Emergence of Indigenous Vegetation Classifications Through Integration of Traditional Ecological Knowledge and Remote Sensing Analyses

Traditional ecological knowledge (TEK) can play an important role in the understanding of ecological systems. Although TEK has complemented scientific and managerial programs in a variety of contexts, its formal incorporation into remote sensing exercises has to date been limited. Here, we show that the vegetation classifications of the Ache, an indigenous hunter-gatherer tribe of the Mbaracayu Forest Reserve in Paraguay, are reflected in a supervised classification of satellite imagery of the reserve. Accuracy of classification was toward the low end of the range of published values, but was reasonable given the difficult nature of separating forest classes from satellite images. Comparison of the resultant map with a more traditionally elaborated vegetation map highlights differences between the two approaches and the gain in information obtained by considering TEK classifications. We suggest that integration of TEK and remote sensing may provide alternative insights into the ecology of vegetation communities and land cover, particularly in remote and densely forested areas where ecological field research is often limited by roads and/or trail systems.     

基于高分辨率遥感影像的城市土地利用景观格局分析

以IKONOS卫星遥感影像为基础数据源,在GIS技术的支持下,获取了泸州市区的土地利用类型。借鉴景观生态学的基本原理和方法,基于Fragstats 3.3软件,用景观格局指数定量分析了泸州市区土地利用景观格局的特征。分析结果表明,泸州市区土地利用景观类型丰富,景观多样性程渡高,景观类型均匀程度也较高,但优势景观类型不明显;由于人类干扰程度较大,土地利用景观破碎,稳定性较差。     

Effects of sheep and goat grazing on the species diversity in the alpine meadows of Western Himalaya

This paper deals with effects of sheep and goat grazing on plant species diversity, species richness and species composition in two important conservation areas of the Western Himalaya; the Valley of Flowers (VOF) National Park and the Great Himalayan National Park (GHNP). The VOF is a completely Protected Area as it is devoid of livestock grazing whereas, 20,000 sheep and goats annually graze in GHNP. Both the National Parks possess sub-alpine and alpine vegetation that is distributed in 13 major habitat types. Present investigations indicate that all the habitat types in VOF are higher in plant species diversity and richness compared to habitat types in GHNP. Similarly, all three eco-climatic zones in VOF are higher in species diversity and richness compared to GHNP. Species diversity also decreases with increasing altitude in both the National Parks. The findings of this study are discussed in the light of the management and conservation of alpine meadows of the Western Himalayas.     

Integration of Visual Quality Considerations in Development of Israeli Vegetation Management Policy

This article deals with the visual quality of Mediterranean vegetation groups in northern Israel, the public's preference of these groups as a visual resource, and the policy options for their management. The study is based on a sample of 44 Mediterranean vegetation groups and three population groups of local residents, who were interviewed using a questionnaire and photographs of the vegetation groups. The results of the research showed that plant classification methods based on flora composition, habitat, and external appearance were found to be suitable for visual plant classification and for the evaluation of visual preference of vegetation groups by the interviewed public. The vegetation groups of planted pine forests and olive groves, characterizing a cultured vegetation landscape, were preferred over typical Mediterranean landscapes such as scrub and grassed scrub. The researchers noted a marked difference between the two products of vegetation management policy, one that proposes the conservation and restoration of the variety of native Mediterranean vegetation landscape, and a second that advanced the development of the cultured landscape of planted olive groves and pines forests, which were highly preferred by the public. The authors suggested the development of an integrated vegetation management policy that would combine both needs and thus reduce the gap between the policy proposed by planners and the local population's visual preference.     

Object-Based Classification as an Alternative Approach to the Traditional Pixel-Based Classification to Identify Potential Habitat of the Grasshopper Sparrow

The traditional method of identifying wildlife habitat distribution over large regions consists of pixel-based classification of satellite images into a suite of habitat classes used to select suitable habitat patches. Object-based classification is a new method that can achieve the same objective based on the segmentation of spectral bands of the image creating homogeneous polygons with regard to spatial or spectral characteristics. The segmentation algorithm does not solely rely on the single pixel value, but also on shape, texture, and pixel spatial continuity. The object-based classification is a knowledge base process where an interpretation key is developed using ground control points and objects are assigned to specific classes according to threshold values of determined spectral and/or spatial attributes. We developed a model using the eCognition software to identify suitable habitats for the Grasshopper Sparrow, a rare and declining species found in southwestern Québec. The model was developed in a region with known breeding sites and applied on other images covering adjacent regions where potential breeding habitats may be present. We were successful in locating potential habitats in areas where dairy farming prevailed but failed in an adjacent region covered by a distinct Landsat scene and dominated by annual crops. We discuss the added value of this method, such as the possibility to use the contextual information associated to objects and the ability to eliminate unsuitable areas in the segmentation and land cover classification processes, as well as technical and logistical constraints. A series of recommendations on the use of this method and on conservation issues of Grasshopper Sparrow habitat is also provided.     

