period. Sixty-one heterotrophic flagellate, 14 naked amoeba, 50 testate amoeba, 4 heliozoan and 83 ciliate morphospecies were identified. The estimated abundance ranges of major groups throughout the year were as follows: heterotrophic flagellates, 0.27–7.8×10⁶ ind. l^?1; naked amoebae, max. 3300 ind. l^?1; testaceans, max. 1600 ind. l^?1; heliozoans, max. 8500 ind. l^?1; ciliates, 132–34,000 ind. l^?1. In terms of biovolume, heterotrophic flagellates dominated throughout the year (max. 0.58 mm³ l^?1), and ciliates only exceeded their biovolume in summer (max. 0.76 mm³ l^?1). Naked amoeba and heliozoan biovolume was about one, and testacean biovolume 1–3, orders of magnitude lower than that of ciliates. In winter, flagellates, mainly chrysomonads, had the highest biomass, whilst ciliates were dominated by peritrichs. In 2005 from April to July a long spring/summer peak occurred for all protozoan groups. Beside chrysomonads typical flagellates were choanoflagellates, bicosoecids and abundant microflagellates (large chrysomonads and Collodictyon). Most abundant ciliates were oligotrichs, while Phascolodon, Urotricha, Vorticella, haptorids, Suctoria, Climacostomum and Stokesia also contributed significantly to biovolume during rapid succession processes. In October and November a second high protozoan peak occurred, with flagellate dominance, and slightly different taxonomic composition.     

The use of medium point density LiDAR elevation data to determine plant community types in Baltic coastal wetlands

This study investigates the use of medium point density LiDAR (light detection and ranging) elevation data for identifying and locating plant community types in Baltic coastal wetlands. Ground-surveyed micro-topography data obtained using real-time kinematic differential GPS were used to analyse and correct the accuracy of LiDAR sourced elevation values in Matlab R2010a. Following the application of elevation corrections, 3 interpolation techniques were applied: Inverse Distance Weighting (IDW), Ordinary Kriging (OK) and the Delaunay Triangulated Irregular Network (TIN) interpolation. Analysis showed that the TIN method produced a more robust model that adequately represented the micro-topographical variation across the wetland. The TIN elevation interpolation was then used to characterise the extent and distribution of the plant communities using known elevation preferences in one coastal wetland site, Tahu. The plant community model developed from the TIN elevation interpolation was then further ground-truthed in two separate Baltic coastal wetland sites, Matsalu and Kudani, in order to test model validity.The results showed that the accuracy of the LiDAR data varied dependent upon plant community type. In 5 of the 6 studied community types, the LiDAR data gave a mean elevation difference of 0.177 m (0.016 SD) above the dGPS elevations. With dGPS elevation corrections, the LiDAR data produced an accurate model of the location of the different plant community types, Kappa coefficient (κ) 0.63, at the initial site, Tahu. The model was found to be very accurate in one of the subsequent ground-truthed sites, κ 0.81, with a similar management history, but less accurate, κ 0.53, in a wetland more exposed to wave action and with a longer history of vegetation management.The inclusion of dGPS ground survey data was shown to considerably improve the accuracy of the LiDAR elevation data to facilitate the identification of plant community types on the basis of elevation. The approach developed in this study of Baltic coastal wetlands may provide a transferable method for rapidly and accurately mapping plant communities in other open environments.     

The effect of lake morphology on aquatic vegetation development and changes under the influence of eutrophication

