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Parsing Long-Term Tree Recruitment, Growth, and Mortality to Identify Hurricane Effects on Structural and Compositional Change in a Tropical Forest
by
Zhang, Jiaying
, Heartsill-Scalley, Tamara
, Bras, Rafael L.
in
Algorithms
/ Forests
/ Growth rate
/ Hurricanes
/ Mortality
/ Recruitment
/ Species composition
/ Trees
/ Tropical forests
/ Watersheds
2022
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Parsing Long-Term Tree Recruitment, Growth, and Mortality to Identify Hurricane Effects on Structural and Compositional Change in a Tropical Forest
by
Zhang, Jiaying
, Heartsill-Scalley, Tamara
, Bras, Rafael L.
in
Algorithms
/ Forests
/ Growth rate
/ Hurricanes
/ Mortality
/ Recruitment
/ Species composition
/ Trees
/ Tropical forests
/ Watersheds
2022
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Parsing Long-Term Tree Recruitment, Growth, and Mortality to Identify Hurricane Effects on Structural and Compositional Change in a Tropical Forest
by
Zhang, Jiaying
, Heartsill-Scalley, Tamara
, Bras, Rafael L.
in
Algorithms
/ Forests
/ Growth rate
/ Hurricanes
/ Mortality
/ Recruitment
/ Species composition
/ Trees
/ Tropical forests
/ Watersheds
2022
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Parsing Long-Term Tree Recruitment, Growth, and Mortality to Identify Hurricane Effects on Structural and Compositional Change in a Tropical Forest
Journal Article
Parsing Long-Term Tree Recruitment, Growth, and Mortality to Identify Hurricane Effects on Structural and Compositional Change in a Tropical Forest
2022
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Overview
After hurricane disturbances in tropical forests, the size structure and species composition are affected by immediate mortality, and subsequent recruitment and individual growth. Often, immediate post-disturbance stand-level data are presented but understanding of the components that affect changes in growth and longer-term responses to forest structure and composition are lacking. To answer questions about how mortality, recruitment, and growth change among successional Plant Functional Types (PFT) through time after a hurricane disturbance, we use long-term census data (1989–2014) collected in the Luquillo Experimental Forest, Puerto Rico. We developed an algorithm to fill missing diameter data from the long-term data set that was collected three months after Hurricane Hugo; and subsequently at five-year intervals. Both the immediate hurricane-induced mortality and subsequent mortality were lower in stems with larger diameters, but varied among successional PFTs Early, Mid, Late, and Palm. Tree growth rates were observed to decrease with time since the hurricane disturbance. Five years after the hurricane, mortality was minimal but then increased gradually with time. In contrast, recruitment was highest five years after the hurricane and then decreased with time. The palm Prestoea montana became the most abundant species in the forest after the hurricane, as it had the lowest immediate hurricane-induced and subsequent mortality, and the highest recruitment. Twenty-five years after the hurricane, the palm and the Late PFT dominate the forest after shifting species composition from pre-hurricane conditions.
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