Mapping Grazing-Induced Degradation in a Semi-Arid Environment: A Rapid and Cost Effective Approach for Assessment and Monitoring

Improved techniques for measuring and monitoring the state of biodiversity are required for reporting on national obligations to international and regional conservation institutions. Measuring the extent of grazing-related degradation in semi-arid ecosystems has proved difficult. Here we present an accurate and cost-effective method for doing this, and apply it in a South African semi-arid region that forms part of a globally significant biodiversity hotspot. We grouped structurally and functionally similar vegetation units, which were expert-mapped at the 1:50,000 scale, into four habitat types, and developed habitat-specific degradation models. We quantified degradation into three categories, using differences between dry and wet season values of the Normalized Difference Vegetation Index (NDVI) for the three succulent karoo habitats, and the difference between maximum and mean NDVI values for the subtropical thicket habitat. Field evaluation revealed an accuracy of 86%. Overall, degradation was high: 24% of the study area was modeled as severely degraded, and only 9% as intact. Levels of degradation were highest for bottomland habitats that were most exposed to grazing impacts. In sharp contrast to our methods, a widely used, broad-scale and snapshot assessment of land cover in South Africa was only 33% accurate, and it considerably underestimated the extent of severely degraded habitat in the study area. While our approach requires a multidisciplinary team, and in particular expert knowledge on the characteristics and spatial delimitation of vegetation types, it is repeatable, rapid, and relatively inexpensive. Consequently, it holds great promise for monitoring and evaluation programs in semi-arid ecosystems, in Africa, and beyond.     

Describing and Mapping Human-Induced Vegetation Change in the Australian Landscape

Australian reporting requirements for native vegetation require improved spatial and temporal information on the anthropogenic effects on vegetation. This includes better linkage of information on vegetation type (e.g., native vegetation association), extent and change, vegetation condition, or modification. The Vegetation Assets, States and Transitions (VAST) framework is presented as a means for ordering vegetation by degree of anthropogenic modification as a series of condition states, from a residual or base-line condition through to total removal. The VAST framework facilitates mapping and accounting for change and trends in the status and condition of vegetation. The framework makes clear the links between land management and vegetation condition states, provides a mechanism for describing the consequences of land management practices on vegetation condition, and contributes to an understanding of resilience. VAST is a simple communication and reporting tool designed to assist in describing and accounting for anthropogenic modification of vegetation. A benchmark is identified for each vegetation association. Benchmarks are based on structure, composition, and current regenerative capacity. This article describes the application of the VAST framework as a consistent national framework to translate and compile existing mapped information on the modification of native vegetation. We discuss the correspondence between these compiled VAST datasets at national and regional scales and describe their relevance for natural resource policy and planning.     

Isotopes, Wool, and Rangeland Monitoring: Let the Sheep Do the Sampling

3 and C₄ plant species consumed by animals. Sheep sample vegetation continuously throughout a year, and as their wool grows it integrates and stores information about their diet. In subtropical and tropical rangelands the majority of grass species are C₄. Since sheep prefer to graze, and their wool is an isotopic record of their diet, we now have the potential to develop a high resolution index to the availability of grass from a sheep's perspective. Isotopic analyses of wool suggest a new direction for monitoring grazing and for the reconstruction of past vegetation changes, which will make a significant contribution to traditional rangeland ecology and management. It is recommended that isotopic and other analyses of wool be further developed for use in rangeland monitoring programs to provide valuable feedback for land managers.     

Preliminary Evidence for Pollen as an Indicator of Recent Floodplain Accumulation Rates and Vegetation Changes: The Barmah-Millewa Forest, SE Australia

Eucalyptus forest; and in the composition of understorey herbs, sedges, and grasslands. Pollen concentration and charcoal and organic content also exhibit post-European changes. Thus, pollen analysis provides a technique for determining changes in sediment budgets and identifying major vegetation changes in floodplains.     

Trends in Vegetation Degradation in Relation to Land Tenure, Rainfall, and Population Changes in Peddie District, Eastern Cape, South Africa

Spatial and temporal variations in vegetation are examined in relation to land tenure, population increase, and rainfall variation in a part of Peddie district, Eastern Cape. Sequential aerial photographs between 1938 and 1988 are analyzed to determine trends in vegetation and population change in three different land-tenure units. The areal extent at each date of four distinct vegetation categories is determined using PC ARC/INFO GIS. Long-term annual rainfall trends for the area are analyzed and juxtaposed with vegetation changes. Extensive ground-truthing exercises are carried out to verify the present condition of vegetation condition in terms of cover and species composition. Differences in land-tenure systems are discerned as the dominant factor controlling variations in vegetation degradation. The study also reveals that neither population changes nor rainfall variations can explain the observed trends in vegetation degradation. Earlier injudicious land-use practices, sustained since the turn of the last century, may provide plausible explanations for the trends and present status of vegetation degradation in the area.     