Habitat, Landscape and Bird Composition in Mountain Forest Fragments

The study attempts to separate the effects of forest fragmentation related to landscape (patch area, isolation) and habitat (altitude, vegetation structure) on bird community composition in a mountain pine forest. Bird composition was related, using a multivariate approach (canonical correspondence analyses), to either habitat or to landscape, eliminating the effect of habitat statistically. Bird composition and species richness varied with patch area and isolation from large pine stands, but this effect could be assigned principally to variation in vegetation structure and altitude. Another effect, that of increasing occurrence and numbers of Anthus trivialis with decreasing distance to nearest low-altitude forest, could be assigned to both habitat (grass cover) and landscape (connectivity effects). Management implications are drawn from the results.     

Control of landscape diversity by catastrophic disturbance: A theory and a case study of fire in a Canadian boreal forest

A landscape may be envisioned as a space partitioned by a number of ecosystem types, and so it conforms to a neo-Clementsian model of succession. A corollary is that intermediate disturbance rates should maximize landscape (beta) diversity. This was confirmed using eight boreal forest landscapes in northwestern Ontario, Canada, where intermediate rates of forest fire were associated with highest landscape diversity. Because current measures of evenness subsume a richness measure, it is not, as yet, feasible to assess the relative contributions of evenness and richness to biological diversity, and thus it was not possible to determine the roles of numbers of habitat types and relative amounts of habitat types in the above situation. Both theory and observations suggest that forest fire control in fire-prone landscapes increases landscape diversity, but that it is lowered by fire control in landscapes of intermediate to low diversity.     

Maximizing Benefits from Riparian Revegetation Efforts: Local- and Landscape-Level Determinants of Avian Response

With limited financial resources available for habitat restoration, information that ensures and/or accelerates success is needed to economize effort and maximize benefit. In the Central Valley of California USA, riparian habitat has been lost or degraded, contributing to the decline of riparian-associated birds and other wildlife. Active restoration of riparian plant communities in this region has been demonstrated to increase local population sizes and species diversity of landbirds. To evaluate factors related to variation in the rate at which bird abundance increased after restoration, we examined bird abundance as a function of local (restoration design elements) and landscape (proportion of riparian vegetation in the landscape and riparian patch density) metrics at 17 restoration projects within five project areas along the Sacramento River. We developed a priori model sets for seven species of birds and used an information theoretic approach to identify factors associated with the rate at which bird abundance increased after restoration. For six of seven species investigated, the model with the most support contained a variable for the amount of riparian forest in the surrounding landscape. Three of seven bird species were positively correlated with the number of tree species planted and three of seven were positively correlated with the planting densities of particular tree species. Our results indicate that restoration success can be enhanced by selecting sites near existing riparian habitat and planting multiple tree species. Hence, given limited resources, efforts to restore riparian habitat for birds should focus on landscape-scale site selection in areas with high proportions of existing riparian vegetation.     

Community participatory landscape classification and biodiversity assessment and monitoring of grazing lands in northern Kenya

In this study, we asked the Ariaal herders of northern Kenya to answer "why, what and how" they classified landscape, and assessed and monitored the biodiversity of 10 km(2) of grazing land. To answer the "why question" the herders classified grazing resources into 39 landscape patches grouped into six landscape types and classified soil as 'warm', 'intermediate' or 'cold' for the purpose of land use. For the "what question" the herders used soil conditions and vegetation characteristics to assess biodiversity. Plant species were described as 'increasers', 'decreasers' or 'stable'. The decreaser species were mostly grasses and forbs preferred for cattle and sheep grazing and the increasers were mostly woody species preferred by goats. The herders evaluated biodiversity in terms of key forage species and used absence or presence of the preferred species from individual landscapes for monitoring change in biodiversity. For the "how question" the herders used anthropogenic indicators concerned with livestock management for assessing landscape potential and suitability for grazing. The anthropogenic indicators were related to soils and biodiversity. The herders used plant species grazing preferences to determine the links between livestock production and biodiversity. By addressing these three questions, the study shows the value of incorporating the indigenous knowledge of herders into classification of landscape and assessment and monitoring of biodiversity in the grazing lands. We conclude that herder knowledge of biodiversity is related to the use as opposed to exclusive conservation practices. This type of knowledge is extremely valuable to conservation agencies for establishing a baseline for monitoring changes in biodiversity in the future.     

