Tropical Forest Science Research Articles

Sensing Forests Directly: The Power of Permanent Plots.

The need to measure, monitor, and understand our living planet is greater than ever. Yet, while many technologies are applied to tackle this need, one developed in the 19th century is transforming tropical ecology. Permanent plots, in which forests are directly sensed tree-by-tree and species-by-species, already provide a global public good. They could make greater contributions still by unlocking our potential to understand future ecological change, as the more that computational and remote technologies are deployed the greater the need to ground them with direct observations and the physical, nature-based skills of those who make them. To achieve this requires building profound connections with forests and disadvantaged communities and sustaining these over time. Many of the greatest needs and opportunities in tropical forest science are therefore not to be found in space or in silico, but in vivo, with the people, places and plots who experience nature directly. These are fundamental to understanding the health, predicting the future, and exploring the potential of Earth's richest ecosystems. Now is the time to invest in the tropical field research communities who make so much possible.

Species composition and community structure of warm temperate deciduous broadleaved forests in Huangguan of Qinling Mountains, China

The Qinling Mountain is a natural boundary between warm temperate zone and subtropical zone. While the China Forest Biodiversity Monitoring Network (CForBio) have basically covered most of the climate regions in China, few plots were located in the climate transition zone. Following the field protocol of CForBio and the Center for Tropical Forest Science (CTFS), a 25 hm2(500 m×500 m) forest plot was established in Huangguan Nature Reserve in Shaanxi Province, China, in 2019. In this study, we analyzed species composition, flora characteristics, diameter class structure, and spatial distribution patterns of dominant tree species based on the data of all woody species with a diameter at breast height (DBH) ≥1 cm. The results showed that there were 75137 woody individuals with DBH ≥1 cm in the plot (95679 when including branching individuals), belonging to 121 species, 83 genera and 44 families. The flora type at the genera level was mainly temperate, accounting for 71.1% of the total genera, and mixed with some tropical components. The dominant species in the community were obvious, with the number of individuals in the top 5 species exceeding 40% of the total number of individuals, the number of individuals in the top 50 species accounting for 95% of the total number of individuals, and the number of individuals in the remaining 61 species being less than 5% of the total. The diameter distribution of all woody indivi-duals in the plot was inverted 'J' type. Spatial distribution patterns varied across the four most abundant species with importance value >5. The degree of aggregation within species decreased with the increases of scales, while the spatial distribution of different species was affected by environmental heterogeneity. Warm-temperate deciduous broadleaved forest in Qinling Mountains had abundant species, stable community structure and good regeneration, reflecting the typical characteristics of the transition from warm temperate zone to subtropical zone. Environmental heterogeneity might be an important factor affecting the spatial distribution of tree species in the plot.

Spatial associations between tree regeneration and soil nutrient in secondary Picea forest in Guandi Mountains, Shanxi, China.

According to the technical specifications of CTFS (Center for Tropical Forest Science), 190 sampling points of 4-hm2 plot (GDS plot) in Guandi Mountains of Shanxi Province, China were investigated to examine the spatial distribution pattern of seedlings and 14 soil indicators, including pH value and nutrient indicators. We analyzed the spatial associations between tree regeneration and soil nutrients, explored the mechanism of tree regeneration pattern of secon-dary Picea forest. The results showed that more seedlings survived in the patches with low contents of available N, available K, available Cu, available Fe, available Mn, available Ni and available Zn. Besides available K, the negative correlation between the other six soil nutrient factors and the number of regeneration seedlings of the Ⅱ (2.5 cm<GD≤4 cm) and Ⅲ (4 cm<GD≤5 cm) diameter classes with relatively large ground diameter (GD) was higher than that in the Ⅰ diameter class (0 cm<GD≤2.5 cm), indicating that soil nutrients had a greater influence on the distribution of regeneration seedlings in larger diameter class, and that the survival of regeneration seedlings was more dependent on soil condition. The soil of GDS was slightly acidic (5.5<pH<6.8). The increase of soil pH was accompanied by the decrease of available Al content, which was conducive to the regeneration and survival of trees. The total explanation of nine soil factors (including soil available N, available K, available Cu, available Fe, available Mn, available Ni, available Zn, available Al and pH value) on the regeneration and distribution of tree species in GDS plots was 19.7%.

