Tropical tree size-frequency distributions from airborne lidar.

In tropical rainforests, tree size and number density are influenced by disturbance history, soil, topography, climate, and biological factors that are difficult to predict without detailed and widespread forest inventory data. Here, we quantify tree size-frequency distributions over an old-growth wet tropical forest at the La Selva Biological Station in Costa Rica by using an individual tree crown (ITC) algorithm on airborne lidar measurements. The ITC provided tree height, crown area, the number of trees >10 m height and, predicted tree diameter, and aboveground biomass from field allometry. The number density showed strong agreement with field observations at the plot- (97.4%; 3% bias) and tree-height-classes level (97.4%; 3% bias). The lidar trees size spectra of tree diameter and height closely follow the distributions measured on the ground but showed less agreement with crown area observations. The model to convert lidar-derived tree height and crown area to tree diameter produced unbiased (0.8%) estimates of plot-level basal area and with low uncertainty (6%). Predictions on basal area for tree height classes were also unbiased (1.3%) but with larger uncertainties (22%). The biomass estimates had no significant bias at the plot- and tree-height-classes level (-5.2% and 2.1%). Our ITC method provides a powerful tool for tree- to landscape-level tropical forest inventory and biomass estimation by overcoming the limitations of lidar area-based approaches that require local calibration using a large number of inventory plots.

Diversity, distribution and dynamics of large trees across an old-growth lowland tropical rain forest landscape.

Large trees, here defined as ≥60 cm trunk diameter, are the most massive organisms in tropical rain forest, and are important in forest structure, dynamics and carbon cycling. The status of large trees in tropical forest is unclear, with both increasing and decreasing trends reported. We sampled across an old-growth tropical rain forest landscape at the La Selva Biological Station in Costa Rica to study the distribution and performance of large trees and their contribution to forest structure and dynamics. We censused all large trees in 238 0.50 ha plots, and also identified and measured all stems ≥10 cm diameter in 18 0.50 ha plots annually for 20 years (1997-2017). We assessed abundance, species diversity, and crown conditions of large trees in relation to soil type and topography, measured the contribution of large trees to stand structure, productivity, and dynamics, and analyzed the decadal population trends of large trees. Large trees accounted for 2.5% of stems and ~25% of mean basal area and Estimated Above-Ground Biomass, and produced ~10% of the estimated wood production. Crown exposure increased with stem diameter but predictability was low. Large tree density was about twice as high on more-fertile flat sites compared to less fertile sites on slopes and plateaus. Density of large trees increased 27% over the study interval, but the increase was restricted to the flat more-fertile sites. Mortality and recruitment differed between large trees and smaller stems, and strongly suggested that large tree density was affected by past climatic disturbances such as large El Niño events. Our results generally do not support the hypothesis of increasing biomass and turnover rates in tropical forest. We suggest that additional landscape-scale studies of large trees are needed to determine the generality of disturbance legacies in tropical forest study sites.

Three decades of annual growth, mortality, physical condition, and microsite for ten tropical rainforest tree species.

In lowland tropical rainforest, hundreds of tree species typically occur within mesoscale landscapes (50-500 ha). There is no consensus ecological theory that accounts for the coexistence of so many species with similar morphologies and the same fundamental requirements of light, nutrients, water, and physical space. In part this is due to the limited understanding of post-establishment ecology for the vast majority of tropical tree species. Of even more concern is the lack of understanding of how these trees are responding to on-going atmospheric and climatic changes. Here we present long-term data on the post-establishment ecology of ten species of tropical rainforest trees that span a broad life-history spectrum. The study site was upland (non-swamp) old-growth tropical wet forest at the La Selva Biological Station (N.E. Costa Rica). Focal individuals from established seedlings to mature trees were assessed annually, with an emphasis on accuracy and long-term consistency of the observations. The annual time-step, rare for longterm studies in tropical rainforest, captures the typically abrupt changes in forest structure and light environments, the frequent instances of major physical damage, and the trees' responses to these events and to interannual and long-term climatic variation. With the completion of the study in 2016, the data for survivorship, growth, and microsite conditions span 4,499 individuals and 34 yr. The first ten years of these data were published as an Ecology/Ecological Archives data paper in 2000 (Clark and Clark 2000), with two subsequent update publications (Clark and Clark 2006, 2012). This final update adds the final six years of observations, digitized field comments, and histories of points of measurement on the trees. The metadata now include the scanned original field data-sheets for the entire study and a narrative detailing the annual qa/qc of the data. The data set is unique for its scope (years of continuous annual measurements, number of monitored individuals), the in-depth documentation, and the unrestricted data access. The data have been used to study life history patterns, tree ecology through ontogeny, and effects on tree performance from interannual and long-term climatic and atmospheric change. They have also contributed to numerous remote-sensing studies. No copyright or proprietary restrictions are associated with the use of this data set other than citation of the paper; the authors believe scientific data should be freely available for scientific use. The authors would appreciate notification of when and how data are used, but this is discretionary on the part of the data users and is in no sense mandatory.

