First direct landscape-scale measurement of tropical rain forest Leaf Area Index, a key driver of global primary productivity

Ecohydrological assessment of the water balance of the world's highest elevation tropical forest (Polylepis)

Polylepis trees grow at elevations above the continuous tree line (3000-5000 m a.s.l.) across the Andes. They tolerate extreme environmental conditions, making them sensitive bioindicators of global climate change. Therefore, investigating their ecohydrological role is key to understanding how the water cycle of Andean headwaters could be affected by predicted changes in environmental conditions, as well as ongoing Polylepis reforestation initiatives in the region. We estimate, for the first time, the annual water balance of a mature Polylepis forest (Polylepis reticulata) catchment (3780 m a.s.l.) located in the south Ecuadorian páramo using a unique set of field ecohydrological measurements including gross rainfall, throughfall, streamflow, and xylem sap flow in combination with the characterization of forest and soil features. We also compare the forest water balance with that of a tussock grass (Calamagrostis intermedia) catchment, the dominant páramo vegetation. Annual gross rainfall during the study period (April 2019-March 2020) was 1290.6 mm yr-1. Throughfall in the Polylepis forest represented 61.2 % of annual gross rainfall. Streamflow was the main component of the water balance of the forested site (59.6 %), while its change in soil water storage was negligible (<1 %). Forest evapotranspiration was 54.0 %, with evaporation from canopy interception (38.8 %) more than twice as high as transpiration (15.1 %). The error in the annual water balance of the Polylepis catchment was small (<15 %), providing confidence in the measurements and assumptions used to estimate its components. In comparison, streamflow and evapotranspiration at the grassland site accounted for 63.7 and 36.0 % of the water balance, respectively. Although evapotranspiration was larger in the forest catchment, its water yield was only marginally reduced (<4 %) in relation to the grassland catchment. The substantially higher soil organic matter content in the forest site (47.6 %) compared to the grassland site (31.8 %) suggests that even though Polylepis forests do not impair the hydrological function of high-Andean catchments, their presence contributes to carbon storage in the litter layer of the forest and the underlying soil. These findings provide key insights into the vegetation-water‑carbon nexus in high Andean ecosystems, which can serve as a basis for future ecohydrological studies and improved management of páramo natural resources considering changes in land use and global climate.

Collaborative Use of Sensor Networks and Cyberinfrastructure to Understand Complex Ecosystem Interactions in a Tropical Rainforest: Challenges and Lessons Learned

Collaborations between ecosystem ecologists and engineers have led to impressive progress in developing complex models of biogeochemical fluxes in response to global climate change. Ecology and engineering iteratively inform and transform each other in these efforts. Nested data streams from local sources, adjacent networks, and remote sensing sources together magnify the capacity of ecosystem ecologists to observe systems in near real-time and address questions at temporal and spatial scales that were previously unobtainable. We describe our research experiences working in a Costa Rican rainforest ecosystem with the challenges presented by constant high humidity, 4300 mm of annual rainfall, flooding, small invertebrates entering the tiniest openings, stinging insects, and venomous snakes. Over the past two decades, we faced multiple challenges and learned from our mistakes to develop a broad program of ecosystem research at multiple levels of integration. This program involved integrated networks of diverse sensors on a series of canopy towers linked to multiple belowground soil sensor arrays that could transport sensor data streams from the forest directly to an off-site location via a fiber optic cable. In our commentary, we highlight three components of our work: (1) the eddy flux measurements using canopy towers; (2) the soil sensor arrays for measuring the spatial and temporal patterns of CO2 and O2 fluxes at the soil-atmosphere interface; and (3) focused investigations of the ecosystem impact of leaf-cutter ants as "ecosystem engineers" on carbon fluxes.

Association of greenness with the disease burden of lower respiratory infections and mediation effects of air pollution and heat: a global ecological study

Exposure to greenness is increasingly linked to beneficial health outcomes, but the associations between greenness and the disease burden of lower respiratory infections (LRIs) are unclear. We used the normalized difference vegetation index (NDVI) and the leaf area index (LAI) to measure greenness and incidence, death, and disability-adjusted life years (DALYs) due to LRIs to represent the disease burden of LRIs. We applied a generalized linear mixed model to evaluate the association between greenness and LRI disease burden and performed a stratified analysis, after adjusting for covariates. Additionally, we assessed the potential mediating effects of fine particulate matter (PM2.5), ozone (O3), nitrogen dioxide (NO2), and heat on the association between greenness and the disease burden of LRIs. In the adjusted model, one 0.1 unit increase of NDVI and 0.5 increase in LAI were significantly inversely associated with incidence, death, and DALYs due to LRIs, respectively. Greenness was negatively correlated with the disease burden of LRIs across 15-65 age group, both sexes, and low SDI groups. PM2.5, O3, and heat mediated the effects of greenness on the disease burden of LRIs. Greenness was significantly negatively associated with the disease burden of LRIs, possibly by reducing exposure to air pollution and heat.