Community structure in different successional stages in north temperate forests of Changbai Mountains, China.

Aims The Changbai Mountains had a large area of undisturbed temperate old-growth forest that was partly destroyed by large-scale industrial logging at the turn of the 20th century and replaced by secondary forests and plantations. Our objective was to further understand ecosystem devel-opment,community composition and structure,and spatial distribution of major tree populations. Methods Three long-term 5.2 hm2 forest plots were established in secondary Populus davidi-ana-Betula platyphylla forest (PBF),secondary conifer and broadleaved mixed forest (SCBMF) and Tilia amurensis-Pinus koraiensis mixed forest (TPMF) in the Changbai Mountains following the proto-cols of the Center for Tropical Forest Science forest dynamic plot. We tagged and recorded the species,diameter at breast height (DBH),height and crown diameter of all live and dead trees with DBH 1 cm. We determined the spatial distribution of five dominant canopy tree species by pair-correlation g(r) function and performed variation partitioning analysis to estimate the environmental effect on spatial distribution. Important findings We recorded 20 949,14 725 and 12 062 live individuals and basal areas of 24.74,32.07 and 56.64 m2.hm–2 in PBF,SCBMF and TPMF,respectively. Tilia amurensis,with the overall highest importance value and basal area,was the major dominant tree species in SCBMF,P. davidianaand B. platyphylla dominated PBF and P. koraiensis dominated TPMF. In the secondary forests BPF and SCBMF,the size-class distribution of Pinus koraiensis,Acer mono,Abies nephrolepis,Picea jezoensis and Tilia amurensis showed the reverse J-shape form,whereas P. koraiensis and T. amurensis showed normal distributions in TPMF. Paired-correlation g(r) function showed that the main tree species had aggregated distributions,and the aggregation intensity decreased with the increasing distances. Environment variables had a strong effect on tree distribution,but the interpretation power of environment variables was very low in TPMF.

A model for analyzing clustered occurrence data.

Spatial or temporal clustering commonly arises in various biological and ecological applications, for example, species or communities may cluster in groups. In this paper, we develop a new clustered occurrence data model where presence-absence data are modeled under a multivariate negative binomial framework. We account for spatial or temporal clustering by introducing a community parameter in the model that controls the strength of dependence between observations thereby enhancing the estimation of the mean and dispersion parameters. We provide conditions to show the existence of maximum likelihood estimates when cluster sizes are homogeneous and equal to 2 or 3 and consider a composite likelihood approach that allows for additional robustness and flexibility in fitting for clustered occurrence data. The proposed method is evaluated in a simulation study and demonstrated using forest plot data from the Center for Tropical Forest Science. Finally, we present several examples using multiple visit occupancy data to illustrate the difference between the proposed model and those of N-mixturemodels.

Community structure of Quercus aliena var acuteserrata forest in the Taibai Mountain, China

