Monitoring habitat preserves in southern California using high spatial resolution multispectral imagery

Habitat preserve systems have been established adjacent to the densely populated regions of southern California to support indigenous plant and animal species that are listed as rare, threatened, or endangered. Monitoring the condition of habitat across these broad preserves is necessary to ensure their long-term viability and may be effectively accomplished using remote sensing techniques with high spatial resolution visible and near-infrared (VNIR) multispectral imagery. The utility of 1 m spatial resolution VNIR imagery for detailed change detection and monitoring of Mediterranean-type ecosystems is assessed here. Image acquisition and preprocessing procedures were conducted to ensure that image-detected changes represented real changes and not artifacts. Change classification products with six spectral-based transition classes were generated using multiband image differencing (MID) for three change periods: 1998-1999, 1998-2001, and 1998-2005. Land cover changes relevant to habitat quality monitoring such as human-induced disturbance, fire, vegetation growth/recovery, and drought related vegetation stress were readily detected using the multitemporal VNIR imagery. Suggestions for operational habitat monitoring using image products and mobile geographic information system technologies are provided.     

Optimising the sampling effort in riparian surveys

Riparian condition is commonly measured as part of stream health monitoring programs as riparian vegetation provides an intricate linkage between the terrestrial and aquatic ecosystems. Field surveys of a riparian zone provide comprehensive riparian attribute data but can be considerably intensive and onerous on resources and workers. Our objective was to assess the impact of reducing the sampling effort on the variation in key riparian health indicators. Subsequently, we developed a non-parametric approach to calculate an information retained (IR) statistic for comparing several constrained systematic sampling schemes to the original survey. The IR statistic is used to select a scheme that reduces the time taken to undertake riparian surveys (and thus potentially the costs) whilst maximising the IR from the original survey. Approximate bootstrap confidence intervals were calculated to improve the inferential capability of the IR statistic. The approach is demonstrated using riparian vegetation indicators collected as part of an aquatic ecosystem health monitoring program in Queensland, Australia. Of the nine alternative sampling designs considered, the sampling design that reduced the sampling intensity per site by sixfold without significantly comprising the quality of the IR, results in halving the time taken to complete a riparian survey at a site. This approach could also be applied to reducing sampling effort involved in monitoring other ecosystem health indicators, where an intensive systematic sampling scheme was initially employed.     

Assessing the health of an urban stream: a case study of Suzhou Creek in Shanghai, China

Restoration of urban streams and rivers has increased rapidly in developing countries in recent years. Estimating river health provides a new perspective on evaluating the ecological conditions of streams and rivers. The Suzhou Creek restoration project in Shanghai, China is a milestone for environmental protection. Based on the environmental and ecological data, including 17 indicators in five categories, collected from March 11 to April 20, 2007, the river health index (RHI) for Suzhou Creek was constructed and analysed to quantify the ecosystem of this urban river after a restoration project. The RHI scores of 34 sites ranged from 19.24 to 33.36, i.e. from poor to good. There were no significant RHI differences among stream orders, while differences in land use resulted in significant differences in channel flow status (B12), channel alteration (B21), channel sinuosity (B22), bank stability (B23), bank profile type (B25) and riparian vegetative zone width (B31). River restoration led to improved hydrological condition and channel physical form, while ammonia nitrogen (B44) and indicator scores of the presence of macro-invertebrate families (B51) were the lowest of any indicator. This case study supports the use of river health assessment as a supplement to water quality analysis in China.     

Status of the Riparian Ecosystem in the Upper San Pedro River, Arizona: Application of an Assessment Model