Managing Moose from Home: Determining Landscape Carrying Capacity for Alces alces Using Remote Sensing

In temperate forests of the northeastern U.S., moose (Alces alces) populations are adapted for mixed-age heterogeneous landscapes that provide abundant herbaceous forage in warm months and coniferous forage during winter. Heterogeneity of forest stands is driven by management activities or natural disturbance, resulting in a multi-age forest at a landscape scale. Here, we present a method to estimate landscape carrying capacity of moose by combining remote sensing classification of forest cover class with literature or field-based estimates of class-specific forage abundance. We used Landsat imagery from 1991 to 2013 for the Allegheny National Forest and 2013–2018 for the Adirondack Park, and associated training polygons, to predict based on NDVI and SWI whether a forested landscape fit into one of three cover classes: mature forest, intermediate timber removal, or overstory timber removal. Our three-classes yielded a mean land cover prediction accuracy of 94.3% (Khat = 0.91) and 86.9% (Khat = 0.76) for ANFR and AP, respectively. In the AP, we applied previously calculated summer crude protein values to our predicted cover types, resulting in an estimated average carrying capacity of 760 moose (SD ± 428) across all sampling years, similar in magnitude to a density estimate of 716 moose (95% CI = 566–906) calculated during the same time. Our approach was able to accurately identify forest timber treatments across landscapes at differing spatial and temporal scales and provide an alternative method to estimate landscape-level ungulate carrying capacity. The ability to accurately identify areas of potential conflict from overbrowsing, or to highlight areas in need of land cover treatments can increase the toolset for ungulate management in managed forest landscapes.

Physical structure and biological composition of canopies in tropical secondary and old-growth forests

The area of tropical secondary forests is increasing rapidly, but data on the physical and biological structure of the canopies of these forests are limited. To obtain such data and to measure the ontogeny of canopy structure during tropical rainforest succession, we studied patch-scale (5 m2) canopy structure in three areas of 18-36 year-old secondary forest in Costa Rica, and compared the results to data from old-growth forest at the same site. All stands were sampled with a stratified random design with complete harvest from ground level to the top of the canopy from a modular portable tower. All canopies were organized into distinct high- and low-leaf-density layers (strata), and multiple strata developed quickly with increasing patch height. The relation of total Leaf Area Index (LAI, leaf area per area of ground) to patch canopy height, the existence of distinct high and low leaf- density layers (strata and free air spaces), the depth and LAI of the canopy strata and free air spaces, and the relation of the number of strata to patch canopy height were remarkably constant across the entire successional gradient. Trees were the most important contributor to LAI at all stages, while contribution of palm LAI increased through succession. We hypothesize that canopy physical structure at the patch scale is driven by light competition and discuss how this hypothesis could be tested. That canopy physical structure was relatively independent of the identity of the species present suggests that canopy physical structure may be conserved even as canopy floristics shift due to changing climate.

Testing the causal mechanism of the peninsular effect in passerine birds from South Korea

The peninsular effect is a geographical phenomenon that explains patterns of species richness. Given that spatial variation in species richness along a peninsular may be driven by multiple processes, we aimed to identify the sources of latitudinal patterns in passerine species richness and test hypotheses regarding (1) recent deterministic processes (climate, primary productivity, forest area, and habitat diversity), (2) anthropogenic processes (habitat fragmentation), and (3) stochastic processes (migration influence) in the Korean peninsula. We used the distribution data of 147 passerine species from 2006 to 2012. Single regression between passerine species richness and latitude supported the existence of the peninsular effect. Mean temperature increased with decreasing latitude, as did habitat diversity but leaf area index and forest area decline. However, mean temperature and forest area only influenced passerine species richness. Although habitat diversity influenced passerine species richness, it was counter to the expectations associated with peninsular effect. The number of habitat patches decreased as latitude increased but it had no effect on passerine species richness. Ratio of migrant species richness showed no significant relationship with leaf area index, forest area, and habitat diversity. However, the ratio of migrant species richness increased with decreasing mean temperature and that contributed to the increase in passerine species. Overall, our finding indicate that the observed species richness pattern in peninsulas with the tip pointing south (in the northern hemisphere) counter to the global latitudinal gradient. These results were caused by the peninsular effect associated with complex mechanism that interact with climate, habitat area, and migrant species inflow.

