Habitat inventory at a regional scale: a comparison of estimates of terrestrial Broad Habitat cover from stratified sample field survey and full census field survey for Wales, UK

Estimates of terrestrial Broad Habitat cover for Wales from the Countryside Survey 2000 stratified sample field mapping programme in Britain are compared with the findings of a full census field mapping project, the Habitat Survey of Wales. The Countryside Survey sampling regime comprised a stratified random sample of 1 km squares [corrected] covering <0.5% of the land surface. Comparative assessment indicates that although few of the sample-derived estimates for individual Broad Habitats are within 30% of the full census survey results, relative extents accord with data from the complete census survey for all Broad Habitats apart from Arable & Horticultural. The accuracy of this estimate is improved when the national boundary of Wales is taken into account in the sample stratification scheme. It is suggested that cultural land-use differences between countries render cropland habitat extent less predictable from physical environmental parameters than semi-natural habitat extent. It is also shown that the precision of sample-derived cover estimates is influenced by habitat pattern: the error term associated with habitats of broadly equal extent is greater for those with the most clumped distributions.     

Woodland restoration in Scotland: ecology, history, culture, economics, politics and change

In the latter half of the 20th century, native pine woodlands in Scotland were restricted to small remnant areas within which there was little regeneration. These woodlands are important from a conservation perspective and are habitat for numerous species of conservation concern. Recent developments have seen a large increase in interest in woodland restoration and a dramatic increase in regeneration and woodland spread. The proximate factor enabling this regeneration is a reduction in grazing pressure from sheep and, particularly, deer. However, this has only been possible as a result of a complex interplay between ecological, political and socio-economic factors. We are currently seeing the decline of land management practices instituted 150-200 years ago, changes in land ownership patterns, cultural revival, and changes in societal perceptions of the Scottish landscape. These all feed into the current move to return large areas of the Scottish Highlands to tree cover. I emphasize the need to consider restoration in a multidisciplinary framework which accounts not just for the ecology involved but also the historical and cultural context.     

Environmental and Strategic Uncertainty in Common Property Management: The Case of Scottish Red Deer

The range of red deer populations in the Scottish Highlands can cover several different landholdings (estates), many of which derive their income primarily from the private hunting (stalking) of stags. The deer belong to nobody and their seasonal movement does not respect the boundaries of individual estates, but a 'rule of capture' does apply as, once shot, the deer become the property of the estate owner. This paper argues that deer populations would best be managed as a common property resource. Indeed, for this reason, the Deer Commission for Scotland has encouraged owners to form Deer Management Groups. These groups are now able to utilize a computer program that models the relationship between grazing quality and population dynamics. However, drawing upon examples from the Western Highlands, the paper finds that common property management must overcome incentives to behave strategically that arise from the characteristics of flow and storage of the resource. The problem is aggravated by the degradation of the habitat that has occurred over centuries. This often means that the resource is below its optimum in terms of stag numbers and quality. Scientific models are an important contribution, but only reduce the environmental uncertainty. Their full potential can only be realized if all landowners are obliged to actively engage in common property management.     

Modeling Streams and Hydrogeomorphic Attributes in Oregon From Digital and Field Data1

Abstract: Managers, regulators, and researchers of aquatic ecosystems are increasingly pressed to consider large areas. However, accurate stream maps with geo‐referenced attributes are uncommon over relevant spatial extents. Field inventories provide high‐quality data, particularly for habitat characteristics at fine spatial resolutions (e.g., large wood), but are costly and so cover relatively small areas. Recent availability of regional digital data and Geographic Information Systems software has advanced capabilities to delineate stream networks and estimate coarse‐resolution hydrogeomorphic attributes (e.g., gradient). A spatially comprehensive coverage results, but types of modeled outputs may be limited and their accuracy is typically unknown. Capitalizing on strengths in both field and regional digital data, we modeled a synthetic stream network and a variety of hydrogeomorphic attributes for the Oregon Coastal Province. The synthetic network, encompassing 96,000 km of stream, was derived from digital elevation data. We used high‐resolution but spatially restricted data from field inventories and streamflow gauges to evaluate, calibrate, and interpret hydrogeomorphic attributes modeled from digital elevation and precipitation data. The attributes we chose to model (drainage area, mean annual precipitation, mean annual flow, probability of perennial flow, channel gradient, active‐channel width and depth, valley‐floor width, valley‐width index, and valley constraint) have demonstrated value for stream research and management. For most of these attributes, field‐measured, and modeled values were highly correlated, yielding confidence in the modeled outputs. The modeled stream network and attributes have been used for a variety of purposes, including mapping riparian areas, identifying headwater streams likely to transport debris flows, and characterizing the potential of streams to provide high‐quality habitat for salmonids. Our framework and models can be adapted and applied to areas where the necessary field and digital data exist or can be obtained.     