Multidecadal stability in tropical rain forest structure and dynamics across an old-growth landscape.

Have tropical rain forest landscapes changed directionally through recent decades? To answer this question requires tracking forest structure and dynamics through time and across within-forest environmental heterogeneity. While the impacts of major environmental gradients in soil nutrients, climate and topography on lowland tropical rain forest (TRF) structure and function have been extensively analyzed, the effects of the shorter environmental gradients typical of mesoscale TRF landscapes remain poorly understood. To evaluate multi-decadal performance of an old-growth TRF at the La Selva Biological Station, Costa Rica, we established 18 0.5-ha annually-censused forest inventory plots in a stratified-random design across major landscape edaphic gradients. Over the 17-year study period, there were moderate differences in stand dynamics and structure across these gradients but no detectable difference in woody productivity. We found large effects on forest structure and dynamics from the mega-Niño event at the outset of the study, with subdecadal recovery and subsequent stabilization. To extend the timeline to >40 years, we combined our findings with those from earlier studies at this site. While there were annual to multiannual variations in the structure and dynamics, particularly in relation to local disturbances and the mega-Niño event, at the longer temporal scale and broader spatial scale this landscape was remarkably stable. This stability contrasts notably with a current hypothesis of increasing biomass and dynamics of TRF, which we term the Bigger and Faster Hypothesis (B&FHo). We consider possible reasons for the contradiction and conclude that it is currently not possible to independently assess the vast majority of previously published B&FHo evidence due to restricted data access.

Tropical rain forest structure, tree growth and dynamics along a 2700-m elevational transect in Costa Rica.

Rapid biological changes are expected to occur on tropical elevational gradients as species migrate upslope or go extinct in the face of global warming. We established a series of 9 1-ha plots in old-growth tropical rainforest in Costa Rica along a 2700 m relief elevational gradient to carry out long-term monitoring of tropical rain forest structure, dynamics and tree growth. Within each plot we mapped, identified, and annually measured diameter for all woody individuals with stem diameters >10 cm for periods of 3-10 years. Wood species diversity peaked at 400-600 m and decreased substantially at higher elevations. Basal area and stem number varied by less than two-fold, with the exception of the 2800 m cloud forest summit, where basal area and stem number were approximately double that of lower sites. Canopy gaps extending to the forest floor accounted for <3% of microsites at all elevations. Height of highest crowns and the coefficient of variation of crown height both decreased with increasing elevation. Rates of turnover of individuals and of stand basal area decreased with elevation, but rates of diameter growth and stand basal area showed no simple relation to elevation. We discuss issues encountered in the design and implementation of this network of plots, including biased sampling, missing key meteorological and biomass data, and strategies for improving species-level research. Taking full advantage of the major research potential of tropical forest elevational transects will require sustaining and extending ground based studies, incorporation of new remotely-sensed data and data-acquisition platforms, and new funding models to support decadal research on these rapidly-changing systems.

Response of an old-growth tropical rainforest to transient high temperature and drought.

Tropical rainforests have experienced episodes of severe heat and drought in recent decades, and climate models project a warmer and potentially drier tropical climate over this century. However, likely responses of tropical rainforests are poorly understood due to a lack of frequent long-term measurements of forest structure and dynamics. We analyzed a 12-year record (1999-2010) of 47 817 annual measurements of canopy height to characterize the response of an old-growth Neotropical rainforest to the severe heat and drought associated with the 1997-1998 El Niño. Well-drained soils on slopes and plateaus experienced a threefold increase in the fraction of the landscape in gaps (≤2 m) and a reduction in the fraction in high canopy (>15 m) causing distributions of canopy height to depart from equilibrium for a period of 2-3 years. In contrast, forests on low-lying alluvial terraces remained in equilibrium and were nearly half as likely to experience upper canopy (>15 m) disturbance over the 12 years of observation. Variation in forest response across topographic positions suggests that tropical rainforests are more sensitive to moisture deficits than high temperature and that topography likely structures landscape-level variation in the severity of drought impacts.

Compositional shifts in Costa Rican forests due to climate-driven species migrations.