Classification and spatial mapping of riparian habitat with applications toward management of streams impacted by nonpoint source pollution

Management of riparian habitats has been recognized for its importance in reducing instream effects of agricultural nonpoint source pollution. By serving as a buffer, well structured riparian habitats can reduce nonpoint source impacts by filtering surface runoff from field to stream. A system has been developed where key characteristics of riparian habitat, vegetation type, height, width, riparian and shoreline bank slope, and land use are classified as discrete categorical units. This classification system recognizes seven riparian vegetation types, which are determined by dominant plant type. Riparian and shoreline bank slope, in addition to riparian width and height, each consist of five categories. Classification by discrete units allows for ready digitizing of information for production of spatial maps using a geographic information system (GIS). The classification system was tested for field efficiency on Tom Beall Creek watershed, an agriculturally impacted third-order stream in the Clearwater River drainage, Nez Perce County, Idaho, USA. The classification system was simple to use during field applications and provided a good inventory of riparian habitat. After successful field tests, spatial maps were produced for each component using the Professional Map Analysis Package (pMAP), a GIS program. With pMAP, a map describing general riparian habitat condition was produced by combining the maps of components of riparian habitat, and the condition map was integrated with a map of soil erosion potential in order to determine areas along the stream that are susceptible to nonpoint source pollution inputs. Integration of spatial maps of riparian classification and watershed characteristics has great potential as a tool for aiding in making management decisions for mitigating off-site impacts of agricultural nonpoint source pollution.     

Testing the Use of a Land Cover Map for Habitat Ranking in Boreal Forests

Habitat loss and modification is one of the major threats to biodiversity and the preservation of conservation values. We use the term conservation value to mean the benefit of nature or habitats for species. The importance of identifying and preserving conservation values has increased with the decline in biodiversity and the adoption of more stringent environmental legislation. In this study, conservation values were considered in the context of land-use planning and the rapidly increasing demand for more accurate methods of predicting and identifying these values. We used a k-nearest neighbor interpreted satellite (Landsat TM) image classified in 61 classes to assess sites with potential conservation values at the regional and landscape planning scale. Classification was made at the National Land Survey of Finland for main tree species, timber volume, land-use type, and soil on the basis of spectral reflectance in satellite image together with broad numerical reference data. We used the number and rarity of vascular plant species observed in the field as indicators for potential conservation values. We assumed that significant differences in the species richness, rarity, or composition of flora among the classes interpreted in the satellite image would also mean a difference in conservation values among these classes. We found significant differences in species richness among the original satellite image classes. Many of the classes examined could be distinguished by the number of plant species. Species composition also differed correspondingly. Rare species were most abundant in old spruce forests (>200 m³/ha), raising the position of such forests in the ranking of categories according to conservation values. The original satellite image classification was correct for 70% of the sites studied. We concluded that interpreted satellite data can serve as a useful source for evaluating habitat categories on the basis of plant species richness and rarity. Recategorization of original satellite image classification into such new conservation value categories is challenging because of the variation in species composition among the new categories. However, it does not represent a major problem for the purposes of early-stage land-use planning. Benefits of interpreted satellite image recategorization as a rapid conservation value assessment tool for land-use planners would be great.     

Identification and mapping of submerged plants in a shallow lake using Quickbird satellite data

Turkey is a country rich in lakes and wetlands--monitoring of all these will require advances in technology such as remote sensing. In this study, the aquatic plants of the large and shallow Lake Mogan, located in Central Anatolia were identified and mapped using high spatial resolution Quickbird imagery. As Lake Mogan is an important bird area the assessment of submerged plant species is of great value for ecosystem conservation and management. Quickbird multispectral image acquired on August 6, 2005 was geometrically corrected and a water mask was used based on strong absorption of Near Infrared (NIR) wavelengths by calm, clear and deep water. The water mask was applied using band reflectance values for a specific pixel satisfying the conditions of band decreasing property (Green>Red>NIR) and NIR相似文献   

高分辨率遥感影像在城市绿地信息提取中的应用研究

高分辨率卫星遥感图像数据量大、空间分辨率高、结构信息复杂、地物同物异谱现象更为突出等特征给专题信息提取技术带来了新的挑战。基于植被的光谱特征,利用监督分类、植被指数分类和目视解译等方法对QuickBird高分辨率卫星遥感影像的绿地信息进行提取,并对分类精度作了比对分析。研究结果表明,监督分类方法不能得到令人满意的结果,运用植被指数分类方法则有明显改善,其中归一化植被指数(NDVI)精度最高,因此NDVI能有效地对植被进行分类与识别。     