Data on aquatic and emergent vegetation, morphology and water quality from 274 Polish lowland lakes surveyed in the years 1996–2009 were used to validate the preliminary typology of Polish lakes based on macrophytes and to indicate the environmental parameters which most significantly determine the vegetation patterns in lakes under various morphological conditions. In highly alkaline lowland lakes representing non-disturbed conditions the key determinants influencing the vegetation patterns were mean depth and the shape of the littoral. Three morphological lake types were distinguished: shallow (<3.5 m), deep, and additionally, within the latter, deep ribbon-shaped, with a clearly elongated base and steep bed slopes. The lake types varied in their vegetation patterns developed under non-disturbed conditions. In the shallow lakes, the share of the phytolittoral in the total lake area (%phytol) was the highest (40–100%, 72.3% on average) and the maximum colonisation depth (C_max) the lowest (3.2 m as the maximum) compared to the lakes from both deep types. In the ribbon-shaped deep lakes, %phytol and the plant coverage (%cover) were the lowest, the proportion of submerged vegetation was extraordinarily high (over 90%) and the emergent vegetation was extremely sparsely developed (<6%) compared to the lakes of the two other types.The alterations of aquatic vegetation resulting from the eutrophication process in distinguished morphological lake types were explored. Within the macrophyte variables tested, three groups of indicators were distinguished: (a) metrics performing best in selected lake types, i.e. the type-specific indicators (abundance metrics, %Pota), (b) metrics performing equally well in all the lake types, considered as the universal indicators (e.g. S_Chara, %Subm and %Emerg) and (c) metrics performing poorly in all the lake types, with generally limited applicability (most of the metrics on syntaxonomic richness). In the shallow lakes, %cover and %phytol performed notably better than in deep lakes, whereas C_max worked best in deep lakes and showed the strongest response in the deep regular-shaped lakes. Moreover, in deep regular-shaped lakes the number of communities of stoneworts and submerged plants (S_Chara and S_Subm), and in deep ribbon-shaped lakes the proportion of area inhabited by vascular plant communities (%Pota) performed exceptionally better than in the other two lake types. The most universal metrics, performing equally well in all the lake types, were the proportions of submerged (%Subm) and emergent (%Emerg) vegetation in the total phytolittoral area.     

Quantile regression analysis as a predictive tool for lake macroinvertebrate biodiversity

The Water Framework Directive introduced in Europe major changes to improve the management of water resources. This study aims to highlight some of the potential implications of its implementation for lake water monitoring in Italy. A Life+ project was launched to plan the first monitoring of lake macroinvertebrates standardized at the national level.Quantile regression analysis was used to explain different metrics of diversity describing macroinvertebrate communities in response to twenty-one variables representing chemical, physical and morphological characteristics of the environment. Nine lakes located in two Italian regions (Piedmont and Sardinia) were analyzed covering a wide trophic spectrum, from oligotrophy to hyper-eutrophy. The lakes were sampled following the national standardized protocol with samples covering the three recognized lake zones: littoral, sublittoral, profundal.The studied lakes had high chemical variability with conductivity ranging between 53 and 561 μS/cm, pH between 6.5 and 9.1, and alkalinity between 14 and 398 mg/l. The bottom sediments were characterized by fine sand (range 51–99%), followed by silt (1–35%) and clay (0–28%). When the Lake Habitat Survey was also applied to these lakes, its synthetic indices (LHMS, Lake Habitat Modification Score and LHQA, Lake Habitat Quality Assessment) produced higher values in natural lakes (mean values ± SD: LHMS = 26 ± 7, LHQA = 57 ± 3) than in the reservoirs (LHMS = 22 ± 4, LHQA = 52 ± 6). In all lakes, macroinvertebrates mainly consisted of chironomids and oligochaetes characterized by relative abundances up to 80% and >90%, respectively.Using quantile regression to evaluate limiting responses, only two variables, namely sampling depth and oxygen percent saturation (oxygen content), resulted the ones that best explained all the analyzed metrics of diversity of the macroinvertebrate communities. Depth and oxygen were then used to suggest synthetic models describing the various metrics of potential community diversity. These models can help the environmental agencies responsible for monitoring at the national level in distinguishing entire lakes or part of them with high biodiversity from those in altered conditions and then address remediation efforts toward the water bodies with the most critical conditions. Such approach could also be used to optimize the sampling procedures for the application of the Benthic Quality Index for lakes currently adopted at national level.     

