Spatial congruence among indicators of recovery completeness in a Mediterranean forest landscape: Implications for planning large-scale restoration
Identifiers
Permanent link (URI): http://hdl.handle.net/10017/38638DOI: 10.1016/j.ecolind.2019.03.046
ISSN: 1470-160X
Date
2019Embargo end date
2021-07-01Funders
Universidad de La Frontera
Fundación de Apoyo a la Investigación del Estado de Sao Paulo
Bibliographic citation
Ecological Indicators, 2019, v. 102, n. , p. 752-759
Keywords
Boosted regression tree
Landscape forest restoration
Vegetation recovery
Natural regeneration
Restoration indicator
Project
Fondecyt grant 1171445
FONDEF grant CA13I10276
Grant PAI80160058 (CONICYT)
Dirección de Investigación (Universidad de La Frontera)
FAPESP 2016/00052-9 (São Paulo Research Foundation)
FONDAP/15110009 (CONICYT)
Document type
info:eu-repo/semantics/article
Version
info:eu-repo/semantics/publishedVersion
Rights
Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)
© 2019 Elsevier
Access rights
info:eu-repo/semantics/openAccess
Abstract
Natural regeneration has been proposed as a cost-effective forest restoration approach for both small and large-scale initiatives. However, attributes for assessing the success of forest restoration through natural regeneration may vary among them in spatial patterns depending on the scale of analysis and on environmental gradients. Here we analysed the spatial patterns of recovery completeness (i.e. how similar attributes in restored forests are to the same attributes in reference forests) in response to environmental factors in a Mediterranean forest landscape of Central Chile. We evaluated (1) forest recovery completeness using basal area (BA), quadratic mean diameter (QMD), adult species density (ASD), adult species richness (ASR), and seedling species richness (SSR); (2) the spatial congruence of recovery completeness estimated by each of these indicators; and (3) the environmental factors potentially shaping these spatial patterns. We used field measurements and geospatial information sources to quantify and predict indicator responses by fitting boosted regression tree models. To assess the spatial congruence of predictions we overlaid high-level recovery completeness values for all indicators. Overall recovery completeness in the study area was 72.7%, suggesting positive prospects for attaining fully restored forests. Recovery completeness had a resulted higher for diversity (92.3%-99.6%) than structural forest attributes (33.5%-76.9%); however, spatial congruence among recovery indicators was low due to the uneven spatial responses of each indicator. The maximum potential spatial congruence was <10%, and was predicted only by two environmental variables (soil bulk density and slope). Our results suggest that low spatial congruence among forest recovery indicators may hinder the monitoring of restoration at large scales. The implications of such divergence in defining restoration success can be enormous given the current global challenge of forest restoration. Although our research was tested in a threatened region of global importance, our results may have wider significance for restoration planning providing cautionary notes and recommendations for the appropriate use of forest recovery indicators when monitoring large-scale restoration projects.
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spatial_altamirano_EI_2019.pdf | 1.245Mb |
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