Species are predicted to shift their distributions upslope or poleward in response to global warming. This prediction is supported by a growing number of studies documenting species migrations in temperate systems but remains poorly tested for tropical species, and especially for tropical plant species. We analyzed changes in tree species composition in a network of 10 annually censused 1-ha plots spanning an altitudinal gradient of 70-2800 m elevation in Costa Rica. Specifically, we combined plot data with herbarium records (accessed through GBIF) to test if the plots' community temperature scores (CTS, average thermal mean of constituent species weighted by basal area) have increased over the past decade as is predicted by climate-driven species migrations. In addition, we quantified the contributions of stem growth, recruitment, and mortality to the observed patterns. Supporting our a priori hypothesis of upward species migrations, we found that there have been consistent directional shifts in the composition of the plots, such that the relative abundance of lowland species, and hence CTS, increased in 90% of plots. The rate of the observed compositional shifts corresponds to a mean thermal migration rate (TMR) of 0.0065 °C yr(-1) (95% CI = 0.0005-0.0132 °C yr(-1) ). While the overall TMR is slower than predicted based on concurrent regional warming of 0.0167 °C yr(-1) , migrations were on pace with warming in 4 of the 10 plots. The observed shifts in composition were driven primarily by mortality events (i.e., the disproportionate death of highland vs. lowland species), suggesting that individuals of many tropical tree species will not be able to tolerate future warming and thus their persistence in the face of climate change will depend on successful migrations. Unfortunately, in Costa Rica and elsewhere, land area inevitably decreases at higher elevations; hence, even species that are able to migrate successfully will face heightened risks of extinction.

Local technicians in long-term research projects: evaluation of 25 years experience in an active tropical research station

Most field ecology is conceived and financed by scientists from urban areas but is actually carried out in rural areas. Field staff can either be imported from urban areas or recruited from local residents. We evaluated the advantages and disadvantages of involving rural residents as local technicians over a 25- year period at active field research site in Costa Rica. We defined "local technicians" as local residents with no university education who acquired significant experience in field data collection, data management and/or laboratory work. We analyzed the experiences of incorporating these technicians into field research In developing countries from the points of view of scientist and of the local technicians themselves. Primary data were written responses from to a standardized survey of 19 senior scientists and Ph.D. students, and results from standardized personal interviews with 22 local technicians. Researchers highlighted the advantages of highly-skilled technicians with minimal staff turnover, as well as the technicians’ knowledge of local ecological conditions. Local technicians considered the primary advantages of their jobs to be opportunities for continuing education training in science as well as cultural enrichment through interactions with people of different cultures. The main challenges identified by researchers were the lack of long-term funding for projects and extended training required for local technicians. Local technicians can be of great benefit to research projects by providing high-quality data collection at reasonable costs with low staff turnover. Over the last 25 years the research model at the field station we studied has evolved to the point that most long-term projects now depend heavily on local technicians. This model of involving local technicians in long-term research has multiple benefits for the researchers, the technicians and the local community, and could be adapted to a variety of settings in rural areas of developing countries. Rev. Biol. Trop. 59 (4): 1455-1462. Epub 2011 December 01.

A novel statistical method for classifying habitat generalists and specialists.

We develop a novel statistical approach for classifying generalists and specialists in two distinct habitats. Using a multinomial model based on estimated species relative abundance in two habitats, our method minimizes bias due to differences in sampling intensities between two habitat types as well as bias due to insufficient sampling within each habitat. The method permits a robust statistical classification of habitat specialists and generalists, without excluding rare species a priori. Based on a user-defined specialization threshold, the model classifies species into one of four groups: (1) generalist; (2) habitat A specialist; (3) habitat B specialist; and (4) too rare to classify with confidence. We illustrate our multinomial classification method using two contrasting data sets: (1) bird abundance in woodland and heath habitats in southeastern Australia and (2) tree abundance in second-growth (SG) and old-growth (OG) rain forests in the Caribbean lowlands of northeastern Costa Rica. We evaluate the multinomial model in detail for the tree data set. Our results for birds were highly concordant with a previous nonstatistical classification, but our method classified a higher fraction (57.7%) of bird species with statistical confidence. Based on a conservative specialization threshold and adjustment for multiple comparisons, 64.4% of tree species in the full sample were too rare to classify with confidence. Among the species classified, OG specialists constituted the largest class (40.6%), followed by generalist tree species (36.7%) and SG specialists (22.7%). The multinomial model was more sensitive than indicator value analysis or abundance-based phi coefficient indices in detecting habitat specialists and also detects generalists statistically. Classification of specialists and generalists based on rarefied subsamples was highly consistent with classification based on the full sample, even for sampling percentages as low as 20%. Major advantages of the new method are (1) its ability to distinguish habitat generalists (species with no significant habitat affinity) from species that are simply too rare to classify and (2) applicability to a single representative sample or a single pooled set of representative samples from each of two habitat types. The method as currently developed can be applied to no more than two habitats at a time.

Local technicians in long-term research projects: evaluation of 25 years experience in an active tropical research station.