Use of Descriptors of Ecosystem Functioning for Monitoring a National Park Network: A Remote Sensing Approach

Baseline assessments and monitoring of protected areas are essential for making management decisions, evaluating the effectiveness of management practices, and tracking the effects of global changes. For these purposes, the analysis of functional attributes of ecosystems (i.e., different aspects of the exchange of matter and energy) has advantages over the traditional use of structural attributes, like a quicker response to disturbances and the fact that they are easily monitored through remote sensing. In this study, we described the spatiotemporal patterns of different aspects of the ecosystem functioning of the Spanish national parks and their response to environmental changes between 1982 and 2006. To do so, we used the NOAA/AVHRR-GIMMS dataset of the Normalized Difference Vegetation Index (NDVI), a linear estimator of the fraction of photosynthetic active radiation intercepted by vegetation, which is the main control of carbon gains. Nearly all parks have significantly changed during the last 25 years: The radiation interception has increased, the contrast between the growing and nongrowing seasons has diminished, and the dates of maximum and minimum interception have advanced. Some parks concentrated more changes than others and the degree of change varied depending on their different environmental conditions, management, and conservation histories. Our approach identified reference conditions and temporal changes for different aspects of ecosystem functioning, which can be used for management purposes of protected areas in response to global changes.     

A GIS-based approach for assessing the regional conservation status of genetic diversity: an example from the southern Appalachians

Conserving genetic diversity requires an assessment of the distribution of genetic variants in relation to patterns of land use and environmental variation at a regional scale. This assessment requires a novel approach to integrating and analyzing the genetic and environmental data across spatial scales. To explore the integration of genetic data with other geospatial data sets, we developed a GIS-based approach for examining patterns of genetic diversity for several species of salamanders in southern Appalachians. The genetic data, from allozyme surveys in the genetics literature, were integrated into a GIS database along with related attributes including population identifications and spatial locations. Using existing geospatial data, we classified sample locations as being either protected from anthropogenic disturbance (e.g., National Parks, Wilderness Areas) or as unprotected (e.g., private lands, multiple-use lands in National Forests). We used multidimensional scaling of allelic frequencies and contributions of populations to interpopulation differences in allelic richness to determine which populations had genetic characteristics most different from other populations in the sample. Measures of genetic differentiation were integrated into the GIS database to facilitate spatial analysis and visualization of the indices in relation to land use. This approach was useful for both identification of populations with components of genetic variation that were not well represented at protected sites and for identifying areas of species distributions where more genetic sampling would be necessary to make informed management decisions. Our approach could be readily adapted for use by managers and geneticists working with other species and types of genetic markers.     

A Conceptual Model for Defining and Assessing Land Management Units Using a Fuzzy Modeling Approach in GIS Environment

Appropriate land management decisions are important for current and future use of the land to ensure its sustainability. This requires that land management units (LMUs) be specified to enable the identification of specific parameters employed in decision making processes. This paper presents the development of a conceptual model, within geographic information systems (GIS), for defining and assessing LMUs from available biophysical information. The model consists of two main components (sub-models): land quality-based suitability analysis and soil erosion estimation. Using a fuzzy set methodology, the first sub-model was constructed to derive a land suitability index (LSI) for a cropping land utilization type. The LSI thus highlights the suitability grades of every pixel in the study area on a continuous basis. A sub-model of soil erosion was established based on the Revised Universal Soil Loss Equation (RUSLE) utilising the same spatial data bases employed for structuring the LSI. Using a soil loss tolerance principle, a fuzzy membership function of average annual soil loss (called soil loss index, SLI) was established, leading to compatibility between LSI and SLI for data integration. LMUs were then derived from various combinations of LSI and SLI. The methodology developed shows the significance of the model for refining available land suitability evaluation systems, which take no account of expected land degradation (from erosion) due to a nominated land use. It also provides a valuable guideline for cost-effective GIS applications in the identification and assessment of homogeneous land units, using available spatial information sets, at a finer scale.     

