title: Landscape-scale consequences of differential tree mortality from catastrophic wind disturbance in the Amazon.
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.
authors.affiliation: School of Forest Resources and Conservation, University of Florida, Gainesville, Florida, 32611, USA. srifai@gmail.com.
authors.forename: Sami W
authors.initials: SW
authors.lastname: Rifai
authors.affiliation: Facultad de Ciencias Forestales, Universidad Nacional Amazonía Peruana, Iquitos, Perú.
authors.forename: José D
authors.initials: JD
authors.lastname: Urquiza Muñoz
authors.affiliation: Climate Sciences Department, Earth Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California, 94720, USA.
authors.forename: Robinson I
authors.initials: RI
authors.lastname: Negrón-Juárez
authors.affiliation: Facultad de Ciencias Forestales, Universidad Nacional Amazonía Peruana, Iquitos, Perú.
authors.forename: Fredy R
authors.initials: FR
authors.lastname: Ramírez Arévalo
authors.affiliation: Facultad de Ciencias Forestales, Universidad Nacional Amazonía Peruana, Iquitos, Perú.
authors.forename: Rodil
authors.initials: R
authors.lastname: Tello-Espinoza
authors.affiliation: Department of Biology, University of Regina, 3737 Wascana Pkwy, Regina, SK, S4S 0A2, Canada.
authors.forename: Mark C
authors.initials: MC
authors.lastname: Vanderwel
authors.affiliation: Department of Biology, University of Florida, Gainesville, Florida, 32611, USA.
authors.forename: Jeremy W
authors.initials: JW
authors.lastname: Lichstein
authors.affiliation: Climate Sciences Department, Earth Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California, 94720, USA.|Department of Geography, University of California, Berkeley, California, 94720, USA.|Instituto Nacional de Pesquisas da Amazônia, Coordenação de Pesquisas de Silvicultura Tropical, 69060-001, Manaus, Amazonas, Brazil.
authors.forename: Jeffrey Q
authors.initials: JQ
authors.lastname: Chambers
authors.affiliation: School of Forest Resources and Conservation, University of Florida, Gainesville, Florida, 32611, USA.|Smithsonian Tropical Research Institute, Apartado 0843-03092, Balboa, Ancon, Republic of Panama.
authors.forename: Stephanie A
authors.initials: SA
authors.lastname: Bohlman
mesh_terms: D004784:Environmental Monitoring; D065928:Forests; D008954:Models, Biological; D010568:Peru; D014197:Trees; D014919:Wind
keywords: 
  INLA
  ; Amazon; Iquitos; Loreto; blowdown; canopy gap; downburst; necromass; selective mortality; spectral mixture analysis; tree mortality; wind disturbance; windthrow; wood density