Lianas maintain insectivorous bird abundance and diversity in a neotropical forest

The spatial habitat heterogeneity hypothesis posits that habitat complexity increases the abundance and diversity of species. In tropical forests, lianas add substantial habitat heterogeneity and complexity throughout the vertical forest profile, which may maintain animal abundance and diversity. The effects of lianas on tropical animal communities, however, remain poorly understood. We propose that lianas have a positive effect on animals by enhancing habitat complexity. Lianas may have a particularly strong influence on the forest bird community, providing nesting substrate, protection from predators, and nutrition (food). Understory insectivorous birds, which forage for insects that specialize on lianas, may particularly benefit. Alternatively, it is possible that lianas have a negative effect on forest birds by increasing predator abundances and providing arboreal predators with travel routes with easy access to bird nests. We tested the spatial habitat heterogeneity hypothesis on bird abundance and diversity by removing lianas, thus reducing forest complexity, using a large-scale experimental approach in a lowland tropical forest in the Republic of Panama. We found that removing lianas decreased total bird abundance by 78.4% and diversity by 77.4% after 8 months, and by 40.0% and 51.7%, respectively, after 20 months. Insectivorous bird abundance and diversity 8 months after liana removal were 91.8% and 89.5% lower, respectively, indicating that lianas positively influence insectivorous birds. The effects of liana removal persisted longer for insectivorous birds than other birds, with 77.3% lower abundance and 76.2% lower diversity after 20 months. Liana removal also altered bird community composition, creating two distinct communities in the control and removal plots, with disproportionate effects on insectivores. Our findings demonstrate that lianas have a strong positive influence on the bird community, particularly for insectivorous birds in the forest understory. Lianas may maintain bird abundance and diversity by increasing habitat complexity, habitat heterogeneity, and resource availability.

Allometric constraints and competition enable the simulation of size structure and carbon fluxes in a dynamic vegetation model of tropical forests (LM3PPA-TV)

Tropical forests are a key determinant of the functioning of the Earth system, but remain a major source of uncertainty in carbon cycle models and climate change projections. In this study, we present an updated land model (LM3PPA-TV) to improve the representation of tropical forest structure and dynamics in Earth system models (ESMs). The development and parameterization of LM3PPA-TV drew on extensive datasets on tropical tree traits and long-term field censuses from Barro Colorado Island (BCI), Panama. The model defines a new plant functional type (PFT) based on the characteristics of shade-tolerant, tropical tree species, implements a new growth allocation scheme based on realistic tree allometries, incorporates hydraulic constraints on biomass accumulation, and features a new compartment for tree branches and branch fall dynamics. Simulation experiments reproduced observed diurnal and seasonal patterns in stand-level carbon and water fluxes, as well as mean canopy and understory tree growth rates, tree size distributions, and stand-level biomass on BCI. Simulations at multiple sites captured considerable variation in biomass and size structure across the tropical forest biome, including observed responses to precipitation and temperature. Model experiments suggested a major role of water limitation in controlling geographic variation forest biomass and structure. However, the failure to simulate tropical forests under extreme conditions and the systematic underestimation of forest biomass in Paleotropical locations highlighted the need to incorporate variation in hydraulic traits and multiple PFTs that capture the distinct floristic composition across tropical domains. The continued pressure on tropical forests from global change demands models which are able to simulate alternative successional pathways and their pace to recovery. LM3PPA-TV provides a tool to investigate geographic variation in tropical forests and a benchmark to continue improving the representation of tropical forests dynamics and their carbon storage potential in ESMs.