A Comparison of Spatial and Spectral Image Resolution for Mapping Invasive Plants in Coastal California

We explored the potential of detecting three target invasive species: iceplant (Carpobrotus edulis), jubata grass (Cortaderia jubata), and blue gum (Eucalyptus globulus) at Vandenberg Air Force Base, California. We compared the accuracy of mapping six communities (intact coastal scrub, iceplant invaded coastal scrub, iceplant invaded chaparral, jubata grass invaded chaparral, blue gum invaded chaparral, and intact chaparral) using four images with different combinations of spatial and spectral resolution: hyperspectral AVIRIS imagery (174 wavebands, 4 m spatial resolution), spatially degraded AVIRIS (174 bands, 30 m), spectrally degraded AVIRIS (6 bands, 4 m), and both spatially and spectrally degraded AVIRIS (6 bands, 30 m, i.e., simulated Landsat ETM data). Overall success rates for classifying the six classes was 75% (kappa 0.7) using full resolution AVIRIS, 58% (kappa 0.5) for the spatially degraded AVIRIS, 42% (kappa 0.3) for the spectrally degraded AVIRIS, and 37% (kappa 0.3) for the spatially and spectrally degraded AVIRIS. A true Landsat ETM image was also classified to illustrate that the results from the simulated ETM data were representative, which provided an accuracy of 50% (kappa 0.4). Mapping accuracies using different resolution images are evaluated in the context of community heterogeneity (species richness, diversity, and percent species cover). Findings illustrate that higher mapping accuracies are achieved with images possessing high spectral resolution, thus capturing information across the visible and reflected infrared solar spectrum. Understanding the tradeoffs in spectral and spatial resolution can assist land managers in deciding the most appropriate imagery with respect to target invasives and community characteristics.     

A Hydrological Model for Predicting the Effects of Dams on the Shoreline Vegetation of Lakes and Reservoirs

/ The species richness of shoreline vegetation of unregulated lakes in Nova Scotia, Canada, is known to increase as a function of catchment area, a topographic variable governing water level fluctuations. Predictions based on catchment area however, fail to account for richness patterns at the margins of lakes enlarged by dams. Here, we compare the vegetation and hydrological regimes of regulated and unregulated systems. Hydrological regimes of regulated systems deviated from natural systems of similar catchment area by being either hypovariable or hypervariable for both within-year and among-year fluctuations in water level. Plant communities of dammed systems were less diverse, contained more exotic species, and were, with one exception, devoid of rare shoreline herbs. Data from "recovering," or previously dammed systems indicated that shoreline communities can be restored upon return of the appropriate hydrological regime. Using observed within-year and among-year water level fluctuation data, we propose a general model for the maintenance or restoration of diverse herbaceous wetlands on shorelines of temperate lakes or reservoirs. Managers can manipulate the within-year water level variation within prescribed limits (1-2 m), while ensuring that among-year variation (SD of summer levels) is less than 25% of within-year variation. This preliminary model is based on data from low-fertility, temperate lakes in river systems. To calibrate the model, plant community data from other regions are needed, as are long-term water-level data for unregulated lakes, data which are essential but largely lacking in many areas.KEY WORDS: Catchment area; Regulated lakes; Shoreline restoration; Rare plants; Exotic plants; Diversity     

A numerical model for drying of spherical object in an indirect type solar dryer and estimating the drying time at different moisture level and air temperature

A numerical model for simultaneous heat and mass transfer was developed for solar drying of spherical objects and the object considered is green peas. Solar collector outlet temperature is assumed as drying chamber temperature and justified through energy balance equations. Assumptions are imposed on heat and mass transfer governing equations without losing the physics of the problem. Discretization is performed by finite difference method with implicit scheme. To generalize, the governing equation and boundary conditions are non-dimensionalized. The set of finite difference equations was solved by Tridiagonal Matrix Algorithm and a computer code in MATLAB was developed to solve them. The drying curves showed two stages of drying, initial, and secondary drying stage. At all drying temperatures and drying time, the center moisture was maximum and it was minimum at the boundary. A percentage of 85.67 surface moisture content and 25.33% center moisture was eliminated in the first 1 hr at 348 K. The product should be dried up to 7.45, 4.74, and 3.74 hr at air drying temperatures of 318, 333, and 348 K respectively, to maintain 10% of the product’s initial moisture content. The result is compared with the experimental result from literature and they are found to be in good agreement.