Estimation of wetland vegetation height and leaf area index using airborne laser scanning data

Wetland vegetation is a core component of wetland ecosystems. Wetland vegetation structural parameters, such as height and leaf area index (LAI) are important variables required by earth-system and ecosystem models. Therefore, rapid, accurate, objective and quantitative estimations of wetland vegetation structural parameters are essential. The airborne laser scanning (also called LiDAR) is an active remote sensing technology and can provide accurate vertical vegetation structural parameters, but its accuracy is limited by short, dense vegetation canopies that are typical of wetland environments. The objective of this research is to explore the potential of estimating height and LAI for short wetland vegetation using airborne discrete-return LiDAR data.The accuracies of raw laser points and LiDAR-derived digital elevation models (DEM) data were assessed using field GPS measured ground elevations. The results demonstrated very high accuracy of 0.09 m in raw laser points and the root mean squared error (RMSE) of the LiDAR-derived DEM was 0.15 m.Vegetation canopy height was estimated from LiDAR data using a canopy height model (CHM) and regression analysis between field-measured vegetation heights and the standard deviation (σ) of detrended LiDAR heights. The results showed that the actual height of short wetland vegetation could not be accurately estimated using the raster CHM vegetation height. However, a strong relationship was observed between the σ and the field-measured height of short wetland vegetation and the highest correlation occurred (R² = 0.85, RMSE = 0.14 m) when sample radius was 1.50 m. The accuracy assessment of the best-constructed vegetation height prediction model was conducted using 25 samples that were not used in the regression analysis and the results indicated that the model was reliable and accurate (R² = 0.84, RMSE = 0.14 m).Wetland vegetation LAI was estimated using laser penetration index (LPI) and LiDAR-predicted vegetation height. The results showed that the vegetation height-based predictive model (R² = 0.79) was more accurate than the LPI-based model (the highest R² was 0.70). Moreover, the LAI predictive model based on vegetation height was validated using the leave-one-out cross-validation method and the results showed that the LAI predictive model had a good generalization capability. Overall, the results from this study indicate that LiDAR has a great potential to estimate plant height and LAI for short wetland vegetation.     

Effect of fire on soil nutrients and under storey vegetation in Chir pine forest in Garhwal Himalaya,India

The study was carried out in the Pinus roxburghii Sargent (Chir pine) forest in the sub-tropical region of Garhwal Himalaya to assess the effect of fire on soil nutrient status at different altitudes (700 m, 800 m and 1000 m), soil depths (0–20 cm, 20–40 cm and 40–60 cm) and on under storey vegetation. The soil nutrients and under storey vegetation were assessed before fire (pre-fire) and after fire (post-fire). The results of the study indicate that fire plays an important role in soil nutrient status and under storey vegetation. The nutrients (soil organic carbon, nitrogen, phosphorus and potassium), decreased in post-fire assessment and with increasing altitudes, and soil depths, compared to pre-fire assessment. The under storey vegetation diminished after fire in all forest sites. The study concludes that in Chir pine forest, fire plays a role in reducing soil nutrients along the altitudinal gradient, soil depths and under storey vegetation. Thus, these nutrients can be saved through some management practices e.g. by early controlled burning and by educating local villagers about the negative impacts of severe wild fires on soil and vegetation.     

Mapping soil organic matter in low-relief areas based on land surface diurnal temperature difference and a vegetation index

Accurate estimates of the spatial variability of soil organic matter (SOM) are necessary to properly evaluate soil fertility and soil carbon sequestration potential. In plains and gently undulating terrains, soil spatial variability is not closely related to relief, and thus digital soil mapping (DSM) methods based on soil–landscape relationships often fail in these areas. Therefore, different predictors are needed for DSM in the plains. Time-series remotely sensed data, including thermal imagery and vegetation indices provide possibilities for mapping SOM in such areas. Two low-relief agricultural areas (Peixian County, 28 km × 28 km and Jiangyan County, 38 km × 50 km) in northwest and middle Jiangsu Province, east China, were chosen as case study areas. Land surface diurnal temperature difference (DTD) extracted from moderate resolution imaging spectroradiometer (MODIS) land surface temperature (LST), and soil-adjusted vegetation index (SAVI) at the peak of growing season calculated from Landsat ETM+ image were used as predictors. Regression kriging (RK) with a mixed linear model fitted by residual maximum likelihood (REML) and residuals interpolated by simple kriging (SK) were used to model and map SOM spatial distribution; ordinary kriging (OK) was used as a baseline comparison. The root mean squared error, mean error and mean absolute error calculated from leave-one-out cross-validation were used to assess prediction accuracy. Results showed that the proposed covariates provided added value to the observations. SAVI aggregated to MODIS resolution was able to identify local highs and lows not apparent from the DTD imagery alone. Despite the apparent similarity of the two areas, the spatial structure of residuals from the linear mixed models were quite different; ranges on the order of 3 km in Jiangyan but 16 km in Peixian, and accuracy of best models differed by a factor of two (3.3 g/kg and 6.3 g/kg SOM, respectively). This suggests that time-series remotely sensed data can provide useful auxiliary variable for mapping SOM in low-relief agricultural areas, with three important cautions: (1) image dates must be carefully chosen; (2) vegetation indices should supplement diurnal temperature differences, (3) model structure must be calibrated for each area.     