Most field ecology is conceived and financed by scientists from urban areas but is actually carried out in rural areas. Field staff can either be imported from urban areas or recruited from local residents. We evaluated the advantages and disadvantages of involving rural residents as local technicians over a 25- year period at active field research site in Costa Rica. We defined "local technicians" as local residents with no university education who acquired significant experience in field data collection, data management and/or laboratory work. We analyzed the experiences of incorporating these technicians into field research in developing countries from the points of view of scientist and of the local technicians themselves. Primary data were written responses from to a standardized survey of 19 senior scientists and Ph.D. students,and results from standardized personal interviews with 22 local technicians. Researchers highlighted the advantages of highly-skilled technicians with minimal staff turnover, as well as the technicians' knowledge of local ecological conditions. Local technicians considered the primary advantages of their jobs to be opportunities for continuing education training in science as well as cultural enrichment through interactions with people of different cultures. The main challenges identified by researchers were the lack of long-term funding for projects and extended training required for local technicians. Local technicians can be of great benefit to research projects by providing high-quality data collection at reasonable costs with low staff turnover. Over the last 25 years the research model at the field station we studied has evolved to the point that most long-term projects now depend heavily on local technicians. This model of involving local technicians in long-term research has multiple benefits for the researchers, the technicians and the local community, and could be adapted to a variety of settings in rural areas of developing countries.

Pervasive canopy dynamics produce short-term stability in a tropical rain forest landscape.

A fundamental property of all forest landscapes is the size frequency distribution of canopy gap disturbances. But characterizing forest structure and changes at large spatial scales has been challenging and most of our understanding is from permanent inventory plots. Here we report the first application of light detection and ranging remote sensing to measurements of canopy disturbance and regeneration in an old-growth tropical rain forest landscape. Pervasive local height changes figure prominently in the dynamics of this forest. Although most canopy gaps recruited to higher positions during 8.5 years, size frequency distributions were similar at two points in time and well-predicted by power-laws. At larger spatial scales (hundreds of ha), height increases and decreases occurred with similar frequency and changes to canopy height that were analysed using a height transition matrix suggest that the distribution of canopy height at the beginning of the study was close to the projected steady-state equilibrium under the recent disturbance regime. Taken together, these findings show how widespread local height changes can produce short-term stability in a tropical rain forest landscape.

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

Leaf Area Index (leaf area per unit ground area, LAI) is a key driver of forest productivity but has never previously been measured directly at the landscape scale in tropical rain forest (TRF). We used a modular tower and stratified random sampling to harvest all foliage from forest floor to canopy top in 55 vertical transects (4.6 m(2)) across 500 ha of old growth in Costa Rica. Landscape LAI was 6.00 +/- 0.32 SEM. Trees, palms and lianas accounted for 89% of the total, and trees and lianas were 95% of the upper canopy. All vertical transects were organized into quantitatively defined strata, partially resolving the long-standing controversy over canopy stratification in TRF. Total LAI was strongly correlated with forest height up to 21 m, while the number of canopy strata increased with forest height across the full height range. These data are a benchmark for understanding the structure and functional composition of TRF canopies at landscape scales, and also provide insights for improving ecosystem models and remote sensing validation.

Explaining variation in tropical plant community composition: influence of environmental and spatial data quality.

The degree to which variation in plant community composition (beta-diversity) is predictable from environmental variation, relative to other spatial processes, is of considerable current interest. We addressed this question in Costa Rican rain forest pteridophytes (1,045 plots, 127 species). We also tested the effect of data quality on the results, which has largely been overlooked in earlier studies. To do so, we compared two alternative spatial models [polynomial vs. principal coordinates of neighbour matrices (PCNM)] and ten alternative environmental models (all available environmental variables vs. four subsets, and including their polynomials vs. not). Of the environmental data types, soil chemistry contributed most to explaining pteridophyte community variation, followed in decreasing order of contribution by topography, soil type and forest structure. Environmentally explained variation increased moderately when polynomials of the environmental variables were included. Spatially explained variation increased substantially when the multi-scale PCNM spatial model was used instead of the traditional, broad-scale polynomial spatial model. The best model combination (PCNM spatial model and full environmental model including polynomials) explained 32% of pteridophyte community variation, after correcting for the number of sampling sites and explanatory variables. Overall evidence for environmental control of beta-diversity was strong, and the main floristic gradients detected were correlated with environmental variation at all scales encompassed by the study (c. 100-2,000 m). Depending on model choice, however, total explained variation differed more than fourfold, and the apparent relative importance of space and environment could be reversed. Therefore, we advocate a broader recognition of the impacts that data quality has on analysis results. A general understanding of the relative contributions of spatial and environmental processes to species distributions and beta-diversity requires that methodological artefacts are separated from real ecological differences.