A portion of Arizona’s San Pedro River is managed as a National Riparian Conservation Area but is potentially affected by ground-water withdrawals beyond the conservation area borders. We applied an assessment model to the Conservation Area as a basis for monitoring long-term changes in riparian ecosystem condition resulting from changes in river water availability, and collected multi-year data on a subset of the most sensitive bioindicators. The assessment model is based on nine vegetation bioindicators that are sensitive to changes in surface water or ground water. Site index scores allow for placement into one of three condition classes, each reflecting particular ranges for site hydrology and vegetation structure. We collected the bioindicator data at 26 sites distributed among 14 reaches that had similar stream flow hydrology (spatial flow intermittency) and geomorphology (channel sinuosity, flood-plain width). Overall, 39% of the riparian corridor fell within condition class 3 (the wettest condition), 55% in condition class 2, and 6% in the driest condition class. Condition class 3 reaches have high cover of herbaceous wetland plants (e.g., Juncus and Schoenoplectus spp.) along the perennial stream channel and dense, multi-aged Populus-Salix woodlands in the flood plain, sustained by shallow ground water in the stream alluvium. In condition class 2, intermittent stream flows result in low cover of streamside wetland herbs, but Populus-Salix remain abundant in the flood plain. Perennial wetland plants are absent from condition class 1, reflecting highly intermittent stream flows; the flood plain is vegetated by Tamarixa small tree that tolerates the deep and fluctuating ground water levels that typify this reach type. Abundance of herbaceous wetland plants and growth rate of Salix gooddingii varied between years with different stream flow rates, indicating utility of these measures for tracking short-term responses to hydrologic change. Repeat measurement of all bioindicators will indicate long-term trends in hydro-vegetational condition.     

The influence of suburban land use on habitat and biotic integrity of coastal Rhode Island streams

Watershed land use in suburban areas can affect stream biota through degradation of instream habitat, water quality, and riparian vegetation. By monitoring stream biotic communities in various geographic regions, we can better understand and conserve our watershed ecosystems. The objective of this study was to examine the relationship between watershed land use and the integrity of benthic invertebrate communities in eight streams that were assessed over a 3-year period (2001-2003). Sites were selected from coastal Rhode Island watersheds along a residential land-use gradient (4-59%). Using the rapid bioassessment protocol, we collected biological, physicochemical, habitat, and nutrient data from wadeable stream reaches and compared metrics of structure and integrity. Principal component analyses showed significant negative correlation of indicators for stream physicochemical, habitat, and instream biodiversity with increasing residential land use (RLU) in the watershed. The physicochemical variables that were most responsive to percent RLU were conductivity, instream habitat, nitrate, and dissolved inorganic nitrogen (DIN). The positive correlation of DIN with percent RLU indicated an anthropogenic source of pollution affecting the streams. The biotic composition of the streams shifted from sensitive to insensitive taxa as percent RLU increased; the most responsive biological variables were percent Ephemeroptera, percent Scrapers, percent Insects, and the Hilsenhoff biotic index. These data show the importance of land management and conservation at the watershed scale to sustaining the biotic integrity of coastal stream ecosystems.     

Riparian vegetation assessment of Cauvery River Basin of South India

The Cauvery river basin of South India has a large phyto-floristic wealth, rightfully enough to constitute a separate phyto-geographic unit. Increase in the anthropogenic pressures within the river basin and surrounding landscapes have persistently stressed the riparian ecosystem structure adversely, besides altering its composition. The objective of this study was to examine the present status of riparian vegetation along the Cauvery river basin, in response to anthropogenic pressures. For vegetation analysis, the riparian forest coming in the middle stretch of Cauvery river was categorized into two zones, viz., forest zone covering ~54 km stretch and agroecosystem zone covering ~80 km stretch. In each zone, tree species were quantified using transects at 8-km interval. Overall tree species accounting for both forest and agroecosystem were recorded and compared. The results indicate that the mean density and basal area of trees per plot were higher in the forest zone than agroecosystem zone. The Shannon–Weiner diversity of forest zone is 4.6, which is higher than agroecosystem. In addition, species composition indicated a relatively low or poor similarity between the two zones. The vegetation density and site disturbance scores for all the study sites reveals that sand mining and grazing areas have exerted negative impact on riparian forest. The results of the present study clearly brought out the need for preparing and implementing site-specific conservation plans for riparian ecosystem.     

The effect of river damming on vegetation: is it always unfavourable? A case study from the River Tiber (Italy)

River damming leads to strong hydromorphological alterations of the watercourse, consequently affecting river vegetation pattern. A multitemporal and spatial analysis of the dam effect on composition, structure and dynamic of the upstream vegetation was performed on Tiber River at Nazzano-dam (Rome). The main research questions were as follows: How does plant landscape vary over time and along the river? Where does the dam effect on vegetation end? How does naturalistic importance of the vegetation affected by damming change over time? Data collection was performed mapping the vegetation in aerial photos related to the period before (1944), during (1954) and after dam construction (1984, 2000). The plant landscape has significantly changed over time and along the river, particularly as a result of the dam construction (1953). The major vegetation changes have involved riparian forests and macrophytes. Dam effect on vegetation is evident up to 3 km, and gradually decreases along an attenuation zone for about another 3 km. Despite the fact that the damming has caused strong local hydromorphological modification of the river ecosystem transforming it into a sub-lacustrine habitat, it has also led to the formation of wetlands of considerable naturalistic importance. Indeed, in these man-made wetlands, optimal hydrological conditions have been created by favouring both the expansion of pre-existing riparian communities and the rooting of new aquatic communities, albeit typical of lacustrine ecosystems. Some of these plant communities have become an important food resource, refuge or nesting habitats for aquatic fauna, while others fall into category of Natura 2000 habitats. Therefore, river damming seems to have indirectly had a “favourable” effect for habitat conservation and local biodiversity.     