Monitoring submersed vegetation in a mesotrophic lake: correlation of two spatio-temporal scales of change

The submersed vegetation of mesotrophic, alkaline Chenango Lake in New York, USA, was monitored at two spatio-temporal scales: a 200 m² grid censused annually from 1978 to 1993 and again in 2001 (12,800 quadrats), and a 1.8 ha littoral zone sampled every 6–10 years (1978, 1984, 1991, and 2001; 3600 quadrats). The grid vegetation fluctuated rather erratically for the first 11 years with each of the dominant species showing a different pattern of change. Frequency values for Chara vulgaris were the most dynamic, while those for Vallisneria americana were the most stable. After 1989, grid vegetation declined, so that by 2001, only four of the original 11 species were present (including the original dominants), and the total number of observations declined to <10% of the maximum recorded. This decline is attributed to vigorous benthic feeding by carp (Cyprinus carpio), not noted in 1978 but relatively abundant by 2001. Frequency changes of species in the 200 m² grid were positively correlated with corresponding frequency changes in the 1.8 ha littoral zone, indicating that a small, carefully chosen area may reflect vegetation at a larger scale. This was particularly true when vegetation change was appreciable.     

Distribution and ecology of the assemblages of myxomycetes associated with major vegetation types in Big Bend National Park,USA

The distribution and ecology of the assemblages of myxomycetes associated with four different microhabitats were studied in Big Bend National Park in Texas. During Mar. 2005, twelve plots (30 × 30 m) were established along an elevational gradient that extended from 564 to 1807 m. Samples of aerial bark from dead and living trees, aerial litter (dead but still attached plant parts), ground litter (fallen dead plant parts) and ground bark (fragments of fallen bark) were collected from these plots, which encompassed all of the major vegetation types found in the Park. Four hundred forty-seven moist chambers were prepared, and 95.8 % (428) produced some evidence (either fruit bodies or plasmodia) of myxomycetes. A total of 71 species were recorded, with ground litter yielding most (45 species). Aerial litter, aerial bark and ground bark yielded 44, 39 and 37 species, respectively. Species abundance distribution measures (diversity, dominance and similarities) varied among the four microhabitats as well as among the major vegetation types. Canonical Correspondence Analysis (CCA) showed that species distribution patterns were closely related to: (1) the major environmental-complex gradients associated with differences in elevation/temperature/moisture conditions that occur from one locality to another; and (2) the different types of microhabitat.     

Diatom taxa and assemblages for establishing nutrient criteria of lakes with anthropogenic hydrologic alteration

Stressor-response models offer guidance for concentration-based nutrient criteria in lakes under human intervention. Diatom-based statistics from biological responses were incorporated to derive taxon-specific and community-level change points (thresholds) of phosphorous and nitrogen in 77 Yangtze floodplain lakes. Diatom metrics relating with conductivity were adopted as response variables, since conductivity explained the maximum variation (38.1%) in diatom assemblages via Bootstrapped regression trees. Nonparametric change-point analysis and Threshold Indicator Taxa ANalysis showed threshold responses of diatom community structure at 0.05–0.08 mg TP/L in connected lakes and 0.02–0.04 mg TP/L in isolated lakes. Distinct community change points of sensitive diatoms occurred at 0.96–1.63 mg TN/L in connected lakes and 0.52–0.63 mg TN/L in isolated lakes. Diatom community structures of tolerant taxa were substantially altered beyond 0.22–0.23 mg/L in connected lakes and 0.52–0.69 mg NO_x/L in isolated lakes. Hydrological river-lake connectivity differed significantly in ecological nutrient criteria with more TN/TP criteria and less NO_x criteria in connected lakes. Given the ecological significance and biological integrity, diatom-based statistics can provide more reliable change points (thresholds) for nutrient criteria than Chl a-nutrient relationships.     

