首页|Estimating optimal sampling area for monitoring tropical forest restoration
Estimating optimal sampling area for monitoring tropical forest restoration
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NSTL
Elsevier
? 2022 Elsevier LtdAlthough critical to evaluating success, monitoring is often neglected in ecological restoration. An important question is how much area should be sampled to adequately monitor restoration projects, particularly as projects become larger. We elucidate this issue by testing the following hypotheses: There is an optimal sampling area (OSA) that efficiently captures variation in the estimation of ecological indicators; The restoration intervention and forest type affect OSA; The OSA change over time as restoration projects age. Information on large-scale vegetation monitoring (n = 374) in the Brazilian Atlantic Forest was used to test our hypotheses. We studied moderately assisted recovery (MAR) and lightly assisted recovery (LAR) projects within three forest types (50.5-ha of sampling). The projects were between three months and seven years in age. We calculated the variance for 11 indicators and the proportion of a restoration site that was sampled. We performed segmented regressions to find the OSA. Across all indicators, OSA ranged from 0.25–2.16% for MAR and 0.24–4.67% for LAR. There was weak evidence that OSA was greater in LAR projects (P = 0.052) and semideciduous seasonal forest type (P = 0.060). OSA increased over time, reaching 4.0% of the project area for projects seven years in age. By knowing the OSA for a range of indicators, practitioners can plan for the minimum monitoring needed to evaluate the restoration trajectory confidently and avoid vague or erroneous conclusions. The restoration of large areas will mark this decade, and this study helps fill the knowledge gap on how to monitor them more effectively.
NSTL
Elsevier
