Structural-functional approach to identify post-disturbance recovery indicators in forests from northwestern Patagonia: a tool to prevent state transitions

作者: L. Cavallero , D.R. López , E. Raffaele , M.A. Aizen

DOI: 10.1016/J.ECOLIND.2014.11.019

关键词:

摘要: Abstract The disruption of the natural post-disturbance recovery process, either by changes in disturbance regime or another disturbance, can trigger transitions to alternative degraded states. In a scenario high pressure on ecological systems, it is essential detect indicators define period when system needs more protection as well supports certain use without affecting its resilience. Recovery be identified non-linear structural and functional variables. Fire largely modulates dynamic stability plant communities worldwide, this case northwestern (NW) Patagonia. ultimate goal study propose structural–functional approach based reference (i.e. chronosequence) tool forests from NW Patagonia (40–42°S), we sampled 25 Austrocedrus chilensis Nothofagus spp. differing post-fire age (0.3–180 years). each community recorded (woody species cover height, solar radiation, air temperature, relative humidity) (annual recruitment woody tree species) attributes. We modeled these attributes function analized relationship between attribute Structural Index (SRI). Communities varying time-since-last-fire were structurally functionally different. Moreover, response variables showed along chronosequence, allowing selection indicators. suggest vegetation instead environmental Horizontal Vertical Vegetation Heterogeneity indices provided information necessary describe spatial reorganization after fire. Tree annual was good indicator forest communities. SRI allowed us phases with high- low-risk degradation during succession. High-risk ( 36 years old) had highest vertical heterogeneity seedling density (>10,000 seedlings ha−1 year−1). Due low levels, at high-risk would vulnerable antropic (e.g. livestock raising, logging) than phases. proposed contributes sustainable management because allows estimate minimum levels which could harvested.

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