Qinling Mountains are biodiversity hotspots in China, with rich vegetation resources and species diversity. To clarify the mechanism underlying biodiversity maintenance during vegetation restoration in this area, we established two permanent plots with each area of 100 m×150 m in the Q. aliena var. acuteserrata secondary forest (SF) and primary forest (PF) in the northern slope of Taibai Mountain in 2016, following the standardized protocols by CTFS (the Center for Tropical Forest Science). We analyzed community composition and structure with measuring all trees with DBH ≥ 1 cm. 2839 and 2840 trees were recorded in the SF and PF plots, respectively. Trees in those two plots belong to 29 families, 45 genera, 65 species and 21 families, 37 genera, 47 species, respectively. The proportions of occasional species and rare species were 38.4% and 24.6% in the SF plot, and 40.4% and 19.2% in the PF plot. Most of the trees were distributed in northern temperate zones, and the proportions of genera were 46.6% and 48.7% in the SF and PF plots, respectively. The diameter of Q. aliena var. acuteserrata in both plots followed a unimodal distribution (more young trees than old ones). The diameter distributions of companion species (e.g., Sorbus alnifolia, Acer davidii, Cornus kousa, and Staphylea holocarpa) were inverted "J" shapes, indicating that those populations could have complete life history. In the pair correlation function g(r) analyses, the aggregation of dominant species were the strongest at 0-2 m scale in the two plots when r=10 m. The degree of aggregation gradually weakened with increasing scale. The population distribution patterns of the dominant species were random or uniform when the scale increased to certain value. The average uniform angle index (W) were 0.56 and 0.58 in the SF and PF, respectively. Trees in the communities followed an aggregated distribution. The average W of the community and dominant species in the SF were smaller than that in the PF, indicating weaker species aggregation in the SF. The average dominance in the SF and PF was both 0.47, indicating that the stands were in a co-dominant state. The average mingling was 0.70 and 0.57 in the SF and PF, respectively, which belonged to high and moderate mingling. Species richness, community stability and spatial distribution patterns of forest community could be affected by human disturbance. The role of interspecific interaction, effects of habitat heterogeneity on species coexistence, and variation of community structure should be considered during vegetation restoration of disturbed forest community.

Creating benchmark measurements of tropical forest bird communities in large plots

Abstract An understanding of how tropical bird communities might respond to climate change and other types of environmental stressors seems particularly urgent, yet we still lack, except for a few sites, even snapshot inventories of avian richness and abundances across most of the tropics. Such benchmark measurements of tropical bird species richness and abundances could provide opportunities for future repeat surveys and, therefore, strong insight into degrees and pace of change in community organization over time. The challenges of creating a network of benchmarked sites include high variation in detectability among species, general rarity of many species that creates hurdles for use of modern bird counting methods aimed at controlling for variation in detectability, and lack of a standardized protocol to create repeatable inventories. We argue that reasonably complete inventories of tropical bird communities require use of multiple survey techniques to provide internal calibrations of abundance estimates and require multiple visits to improve completeness of richness inventories. We suggest that a network of large (50–100 ha) plots scattered across the tropics can also provide insights into geographic variation in and drivers of avian community structure analogous to insights provided by the Smithsonian Center for Tropical Forest Science Forest Global Earth Observatory network of forest dynamics plots. Perhaps most importantly, large plots provide opportunities for use of multiple survey techniques to estimate abundances while also using some exactly repeatable survey techniques that can greatly improve abilities to quantify change over time. We provide guidance on establishment of and survey methods for large tropical bird plots as well as important recommendations for collection and archiving of metadata to safeguard the long-term utility of valuable benchmark data.

Tree Demography Plots

The pantropical network of large tree demography plots coordinated by the Smithsonian’s Center for Tropical Forest Science has now gone global, as part of the Smithsonian Institution Global Earth Observatories. Some four million tropical trees, representing about 10,000 species, are now tagged, provisionally identified and periodically recensused. Some 3,000 species are captured in the six plots within Malesia. These include species rarely collected and many that are now endangered. Easy location of trees for periodic examination for fertile material and detailed ecological data, together with seasoned in-country research teams, provide unique opportunities for research collaboration.

Community characteristics and stability analysis of secondary deciduous broad-leaved forest in Mopan Mountains, Jilin Province, China.

