Literature DB >> 17643191

Optimising vegetation monitoring. A case study in A French lowland forest.

Frédéric Archaux1, Laurent Bergès.   

Abstract

Biodiversity monitoring surveys are rarely optimised statistically before being initiated. Here, we optimised the monitoring of plants in a temperate forest. The total inventory cost, the number and size of quadrats were optimised to detect a 10% change in species richness over 5 years with alpha = beta = 0.05, using data from ongoing long-term floristic monitoring programs. The procedure showed that the inventory cost would be ca 15% lower using 100-, 200-m2 quadrats instead of 300- or 400-m2 quadrats. Despite the cost associated with the optimisation (e.g. gathering preliminary data) and the imprecise estimates (due to the typically small sample size of the pilot studies), optimisation would often be a better option than expert opinion when designing a monitoring survey.

Mesh:

Year:  2007        PMID: 17643191     DOI: 10.1007/s10661-007-9874-0

Source DB:  PubMed          Journal:  Environ Monit Assess        ISSN: 0167-6369            Impact factor:   2.513


  3 in total

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Journal:  J Environ Monit       Date:  2001-10

2.  Understanding statistical power in the context of applied research.

Authors:  Thom Baguley
Journal:  Appl Ergon       Date:  2004-03       Impact factor: 3.661

3.  Power calculations for matched case-control studies.

Authors:  W D Dupont
Journal:  Biometrics       Date:  1988-12       Impact factor: 2.571

  3 in total
  4 in total

1.  Ground vegetation monitoring in Swiss forests: comparison of survey methods and implications for trend assessments.

Authors:  Anne Thimonier; Peter Kull; Walter Keller; Barbara Moser; Thomas Wohlgemuth
Journal:  Environ Monit Assess       Date:  2010-11-04       Impact factor: 2.513

2.  Long-term monitoring of western aspen--lessons learned.

Authors:  E K Strand; S C Bunting; L A Starcevich; M T Nahorniak; G Dicus; L K Garrett
Journal:  Environ Monit Assess       Date:  2015-07-28       Impact factor: 2.513

3.  Detecting change in advance tree regeneration using forest inventory data: the implications of type II error.

Authors:  James A Westfall; William H McWilliams
Journal:  Environ Monit Assess       Date:  2011-09-20       Impact factor: 2.513

4.  A road map for designing and implementing a biological monitoring program.

Authors:  Joel H Reynolds; Melinda G Knutson; Ken B Newman; Emily D Silverman; William L Thompson
Journal:  Environ Monit Assess       Date:  2016-06-08       Impact factor: 2.513

  4 in total

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