Search for: All records

Abstract Field measurements demonstrate a carbon sink in the Amazon and Congo basins, but the cause of this sink is uncertain. One possibility is that forest landscapes are experiencing transient recovery from previous disturbance. Attributing the carbon sink to transient recovery or other processes is challenging because we do not understand the sensitivity of conventional remote sensing methods to changes in aboveground carbon density (ACD) caused by disturbance events. Here we use ultra-high-density drone lidar to quantify the impact of a blowdown disturbance on ACD in a lowland rain forest in Costa Rica. We show that the blowdown decreased ACD by at least 17.6%, increased the number of canopy gaps, and altered the gap size-frequency distribution. Analyses of a canopy-height transition matrix indicate departure from steady-state conditions. This event will initiate a transient sink requiring an estimated 24–49 years to recover pre-disturbance ACD. Our results suggest that blowdowns of this magnitude and extent can remain undetected by conventional satellite optical imagery but are likely to alter ACD decades after they occur. 

Habitat‐suitability indices (HSI) have been employed in restoration to identify optimal sites for planting native species. Often, HSI are based on abiotic variables and do not include biotic interactions, even though similar abiotic conditions can favor both native and nonnative species. Biotic interactions such as competition may be especially important in invader‐dominated habitats because invasive species often have fast growth rates and can exploit resources quickly. In this study, we test the utility of an HSI of microtopography derived from airborne LiDAR to predict post‐disturbance recovery and native planting success in native shrub‐dominated and nonnative, invasive grass‐dominated dryland habitats in Hawaiʻi. The HSI uses high‐resolution digital terrain models to classify sites' microtopography as high, medium, or low suitability, based on wind exposure and topographic position. We used a split‐plot before‐after‐control‐impact design to implement a disturbance experiment within native shrub (Dodonaea viscosa) and nonnative, invasive grass (Cenchrus clandestinus)‐dominated ecosystems across three microtopography categories. In contrast to previous studies using the same HSI, we found that microtopography was a poor predictor of pre‐disturbance conditions for soil nutrients, organic matter content, or foliar C:N, within bothDodonaeaandCenchrusvegetation types. In invader‐dominatedCenchrusplots, microtopography helped predict cover, but not as expected (i.e., highest cover would be in high‐suitability plots):D. viscosahad the greatest cover in low‐suitability andC. clandestinushad the greatest cover in medium‐suitability plots. Similarly, in native‐dominatedDodonaeaplots, microtopography was a poor predictor ofD. viscosa,C. clandestinus, and total plant cover. Although we found some evidence that microtopography helped inform post‐disturbance plant recovery ofD. viscosaand total plant cover, vegetation type was a more important predictor. Important for considering the success of plantings, percent cover ofD. viscosadecreased while percent cover ofC. clandestinusincreased within both vegetation types 20 months after disturbance. Our results are evidence that HSIs based on topographic features may prove most useful for choosing planting sites in harsh habitats or those already dominated by native species. In more productive habitats, competition from resident species may offset any benefits gained from “better” suitability sites.

 

The distribution of canopy heights in tropical rain forests directly affects carbon storage and the maintenance of biodiversity. We report results from a unique 20‐yr record of annual monitoring of canopy‐height distributions across an old‐growth tropical rain forest landscape at the La Selva Biological Station in Costa Rica. Canopy heights to 15 m were measured annually in 18 0.50‐ha plots at 231 points on a 5 × 5 m grid from 1999–2018 (nine plots in 1999), and heights >15 m were classified as “high canopy.” During the study two major disturbance events (one immediately prior to the study) dominated the landscape‐scale distribution of canopy heights. Height recovery from the 1997–1998 strong El Niño disturbance took approximately 15 yr. Frequency of canopy gaps varied an order of magnitude among years and 96% disappeared in ≤2 yr. High‐canopy coverage and gap frequency varied substantially across the local gradients of soil nutrients and topography, and plot‐level conditions and trends frequently differed from the landscape‐level patterns. In contrast to the two major landscape‐level disturbances, significant plot‐level disturbances were common throughout two decades. Including a similar data set taken in 1992, canopy‐height distributions for the last three decades over this old‐growth tropical rain forest landscape are most parsimoniously interpreted as showing local disturbance and recovery and no unidirectional trends over time. Together these results suggest that understanding the landscape‐ and plot‐level dynamics of tropical rain forest canopy‐height distributions will require repeat sampling for multiple decades, while accurately measuring gap frequency and recovery will require sample intervals of ≤2 yr.

 

The Janzen–Connell hypothesis is a well-known explanation for why tropical forests have large numbers of tree species. A fundamental prediction of the hypothesis is that the probability of adult recruitment is less in regions of high conspecific adult density, a pattern mediated by density-dependent mortality in juvenile life stages. Although there is strong evidence in many tree species that seeds, seedlings, and saplings suffer conspecific density-dependent mortality, no study has shown that adult tree recruitment is negatively density dependent. Density-dependent adult recruitment is necessary for the Janzen–Connell mechanism to regulate tree populations. Here, we report density-dependent adult recruitment in the population ofHandroanthus guayacan, a wind-dispersed Neotropical canopy tree species. We use data from high-resolution remote sensing to track individual trees with proven capacity to flower in a lowland moist forest landscape in Panama and analyze these data in a Bayesian framework similar to capture–recapture analysis. We independently quantify probabilities of adult tree recruitment and detection and show that adult recruitment is negatively density dependent. The annualized probability of adult recruitment was 3.03% ⋅ year⁻¹. Despite the detection of negative density dependence in adult recruitment, it was insufficient to stabilize the adult population ofH. guayacan, which increased significantly in size over the decade of observation.

 

Mapping tree species richness across the tropics is of great interest for effective conservation and biodiversity management. In this study, we evaluated the potential of full‐waveform lidar data for mapping tree species richness across the tropics by relating measurements of vertical canopy structure, as a proxy for the occupation of vertical niche space, to tree species richness.

Tropics.

Present.

Trees.

First, we evaluated the characteristics of vertical canopy structure across 15 study sites using (simulated) large‐footprint full‐waveform lidar data (22 m diameter) and related these findings to in‐situ tree species information. Then, we developed structure–richness models at the local (within 25–50 ha plots), regional (biogeographical regions) and pan‐tropical scale at three spatial resolutions (1.0, 0.25 and 0.0625 ha) using Poisson regression.

The results showed a weak structure–richness relationship at the local scale. At the regional scale (within a biogeographical region) a stronger relationship between canopy structure and tree species richness across different tropical forest types was found, for example across Central Africa and in South America [R²ranging from .44–.56, root mean squared difference as a percentage of the mean (RMSD%) ranging between 23–61%]. Modelling the relationship pan‐tropically, across four continents, 39% of the variation in tree species richness could be explained with canopy structure alone (R² = .39 and RMSD% = 43%, 0.25‐ha resolution).

Our results may serve as a basis for the future development of a set of structure–richness models to map high resolution tree species richness using vertical canopy structure information from the Global Ecosystem Dynamics Investigation (GEDI). The value of this effort would be enhanced by access to a larger set of field reference data for all tropical regions. Future research could also support the use of GEDI data in frameworks using environmental and spectral information for modelling tree species richness across the tropics.