The secondary deciduous broad-leaved forests in northeastern China were generally regenerated from the disturbed broad-leaved Korean pine forests, which are widely distributed in Changbai Mountains area. To understand their composition, structure and stability, a 5.76 hm2(240 m × 240 m) forest plot was established in the Mopan Mountains, Jilin Province in 2005, following the standards of the Center for Tropical Forest Science (CTFS). In this study, we analyzed the species composition, size class structure, survival curves of the main tree species and community stability of all woody plants with DBH ≥1 cm. The results showed that a total of 13368 individuals with DBH ≥1 cm were found, belonging to 39 species, 31 genera and 19 families. There were 12 species with importance value ≥1. The species composition was complex, with obvious characteristics of mixed broad-leaved forest. The abundance varied significantly among different species. The rare species and occasional species accounted for 23.1% and 43.6% of the total number of the species, respectively. The size distribution of all individuals showed a reverse "J" shape, which indicated that the community was in a stable and normal growth status. Fraxinus rhynchophylla, Quercus mongolica, Acer mono, and Maackia amurensis out of the six major species fitted reverse "J" form, Juglans manshurica showed an approximately normal distribution, and Ulmus japonica showed a "L" shape distribution. The survival curves of the six major tree species showed that the populations of F. rhynchophylla, Q. mongolica, A. mono, and M. amurensis were stable, J. mandshurica was declining, and U. japonica was growing. Results from the stability analysis of M-Godron indicated that the community was relatively stable at present.

Assessing terrestrial laser scanning for developing non-destructive biomass allometry

Forests provide essential ecosystem services and hold approximately 45% of global terrestrial carbon. Estimates of the quantity and spatial distribution of global forest carbon are built on the assumption that regional- or national-scale allometry accurately captures growth form across the wide spectrum of plant size. Allometry is painstaking and costly to create: trees must be cut, dried, and weighed, over the span of months. This bottleneck has left most equations low in sample size and without large trees (>50 cm), which can contain over 40% of aboveground carbon. Terrestrial laser scanning (TLS) can potentially increase the range and sample size of allometric equations through non-destructive biomass estimation and must be evaluated in this context. We deployed TLS at the Center for Tropical Forest Science - Forest Global Earth Observatory (CTFS-ForestGEO) plot in Front Royal, Virginia and virtually reconstructed 329 trees with diameters up to 123 cm. Three-dimensional tree models were the basis for 22 local allometric relationships for comparison to the Jenkins et al. (2003) and Chojnacky et al. (2014) equations. Overall, TLS allometry had lower RMSE and predicted higher tree-level biomass compared to the equivalent national equations. We evaluated site-wide allometry for errors from insufficient sample size and diameter range. Allometric equations did not stabilize to a consistent set of parameters until 100–200 samples were reached and exclusion of large trees severely limited prediction accuracy. This work implies that current biomass equations may be inadequate and highlights TLS stem modeling as an appropriate method of non-destructive allometric equation development for updating allometry and reducing uncertainty in landscape-level biomass estimates.

Research and Conservation on an Artificial Island in a Shipping Lane and Elsewhere in the Tropics

Research and Conservation on an Artificial Island in a Shipping Lane and Elsewhere in the Tropics

Comparison of lidar- and allometry-derived canopy height models in an eastern deciduous forest

Abstract Tree crown geometry and height, especially when coupled with remotely sensed data, can aid in the characterization of tree and forest structure. In this study, we develop mixed-effects model allometric equations for tree height, crown radius, and crown depth using data collected on 374 trees across 14 species within the extent of the joint Center for Tropical Forest Science (CTFS) and Smithsonian Institute’s Forest Global Earth Observatory (ForestGEO) MegaPlot on Prospect Hill at Harvard Forest, Massachusetts. We applied allometry to a census of the 35-ha plot on Prospect Hill to evaluate tree height and crown radius estimates using a lidar canopy height model. We found significant relationships using stem diameter-at-breast-height (DBH) and species to estimate tree height (ρr2 = 0.70, RMSE = 2.96 m), crown depth (ρr2 = 0.35, RMSE = 3.24 m) and crown radius (ρr2 = 0.43, RMSE = 1.22 m). Using Fast Fourier Transforms (FFTs), we compared the power spectra of a lidar canopy height model to five synthetic canopy height models derived from allometric estimates of height and crown radius. The FFTs showed good agreement between lidar and synthetic canopy height models (CHMs) at spatial wavelengths longer than 64 m, or about the distance across 3–4 dominant tree crowns, and poorer agreement at shorter spatial wavelengths, which we attribute to the simple crown shape applied to modeled crowns and a lack of crown overlap in the synthetic CHMs compared to the lidar CHM. At the tree level, some species exhibited tight links between lidar-measured height and estimated tree height (e.g., Quercus rubra, Quercus velutina, Pinus strobus), suggesting height allometry provided reasonable estimates of tree height for some species despite a negative bias in the synthetic canopy height models relative to the lidar canopy height model.

