An operational method to assess impacts of land clearing on terrestrial biodiversity
Introduction
There remains considerable demand to clear or modify native vegetation for agricultural development. The Food and Agriculture Organization of the United Nations (FAO, 2005) estimated that 13 million ha of forest were cleared per year, mainly for conversion to agriculture, and listed 28 countries in which the net loss of forest exceeded 100,000 ha per annum between 2000 and 2005. Even in countries where the net loss of forest cover is lower, there is still substantial conversion of native vegetation to other land cover types. For example, in the United States of America (USA), natural pine forests were cleared or converted to planted forests at an average rate of 246,000 ha per annum between 1989 and 1999 (Wear and Greis, 2002) and woody vegetation in Australia was converted to another vegetation type or land use at an average rate of around 470,000 ha of per annum between 1988 and 2001 (The Australian Greenhouse Office, 2005).
Excessive clearing of native vegetation poses a threat to biodiversity and its attendant ecosystem services (Millennium Ecosystem Assessment, 2005). The impacts of excessive land clearing include: (1) reduced abundance, localized extinctions and declining viability of native biota populations (Cogger et al., 2003); (2) disruptions in ecological processes (e.g. soil formation, soil stability, water quality, insect control, carbon sequestration) that help sustain agricultural production and human health (Millennium Ecosystem Assessment, 2005); and (3) a reduction in the resilience of ecosystems to change (e.g. climate change) (Walker and Salt, 2006). Excessive land clearing is a significant factor in the demise of numerous societies (Diamond, 2005).
Regulation is an important element of governance for controlling land clearing (Kishor, 2004). Morton et al. (2002) identified effective regulation of land clearing as one of the most cost-effective means of biodiversity conservation. However, few operational tools (as distinct from indicators and metrics) for assessing impacts on biodiversity of clearing native vegetation have been published. Examples of methods that are employed as part of operational procedures to assess impacts of land clearing on biodiversity are: Habitat Evaluation Procedures (US Fish and Wildlife Service, 1980) in which impacts are predicted using habitat models (Habitat Suitability Indices) for indicator species (Roloff and Kernohan, 1999); Indices of Biotic Integrity, which are based on species metrics for indicator species (typically invertebrates) for assessing impacts of development on aquatic ecosystems (Andreasen et al., 2001); Habitat Hectares (Parkes et al., 2003) in which change in habitat value is assessed according to the deviation from reference conditions.
The aim of this research was to produce an objective, transparent and operationally feasible method to assess impacts on terrestrial biodiversity of proposals to clear native vegetation for rural land uses. The methodology was developed to support a policy to allow land clearing only if it ‘improved or maintained environmental outcomes’. This assessment methodology is used with other decision-support tools that assess impacts of land clearing on threatened species, soils, water quality, salinity and vegetation known as invasive native scrub. These tools are not discussed here.
While this paper is structured in the traditional Materials and methods, Results, Discussion format, it is important to note that many of the important outcomes of this research are contained in the Materials and methods where the assessment methodology is described. In the Results we present outcomes from field trials and the first 12 months of implementation.
Section snippets
Study area
The assessment methodology was developed for applications to clear native vegetation in rural and semi rural areas in the State of NSW, an area of 80 million ha in eastern Australia. Approximately 60% of the native vegetation in NSW has been cleared, with the most heavily cleared regions being those that are most productive for irrigation, broad-acre cropping and grazing for sheep and cattle (data from Benson, 1999). Recent land clearing in NSW remains high with annual estimates between 60,000
Field trials
The gross areas of native vegetation proposed for clearing in the 77 trials ranged from 0.14 to 1254 ha with a mean of 123 ha. These areas were calculated from polygons bounding the outermost remnants of native vegetation in the proposals, so can be a misleading indicator of the net area of native vegetation proposed for clearing. Approximately half of all proposals (49%) were entirely in native vegetation in ‘low condition’ (e.g. trees scattered among improved pasture or cultivation), so the net
The rationale for using the selected biodiversity assessment techniques
We employed several different biodiversity surrogates and assessment techniques to assess the impacts of land clearing on biodiversity. As no single surrogate for biodiversity is comprehensive we spread risk (Lindenmayer et al., 2002) by using different surrogates for biodiversity across multiple scales. Surrogates for biodiversity and the techniques used to measure these were selected after considering the range of surrogates available and the range of feasible assessment techniques given the
Conclusions
Effective regulation is an important element of governance to control land clearing (Kishor, 2004). A transparent, quantitative and codified approach for regulating clearing as presented here: (a) provides a consistent scientific basis for assessing individual proposals to clear native vegetation; (b) protects assessment staff from pressures by vested interests; (c) allows all stakeholders to examine, question and propose improvements to the methodology; (d) generates data that can be used for
Acknowledgements
Thanks to many colleagues in the NSW Government who made contributions to BioMetric, the many staff in Catchment Management Authorities who tested the tool and provided critical feedback and the many stakeholders who provided suggestions that improved earlier versions of the tool. This feedback and the results of research funded by the NSW Government through its Environmental Trust (Better Knowledge Better Bush Project) continue to provide input for periodic reviews of BioMetric and the
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