Managing road corridors to limit fire hazard. A simulation approach in southern France

Road corridors are sources of fire ignition and fire spread in French Mediterranean areas, but little is known about the flammability of vegetation and the probability of fire ignition and spread to neighbouring forests. This study simulated fire propagation in road corridors with the help of a cellular automata (CA). We assessed the relative importance of vegetation type, fuel treatment and the spatial patterning of vegetation on the probability of fire spreading to forests. The cellular automaton simulator was implemented with different types of corridors (30 m × 40 m), on the basis of an extensive field survey of vegetation. We used data from laboratory flammability experiments to determine the probability of ignition and propagation for each of the 20 cm × 20 cm cells of the CA. The probability of a fire reaching the neighbouring forest (P_FR) indicated that certain types of road corridors represent a very high risk owing to a combination of highly flammable vegetation and high spatial connectivity. The lowest P_FR values correspond to corridors with a decreasing vegetation flammability gradient in the vicinity of the forest. A several meter-wide embankment with low-flammable and/or managed vegetation can substantially reduce P_FR. These results suggest that firewise landscaping and local vegetation management can reduce fire risk in road corridors. Each corridor type should be subjected to specific vegetation management to account for flammability, growth pattern and lifetime.     

Development,calibration, and validation of a littoral zone plant index of biotic integrity (PIBI) for lacustrine wetlands

We examine lacustrine wetland plant assemblages in the Central Corn Belt Plain portion of the Lake Michigan basin and developed a multimetric plant index of biotic integrity (PIBI). Our objectives were to determine the structural and functional attributes of littoral zone plant assemblages of least-impacted lacustrine wetlands, establish and test candidate metrics, statistically test and calibrate metrics, and finally validate a PIBI along a disturbance gradient. Of 35 candidate metrics, we chose 11 metrics that were grouped into four categories: species richness and composition, species tolerance, guild structure, and vegetation abundance. Based on Spearman correlations, we identified a suite of metrics, particularly those related to species richness and tolerance that had a strong response to human-induced habitat change. The overall PIBI correlated strongly with independent measures of habitat quality (p < 0.001) using a qualitative habitat index developed for lacustrine habitats. We validated the lacustrine PIBI by comparing index response to various landuse, landcover, and management types. Least impacted lakes and lakes classified as recreational or undergoing ecological restoration were not statistically separable and received the highest index scores, while the lowest scores were associated with industrial and residential land use. Least-impacted sites differ significantly (p < 0.001) from both industrial and residential lakes.     

Airborne hyperspectral data predict Ellenberg indicator values for nutrient and moisture availability in dry grazed grasslands within a local agricultural landscape

Species-based ecological indices, such as Ellenberg indicators, reflect plant habitat preferences and can be used to describe local environment conditions. One disadvantage of using vegetation data as a substitute for environmental data is the fact that extensive floristic sampling can usually only be carried out at a plot scale within limited geographical areas. Remotely sensed data have the potential to provide information on fine-scale vegetation properties over large areas. In the present study, we examine whether airborne hyperspectral remote sensing can be used to predict Ellenberg nutrient (N) and moisture (M) values in plots in dry grazed grasslands within a local agricultural landscape in southern Sweden. We compare the prediction accuracy of three categories of model: (I) models based on predefined vegetation indices (VIs), (II) models based on waveband-selected VIs, and (III) models based on the full set of hyperspectral wavebands. We also identify the optimal combination of wavebands for the prediction of Ellenberg values. The floristic composition of 104 (4 m × 4 m grassland) plots on the Baltic island of Öland was surveyed in the field, and the vascular plant species recorded in the plots were assigned Ellenberg indicator values for N and M. A community-weighted mean value was calculated for N (mN) and M (mM) within each plot. Hyperspectral data were extracted from an 8 m × 8 m pixel window centred on each plot. The relationship between field-observed and predicted mean Ellenberg values was significant for all three categories of prediction models. The performance of the category II and III models was comparable, and they gave lower prediction errors and higher R² values than the category I models for both mN and mM. Visible and near-infrared wavebands were important for the prediction of both mN and mM, and shortwave infrared wavebands were also important for the prediction of mM. We conclude that airborne hyperspectral remote sensing can detect spectral differences in vegetation between grassland plots characterised by different mean Ellenberg N and M values, and that remote sensing technology can potentially be used to survey fine-scale variation in environmental conditions within a local agricultural landscape.     