Mapping River Bathymetry With a Small Footprint Green LiDAR: Applications and Challenges1

Kinzel, Paul J., Carl J. Legleiter, and Jonathan M. Nelson, 2012. Mapping River Bathymetry with a Small Footprint Green LiDAR: Applications and Challenges. Journal of the American Water Resources Association (JAWRA) 1‐22. DOI: 10.1111/jawr.12008 Abstract: Airborne bathymetric Light Detection And Ranging (LiDAR) systems designed for coastal and marine surveys are increasingly sought after for high‐resolution mapping of fluvial systems. To evaluate the potential utility of bathymetric LiDAR for applications of this kind, we compared detailed surveys collected using wading and sonar techniques with measurements from the United States Geological Survey’s hybrid topographic/bathymetric Experimental Advanced Airborne Research LiDAR (EAARL). These comparisons, based upon data collected from the Trinity and Klamath Rivers, California, and the Colorado River, Colorado, demonstrated that environmental conditions and postprocessing algorithms can influence the accuracy and utility of these surveys and must be given consideration. These factors can lead to mapping errors that can have a direct bearing on derivative analyses such as hydraulic modeling and habitat assessment. We discuss the water and substrate characteristics of the sites, compare the conventional and remotely sensed river‐bed topographies, and investigate the laser waveforms reflected from submerged targets to provide an evaluation as to the suitability and accuracy of the EAARL system and associated processing algorithms for riverine mapping applications.     

Testing a GIS Model of Habitat Suitability for a Declining Grassland Bird

Demand for information that can be used to manage loggerhead shrikes has recently increased because of concern over declining populations and loss of open, non-forested habitat. A previously-developed habitat model was modified to predict shrike habitat quality on Fort Riley Military Reservation (FRMR) in Kansas. Shrike habitat suitability indices were calculated based on the amount of potential and usable foraging habitat, and the number of potential nesting sites within a specified area. Interpretation of high quality digital photographs was used to delineate land cover classes, hedgerows and tree counts. These data were entered into a geographic information system (GIS) as individual data sets. The shrike habitat model was then employed to produce a GIS database predicting low, moderate, and high quality shrike habitat throughout the Reservation. Model results indicated that 67% of the Reservation was suitable habitat for loggerhead shrikes. Although over 80% of FRMR was mapped as grassland, the presence of few to several isolated trees or hedgerows was identified as a key factor in modeling habitat suitability. The accuracy of the GIS model was 82% in predicting suitable (moderate and high quality) loggerhead shrike habitat using an independent set of 66 recent shrike observations. The number of potential nesting sites and percent cover of usable foraging habitat were significantly related to habitat suitability of the sites occupied by shrikes.     

Remote sensing of coastal food resources

Since tidal marshes and estuaries cover large areas of the world's coasts and exhibit a very high net primary productivity, they offer a most important food source for an ever increasing world population. The food web of numerous estuaries and coastal waters is based on the primary productivity of coastal marshes that constitute centers of solar energy fixation and an important link in the mineral cycles. The fixed carbon and minerals enterthe water primarily as detritus where a complex food web makes them accessible to commercially important fish and benthic communities. With the launch of LANDSAT, NOAA-2, and Skylab, relatively high resolution spacecraft data became available for mapping and inventorying tidal marshes and their productivity on a global scale. Upwelling regions that attract large fish populations as well as other coastal water properties relating to the presence of finfish, Crustacea, and shellfish could be identified and observed. Using multispectral analysis techniques, classification accuracies greater than 80 percent have been obtained for most marsh plant species, and greater than 90 percent for key types such asSpartina alterniflora, which is the primary producer in large tide marshes of the coastal eastern USA. The capacity of remote sensors on spacecraft such as NOAA-2, LANDSAT, and Skylab to assess coastal food resources on a global scale is discussed from the point of view of resolution, classification accuracy, and cost effectiveness.     