Patterns of tree mortality in a temperate deciduous forest derived from a large forest dynamics plot

AbstractTree mortality is one of the most influential drivers of forest dynamics, and characterizing patterns of tree mortality is critical to understanding forest dynamics and ecosystem function in the present era of global change. Here, we use a unique data set of mortality in a temperate deciduous forest to characterize rates and drivers of mortality. At the 25.6‐ha Center for Tropical Forest Science—Forest Global Earth Observatory forest dynamics plot at the Smithsonian Conservation Biology Institute (Virginia, USA), we conducted two full tree censuses in 2008 and 2013 and then tracked mortality over the next 2 years (2014 and 2015). Overall, the mortality rate, m, of stems ≥10 cm diameter was 1.3–2.1%/yr. Biomass mortality, M, was 1.9–3.4 Mg·ha−1·yr−1 at the stand level (0.6–1.1%/yr of biomass), less than biomass gains from growth and recruitment, resulting in net live biomass accumulation. Small stems died at the highest rate; however, contributions to M increased toward larger size classes. Most species had m &lt; 2%/yr and M &lt; 0.25 Mg·ha−1·yr−1 (&lt;3%/yr of biomass), whereas two to four species had anomalously high mortality rates during each census period, accounting for 15–24% of m (n = 2, Cercis canadensis, Ulmus species) and 39–75% of M (n = 4 Quercus species). Stems that died, whether or not in association with mechanical damage, tended to grow more slowly in preceding years than surviving stems and, for certain shade‐intolerant species, tended to be in neighborhoods with higher basal area. These findings show how relatively fine‐scale mortality processes contribute to stand‐level compositional change and carbon cycling. The mortality patterns reported here will provide a valuable basis for understanding future disturbance events within eastern deciduous forests and for comparing across forest types.

Lidar detection of individual tree size in tropical forests

Abstract Characterization of tropical forest trees has been limited to field-based techniques focused on measurement of diameter of the cylindrical part of the bole, with large uncertainty in measuring large trees with irregular shapes, and other size attributes such as total tree height and the crown size. Here, we introduce a methodology to decompose lidar point cloud data into 3D clusters corresponding to individual tree crowns (ITC) that enables the estimation of many biophysical variables of tropical forests such as tree height, crown area, crown volume, and tree number density. The ITC-based approach was tested using airborne high-resolution lidar data collected over the 50-ha Center for Tropical Forest Science (CTFS) plot in the Barro Colorado Island, Panama. The lack of tree height and crown size measurements in the field prohibits the direct validation of the ITC metrics. We assess the reliability of our method by comparing the aboveground biomass (AGB) estimated using ground and lidar individual tree measurements at multiple spatial scales, namely 1 ha, 2.25 ha, 4 ha, and 6.25 ha. We examined four different lidar-derived AGB models, with three based on individual tree height, crown volume, and crown area, and one with mean top canopy height (TCH) calculated at the plot level using the lidar canopy height model. Results show that the predictive power of all models based on ITC size and TCH increases with decreasing spatial resolution from 16.9% at 1 ha for the worst model to 5.0% at 6.25 ha for the best model. The TCH-based model performed slightly better than ITC-based models except at higher spatial scales (~ 4 ha) and when errors due to edge effects associated with tree crowns were reduced. Unlike the TCH models that change regionally depending on forest type and structure allometry, the ITC-based models are derived as a function of individual tree allometry and can be extended globally to all tropical forests. The method for lidar detection of individual crown size overcome some limitations of ground-based inventories such as 1) it is able to access crowns of large trees and 2) it enables the assessment of directional changes in tree density, canopy architecture and forest dynamics over large and inaccessible areas to support robust tropical ecological studies.

