Next Article in Journal
GPVC: Graphics Pipeline-Based Visibility Classification for Texture Reconstruction
Previous Article in Journal
Ground and Multi-Class Classification of Airborne Laser Scanner Point Clouds Using Fully Convolutional Networks
Previous Article in Special Issue
Detecting Human Presence and Influence on Neotropical Forests with Remote Sensing
Article Menu
Issue 11 (November) cover image

Export Article

Open AccessFeature PaperArticle
Remote Sens. 2018, 10(11), 1724; https://doi.org/10.3390/rs10111724

Tropical Deforestation and Recolonization by Exotic and Native Trees: Spatial Patterns of Tropical Forest Biomass, Functional Groups, and Species Counts and Links to Stand Age, Geoclimate, and Sustainability Goals

1
USDA Forest Service, International Institute of Tropical Forestry, Río Piedras 00926, Puerto Rico
2
Colorado State University, Center for Ecological Management of Military Lands, Fort Collins, CO 80523, USA
3
USDA Forest Service, Northern Research Station, Saint Paul, MN 55108, USA
4
US National Park Service, Inventory and Monitoring Network, Fort Collins, CO 80525, USA
5
Colorado State University, Ecosystem Science and Sustainability, Fort Collins, CO 80523, USA
6
USDA Forest Service, Southern Research Station, Asheville, NC 28804, USA
7
Consulting Research Ecology, Portland, OR 97212, USA
8
Red Castle Resources, Salt Lake City, UT 84103, USA
*
Author to whom correspondence should be addressed.
Received: 2 August 2018 / Revised: 9 October 2018 / Accepted: 19 October 2018 / Published: 1 November 2018
(This article belongs to the Special Issue Remote Sensing of Tropical Forest Biodiversity)
Full-Text   |   PDF [25666 KB, uploaded 1 November 2018]   |  

Abstract

We mapped native, endemic, and introduced (i.e., exotic) tree species counts, relative basal areas of functional groups, species basal areas, and forest biomass from forest inventory data, satellite imagery, and environmental data for Puerto Rico and the Virgin Islands. Imagery included time series of Landsat composites and Moderate Resolution Imaging Spectroradiometer (MODIS)-based phenology. Environmental data included climate, land-cover, geology, topography, and road distances. Large-scale deforestation and subsequent forest regrowth are clear in the resulting maps decades after large-scale transition back to forest. Stand age, climate, geology, topography, road/urban locations, and protection are clearly influential. Unprotected forests on more accessible or arable lands are younger and have more introduced species and deciduous and nitrogen-fixing basal areas, fewer endemic species, and less biomass. Exotic species are widespread—except in the oldest, most remote forests on the least arable lands, where shade-tolerant exotics may persist. Although the maps have large uncertainty, their patterns of biomass, tree species diversity, and functional traits suggest that for a given geoclimate, forest age is a core proxy for forest biomass, species counts, nitrogen-fixing status, and leaf longevity. Geoclimate indicates hard-leaved species commonness. Until global wall-to-wall remote sensing data from specialized sensors are available, maps from multispectral image time series and other predictor data should help with running ecosystem models and as sustainable development indicators. Forest attribute models trained with a tree species ordination and mapped with nearest neighbor substitution (Phenological Gradient Nearest Neighbor method, PGNN) yielded larger correlation coefficients for observed vs. mapped tree species basal areas than Cubist regression tree models trained separately on each species. In contrast, Cubist regression tree models of forest structural and functional attributes yielded larger such correlation coefficients than the ordination-trained PGNN models. View Full-Text
Keywords: deciduousness; protected areas; leaf thickness; sclerophylly; forest recovery; biophysical and socioeconomic controls; sustainable development goals; tree species richness; Earth system models; cloud forest; mountain habitats; species distribution models; leaf toughness; lithology; endemism deciduousness; protected areas; leaf thickness; sclerophylly; forest recovery; biophysical and socioeconomic controls; sustainable development goals; tree species richness; Earth system models; cloud forest; mountain habitats; species distribution models; leaf toughness; lithology; endemism
Figures

Graphical abstract

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Helmer, E.H.; Ruzycki, T.S.; Wilson, B.T.; Sherrill, K.R.; Lefsky, M.A.; Marcano-Vega, H.; Brandeis, T.J.; Erickson, H.E.; Ruefenacht, B. Tropical Deforestation and Recolonization by Exotic and Native Trees: Spatial Patterns of Tropical Forest Biomass, Functional Groups, and Species Counts and Links to Stand Age, Geoclimate, and Sustainability Goals. Remote Sens. 2018, 10, 1724.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Remote Sens. EISSN 2072-4292 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top