FORUM: Restoration of Stream Habitats in the Western United States: Restoration as Reexpression of Habitat Capacity

/ Ecological restoration is increasingly invoked as a tool for the maintenance and regeneration of biodiversity. Yet the conceptual foundations and assumptions underlying many restoration management activities are frequently unclear or unstated. Unforeseen, undesirable consequences of restoration activities may emerge as a result. A general conceptual framework for restoration is needed to better accommodate dynamic habitat systems and evolving biota in restoration strategies. A preliminary framework for stream habitat restoration emphasizing stream habitat-biota development is proposed. As developing systems, streams and stream biota exhibit temporal behaviors that change with stream environments. Underlying the dynamic development of streams is potential capacity. Streams express this capacity as an array of habitats over time and across the landscape. Human land uses in the western United States have rapidly altered aquatic habitats and the processes that shape habitat. As a result, the diversity of native fishes and their habitats has been suppressed. Restoration is fundamentally about allowing stream systems to reexpress their capacities. Several steps are provided to guide stream restoration activities. Key tasks include: identification of the historic patterns of habitat development; identification of developmental constraints; relief of those constraints; classification of sensitive, critical, or refuge habitats; protection of the developmental diversity that remains; and monitoring of biotic responses to habitat development. KEY WORDS: Stream habitat; Stream biota; System capacity; System development; Restoration; Classification     

A hybrid scheme for comparing the effects of bird diversity conservation approaches on landscape patterns and biodiversity in the Shangan sub-watershed in Taiwan

This work utilizes bird survey data, regression modeling, land-use modeling and landscape metrics to evaluate the effects of various spatial bird diversity conservation approaches on land-use allocation, land-use patterns, and biodiversity in the Shangan sub-watershed in central Taiwan. A survey of the distribution of species revealed that bird species are concentrated in the central and western parts of the sub-watershed. The results obtained using a Shannon-Weaver diversity regression model suggest that diversity of land-use increases the diversity of bird species. Logistic regression results verify that socio-economic factors determine the potential advantages of designating a particular type of land-use in certain parts of the study area. The results of land-use simulation modeling indicate that the eastern and southwestern areas of the sub-watershed will change most frequently between 2007 and 2017. Additionally, increasing the areas to protect bird diversity will effectively increase the patch size, habitat core area, edge effect and habitat connectivity. The Shannon-Weaver diversity regression model shows that protecting bird species diversity in large areas increases bird diversity. The proposed modeling approach is an effective tool that provides useful information for ecological planning and policymaking related to watersheds.     

Managing Radioactively Contaminated Land: Implications for Habitat Diversity

Radioactive contamination of agricultural land may necessitate long-term changes in food production systems, through application of selected countermeasures, in order to reduce the accumulation of radionuclides in food. We quantified the impact of selected countermeasures on habitat diversity, using the hypothetical case of two agricultural areas in Finland. The management scenarios studied were conversions from grassland to cereal production and from grassland and crop production to afforestation. The two study sites differed with respect to present agricultural production: one being predominantly cereal production and seminatural grasslands, while the other was dominated by intensive grass and dairy production. Some of the management scenarios are expected to affect landscape structures and habitat diversity. These potential changes were assessed using a spatial pattern analysis program in connection with geographic information systems. The studied landscape changes resulted in a more monotonous landscape structure compared to the present management, by increasing the mean habitat patch size, reducing the total habitat edge length and reducing the overall habitat diversity calculated by the Shannon diversity index. The degree of change was dependent on the present agricultural management practice in the case study sites. Where dairy production was predominant, the landscape structure changes were mostly due to conversion of intensive pastures and grasslands to cereal production. In the area dominated by cereal production and seminatural grasslands, the greatest predicted impacts resulted from afforestation of meadows and pastures. The studied management changes are predicted to reduce biodiversity at the species level as well as diminishing species-rich habitats. This study has predicted prominent side effects in habitat diversity resulting from application of management scenarios. These potential long-term impacts should be considered by decision-makers when planning future strategies in the event of radionuclide deposition.     

