3 results
Effects of different sampling scales and selection criteria on modelling net primary productivity of Indonesian tropical forests
- STEPHAN J. GMUR, DANIEL J. VOGT, KRISTIINA A. VOGT, ASEP S. SUNTANA
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- Journal:
- Environmental Conservation / Volume 41 / Issue 2 / June 2014
- Published online by Cambridge University Press:
- 17 October 2013, pp. 187-197
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The availability of spatial data sourced from either field-derived or satellite-based systems has created new opportunities to estimate and/or monitor changes in carbon sequestration rates, climate change impacts or the potential habitat alterations occurring across large landscapes. However, an effort to create models is not standardized, in part, due to different needs and data sources available for the models. For example, data may have different spatial resolutions with varying degrees of complexity in regards to inputs and statistical methods. This study determines effects of 20, 15, 10, five and one km sampling resolutions on detection of changes in net primary productivity (NPP), occupancy selection criteria for areas to be included in the sample and identification of significant variables impacting NPP in Indonesia forests. Production forest designated for selective harvest was used to define the sampling areas. Variances explained by predictive models were similar across cell sizes although relative importance of variables was different. Partial dependence plots were used to search for potential thresholds or tipping points of NPP change as affected by an independent variable such as minimum daytime temperature. Applying different cell occupancy selection rules significantly changed the overall distribution of NPP values. The magnitude of those changes within a cell size varied with changes in cell size. The mean estimated NPP for production forests across Indonesia differed significantly at every sampling resolution and occupancy selection criteria. Lows ranged from 1.107 to 1.121 kg C m−2 yr−1 for the 1-km cell size for the three occupancy selection criteria with highs ranging from 1.245 to 1.189 kg C m−2 yr−1 for the 20-km cell size. The difference in NPP values between these two cell sizes for the three occupancy selection criteria extrapolates to a range in annual biomass of 132 × 106 to 66 × 106 t for the total area of production forests in Indonesia.
18 - Bridging the gap between landscape ecology and natural resource management
- Edited by Jianguo Liu, Michigan State University, William W. Taylor, Michigan State University
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- Book:
- Integrating Landscape Ecology into Natural Resource Management
- Published online:
- 14 January 2010
- Print publication:
- 01 August 2002, pp 433-460
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Summary
Introduction
In every respect, the valley rules the stream.
Noel Hynes (1975)The challenges facing natural resource managers occur over entire landscapes and involve landscape components at many scales. Many resource managers are shifting their approach from managing resources such as fish, wildlife, and water separately to managing for the integrity of entire ecosystems (Christensen et al., 1996). Indeed, nearly all resource management agencies in the USA have recognized that informed management decisions cannot be made exclusively at the level of habitat units or local sites. It is generally accepted that ecological patterns and processes must be considered over large areas when biodiversity and ecological function must be maintained while the goods and services desired by the public are provided. For example, forest managers must determine the patterns and timing of tree harvesting while maintaining an amount and arrangement of habitats that will sustain many species. Managers of parks and nature reserves must be attentive to actions occurring on surrounding lands outside their jurisdiction. Aquatic resource managers must broaden their perspective to encompass the terrestrial and human landscape to manage stream and lake resources effectively (Hynes, 1975, widely regarded as the father of modern stream ecology and quoted above; Naiman et al., 1995). Landscape ecology also is implicit in the paradigm of ecosystem management (Grumbine,1994; Christensen et al., 1996).
Despite the acknowledged importance of a landscape perspective by both scientists and resource managers, determining how to implement management at broader scales is very much a work in progress.
6 - Linking ecological and social scales for natural resource management
- Edited by Jianguo Liu, Michigan State University, William W. Taylor, Michigan State University
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- Book:
- Integrating Landscape Ecology into Natural Resource Management
- Published online:
- 14 January 2010
- Print publication:
- 01 August 2002, pp 143-176
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Summary
Introduction
Natural resource management has moved from a single disciplinary and one resource management approach to an interdisciplinary and ecosystem-based approach. Many conceptual models are being developed to understand and implement ecosystem management and forest certification initiatives that require an integration of data from both the social and natural systems (Vogt et al., 1997, 1999a,b). These changed approaches to natural resource management arose from a perception that variables critical in controlling the health and functioning of an ecosystem could only be determined by integrating information from both the social and the natural sciences (Vogt et al., 1997). However, it has been difficult to take many of the theoretical discussions and the frameworks or conceptual models that they have produced and to operationalize or put them into practice on the ground.
Despite these discussions and the recognition of their importance, social and natural science data have been ineffectively incorporated into the management and trade-off assessments of natural resources (Berry and Vogt, 1999).We hypothesize that some of this has occurred because of the distinct spatial scales being used by different disciplines which have not allowed for integration of information to occur at a causal level. The complexity and uncertainty of data needed to understand ecosystems by both social and natural scientists have also made it difficult for managers to recognize when the wrong indicators are being monitored or whether a system could degrade due to management (Larson et al., 1999; Vogt et al., 1999c). The need to link data causally from both disciplines as part of ecosystem management has given greater impetus to develop practical tools that would allow this integration to be accomplished.