Comparison of Smartphone and Drone Lidar Methods for Characterizing Spatial Variation in PAI in a Tropical Forest

Estimating leaf area index (LAI) and assessing spatial variation in LAI across a landscape is crucial to many ecological studies. Several direct and indirect methods of LAI estimation have been developed and compared; however, many of these methods are prohibitively expensive and/or time consuming. Here, we examine the feasibility of using the free image processing software CAN-EYE to estimate effective plant area index (PAIeff) from hemispherical canopy images taken with an extremely inexpensive smartphone clip-on fisheye lens. We evaluate the effectiveness of this inexpensive method by comparing CAN-EYE smartphone PAIeff estimates to those from drone lidar over a lowland tropical forest at La Selva Biological Station, Costa Rica. We estimated PAIeff from drone lidar using a method based in radiative transfer theory that has been previously validated using simulated data; we consider this a conservative test of smartphone PAIeff reliability because above-canopy lidar estimates share few assumptions with understory image methods. Smartphone PAIeff varied from 0.1 to 4.4 throughout our study area and we found a significant correlation (r = 0.62, n = 42, p < 0.001) between smartphone and lidar PAIeff, which was robust to image processing analytical options and smartphone model. When old growth and secondary forests are assumed to have different leaf angle distributions for the lidar PAIeff algorithm (spherical and planophile, respectively) this relationship is further improved (r = 0.77, n = 42, p < 0.001). However, we found deviations in the magnitude of the PAIeff estimations depending on image analytical options. Our results suggest that smartphone images can be used to characterize spatial variation in PAIeff in a complex, heterogenous tropical forest canopy, with only small reductions in explanatory power compared to true digital hemispherical photography.

Estimation of the commercial height of trees with laser meter: a viable alternative for forest management in the Brazilian Amazon

Commercial height of the tree is a key variable for estimating the wood stock in tropical forests managed for timber production purposes. Most available measurement devices suffer limitations in this type of forest, promoting low precision measurements with high variation errors. The laser meter device appears as a viable alternative, as in addition to using trigonometric principles, it is not necessary that the device is close to the eyes of the meter to carry out the measurement. The device can be used to measure commercial height of trees on flat or sloping terrain, at different distances from the tree. However, there are no studies evaluating the precision of this device. The objective of this study was to determine the precision of the laser meter method for estimating the commercial height of trees, as compared to the actual measurement in a tropical forest in the Brazilian Amazon. Measurements were made on 300 trees with commercial height between 7 and 14 m. Actual commercial heights were measured with graduated ruler. Applied tests were paired t test, graphical analysis of residuals and calculations of bias statistics, mean absolute deviation, standard deviation of differences, and coefficient of determination (R 2). Paired t test indicated that the mean of the heights measured by the laser meter is statistically equal to that of the graduated ruler. Measurements with laser meter did not show bias and had mean error of 0.0745. The standard deviation of the differences indicated dispersion of errors of 0.97, equal to that shown in the graduated rule. Laser meter presents an alternative method for estimating the commercial height of trees in tropical forest in the Brazilian Amazon. There was no tendency to underestimate or overestimate the commercial heights of trees. Use of the laser meter is potentially of use for measuring the commercial height of trees in tropical forests.

Small-Scale Forest Structure Influences Spatial Variability of Belowground Carbon Fluxes in a Mature Mediterranean Beech Forest

The tree belowground compartment, especially fine roots, plays a relevant role in the forest ecosystem carbon (C) cycle, contributing largely to soil CO2 efflux (SR) and to net primary production (NPP). Beyond the well-known role of environmental drivers on fine root production (FRP) and SR, other determinants such as forest structure are still poorly understood. We investigated spatial variability of FRP, SR, forest structural traits, and their reciprocal interactions in a mature beech forest in the Mediterranean mountains. In the year of study, FRP resulted in the main component of NPP and explained about 70% of spatial variability of SR. Moreover, FRP was strictly driven by leaf area index (LAI) and soil water content (SWC). These results suggest a framework of close interactions between structural and functional forest features at the local scale to optimize C source–sink relationships under climate variability in a Mediterranean mature beech forest.

Landscape Representation by a Permanent Forest Plot and Alternative Plot Designs in a Typhoon Hotspot, Fushan, Taiwan