Qualitative differences in tree species distributions along soil chemical gradients give clues to the mechanisms of specialization: why boron may be the most important soil nutrient at Barro Colorado Island

Qualitative differences in tree species distributions along soil chemical gradients give clues to the mechanisms of specialization: why boron may be the most important soil nutrient at Barro Colorado Island

Community characteristics of a mid-subtropical evergreen broad-leaved forest plot in the Wuyi Mountains, Fujian Province, southeastern China

Wuyi Mountains preserve the primary forest ecosystem characteristic of the mid-subtropics. We established a large-scale plots in this area according to standard international protocols (Center for Tropical Forest Science, CTFS). Community characteristics such as flora composition, floristic characteristics, DBH structure and spatial distribution patterns in a 9.6 ha plot were analyzed. The results showed that the vascular ·研究报告·

Tropical Forests in the Anthropocene

The Anthropocene is characterized as an epoch when human influence has begun to fundamentally alter many aspects of the Earth system and many of the planet's biomes. Here, we review and synthesize our understanding of Anthropocene changes in tropical forests. Key facets include deforestation driven by agricultural expansion, timber and wood extraction, the loss of fauna that maintain critical ecological connections, the spread of fire, landscape fragmentation, the spread of second-growth forests, new species invasion and pathogen spread, increasing CO2, and climate change. The patterns of change are spatially heterogeneous, are often characterized by strong interactions among different drivers, can have both large-scale and remote effects, and can play out through ecological cascades over long timescales. As a consequence, most tropical forests are on a trajectory to becoming altered ecosystems, with the degree of alteration dependent on the intensity and duration of the current bottleneck of human-induced pressures. We highlight the importance of this understanding to develop the strategies necessary for shaping the transition of tropical forests through the early Anthropocene, as well as highlight the opportunities and challenges for the tropical forest science community in the coming decades.

Forest structure in low-diversity tropical forests: a study of Hawaiian wet and dry forests.

The potential influence of diversity on ecosystem structure and function remains a topic of significant debate, especially for tropical forests where diversity can range widely. We used Center for Tropical Forest Science (CTFS) methodology to establish forest dynamics plots in montane wet forest and lowland dry forest on Hawai‘i Island. We compared the species diversity, tree density, basal area, biomass, and size class distributions between the two forest types. We then examined these variables across tropical forests within the CTFS network. Consistent with other island forests, the Hawai‘i forests were characterized by low species richness and very high relative dominance. The two Hawai‘i forests were floristically distinct, yet similar in species richness (15 vs. 21 species) and stem density (3078 vs. 3486/ha). While these forests were selected for their low invasive species cover relative to surrounding forests, both forests averaged 5–>50% invasive species cover; ongoing removal will be necessary to reduce or prevent competitive impacts, especially from woody species. The montane wet forest had much larger trees, resulting in eightfold higher basal area and above-ground biomass. Across the CTFS network, the Hawaiian montane wet forest was similar to other tropical forests with respect to diameter distributions, density, and aboveground biomass, while the Hawai‘i lowland dry forest was similar in density to tropical forests with much higher diversity. These findings suggest that forest structural variables can be similar across tropical forests independently of species richness. The inclusion of low-diversity Pacific Island forests in the CTFS network provides an ∼80-fold range in species richness (15–1182 species), six-fold variation in mean annual rainfall (835–5272 mm yr−1) and 1.8-fold variation in mean annual temperature (16.0–28.4°C). Thus, the Hawaiian forest plots expand the global forest plot network to enable testing of ecological theory for links among species diversity, environmental variation and ecosystem function.

