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Title: Landscape-scale consequences of differential tree mortality from catastrophic wind disturbance in the Amazon
Authors: Rifai, Sami Walid
Urquiza-Mu?oz, Jos? D.
Negrón-Juárez, Robinson I.
Ramirez Arevalo, Fredy Francisco
Rodil, Tello-espinoza,
Vanderwel, Mark C.
Lichstein, Jeremy W.
Chambers, Jeffrey Quintin
Bohlman, Stephanie Ann
Keywords: Biomass
Carbon Sink
Catastrophic Event
Environmental Disturbance
Landscape Change
Numerical Model
Regression Analysis
Spectral Analysis
Uncertainty Analysis
Wood Quality
Biological Model
Environmental Monitoring
Environmental Monitoring
Models, Biological
Issue Date: 2016
metadata.dc.publisher.journal: Ecological Applications
metadata.dc.relation.ispartof: Volume 26, Número 7, Pags. 2225-2237
Abstract: Wind disturbance can create large forest blowdowns, which greatly reduces live biomass and adds uncertainty to the strength of the Amazon carbon sink. Observational studies from within the central Amazon have quantified blowdown size and estimated total mortality but have not determined which trees are most likely to die from a catastrophic wind disturbance. Also, the impact of spatial dependence upon tree mortality from wind disturbance has seldom been quantified, which is important because wind disturbance often kills clusters of trees due to large treefalls killing surrounding neighbors. We examine (1) the causes of differential mortality between adult trees from a 300-ha blowdown event in the Peruvian region of the northwestern Amazon, (2) how accounting for spatial dependence affects mortality predictions, and (3) how incorporating both differential mortality and spatial dependence affect the landscape level estimation of necromass produced from the blowdown. Standard regression and spatial regression models were used to estimate how stem diameter, wood density, elevation, and a satellite-derived disturbance metric influenced the probability of tree death from the blowdown event. The model parameters regarding tree characteristics, topography, and spatial autocorrelation of the field data were then used to determine the consequences of non-random mortality for landscape production of necromass through a simulation model. Tree mortality was highly non-random within the blowdown, where tree mortality rates were highest for trees that were large, had low wood density, and were located at high elevation. Of the differential mortality models, the non-spatial models overpredicted necromass, whereas the spatial model slightly underpredicted necromass. When parameterized from the same field data, the spatial regression model with differential mortality estimated only 7.5% more dead trees across the entire blowdown than the random mortality model, yet it estimated 51% greater necromass. We suggest that predictions of forest carbon loss from wind disturbance are sensitive to not only the underlying spatial dependence of observations, but also the biological differences between individuals that promote differential levels of mortality. © 2016 by the Ecological Society of America.
metadata.dc.identifier.doi: 10.1002/eap.1368
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