Changes in Forest Area Along Stream Networks in an Agricultural Catchment of the Great Barrier Reef Lagoon

Scenes from the series of multispectral sensors on the Landsat satellites were used to map recent changes (between 1972 and 2004) in forest cover within and adjacent to stream networks of an intensively farmed region of the southern Great Barrier Reef catchment (Australia). Unsupervised ISODATA classifications of Tasseled-Cap transformed data (at 57 m ground resolution) mapped forest and cleared areas within 150 m of Pisoneer catchment waterways with 72.2% overall accuracy (K(hat) = 0.469), when adjusted for the size of each class. Although the user's accuracy was higher for the forest class (82.1 +/- 8.4% at alpha = 0.05), large errors of commission (34.2 +/- 8.3%) substantially affected map accuracy for the cleared class. The main reasons for misclassification include: (1) failure to discriminate narrowly vegetated riparian strips; (2) misregistration of scenes; and (3) spectral similarity of ground cover. Error matrix probabilities were used to adjust the mapped area of classes, resulting in a decline of forest cover by 12.3% and increase of clearing by 18.5% (22.4 km(2) change; 95% confidence interval: 14.3-29.6 km(2)) between 1972 and 2004. Despite the mapping errors, Landsat data were able to identify broad patterns of land cover change that were verified from aerial photography. Most of the forest losses occurred in open forest to woodland habitat dominated by Eucalyptus, Corymbia, and Lophostemon species, which were largely replaced by sugarcane cropping. Melaleuca communities were similarly affected, though they have a much smaller distribution in the catchment.     

Characterizing the Extent of Spatially Integrated Floodplain and Wetland Systems in the White River,Indiana, USA

Floodplain delineation may inform protection of wetland systems under local, state, or federal laws. Nationally available Federal Emergency Management Agency Flood Insurance Rate Maps (FIRMs, “100‐year floodplain” maps) focus on urban areas and higher‐order river systems, limiting utility at large scales. Few other national‐scale floodplain data are available. We acquired FIRMs for a large watershed and compared FIRMs to floodplain and integrated wetland area mapping methods based on (1) geospatial distance, (2) geomorphic setting, and (3) soil characteristics. We used observed flooding events (OFEs) with recurrence intervals of 25‐50 to >100 years to assess floodplain estimate accuracy. FIRMs accurately reflected floodplain areas based on OFEs and covered 32% of river length, whereas soil‐based mapping was not as accurate as FIRMs but characterized floodplain areas over approximately 65% of stream length. Geomorphic approaches included more areas than indicated by OFE, whereas geospatial approaches tended to cover less area. Overall, soil‐based methods have the highest utility in determining floodplains and their integrated wetland areas at large scales due to the use of nationally available data and flexibility for regional application. These findings will improve floodplain and integrated wetland system extent assessment for better management at local, state, and national scales.     

Seasonal food use by white-tailed deer at Valley Forge National Historical Park,Pennsylvania, USA

Food habits of white-tailed deer (Odocoileus virginianus) were examined from January to November 1984 via fecal-pellet analysis at Valley Forge National Historical Park (VFNHP), which represents an island habitat for deer surrounded by extensive urbanization, in southeastern Pennsylvania. In addition, use of fields by deer was compared to food habits. Herbaceous vegetation (forbs, leaves of woody plants, and conifer needles) was the predominant food type in all seasons except fall. Acorns and graminoids (grasses and sedges) were important food resources in fall and spring, respectively. Use of woody browse (twigs) was similar among seasons. Field use was relatively high during fall, winter without snow cover (<20 cm), and spring when food resources in fields were readily available. In contrast, use of fields was lowest in summer when preferred woodland foods were available and in winter with snow cover when food in fields was not readily accessible. Patterns of food-type use by deer at VFNHP indicate the year-round importance of nonwoody foods and field habitats to deer populations on public lands such as national parks in the northeastern United States.     