Seasonal change detection of riparian zones with remote sensing images and genetic programming in a semi-arid watershed

Riparian zones are deemed significant due to their interception capability of non-point source impacts and the maintenance of ecosystem integrity region wide. To improve classification and change detection of riparian buffers, this paper developed an evolutionary computational, supervised classification method--the RIparian Classification Algorithm (RICAL)--to conduct the seasonal change detection of riparian zones in a vast semi-arid watershed, South Texas. RICAL uniquely demonstrates an integrative effort to incorporate both vegetation indices and soil moisture images derived from LANDSAT 5 TM and RADARSAT-1 satellite images, respectively. First, an estimation of soil moisture based on RADARSAT-1 Synthetic Aperture Radar (SAR) images was conducted via the first-stage genetic programming (GP) practice. Second, for the statistical analyses and image classification, eight vegetation indices were prepared based on reflectance factors that were calculated as the response of the instrument on LANDSAT. These spectral vegetation indices were then independently used for discriminate analysis along with soil moisture images to classify the riparian zones via the second-stage GP practice. The practical implementation was assessed by a case study in the Choke Canyon Reservoir Watershed (CCRW), South Texas, which is mostly agricultural and range land in a semi-arid coastal environment. To enhance the application potential, a combination of Iterative Self-Organizing Data Analysis Techniques (ISODATA) and maximum likelihood supervised classification was also performed for spectral discrimination and classification of riparian varieties comparatively. Research findings show that the RICAL algorithm may yield around 90% accuracy based on the unseen ground data. But using different vegetation indices would not significantly improve the final quality of the spectral discrimination and classification. Such practices may lead to the formulation of more effective management strategies for the handling of non-point source pollution, bird habitat monitoring, and grazing and live stock management in the future.     

Resource Selection Probability Functions for Gopher Tortoise: Providing a Management Tool Applicable Across the Species’ Range

The gopher tortoise (Gopherus polyphemus) is protected by conservation policy throughout its range. Efforts to protect the species from further decline demand detailed understanding of its habitat requirements, which have not yet been rigorously defined. Current methods of identifying gopher tortoise habitat typically rely on coarse soil and vegetation classifications, and are prone to over-prediction of suitable habitat. We used a logistic resource selection probability function in an information-theoretic framework to understand the relative importance of various environmental factors to gopher tortoise habitat selection, drawing on nationwide environmental datasets, and an existing tortoise survey of the Ft. Benning military base. We applied the normalized difference vegetation index (NDVI) as an index of vegetation density, and found that NDVI was strongly negatively associated with active burrow locations. Our results showed that the most parsimonious model included variables from all candidate model types (landscape features, topography, soil, vegetation), and the model groups describing soil or vegetation alone performed poorly. These results demonstrate with a rigorous quantitative approach that although soil and vegetation are important to the gopher tortoise, they are not sufficient to describe suitable habitat. More widely, our results highlight the feasibility of constructing highly accurate habitat suitability models from data that are widely available throughout the species’ range. Our study shows that the widespread availability of national environmental datasets describing important components of gopher tortoise habitat, combined with existing tortoise surveys on public lands, can be leveraged to inform knowledge of habitat suitability and target recovery efforts range-wide.     

Potential Effects of Direct Transfer Payments on Farmland Habitat Diversity in a Marginal European Landscape

Farmland habitat diversity in marginal European landscapes changed significantly in the past decades. Further changes toward homogenization are expected, particularly in the course of European agricultural policy. Based on three alternative transfer payment schemes, we modeled spatially explicit potential effects on the farmland habitat diversity in a marginal European landscape. We defined (1) a scenario with direct transfer payments coupled to production, (2) a scenario with direct transfer payments decoupled from production, and (3) a scenario phasing out all direct transfer payments. We characterized habitat diversity with three indices: habitat richness, evenness, and rarity. The habitat pattern in 1995 served as reference for comparison. All scenarios predicted a general trend of homogenization of the farmland habitat pattern, yet to a differing extent. Transfer payments coupled to production (Scenario 1) favored the abandonment of agricultural production, particularly in low-productive areas and arable land use in more productive areas. Habitat richness and habitat evenness had intermediate values in this scenario. Decoupling transfer payments from production (Scenario 2) supported grassland as most profitable farming system. This led to a grassland-dominated landscape with low values of all habitat diversity indices. Phasing out transfer payments (Scenario 3) resulted in complete abandonment or afforestation of agricultural land and extremely low values in all habitat diversity indices. Scenario results indicate that transfer payments may prevent cessation of agricultural production, but may not counteract homogenization in marginal landscapes. Conserving high farmland habitat diversity in such landscapes may require support schemes, e.g., Pillar Two of EU Common Agricultural Policy.