Assessing the wildlife habitat value of New England salt marshes: I. Model and application

We developed an assessment model to quantify the wildlife habitat value of New England salt marshes based on marsh characteristics and the presence of habitat types that influence habitat use by terrestrial wildlife. Applying the model to 12 salt marshes located in Narragansett Bay, RI resulted in assessment scores that ranged over a factor of 1.5 from lowest to highest. Pre-classifying the results based on marsh size and morphology helped to compare assessment scores between marshes, and demonstrated that even the lower ranking marshes had substantial habitat value. Stepwise multiple regression analysis of assessment scores and model components demonstrated that salt marsh morphology, the degree of anthropogenic modification, and salt marsh vegetative heterogeneity were significant variables and accounted for 91.3% of the variability in component scores. Our results suggest that targeting these components for restoration may lead to improved assessment scores for our study marshes. We also examined the use of lower resolution remote sensing data in the assessment in order to minimize the time and effort required to complete the model. Scores obtained using smaller-scale, lower resolution data were significantly lower than those obtained using larger-scale, higher resolution data (df = 11; t = 2.2; p < 0.001). The difference was significantly positively correlated with the portion of the assessment score that could be attributed to trees, pools, and pannes and marsh size (r (2) =0.50, F = 4.6, p = 0.04), and could indicate a bias against smaller, more heterogeneous marshes. We conclude that potential differences need to be weighed against the time benefit of using this type of data, bearing in mind the marsh size and the goals of the assessment. Overall, our assessment can provide information to aid in prioritizing marshes for protection and restoration, identify marshes that may harbor significant biodiversity, or help monitor changes in habitat value over time.     

Effects of geomorphology, habitat, and spatial location on fish assemblages in a watershed in Ohio, USA

In this paper, we evaluate relationships between in-stream habitat, water chemistry, spatial distribution within a predominantly agricultural Midwestern watershed and geomorphic features and fish assemblage attributes and abundances. Our specific objectives were to: (1) identify and quantify key environmental variables at reach and system wide (watershed) scales; and (2) evaluate the relative influence of those environmental factors in structuring and explaining fish assemblage attributes at reach scales to help prioritize stream monitoring efforts and better incorporate all factors that influence aquatic biology in watershed management programs. The original combined data set consisted of 31 variables measured at 32 sites, which was reduced to 9 variables through correlation and linear regression analysis: stream order, percent wooded riparian zone, drainage area, in-stream cover quality, substrate quality, gradient, cross-sectional area, width of the flood prone area, and average substrate size. Canonical correspondence analysis (CCA) and variance partitioning were used to relate environmental variables to fish species abundance and assemblage attributes. Fish assemblages and abundances were explained best by stream size, gradient, substrate size and quality, and percent wooded riparian zone. Further data are needed to investigate why water chemistry variables had insignificant relationships with IBI scores. Results suggest that more quantifiable variables and consideration of spatial location of a stream reach within a watershed system should be standard data incorporated into stream monitoring programs to identify impairments that, while biologically limiting, are not fully captured or elucidated using current bioassessment methods.     

Assessing the ecological condition of streams in a southeastern Brazilian basin using a probabilistic monitoring design