Permanent forest dynamics plots have provided valuable insights into many aspects of forest ecology. The evaluation of their representativeness within the landscape is necessary to understanding the limitations of findings from permanent plots at larger spatial scales. Studies on the representativeness of forest plots with respect to landscape heterogeneity and disturbance effect have already been carried out, but knowledge of how multiple disturbances affect plot representativeness is lacking—particularly in sites where several disturbances can occur between forest plot censuses. This study explores the effects of five typhoon disturbances on the Fushan Forest Dynamics Plot (FFDP) and its surrounding landscape, the Fushan Experimental Forest (FEF), in Taiwan where typhoons occur annually. The representativeness of the FFDP for the FEF was studied using four topographical variables derived from a digital elevation model and two vegetation indices (VIs), Normalized Difference Vegetation Index (NDVI) and Normalized Difference Infrared Index (NDII), calculated from Landsat-5 TM, Landsat-7 ETM+, and Landsat-8 OLI data. Representativeness of four alternative plot designs were tested by dividing the FFDP into subplots over wider elevational ranges. Results showed that the FFDP neither represents landscape elevational range (<10%) nor vegetation cover (<7% of the interquartile range, IQR). Although disturbance effects (i.e., ΔVIs) were also different between the FFDP and the FEF, comparisons showed no under- or over-exposure to typhoon damage frequency or intensity within the FFDP. In addition, the ΔVIs were of the same magnitudes in the plots and the reserve, and the plot covered 30% to 75.9% of IQRs of the reserve ΔVIs. Unexpectedly, the alternative plot designs did not lead to increased representation of damage for 3 out of the 4 tested typhoons and they did not suggest higher representativeness of rectangular vs. square plots. Based on the comparison of mean Euclidian distances, two rectangular plots had smaller distances than four square or four rectangular plots of the same area. Therefore, this study suggests that the current FFDP provides a better representation of its landscape disturbances than alternatives, which contained wider topographical variation and would be more difficult to conduct ground surveys. However, upscaling needs to be done with caution as, in the case of the FEF, plot representativeness varied among typhoons.

Exploring the visual world of fossilized and modern fungus gnat eyes (Diptera: Keroplatidae) with X-ray microtomography

Animal eyes typically possess specialized regions for guiding different behavioural tasks within their specific visual habitat. These specializations, and evolutionary changes to them, can be crucial for understanding an animal's ecology. Here, we explore how the visual systems of some of the smallest flying insects, fungus gnats, have adapted to different types of forest habitat over time (approx. 30 Myr to today). Unravelling how behavioural, environmental and phylogenetic factors influence the evolution of visual specializations is difficult, however, because standard quantitative techniques often require fresh tissue and/or provide data in eye-centric coordinates that prevent reliable comparisons between species with different eye morphologies. Here, we quantify the visual world of three gnats from different time periods and habitats using X-ray microtomography to create high-resolution three-dimensional models of the compound eyes of specimens in different preservation states—fossilized in amber, dried or stored in ethanol. We present a method for analysing the geometric details of individual corneal facets and for estimating and comparing the sensitivity, spatial resolution and field of view of species across geographical space and evolutionary time. Our results indicate that, despite their miniature size, fungus gnats do have variations in visual properties across their eyes. We also find some indication that these visual specializations vary across species and may represent adaptations to their different forest habitats. Overall, the findings demonstrate how such investigations can be used to study the evolution of visual specializations—and sensory ecology in general—across a range of insect taxa from different geographical locations and across time.

Integrating LiDAR, Multispectral and SAR Data to Estimate and Map Canopy Height in Tropical Forests

Developing accurate methods to map vegetation structure in tropical forests is essential to protect their biodiversity and improve their carbon stock estimation. We integrated LIDAR (Light Detection and Ranging), multispectral and SAR (Synthetic Aperture Radar) data to improve the prediction and mapping of canopy height (CH) at high spatial resolution (30 m) in tropical forests in South America. We modeled and mapped CH estimated from aircraft LiDAR surveys as a ground reference, using annual metrics derived from multispectral and SAR satellite imagery in a dry forest, a moist forest, and a rainforest of tropical South America. We examined the effect of the three forest types, five regression algorithms, and three predictor groups on the modelling and mapping of CH. Our CH models reached errors ranging from 1.2–3.4 m in the dry forest and 5.1–7.4 m in the rainforest and explained variances from 94–60% in the dry forest and 58–12% in the rainforest. Our best models show higher accuracies than previous works in tropical forests. The average accuracy of the five regression algorithms decreased from dry forests (2.6 m +/− 0.7) to moist (5.7 m +/− 0.4) and rainforests (6.6 m +/− 0.7). Random Forest regressions produced the most accurate models in the three forest types (1.2 m +/− 0.05 in the dry, 4.9 m +/− 0.14 in the moist, and 5.5 m +/− 0.3 the rainforest). Model performance varied considerably across the three predictor groups. Our results are useful for CH spatial prediction when GEDI (Global Ecosystem Dynamics Investigation lidar) data become available.

