title: Identifying potential indicators of conservation value using natural heritage occurrence data.
abstract: Conservation planning based on the occurrence of rare species has been criticized as being too limited in scope to conserve biodiversity as a whole. Conversely, planning based on indicator taxa may lack sufficient focus to conserve those species in greatest need of conservation. An alternative approach is to identify a variety of species at risk that are associated with areas of conservation value, which is defined based on species-independent characteristics. We identified potential indicators of conservation value using occurrence data on species at risk and independent information on conservation value that incorporated indices of ecosystem integrity. We propose a taxonomically diverse group of indicator species that are strongly associated with areas of exceptional ecosystem integrity, to serve as a focus for further research and in planning for biodiversity conservation. We identify potential indicator species by defining a null model in which species at risk are equally associated with areas of high ecosystem integrity, then by conducting randomization tests to identify noncompliant species in the state of Michigan, USA. Areas of high ecosystem integrity are selected using criteria to flag (1) secure biotic communities with structural integrity and few exotic species, (2) natural areas subjected to expert review, (3) contiguous relict areas of forest interior, (4) contiguous areas of unmodified wetland, and (5) all these areas combined. We determine the spatial occurrence of species at risk using data from Michigan's statewide Natural Heritage database. The potential indicators include plants, insects, and birds. Their species identity and distribution of occurrences varies with the five scenarios, and together the species broadly cover the entire state. These species at risk, many of which occur throughout the Great Lakes region, may be used to identify additional areas potentially high in conservation value and to monitor their conservation. The ecological criteria and numerical methods we employ may be broadly applicable as Heritage Program databases in North America and parts of Latin America grow to become representative of species distributions.
authors.affiliation: Michigan Natural Features Inventory, Michigan State University, P.O. Box 30444, Lansing, Michigan 48909-7944, USA. pearman@zool.unizh.ch
authors.forename: Peter B
authors.initials: PB
authors.lastname: Pearman
authors.forename: Michael R
authors.initials: MR
authors.lastname: Penskar
authors.forename: Edward H
authors.initials: EH
authors.lastname: Schools
authors.forename: Helen D
authors.initials: HD
authors.lastname: Enander
mesh_terms: D000818:Animals; D044822:Biodiversity; D005075:Biological Evolution; D003247:Conservation of Natural Resources; D030541:Databases, Genetic; D004463:Ecology; D004784:Environmental Monitoring; D005843:Geography; D006114:Great Lakes Region; D008824:Michigan; D009656:North America; D011157:Population Dynamics; D013045:Species Specificity