HUMAN OR NATURAL DISTURBANCE: LANDSCAPE-SCALE DYNAMICS OF THE TROPICAL FORESTS OF PUERTO RICO

There is a long history of experimental research in the Luquillo Experimental Forest in Puerto Rico. These experiments have addressed questions about biotic thresholds, assessed why communities vary along natural gradients, and have explored forest responses to a range of both anthropogenic and non-anthropogenic disturbances. Combined, these studies cover many of the major disturbances that affect tropical forests around the world and span a wide range of topics, including the effects of forest thinning, ionizing radiation, hurricane disturbance, nitrogen deposition, drought, and global warming. These invaluable studies have greatly enhanced our understanding of tropical forest function under different disturbance regimes and informed the development of management strategies. Here we summarize the major field experiments that have occurred within the Luquillo Experimental Forest. Taken together, results from the major experiments conducted in the Luquillo Experimental Forest demonstrate a high resilience of Puerto Rico’s tropical forests to a variety of stressors.

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Trailblazing the Carbon Cycle of Tropical Forests from Puerto Rico

Forests ◽

10.3390/f8040101 ◽

2017 ◽

Vol 8 (4) ◽

pp. 101 ◽

Cited By ~ 5

Author(s):

Sandra Brown ◽

Ariel Lugo

Keyword(s):

Puerto Rico ◽

Carbon Cycle ◽

Tropical Forests

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Comparisons of spatial patterns between windthrow and logging at two spatial scales

Canadian Journal of Forest Research ◽

10.1139/cjfr-2013-0402 ◽

2014 ◽

Vol 44 (7) ◽

pp. 740-749 ◽

Cited By ~ 4

Author(s):

Kaysandra Waldron ◽

Jean-Claude Ruel ◽

Sylvie Gauthier ◽

Philippe Goulet

Keyword(s):

Spatial Scales ◽

Natural Disturbance ◽

Landscape Scale ◽

Canopy Openness ◽

Managed Forests ◽

Eastern Canada ◽

Spatial Characteristics ◽

Management Context ◽

Landscape Scales ◽

Shape Complexity

Windthrow is a dominant natural disturbance in the boreal forest of eastern Canada. To provide the range of variability of a natural disturbance, its spatial distribution and patch metrics at stand and landscape scales have to be considered, together with the characterization of its severity. Our study characterized both partial windthrow (PW) and total windthrow (TW) spatial distributions at the landscape scale and patchiness within affected stands (stand scale). Landscape scale corresponded to three areas of about 5000 ha. Stand scale was the finest scale of analysis and corresponded to each affected stand within landscapes. In addition, windthrow spatial characteristics were compared with spatial characteristics of harvested areas (CUT). At the landscape scale, our results showed that TW stands were more isolated than PW stands and that mean shape complexity of disturbed stands was low, regardless of whether the disturbance was a windthrow or a harvested area. At the affected stand scale, residual trees covered a significantly higher proportion of PW stands than TW stands and CUT. CUT and TW did not share many spatial characteristics at the stand scale. CUT had a significantly higher proportion of complete canopy openness than TW. Our results showed that PW are spatially heterogeneous at both landscape and stand scales. In an ecosystem management context, i.e., a management that reduces the discrepancy between natural and managed forests, our results showed that forest managers could practice a variety of harvesting methods of different intensities.

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Characterization of Dry-Season Phenology in Tropical Forests by Reconstructing Cloud-Free Landsat Time Series

Remote Sensing ◽

10.3390/rs13234736 ◽

2021 ◽

Vol 13 (23) ◽

pp. 4736

Author(s):

Xiaolin Zhu ◽

Eileen H. Helmer ◽

David Gwenzi ◽

Melissa Collin ◽

Sean Fleming ◽

...

Keyword(s):

Time Series ◽

Puerto Rico ◽

Tropical Forests ◽

Tropical Dry Forest ◽

Dry Season ◽

Dry Forest ◽

High Quality ◽

Forest Zone ◽

Fine Resolution ◽

Field Plots

Fine-resolution satellite imagery is needed for characterizing dry-season phenology in tropical forests since many tropical forests are very spatially heterogeneous due to their diverse species and environmental background. However, fine-resolution satellite imagery, such as Landsat, has a 16-day revisit cycle that makes it hard to obtain a high-quality vegetation index time series due to persistent clouds in tropical regions. To solve this challenge, this study explored the feasibility of employing a series of advanced technologies for reconstructing a high-quality Landsat time series from 2005 to 2009 for detecting dry-season phenology in tropical forests; Puerto Rico was selected as a testbed. We combined bidirectional reflectance distribution function (BRDF) correction, cloud and shadow screening, and contaminated pixel interpolation to process the raw Landsat time series and developed a thresholding method to extract 15 phenology metrics. The cloud-masked and gap-filled reconstructed images were tested with simulated clouds. In addition, the derived phenology metrics for grassland and forest in the tropical dry forest zone of Puerto Rico were evaluated with ground observations from PhenoCam data and field plots. Results show that clouds and cloud shadows are more accurately detected than the Landsat cloud quality assessment (QA) band, and that data gaps resulting from those clouds and shadows can be accurately reconstructed (R2 = 0.89). In the tropical dry forest zone, the detected phenology dates (such as greenup, browndown, and dry-season length) generally agree with the PhenoCam observations (R2 = 0.69), and Landsat-based phenology is better than MODIS-based phenology for modeling aboveground biomass and leaf area index collected in field plots (plot size is roughly equivalent to a 3 × 3 Landsat pixels). This study suggests that the Landsat time series can be used to characterize the dry-season phenology of tropical forests after careful processing, which will help to improve our understanding of vegetation–climate interactions at fine scales in tropical forests.

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