Retrieval of the Fraction of Radiation Absorbed by Photosynthetic Components (FAPARgreen) for Forest using a Triple-Source Leaf-Wood-Soil Layer Approach

The fraction of absorbed photosynthetically active radiation (FAPAR) is generally divided into the fraction of radiation absorbed by the photosynthetic components (FAPARgreen) and the fraction of radiation absorbed by the non-photosynthetic components (FAPARwoody) of the vegetation. However, most global FAPAR datasets do not take account of the woody components when considering the canopy radiation transfer. The objective of this study was to develop a generic algorithm for partitioning FAPARcanopy into FAPARgreen and FAPARwoody based on a triple-source leaf-wood-soil layer (TriLay) approach. The LargE-Scale remote sensing data and image simulation framework (LESS) model was used to validate the TriLay approach. The results showed that the TriLay FAPARgreen had higher retrieval accuracy, as well as a significantly lower bias (R2 = 0.937, Root Mean Square Error (RMSE) = 0.064, and bias = −6.02% for black-sky conditions; R2 = 0.997, RMSE = 0.025 and bias = −4.04% for white-sky conditions) compared to the traditional linear method (R2 = 0.979, RMSE = 0.114, and bias = −18.04% for black-sky conditions; R2 = 0.996, RMSE = 0.106 and bias = −16.93% for white-sky conditions). For FAPAR that did not take account of woody components (FAPARnoWAI), the corresponding results were R2 = 0.920, RMSE = 0.071, and bias = −7.14% for black-sky conditions, and R2 = 0.999, RMSE = 0.043, and bias = −6.41% for white-sky conditions. Finally, the dynamic FAPARgreen, FAPARwoody, FAPARcanopy and FAPARnoWAI products for a North America region were generated at a resolution of 500 m for every eight days in 2017. A comparison of the results for FAPARgreen against those for FAPARnoWAI and FAPARcanopy showed that the discrepancy between FAPARgreen and other FAPAR products for forest vegetation types could not be ignored. For deciduous needleleaf forest, in particular, the black-sky FAPARgreen was found to contribute only about 23.86% and 35.75% of FAPARcanopy at the beginning and end of the year (from January to March and October to December, JFM and OND), and 75.02% at the peak growth stage (from July to September, JAS); the black-sky FAPARnoWAI was found to be overestimated by 38.30% and 28.46% during the early (JFM) and late (OND) part of the year, respectively. Therefore, the TriLay approach performed well in separating FAPARgreen from FAPARcanopy, which is of great importance for a better understanding of the energy exchange within the canopy.

Photosynthetic heat tolerance of shade and sun leaves of three tropical tree species

Previous studies of heat tolerance of tropical trees have focused on canopy leaves exposed to full sunlight and high temperatures. However, in lowland tropical forests with leaf area indices of 5-6, the vast majority of leaves experience varying degrees of shade and a reduced heat load compared to sun leaves. Here we tested whether heat tolerance is lower in shade than in sun leaves. For three tropical tree species, Calophyllum inophyllum, Inga spectabilis, and Ormosia macrocalyx, disks of fully developed shade and sun leaves were subjected to 15-min heat treatments, followed by measurement of chlorophyll a fluorescence after 48 h of recovery. In two of the three species, the temperature causing a 50% decrease of the fluorescence ratio F_v/F_m (T₅₀) was significantly lower (by ~ 1.0 °C) in shade than in sun leaves, indicating a moderately decreased heat tolerance of shade leaves. In shade leaves of these two species, the rise in initial fluorescence, F₀, also occurred at lower temperatures. In the third species, there was no shade-sun difference in T₅₀. In situ measurements of photosynthetic CO₂ assimilation showed that the optimum temperature for photosynthesis tended to be lower in shade leaves, although differences were not significant. At supra-optimal temperatures, photosynthesis was largely constrained by stomatal conductance, and the high-temperature CO₂ compensation point, T_Max, occurred at considerably lower temperatures than T₅₀. Our study demonstrates that the temperature response of shade leaves of tropical trees differs only marginally from that of sun leaves, both in terms of heat tolerance and photosynthetic performance.