Data and database standards for permanent forest plots in a global network

The Center for Tropical Forest Science established a network of 50-ha forest inventory plots in the 1980s, and now assists local scientists with field and database methods at 44 large-scale plots across boreal, temperate, and tropical forest biomes. We published detailed field methods over a decade ago, but at that time, data were maintained in spreadsheet-like formats, most harboring design flaws that resulted in frequent errors. We since established detailed database methods and a normalized data model for housing multiple censuses of large plots. Our largest databases include >2 million measurements, and each has a master version on a server where all collaborators can access and edit data. This paper focuses on the data requirements for handling tree census data and how to design databases to meet these requirements and to ensure data integrity. There are six key elements of a tree census which the database must reflect: (1) measurements, including individual trees (genetic units), stems within trees, and multiple measurements of stems; both field and data methods must assure that every tree, stem, and measurement is precisely identified and can be relocated easily; (2) coordinates, including quadrats within a plot, because field mapping is usually done by assigning x–y coordinates relative to local quadrat markers; (3) taxonomy, carrying a species identity for every tree with a history of individual re-identifications; (4) personnel, with records of the people who performed field and data work per quadrat; (5) assessment of field error via random re-measurements; and (6) a log of changes and a system of archiving so that errors can be tracked and past versions can be reconstructed and cited in publications. A well-designed database model reduces a variety of integrity errors and improves access to data tables in identical formats across many plots, allowing data analyses to be easily replicated and results to be compared. The principal disadvantage is that complexity of the database requires experienced data managers.

Detecting tropical forest biomass dynamics from repeated airborne lidar measurements

Abstract. Reducing uncertainty of terrestrial carbon cycle depends strongly on the accurate estimation of changes of global forest carbon stock. However, this is a challenging problem from either ground surveys or remote sensing techniques in tropical forests. Here, we examine the feasibility of estimating changes of tropical forest biomass from two airborne lidar measurements of forest height acquired about 10 yr apart over Barro Colorado Island (BCI), Panama. We used the forest inventory data from the 50 ha Center for Tropical Forest Science (CTFS) plot collected every 5 yr during the study period to calibrate the estimation. We compared two approaches for detecting changes in forest aboveground biomass (AGB): (1) relating changes in lidar height metrics from two sensors directly to changes in ground-estimated biomass; and (2) estimating biomass from each lidar sensor and then computing changes in biomass from the difference of two biomass estimates, using two models, namely one model based on five relative height metrics and the other based only on mean canopy height (MCH). We performed the analysis at different spatial scales from 0.04 ha to 10 ha. Method (1) had large uncertainty in directly detecting biomass changes at scales smaller than 10 ha, but provided detailed information about changes of forest structure. The magnitude of error associated with both the mean biomass stock and mean biomass change declined with increasing spatial scales. Method (2) was accurate at the 1 ha scale to estimate AGB stocks (R2 = 0.7 and RMSEmean = 27.6 Mg ha−1). However, to predict biomass changes, errors became comparable to ground estimates only at a spatial scale of about 10 ha or more. Biomass changes were in the same direction at the spatial scale of 1 ha in 60 to 64% of the subplots, corresponding to p values of respectively 0.1 and 0.033. Large errors in estimating biomass changes from lidar data resulted from the uncertainty in detecting changes at 1 ha from ground census data, differences of approximately one year between the ground census and lidar measurements, and differences in sensor characteristics. Our results indicate that the 50 ha BCI plot lost a significant amount of biomass (−0.8 Mg ha−1 yr−1 ± 2.2(SD)) over the past decade (2000–2010). Over the entire island and during the same period, mean AGB change was 0.2 ± 2.4 Mg ha−1 yr−1 with old growth forests losing −0.7 Mg ha−1 yr−1 ± 2.2 (SD), and secondary forests gaining +1.8 Mg ha yr−1 ± 3.4 (SD) biomass. Our analysis suggests that repeated lidar surveys, despite taking measurement with different sensors, can estimate biomass changes in old-growth tropical forests at landscape scales (&gt;10 ha).