Prompt assessment and management actions are required if we are to reduce the current rapid loss of habitat and biodiversity worldwide. Statistically valid quantification of the biota and habitat condition in water bodies are prerequisites for rigorous assessment of aquatic biodiversity and habitat. We assessed the ecological condition of streams in a southeastern Brazilian basin. We quantified the percentage of stream length in good, fair, and poor ecological condition according to benthic macroinvertebrate assemblage. We assessed the risk of finding degraded ecological condition associated with degraded aquatic riparian physical habitat condition, watershed condition, and water quality. We describe field sampling and implementation issues encountered in our survey and discuss design options to remedy them. Survey sample sites were selected using a spatially balanced, stratified random design, which enabled us to put confidence bounds on the ecological condition estimates derived from the stream survey. The benthic condition index indicated that 62 % of stream length in the basin was in poor ecological condition, and 13 % of stream length was in fair condition. The risk of finding degraded biological condition when the riparian vegetation and forests in upstream catchments were degraded was 2.5 and 4 times higher, compared to streams rated as good for the same stressors. We demonstrated that the GRTS statistical sampling method can be used routinely in Brazilian rain forests and other South American regions with similar conditions. This survey establishes an initial baseline for monitoring the condition and trends of streams in the region.     

Sediment grain size estimation using airborne remote sensing, field sampling, and robust statistic

Remote sensing has been used since the 1980s to study parameters in relation with coastal zones. It was not until the beginning of the twenty-first century that it started to acquire imagery with good temporal and spectral resolution. This has encouraged the development of reliable imagery acquisition systems that consider remote sensing as a water management tool. Nevertheless, the spatial resolution that it provides is not adapted to carry out coastal studies. This article introduces a new methodology for estimating the most fundamental physical property of intertidal sediment, the grain size, in coastal zones. The study combines hyperspectral information (CASI-2 flight), robust statistic, and simultaneous field work (chemical and radiometric sampling), performed over Santander Bay, Spain. Field data acquisition was used to build a spectral library in order to study different atmospheric correction algorithms for CASI-2 data and to develop algorithms to estimate grain size in an estuary. Two robust estimation techniques (MVE and MCD multivariate M-estimators of location and scale) were applied to CASI-2 imagery, and the results showed that robust adjustments give acceptable and meaningful algorithms. These adjustments have given the following R(2) estimated results: 0.93 in the case of sandy loam contribution, 0.94 for the silty loam, and 0.67 for clay loam. The robust statistic is a powerful tool for large dataset.     

An automated (novel) algorithm for estimating green vegetation cover fraction from digital image: UIP-MGMEP

Green vegetation cover fraction (VCF) is an important indicator of vegetation status in ecology and agronomy. Digital image analysis (DIA) has been widely accepted as a new VCF measurement technique. In this study, we present a novel fully automatic threshold segmentation algorithm for VCF measurements, which is named as upper inflection point plus mean gradient magnitude of edge pixels (UIP-MGMEP). The algorithm performs VCF estimation upon the vegetation index Excess Green (EXG). UIP-MGMEP optimizes the EXG threshold by searching the upper inflection point (UIP) of the M-Et curve (mean gradient magnitude of edge pixels (MGMEP) vs. EXG threshold), based on the assumption that EXG variance of the boundary pixels between vegetation and background is larger than the variance of the background. Five typical sample images are used to illustrate how ground complexity reduces the distinctness of the UIP. Three controlled experiments are illustrated to test the robustness of UIP-MGMEP to resolution, exposure, and ground complexity. The results show that UIP-MGMEP is a promising algorithm for automatic VCF estimation upon digital images. Compared to broad-leaved grass, narrow-leaved grass is more sensitive to resolution and exposure. To reduce ground complexity, smaller footprint size while more images to cover the same area may be better than one image with large footprint size. UIP-MGMEP is fully automatic, making it promising for batch processing of VCF measurements that is very difficult in any wide-range field survey in the past. UIP-MGMEP algorithm can only extract green vegetation and is not suitable for non-green (even grayish-green) vegetation, due to the limits of vegetation index EXG. In addition, UIP-MGMEP is not recommended for images with VCF less than 0.5% or greater than 99.5%.     

Precision Measurements from Very-Large Scale Aerial Digital Imagery

Managers need measurements and resource managers need the length/width of a variety of items including that of animals, logs, streams, plant canopies, man-made objects, riparian habitat, vegetation patches and other things important in resource monitoring and land inspection. These types of measurements can now be easily and accurately obtained from very large scale aerial (VLSA) imagery having spatial resolutions as fine as 1 millimeter per pixel by using the three new software programs described here. VLSA images have small fields of view and are used for intermittent sampling across extensive landscapes. Pixel-coverage among images is influenced by small changes in airplane altitude above ground level (AGL) and orientation relative to the ground, as well as by changes in topography. These factors affect the object-to-camera distance used for image-resolution calculations. ‘ImageMeasurement’ offers a user-friendly interface for accounting for pixel-coverage variation among images by utilizing a database. ‘LaserLOG’ records and displays airplane altitude AGL measured from a high frequency laser rangefinder, and displays the vertical velocity. ‘Merge’ sorts through large amounts of data generated by LaserLOG and matches precise airplane altitudes with camera trigger times for input to the ImageMeasurement database. We discuss application of these tools, including error estimates. We found measurements from aerial images (collection resolution: 5–26 mm/pixel as projected on the ground) using ImageMeasurement, LaserLOG, and Merge, were accurate to centimeters with an error less than 10%. We recommend these software packages as a means for expanding the utility of aerial image data.     