Spatial analysis of habitat selection by Sitka black-tailed deer in Southeast Alaska,USA

We used a vector-based geographic information system (GIS) to examine habitat selection by radiocollared Sitka black-tailed deer (Odocoileus hemionus sitkensis) in logged forests of southeast Alaska. Our main objective was to explain deer habitat selection relative to old-growth/clear-cut edges and edge habitats at two different spatial scales. Deer home ranges contained higher percentages of recent clear-cuts (50–69%) than the study area (37%;P<0.01) and had higher old-growth/clear-cut edge densities than expected by chance (P<0.01). Deer relocation points were closer to old-growth/clear-cut edges (average=135 m) than random points located within each deer's relocation area (average=168 m;P=0.05). Likewise, deer relocations were closer to old-growth/clear-cut edges than points randomly located within old-growth stands or recent clear-cuts (P<0.01). As the size of clear-cuts increased, both deer relocation density and the proportion of a clear-cut occupied by deer home ranges decreased. Because old growth is important deer habitat and clear-cuts can produce deer forage for only 20–30 years after logging in southeast Alaska, deer management plans such as preserving entire watersheds and maintaining mixes of old growth and recent clear-cut have been proposed. Our data suggest that deer need a diversity of habitats near each other within their home ranges.     

Forecasts of habitat loss and fragmentation due to urban growth are sensitive to source of input data

The conversion of natural habitat to urban settlements is a primary driver of biodiversity loss, and species' persistence is threatened by the extent, location, and spatial pattern of development. Urban growth models are widely used to anticipate future development and to inform conservation management, but the source of spatial input to these models may contribute to uncertainty in their predictions. We compared two sources of historic urban maps, used as input for model calibration, to determine how differences in definition and scale of urban extent affect the resulting spatial predictions from a widely used urban growth model for San Diego County, CA under three conservation scenarios. The results showed that rate, extent, and spatial pattern of predicted urban development, and associated habitat loss, may vary substantially depending on the source of input data, regardless of how much land is excluded from development. Although the datasets we compared both represented urban land, different types of land use/land cover included in the definition of urban land and different minimum mapping units contributed to the discrepancies. Varying temporal resolution of the input datasets also contributed to differences in projected rates of development. Differential predicted impacts to vegetation types illustrate how the choice of spatial input data may lead to different conclusions relative to conservation. Although the study cannot reveal whether one dataset is better than another, modelers should carefully consider that geographical reality can be represented differently, and should carefully choose the definition and scale of their data to fit their research objectives.     

EXAMINING LAND USE INFLUENCES ON STREAM HABITATS AND MACROINVERTEBRATES: A GIS APPROACH1

ABSTRACT: Geographic Information Systems (GIS) were used to assess the relationships between land use patterns and the physical habitat and macroinvertebrate fauna of streams within similar sized watersheds. Eleven second or third order watersheds ranging from highly urbanized to heavily forested were selected along Lake Superior's North Shore. Land use patterns within the watersheds were quantified using readily available digital land use/land cover information, with a minimum mapping resolution of 16 ha. Physical habitat features, describing substrate characteristics and stream morphology, were characterized at sample points within each stream. Principle component and correlation analyses were used to identify relationships between macroinvertebrates and stream physical habitat, and between habitat and land use patterns. Substrate characteristics and presence of coarse woody debris were found to have the strongest correlations with macreinvertebrate assemblage richness and composition. Agricultural and urban land use was correlated with substrate characteristics. Algal abundance, associated with macroinvertebrate compositional differences, was correlated with housing density and non-forest land covers. The use of readily available spatial data, even at this relatively coarse scale, provides a means to detect the primary relationships between land use and stream habitat quality; finer-resolution GIS databases are needed to assess more subtle influences, such as those due to riparian conditions.     

Traffic mortality and the role of minor roads

Roads have large impacts on wildlife, as they form one of the principal causes of mortality, and disturbance and fragmentation of habitat. These impacts are mainly studied and mitigated on major roads. It is, however, a widespread misconception that most animals are killed on major roads. In this paper, we argue that minor roads have a larger impact on wildlife with respect to habitat destruction, noise load and traffic mortality. We use data on traffic related deaths in badgers (Meles meles) in The Netherlands to illustrate that traffic mortality is higher on minor roads. We ask for a more extensive investigation of the environmental impacts of minor roads. Moreover, we argue that the success of mitigation on roads drastically increases when both major and minor roads are integrated in the planning of traffic flows. Therefore, we propose a strategy based on the concept of a "traffic-calmed area". Traffic-calmed areas create opportunities for wildlife by decreasing limitations for animal movement. We ask for further studies to estimate what size traffic-calmed areas should be to maintain minimum viable animal populations.     

