Cowley J.,National Park Service |
Landres P.,U.S. Department of Agriculture |
Memory M.,Everglades and Dry Tortugas National Parks |
Scott D.,Campaign for Americas Wilderness |
Lindholm A.,NPS Alaska Region Wilderness Coordinator
Park Science | Year: 2011
Cultural resources are an integral part of wilderness and wilderness character, and all wilderness areas have a human history. This article develops a foundation for wilderness and cultural resource staffs to continue communicating with one another in order to make better decisions for wilderness stewardship. Following a discussion of relevant legislative history, we describe how cultural resources are the fifth quality of wilderness character. Examples of how cultural resources in wilderness are being managed in a variety of parks include working with tribes to manage ethnographic resources in wilderness and using the Minimum Requirements Analysis to determine the appropriateness of historic preservation actions and activities. The article closes with three recommendations to help parks address managing cultural resources in wilderness in the future.
Szantoi Z.,University of Florida |
Escobedo F.,University of Florida |
Abd-Elrahman A.,University of Florida |
Smith S.,University of Florida |
Pearlstine L.,Everglades and Dry Tortugas National Parks
International Journal of Applied Earth Observation and Geoinformation | Year: 2013
In order to monitor natural and anthropogenic disturbance effects to wetland ecosystems, it is necessary to employ both accurate and rapid mapping of wet graminoid/sedge communities. Thus, it is desirable to utilize automated classification algorithms so that the monitoring can be done regularly and in an efficient manner. This study developed a classification and accuracy assessment method for wetland mapping of at-risk plant communities in marl prairie and marsh areas of the Everglades National Park. Maximum likelihood (ML) and Support Vector Machine (SVM) classifiers were tested using 30.5 cm aerial imagery, the normalized difference vegetation index (NDVI), first and second order texture features and ancillary data. Additionally, appropriate window sizes for different texture features were estimated using semivariogram analysis. Findings show that the addition of NDVI and texture features increased classification accuracy from 66.2% using the ML classifier (spectral bands only) to 83.71% using the SVM classifier (spectral bands, NDVI and first order texture features). © 2013 Elsevier B.V.
Labiosa W.B.,U.S. Geological Survey |
Forney W.M.,U.S. Geological Survey |
Esnard A.-M.,Florida Atlantic University |
Mitsova-Boneva D.,Florida Atlantic University |
And 7 more authors.
Environmental Modelling and Software | Year: 2013
Land-use land-cover change is one of the most important and direct drivers of changes in ecosystem functions and services. Given the complexity of the decision-making, there is a need for Internet-based decision support systems with scenario evaluation capabilities to help planners, resource managers and communities visualize, compare and consider trade-offs among the many values at stake in land use planning. This article presents details on an Ecosystem Portfolio Model (EPM) prototype that integrates ecological, socio-economic information and associated values of relevance to decision-makers and stakeholders. The EPM uses a multi-criteria scenario evaluation framework, Geographic Information Systems (GIS) analysis and spatially-explicit land-use/land-cover change-sensitive models to characterize changes in important land-cover related ecosystem values related to ecosystem services and functions, land parcel prices, and community quality-of-life (QoL) metrics. Parameters in the underlying models can be modified through the interface, allowing users in a facilitated group setting to explore simultaneously issues of scientific uncertainty and divergence in the preferences of stakeholders. One application of the South Florida EPM prototype reported in this article shows the modeled changes (which are significant) in aggregate ecological value, landscape patterns and fragmentation, biodiversity potential and ecological restoration potential for current land uses compared to the 2050 land-use scenario. Ongoing refinements to EPM, and future work especially in regard to modifiable sea level rise scenarios are also discussed. © 2012 .
Hallac D.E.,Yellowstone Center for Resources |
Sadle J.,Everglades and Dry Tortugas National Parks |
Pearlstine L.,Everglades and Dry Tortugas National Parks |
Herling F.,Everglades and Dry Tortugas National Parks |
Shinde D.,Everglades and Dry Tortugas National Parks
Marine and Freshwater Research | Year: 2012
Recreational motor boating in shallow water can damage submerged natural resources through propeller scarring and these impacts represent one of many factors that affect the health of seagrass ecosystems. Understanding the patterns of seagrass scarring and associations with physical and visitor-use factors can assist in development of management plans that seek to minimise resource damage within marine protected areas. A quantification of seagrass scarring of Florida Bay in Everglades National Park, using aerial imagery, resulted in the detection of a substantial number and length of seagrass scars. Geospatial analyses indicated that scarring was widespread, with the densest areas found in shallow depths, near navigational channels, and around areas most heavily used by boats. Modelling identified areas of high scarring probability, including areas that may experience increased scarring in the future as a result of a reallocation of impacts if management strategies are implemented. New boating-management strategies are warranted to protect seagrass in Florida Bay. An adaptive approach focusing on the most heavily scarred areas, should consider a variety of management options, including education, improved signage, new enforcement efforts and boating restrictions, such as non-motorised zones, or temporary closures. These methods and recommendations are broadly applicable to management of shallow water systems before and after resource impacts have occurred. © 2012 CSIRO.