Bio-thermal effects of open dumps on surroundings detected by remote sensing—Influence of geographical conditions

This study has used remotely sensed data of Landsat-8 for monitoring open dumps of Municipal Solid Waste (MSW) using vegetation health as a bio-indicator and thermal emissions from it. Open dump of Mahmood Booti has been found to affect the surrounding vegetation up to 800 m in dry summers and reducing to 400 m in winters, while averaging to a distance of about 650 m. Average thermal influence zone has been observed to have same radial extent of about 650 m varying between the minimum of 350 m in dry summer and maximum of 1000 m in winter. All the corresponding details of bio-indicators and temperature variations have also been discussed. In addition to this, the results and methodology of spatial analysis for Mahmood Booti dump of Lahore, Pakistan, surrounded by a heterogeneous land cover, have been compared with the main dumping facility of Faisalabad, Pakistan, which is surrounded by a homogeneous vegetation cover all around. This comparison yielded two main conclusions, first, the surrounding geography of an open MSW dump affects the severity of bio-thermal effects, in addition to waste age, characterization, pile etc. Second, GIS analysis for studying bio-thermal effects requires modification that varies for prevailing neighborhood land cover conditions of MSW open dumps. Use of remotely sensed data for monitoring dumped MSW is a good alternative but selection of proper GIS methodology, representing natural setting of phenomena is equally important as that of the accuracy of the remotely sensed data.     

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.     

Benefits of clonal integration between interconnected ramets of Vallisneria spiralis in heterogeneous light environments

Interconnected ramets of the submersed macrophyte Vallisneria spiralis were subjected to two homogeneous treatments (shading or not shading whole plants) and two heterogeneous treatments (only shading basal or apical ramets of plants). The benefits and costs of clonal integration between connected ramets grown in heterogeneous treatments were examined. Results showed that shading apical ramets induced significant benefits to the performance of whole plant in terms of dry weight per plant (P < 0.01) and number of ramets per plant (P < 0.05). Especially for the unshaded basal ramets, their dry weight, number of ramets, number of branches and total stolon length were 89%, 30%, 29% and 58% higher than the corresponding ramets in homogeneous treatment, respectively. Compared to their controls in homogeneous treatments, unshaded basal ramets produced more leaf mass (0.15 g versus 0.11 g) whereas shaded apical ramets produced more root mass (0.012 g versus 0.008 g). However, there was a different pattern of integration when basal ramets were shaded. Shading basal ramets led to a significant decrease in stolon growth, but the individual performance of shaded ramets improved. Cost-benefit analyses revealed that dry weight per ramet of basal shaded ramets was 31% greater than that of basal shaded ramets in the homogeneous treatment. We can conclude that V. spiralis can benefit from clonal integration in heterogeneous light environments, but that the scale of these benefits is related to the quality of light environments where the clone become established.     

Livestock paths on Namaqualand quartz fields: Will the endemic flora disappear?

Quartz fields are rare features that contribute significantly to vegetation diversity and endemism of South Africa's Succulent Karoo Biome. The Riethuis-Wallekraal quartz fields in the north-western Namaqualand area of South Africa contain 17 quartz field specialist species of which seven are endemic to this specific area. Hoof-action by livestock has formed paths of approximately 0.30 m on these quartz fields. It would be important to conservationists to understand whether direct (e.g. trampling) and indirect effects (e.g. burial of flora by sediment movement) associated with the livestock paths holds any threat to the dwarf succulent (< 0.05 m) and micro-chamaephytes (0.06–0.15 m) endemic to the quartz fields. We tested the hypotheses that the unique quartz field vegetation and biological soil crusts would be affected by loose soil particles transported downslope from the paths. The soil stability index, total vegetation cover, cover of specialized quartz field species and species diversity were lower on livestock paths but did not differ between upslope and downslope locations. Livestock paths also had lower cover and fewer quartz field specialist species. It is concluded that under conditions of intense and continuous grazing, livestock are likely to have an even stronger negative impact on the specialist quartz field flora.