Seagrass resource assessment using remote sensing methods in St. Joseph Sound and Clearwater Harbor,Florida, USA

In the event of a natural or anthropogenic disturbance, environmental resource managers require a reliable tool to quickly assess the spatial extent of potential damage to the seagrass resource. The temporal availability of the Landsat 5 Thematic Mapper (TM) imagery provided a suitable option to detect and assess damage of the submerged aquatic vegetation (SAV). This study examined Landsat TM imagery classification techniques to create two-class (SAV presence/absence) and three-class (SAV estimated coverage) SAV maps of the seagrass resource. The Mahalanobis Distance method achieved the highest overall accuracy (86%) and validation accuracy (68%) for delineating the seagrass resource (two-class SAV map). The Maximum Likelihood method achieved the highest overall accuracy (74%) and validation accuracy (70%) for delineating the seagrass resource three-class SAV map. The Landsat 5 TM imagery classification provided a seagrass resource map product with similar accuracy to the aerial photointerpretation maps (validation accuracy 71%). The results support the application of remote sensing methods to analyze the spatial extent of the seagrass resource.     

A bioassessment approach for mid-continent great rivers: the Upper Mississippi, Missouri, and Ohio (USA)

The objectives of the Environmental Monitoring and Assessment Program for Great River Ecosystems (EMAP-GRE) are to (1) develop and demonstrate, in collaboration with states, an assessment program yielding spatially unbiased estimates of the condition of mid-continent great rivers; (2) evaluate environmental indicators for assessing great rivers; and (3) assess the current condition of selected great river resources. The purpose of this paper is to describe EMAP-GRE using examples based on data collected in 2004-2006 with emphasis on an approach to determining reference conditions. EMAP-GRE includes the Upper Mississippi River, the Missouri River, and the Ohio River. Indicators include biotic assemblages (fish, macroinvertebrates, plankton, algae), water chemistry, and aquatic and riparian physical habitat. Reference strata (river reaches for which a single reference expectation is appropriate) were determined by ordination of the fish assemblage and examination of spatial variation in environmental variables. Least disturbed condition of fish assemblages for reference strata was determined by empirical modeling in which we related fish assemblage metrics to a multimetric stressor gradient. We inferred least disturbed condition from the y-intercept, the predicted condition when stress was least. Thresholds for dividing the resource into management-relevant condition classes for biotic indicators were derived using predicted least disturbed condition to set the upper bound on the least disturbed condition class. Also discussed are the outputs of EMAP-GRE, including the assessment document, multimetric indices of condition, and unbiased data supporting state and tribal Clean Water Act reporting, adaptive management, and river restoration.     

An assessment of the impacts of timber plantations on water quality and biodiversity values of Marbellup Brook, Western Australia

Despite the fact that the establishment and maintenance of blue gum plantations can potentially result in the removal of riparian vegetation, the presence of increased levels of sediments, pesticides, and nutrients, and consequently, the loss of in-stream biodiversity, few studies exist that have looked at the impacts of timber plantations on in-stream biota. The goals of this study were thus to determine water quality, riparian condition, and in-stream biodiversity values of local streams draining blue gum plantations in the Marbellup Brook catchment in Western Australia and to compare these values with those of streams associated with other land uses. Selected water quality and habitat variables and in-stream macroinvertebrate biodiversity were measured in 2006 and 2007 at 28 sites falling into five broad categories based on the predominant land use within 200 m of each study reach. Overall, the results indicated that ??blue gum plantation?? sites often had better water quality, riparian condition, and biodiversity values than ??pasture unfenced,?? and sometimes ??pasture fenced?? sites, but water quality and biodiversity values at these sites were not as good as those associated with ??remnant?? native vegetation sites. The location of the blue gum plantation sites along the disturbance gradient investigated was attributed to both present management and past land uses in the subcatchments investigated. As this study was conducted at a time when blue gum plantations were in an on-growing phase, it was recommended that future research on the impact of blue gum plantations on waterways in southwestern Australia should include an investigation of the impacts of timber clear-cutting and extraction. Longer-term cumulative and downstream effects of blue gum plantations on local waterways also need to be investigated.     