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   

A review of approaches for classifying benthic habitats and evaluating habitat quality

We have assessed the current state of knowledge relative to methods used in assessing sub-tidal benthic habitat quality and the classification of benthic habitats. While our main focus is on marine habitat, we extensively draw on knowledge gained in freshwater systems where benthic assessment procedures are at an advanced stage of maturity. We found a broad range of sophistication/complication in terms of the methods applied in assessing and mapping benthic habitats. The simplest index or metric involved some assessment of species richness, while the most complicated required utilizing multi-variate analysis. The simplest mapping attempts equated physical substrate with benthic habitat while the most sophisticated relied on extensive environmental preference and groundtruth data for species of concern. The leading edge of methods for benthic habitat mapping involves combining the advances in optical and acoustic methods that allow for routine classifying and mapping of the seafloor with biological and habitat data for species of concern. The objective of this melding of dispirit methods is to produce benthic habitat maps with broad system wide coverage and sound biological underpinning. It is clear that the disparity in information density between the physical and biological sides of the equation currently hinder applicability and acceptability of benthic habitat mapping efforts. In addition to the lack of basic information on the biological and environmental tolerances of targeted species, the proliferation of metrics for characterizing and assessing biological conditions further clouds the usefulness of any broad scale mapping attempt. The problem of data density mismatch between physical and biological methods will likely not be solved until acoustic methods can routinely resolve the elusive biological components that make a physical substrate a habitat.     

Spatial Rule-Based Assessment of Habitat Potential to Predict Impact of Land Use Changes on Biodiversity at Municipal Scale

In human dominated landscapes, ecosystems are under increasing pressures caused by urbanization and infrastructure development. In Alpine valleys remnant natural areas are increasingly affected by habitat fragmentation and loss. In these contexts, there is a growing risk of local extinction for wildlife populations; hence assessing the consequences on biodiversity of proposed land use changes is extremely important. The article presents a methodology to assess the impacts of land use changes on target species at a local scale. The approach relies on the application of ecological profiles of target species for habitat potential (HP) assessment, using high resolution GIS-data within a multiple level framework. The HP, in this framework, is based on a species-specific assessment of the suitability of a site, as well of surrounding areas. This assessment is performed through spatial rules, structured as sets of queries on landscape objects. We show that by considering spatial dependencies in habitat assessment it is possible to perform better quantification of impacts of local-level land use changes on habitats.     

Evaluation of Methods for Delineating Riparian Zones in a Semi‐Arid Montane Watershed

Riparian zones in semi‐arid, mountainous regions provide a disproportionate amount of the available wildlife habitat and ecosystem services. Despite their importance, there is little guidance on the best way to map riparian zones for broad spatial extents (e.g., large watersheds) when detailed maps from field data or high‐resolution imagery and terrain data are not available. Using well‐established accuracy metrics (e.g., kappa, precision, computational complexity), we evaluated eight methods commonly used to map riparian zones. Focusing on a semi‐arid, mountainous watershed, we found that the most accurate and robust method for mapping riparian zones combines data on upstream drainage area and valley topography. That method performed best regardless of stream order, and was most effective when implemented with fine resolution topographic and stream line data. Other commonly used methods to model riparian zones, such as those based on fixed‐width buffers, yielded inaccurate results. We recommend that until very‐high resolution (<1 m) elevation data are available at broad extents, models of riparian zones for semi‐arid mountainous regions should incorporate drainage area, valley topography, and quantify uncertainty.     

Modeling Stream Channel Characteristics From Drainage‐Enforced DEMs in Puget Sound,Washington, USA1

Abstract: Mapping stream channels and their geomorphic attributes is an important step in many watershed research and management projects. Often insufficient field data exist to map hydromorphologic attributes across entire drainage basins, necessitating the application of hydrologic modeling tools to digital elevation models (DEMs) via a geographic information system (GIS). In this article, we demonstrate methods for deriving synthetic stream networks via GIS across large and diverse basins using drainage‐enforced DEMs, along with techniques for estimating channel widths and gradient on the reach scale. The two‐step drainage enforcement method we used produced synthetic stream networks that displayed a high degree of positional accuracy relative to the input streams. The accuracies of our estimated channel parameters were assessed with field data, and predictions of bankfull width, wetted width and gradient were strongly correlated with measured values (r² = 0.92, r² = 0.95, r² = 0.88, respectively). Classification accuracies of binned channel attributes were also high. Our methodology allows for the relatively rapid mapping of stream channels and associated morphological attributes across large geographic areas. Although initially developed to provide salmon recovery planners with important salmon habitat information, we suggest these methodologies are relevant to a variety of research and management questions.