title: Long-term datasets in biodiversity research and monitoring: assessing change in ecological communities through time.
abstract: The growing need for baseline data against which efforts to reduce the rate of biodiversity loss can be judged highlights the importance of long-term datasets, some of which are as old as ecology itself. We review methods of evaluating change in biodiversity at the community level using these datasets, and contrast whole-community approaches with those that combine information from different species and habitats. As all communities experience temporal turnover, one of the biggest challenges is distinguishing change that can be attributed to external factors, such as anthropogenic activities, from underlying natural change. We also discuss methodological issues, such as false alerts and modifications in design, of which users of these data sets need to be aware.
authors.affiliation: Scottish Oceans Institute, School of Biology, University of St Andrews, St Andrews, Fife KY16 8LB, UK. aem1@st-andrews.ac.uk
authors.forename: Anne E
authors.initials: AE
authors.lastname: Magurran
authors.forename: Stephen R
authors.initials: SR
authors.lastname: Baillie
authors.forename: Stephen T
authors.initials: ST
authors.lastname: Buckland
authors.forename: Jan McP
authors.initials: JM
authors.lastname: Dick
authors.forename: David A
authors.initials: DA
authors.lastname: Elston
authors.forename: E Marian
authors.initials: EM
authors.lastname: Scott
authors.forename: Rognvald I
authors.initials: RI
authors.lastname: Smith
authors.forename: Paul J
authors.initials: PJ
authors.lastname: Somerfield
authors.forename: Allan D
authors.initials: AD
authors.lastname: Watt
mesh_terms: D000818:Animals; D044822:Biodiversity; D016208:Databases, Factual; D004463:Ecology / Q000379:methods*; D006801:Humans; D013997:Time Factors