Integrating in-situ, Landsat, and MODIS data for mapping in Southern African savannas: experiences of LCCS-based land-cover mapping in the Kalahari in Namibia

Integrated ecosystem assessment initiatives are important steps towards a global biodiversity observing system. Reliable earth observation data are key information for tracking biodiversity change on various scales. Regarding the establishment of standardized environmental observation systems, a key question is: What can be observed on each scale and how can land cover information be transferred? In this study, a land cover map from a dry semi-arid savanna ecosystem in Namibia was obtained based on the UN LCCS, in-situ data, and MODIS and Landsat satellite imagery. In situ botanical relevé samples were used as baseline data for the definition of a standardized LCCS legend. A standard LCCS code for savanna vegetation types is introduced. An object-oriented segmentation of Landsat imagery was used as intermediate stage for downscaling in-situ training data on a coarse MODIS resolution. MODIS time series metrics of the growing season 2004/2005 were used to classify Kalahari vegetation types using a tree-based ensemble classifier (Random Forest). The prevailing Kalahari vegetation types based on LCCS was open broadleaved deciduous shrubland with an herbaceous layer which differs from the class assignments of the global and regional land-cover maps. The separability analysis based on Bhattacharya distance measurements applied on two LCCS levels indicated a relationship of spectral mapping dependencies of annual MODIS time series features due to the thematic detail of the classification scheme. The analysis of LCCS classifiers showed an increased significance of life-form composition and soil conditions to the mapping accuracy. An overall accuracy of 92.48% was achieved. Woody plant associations proved to be most stable due to small omission and commission errors. The case study comprised a first suitability assessment of the LCCS classifier approach for a southern African savanna ecosystem.     

Factors influencing the sinuosity of Pannagon River, Kottayam, Kerala, India: An assessment using remote sensing and GIS

The present study was carried out to identify the factors influencing the sinuosity of the Pannagon river, using the IRS P6 LISS III data and Geographical Information System (GIS) on 1:50,000 scale. The river follows meandering course and exhibits a narrow, highly sinuous and incised channel. Several lines of evidence including satellite and topographic data, geological maps and field investigations and the generated themes on lithology, structure, geomorphology, slope, riparian vegetation and hydrology have analyzed to understand the controls on the channel morphology of the Pannagon river. The average of sinuosity index of the selected reaches in the river on 1967 was 1.6 and of 2004 was 1.8. The sinuous patches are more in the lower reaches of the river and most of the area comes under floodplain with thick column of alluvial deposits. The analysis shown that the style and degree of sinuosity of the Pannagon river depends on a number of geological factors, including tectonics and the riparian vegetation also plays a major role.     

Local versus landscape spatial influence on biodiversity: a case study across five European industrialized areas

Land use change—mostly habitat loss and fragmentation—has been recognized as one of the major drivers of biodiversity loss worldwide. According to the habitat amount hypothesis, these phenomena are mostly driven by the habitat area effect. As a result, species richness is a function of both the extent of suitable habitats and their availability in the surrounding landscape, irrespective of the dimension and isolation of patches of suitable habitat. In this context, we tested how the extent of natural areas, selected as proxies of suitable habitats for biodiversity, influences species richness in highly anthropogenic landscapes. We defined five circular sampling areas of 5 km radius, including both natural reserves and anthropogenic land uses, centred in five major industrial sites in France, Italy and Germany. We monitored different biodiversity indicators for both terrestrial and aquatic ecosystems, including breeding birds, diurnal butterflies, grassland vegetation, odonata, amphibians, aquatic plants and benthic diatoms. We studied the response of the different indicators to the extent of natural land uses in the sampling area (local effect) and in the surrounding landscape (landscape effect), identified as a peripheral ring encircling the sampling area. Results showed a positive response of five out of seven biodiversity indicators, with aquatic plants and odonata responding positively to the local effect, while birds, vegetation and diatoms showed a positive response to the landscape effect. Diatoms also showed a significant combined response to both effects. We conclude that surrounding landscapes act as important biodiversity sources, increasing the local biodiversity in highly anthropogenic contexts.