Seasonal and drought-related changes in leaf area profiles depend on height and light environment in an Amazon forest

Seasonal dynamics in the vertical distribution of leaf area index (LAI) may impact the seasonality of forest productivity in Amazonian forests. However, until recently, fine-scale observations critical to revealing ecological mechanisms underlying these changes have been lacking. To investigate fine-scale variation in leaf area with seasonality and drought we conducted monthly ground-based LiDAR surveys over 4 yr at an Amazon forest site. We analysed temporal changes in vertically structured LAI along axes of both canopy height and light environments. Upper canopy LAI increased during the dry season, whereas lower canopy LAI decreased. The low canopy decrease was driven by highly illuminated leaves of smaller trees in gaps. By contrast, understory LAI increased concurrently with the upper canopy. Hence, tree phenological strategies were stratified by height and light environments. Trends were amplified during a 2015-2016 severe El Niño drought. Leaf area low in the canopy exhibited behaviour consistent with water limitation. Leaf loss from short trees in high light during drought may be associated with strategies to tolerate limited access to deep soil water and stressful leaf environments. Vertically and environmentally structured phenological processes suggest a critical role of canopy structural heterogeneity in seasonal changes in Amazon ecosystem function.

Prediction of forest aboveground net primary production from high-resolution vertical leaf-area profiles

Temperature and precipitation explain about half the variation in aboveground net primary production (ANPP) among tropical forest sites, but determinants of remaining variation are poorly understood. Here, we test the hypothesis that the amount of leaf area, and its vertical arrangement, predicts ANPP when other variables are held constant. Using measurements from airborne lidar in a lowland Neotropical rain forest, we quantify vertical leaf-area profiles and develop models of ANPP driven by leaf area and other measurements of forest structure. Vertical leaf-area profiles predict 38% of the variation among plots. This number is 4.5 times greater than models using total leaf area (disregarding vertical arrangement) and 2.1 times greater than models using canopy height alone. Furthermore, ANPP predictions from vertical leaf-area profiles were less biased than alternate metrics. Variation in ANPP not attributable to temperature or precipitation can be predicted by the vertical distribution of leaf area in this system.

Optimizing the Remote Detection of Tropical Rainforest Structure with Airborne Lidar: Leaf Area Profile Sensitivity to Pulse Density and Spatial Sampling

Airborne Laser Scanning (ALS) has been considered as a primary source to model the structure and function of a forest canopy through the indicators leaf area index (LAI) and vertical canopy profiles of leaf area density (LAD). However, little is known about the effects of the laser pulse density and the grain size (horizontal binning resolution) of the laser point cloud on the estimation of LAD profiles and their associated LAIs. Our objective was to determine the optimal values for reliable and stable estimates of LAD profiles from ALS data obtained over a dense tropical forest. Profiles were compared using three methods: Destructive field sampling, Portable Canopy profiling Lidar (PCL) and ALS. Stable LAD profiles from ALS, concordant with the other two analytical methods, were obtained when the grain size was less than 10 m and pulse density was high (>15 pulses m−2). Lower pulse densities also provided stable and reliable LAD profiles when using an appropriate adjustment (coefficient K). We also discuss how LAD profiles might be corrected throughout the landscape when using ALS surveys of lower density, by calibrating with LAI measurements in the field or from PCL. Appropriate choices of grain size, pulse density and K provide reliable estimates of LAD and associated tree plot demography and biomass in dense forest ecosystems.

Tropical forest light regimes in a human-modified landscape

Light is the key energy input for all vegetated systems. Forest light regimes are complex, with the vertical pattern of light within canopies influenced by forest structure. Human disturbances in tropical forests impact forest structure and hence may influence the light environment and thus competitiveness of different trees. In this study, we measured vertical diffuse light profiles along a gradient of anthropogenic disturbance, sampling intact, logged, secondary, and fragmented sites in the biodiversity hot spot of the Atlantic forest, southeast Brazil, using photosynthetically active radiation sensors and a novel approach with estimations of vertical light profiles from hemispherical photographs. Our results show clear differences in vertical light profiles with disturbance: Fragmented forests are characterized by rapid light extinction within their low canopies, while the profiles in logged forests show high heterogeneity and high light in the mid-canopy despite decades of recovery. The secondary forest showed similar light profiles to intact forest, but with a lower canopy height. We also show that in some cases the upper canopy layer and heavy liana infestations can severely limit light penetration. Light extinction with height above the ground and depth below the canopy top was highest in fragmented forest and negatively correlated with canopy height. The novel, inexpensive, and rapid methods described here can be applied to other sites to quantify rarely measured vertical light profiles.

