Tradeoffs of different types of species occurrence data for use in systematic conservation planning


Autoria(s): Rondinini, C.; Wilson, K. A.; Boitani, L.; Grantham, H.; Possingham, H. P.
Data(s)

01/10/2006

Resumo

Data on the occurrence of species are widely used to inform the design of reserve networks. These data contain commission errors (when a species is mistakenly thought to be present) and omission errors (when a species is mistakenly thought to be absent), and the rates of the two types of error are inversely related. Point locality data can minimize commission errors, but those obtained from museum collections are generally sparse, suffer from substantial spatial bias and contain large omission errors. Geographic ranges generate large commission errors because they assume homogenous species distributions. Predicted distribution data make explicit inferences on species occurrence and their commission and omission errors depend on model structure, on the omission of variables that determine species distribution and on data resolution. Omission errors lead to identifying networks of areas for conservation action that are smaller than required and centred on known species occurrences, thus affecting the comprehensiveness, representativeness and efficiency of selected areas. Commission errors lead to selecting areas not relevant to conservation, thus affecting the representativeness and adequacy of reserve networks. Conservation plans should include an estimation of commission and omission errors in underlying species data and explicitly use this information to influence conservation planning outcomes.

Identificador

http://espace.library.uq.edu.au/view/UQ:81180

Idioma(s)

eng

Publicador

Blackwell Publishing

Palavras-Chave #Commission Error #Geographic Range #Omission Error #Point Data #Predicted Distribution Data #Reserve Selection #Ecology #Reserve Selection Procedures #Cape Floristic Region #Distribution Models #Biodiversity Hotspots #Detection Probabilities #Ecological Transition #Survey Intensity #Habitat Models #South-africa #Bias #0501 Ecological Applications #050202 Conservation and Biodiversity #050205 Environmental Management #050209 Natural Resource Management #050211 Wildlife and Habitat Management
Tipo

Journal Article