Premium
Recent developments in analysis of spatial and temporal data for landscape qualities and monitoring
Author(s) -
WALLACE J. F.,
CACCETTA P. A.,
KIIVERI H. T.
Publication year - 2004
Publication title -
austral ecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.688
H-Index - 87
eISSN - 1442-9993
pISSN - 1442-9985
DOI - 10.1111/j.1442-9993.2004.01356.x
Subject(s) - environmental resource management , biodiversity , resource (disambiguation) , computer science , scale (ratio) , data science , natural resource management , geography , temporal scales , natural resource , ecology , cartography , environmental science , computer network , biology
Abstract Monitoring biodiversity presents the challenge of informing complex aspects of biological systems with consistent, repeatable, data‐based indicators. The present paper does not address directly the selection of indicators for rangeland biodiversity, but rather presents essential aspects and examples of monitoring systems that address natural resource questions at comparable scales. In general, concepts of landscape quality, such as range condition, conservation value, health and biodiversity, are descriptive rather than quantitative and are either ill‐defined or multiply defined. Assessment of the status of such indicators involves value systems, as well as process understanding at a range of scales for which data are often unavailable. Effective monitoring systems, in contrast, require repeated quantitative data at suitable temporal density and spatial scale, as well as appropriate methods and a conceptual framework to simplify and interpret these data. In recent years, broad‐scale operational monitoring systems for land and vegetation have been developed in Australia based on sequences of satellite data, digital elevation models, ground information and appropriate statistical methods. These same datasets have been used to inform landscape qualities over broad areas; examples are given of the production of salinity risk maps and conservation management zones based on fragmentation patterns. These results have been achieved as a partnership between ecologists, resource scientists and statisticians and illustrate how surrogates for integrated concepts such as biodiversity can be derived from available data.