Tropical rainforest carbon sink declines during El Niño as a result of reduced photosynthesis and increased respiration rates

Changes in tropical forest carbon sink strength during El Niño Southern Oscillation (ENSO) events can indicate future behavior under climate change. Previous studies revealed ˜6 Mg C ha^-1  yr^-1 lower net ecosystem production (NEP) during ENSO year 1998 compared with non-ENSO year 2000 in a Costa Rican tropical rainforest. We explored environmental drivers of this change and examined the contributions of ecosystem respiration (RE) and gross primary production (GPP) to this weakened carbon sink. For 1998-2000, we estimated RE using chamber-based respiration measurements, and we estimated GPP in two ways: using (1) the canopy process model MAESTRA, and (2) combined eddy covariance and chamber respiration data. MAESTRA-estimated GPP did not statistically differ from GPP estimated using approach 2, but was ˜ 28% greater than published GPP estimates for the same site and years using eddy covariance data only. A 7% increase in RE (primarily increased soil respiration) and a 10% reduction in GPP contributed equally to the difference in NEP between ENSO year 1998 and non-ENSO year 2000. A warming and drying climate for tropical forests may yield a weakened carbon sink from both decreased GPP and increased RE. Understanding physiological acclimation will be critical for the large carbon stores in these ecosystems.

The structure of tropical forests and sphere packings

The search for simple principles underlying the complex architecture of ecological communities such as forests still challenges ecological theorists. We use tree diameter distributions--fundamental for deriving other forest attributes--to describe the structure of tropical forests. Here we argue that tree diameter distributions of natural tropical forests can be explained by stochastic packing of tree crowns representing a forest crown packing system: a method usually used in physics or chemistry. We demonstrate that tree diameter distributions emerge accurately from a surprisingly simple set of principles that include site-specific tree allometries, random placement of trees, competition for space, and mortality. The simple static model also successfully predicted the canopy structure, revealing that most trees in our two studied forests grow up to 30-50 m in height and that the highest packing density of about 60% is reached between the 25- and 40-m height layer. Our approach is an important step toward identifying a minimal set of processes responsible for generating the spatial structure of tropical forests.

Convergent Evolution towards High Net Carbon Gain Efficiency Contributes to the Shade Tolerance of Palms (Arecaceae)

Most palm species occur in the shaded lower strata of tropical rain forests, but how their traits relate to shade adaptation is poorly understood. We hypothesized that palms are adapted to the shade of their native habitats by convergent evolution towards high net carbon gain efficiency (CGE_n), which is given by the maximum photosynthetic rate to dark respiration rate ratio. Leaf mass per area, maximum photosynthetic rate, dark respiration and N and P concentrations were measured in 80 palm species grown in a common garden, and combined with data of 30 palm species growing in their native habitats. Compared to other species from the global leaf economics data, dicotyledonous broad-leaved trees in tropical rainforest or other monocots in the global leaf economics data, palms possessed consistently higher CGE_n, achieved by lowered dark respiration and fairly high foliar P concentration. Combined phylogenetic analyses of evolutionary signal and trait evolution revealed convergent evolution towards high CGE_n in palms. We conclude that high CGE_n is an evolutionary strategy that enables palms to better adapt to shady environments than coexisting dicot tree species, and may convey advantages in competing with them in the tropical forest understory. These findings provide important insights for understanding the evolution and ecology of palms, and for understanding plant shade adaptations of lower rainforest strata. Moreover, given the dominant role of palms in tropical forests, these findings are important for modelling carbon and nutrient cycling in tropical forest ecosystems.

Aboveground tree growth varies with belowground carbon allocation in a tropical rainforest environment

Young secondary forests and plantations in the moist tropics often have rapid rates of biomass accumulation and thus sequester large amounts of carbon. Here, we compare results from mature forest and nearby 15–20 year old tree plantations in lowland Costa Rica to evaluate differences in allocation of carbon to aboveground production and root systems. We found that the tree plantations, which had fully developed, closed canopies, allocated more carbon belowground - to their root systems - than did mature forest. This increase in belowground carbon allocation correlated significantly with aboveground tree growth but not with canopy production (i.e., leaf fall or fine litter production). In contrast, there were no correlations between canopy production and either tree growth or belowground carbon allocation. Enhanced allocation of carbon to root systems can enhance plant nutrient uptake, providing nutrients beyond those required for the production of short-lived tissues such as leaves and fine roots, and thus enabling biomass accumulation. Our analyses support this deduction at our site, showing that enhanced allocation of carbon to root systems can be an important mechanism promoting biomass accumulation during forest growth in the moist tropics. Identifying factors that control when, where and for how long this occurs would help us to improve models of forest growth and nutrient cycling, and to ascertain the role that young forests play in mitigating increased atmospheric carbon dioxide.