Assessing and monitoring forest biodiversity: A suggested framework and indicators

Abstract Enlightened forest management requires reliable information on the status and condition of each forest – interpreted from a broad context – and of change in forest conditions over time. The process of forest planning must begin with a clear statement of goals, from which detailed objectives and management plans follow. Goals and objectives for forest management should reflect the conservation value of a forest relative to other forests of the same general type. This paper reviews some recent assessments (with emphasis on North America), presents a framework for forest assessment and monitoring, and suggests some indicators of biodiversity in forests. Among the broad assessments of forest status and conservation value are a global `forest frontiers' assessment by the World Resources Institute, gap analysis projects that assess the level of representation of forests and other communities in protected areas, and ecoregion-based conservation assessments conducted by the World Wildlife Fund. Also important is information on change in forest area and condition over time. Among the common changes in forests over the past two centuries are loss of old forests, simplification of forest structure, decreasing size of forest patches, increasing isolation of patches, disruption of natural fire regimes, and increased road building, all of which have had negative effects on native biodiversity. These trends can be reversed, or at least slowed, through better management. Progress toward forest recovery can be measured through the use of ecological indicators that correspond to the specific conditions and trends of concern. Although there is a wealth of indicators to choose from, most have been poorly tested and require rigorous validation in order to be interpreted with confidence.

[1]  Larry D. Harris,et al.  The fragmented forest : island biogeography theory and the preservation of biotic diversity / Larry D. Harris , 1984 .

[2]  Daniel Simberloff,et al.  The role of science in the preservation of forest biodiversity , 1999 .

[3]  Reed F. Noss,et al.  Endangered Ecosystems of the United States: A Preliminary Assessment of Loss and Degradation , 1996, Restoration & Management Notes.

[4]  K. McGarigal,et al.  FRAGSTATS: spatial pattern analysis program for quantifying landscape structure. , 1995 .

[5]  Carl J. Walters,et al.  Adaptive Management of Renewable Resources , 1986 .

[6]  B. Csuti,et al.  A Gap Analysis of the Management Status of the Vegetation of Idaho (U.S.A.) , 1995 .

[7]  P. Angelstam The ghost of forest past — natural disturbance regimes as a basis for reconstruction of biologically diverse forests in Europe , 1996 .

[8]  J. Faaborg,et al.  Habitat fragmentation in the temperate zone , 1999 .

[9]  D. Wilcove,et al.  Conserving Biological Diversity in Our National Forests , 1987 .

[10]  R. Lambeck,et al.  Focal Species: a Multi-species Umbrella for Nature Conservation Focal Species for Nature Conservation Lambeck , 2022 .

[11]  Jerry F. Franklin,et al.  Creating a forestry for the 21st century : the science of ecosystem management , 1997 .

[12]  Nels Johnson,et al.  The last frontier forests: ecosystems and economies on the edge. What is the status of the worlds remaining large natural forest ecosystems? , 1997 .

[13]  R. Noss Indicators for Monitoring Biodiversity: A Hierarchical Approach , 1990 .

[14]  R. Hobbs,et al.  Biological Consequences of Ecosystem Fragmentation: A Review , 1991 .

[15]  R. G. Wright,et al.  GAP ANALYSIS: A GEOGRAPHIC APPROACH TO PROTECTION OF BIOLOGICAL DIVERSITY , 1993 .

[16]  J. Rappole,et al.  The Science of Conservation Planning: Habitat Conservation Under The Endangered Species Act , 1997 .

[17]  Tim Gerrodette,et al.  The Uses of Statistical Power in Conservation Biology: The Vaquita and Northern Spotted Owl , 1993 .

[18]  Nathan H. Schumaker,et al.  Using Landscape Indices to Predict Habitat Connectivity , 1996 .

[19]  D. Doak Source‐Sink Models and the Problem of Habitat Degradation: General Models and Applications to the Yellowstone Grizzly , 1995 .