Model-Based Estimation of Amazonian Forests Recovery Time after Drought and Fire Events

Abstract

In recent decades, droughts, deforestation and wildfires have become recurring phenomena that have heavily affected both human activities and natural ecosystems in Amazonia. The time needed for an ecosystem to recover from carbon losses is a crucial metric to evaluate disturbance impacts on forests. However, little is known about the impacts of these disturbances, alone and synergistically, on forest recovery time and the resulting spatiotemporal patterns at the regional scale. In this study, we combined the 3-PG forest growth model, remote sensing and field derived equations, to map the Amazonia-wide (3 km of spatial resolution) impact and recovery time of aboveground biomass (AGB) after drought, fire and a combination of logging and fire. Our results indicate that AGB decreases by 4%, 19% and 46% in forests affected by drought, fire and logging + fire, respectively, with an average AGB recovery time of 27 years for drought, 44 years for burned and 63 years for logged + burned areas and with maximum values reaching 184 years in areas of high fire intensity. Our findings provide two major insights in the spatial and temporal patterns of drought and wildfire in the Amazon: (1) the recovery time of the forests takes longer in the southeastern part of the basin, and, (2) as droughts and wildfires become more frequent—since the intervals between the disturbances are getting shorter than the rate of forest regeneration—the long lasting damage they cause potentially results in a permanent and increasing carbon losses from these fragile ecosystems.

Monitoring post-fire recovery of various vegetation biomes using multi-wavelength satellite remote sensing

“…AMSR2 data were provided by Vrije Universiteit Amsterdam (Richard de Jeu) and NASA GSFC (Goddard Space Flight Center) (Manfred Owe) (2014). AMSR2/GCOM-W1 surface soil moisture (LPRM) L3 1 d 25 km × 25 km ascending V001 data were edited by the Goddard Earth Sciences Data and Information Services Center (GES DISC) (Bill Teng) of Greenbelt, Maryland, USA (https://doi.org/10.5067/M5DTR2QUYLS2, de Jeu and Owe, 2014). TWS data were obtained from the GFZ (German Research Centre for Geosciences) GravIS (Gravity Information Service) web portal.…”

Natural forests for a safe climate: Enhancing ecosystem integrity, biodiversity and adaptive capacity for climate mitigation

“…In many forest systems, fires in previously logged or managed landscapes can be more intense/severe, emit more carbon to the atmosphere, and take longer to recover than fires in ecologically mature or primary forests due to increased fuel availability, lower fuel moisture, and dense secondary forests that carry crown fires and are susceptible to extensive tree mortality (Odion et al, 2004;Stone et al, 2004;Thompson et al, 2007;Lindenmayer et al, 2009Lindenmayer et al, , 2011Price and Bradstock, 2012;Kukavskaya et al, 2013;Taylor et al, 2014;Bradley et al, 2016;Dieleman et al, 2020;De Faria et al, 2021;Landi et al, 2021). In general, larger and older trees have a greater chance of surviving fires due to thicker bark and lower relative scorch height (Laurance and Williamson, 2001;Lindenmayer et al, 2019).…”

Altitudinal differentiation of forest resilience to drought in a dryland mountain

“…The greater the drought intensity the ecosystem experiences, the longer the recovery time is required (Schwalm et al, 2017;Fu et al, 2017). At the same time, forest showed longer recovery time than other ecosystems, and the risk of incomplete recovery was higher (De Faria et al, 2021;Forzieri et al, 2022). However, forest resilience of dryland mountains under drought disturbance has not been systematically studied.…”