The role of microtopography and resident species in post-disturbance recovery of arid habitats in Hawai'i.

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 Hawai'i. 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 both Dodonaea and Cenchrus vegetation types. In invader-dominated Cenchrus plots, microtopography helped predict cover, but not as expected (i.e., highest cover would be in high-suitability plots): D. viscosa had the greatest cover in low-suitability and C. clandestinus had the greatest cover in medium-suitability plots. Similarly, in native-dominated Dodonaea plots, microtopography was a poor predictor of D. viscosa, C. clandestinus, and total plant cover. Although we found some evidence that microtopography helped inform post-disturbance plant recovery of D. viscosa and total plant cover, vegetation type was a more important predictor. Important for considering the success of plantings, percent cover of D. viscosa decreased while percent cover of C. clandestinus increased 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.

Density-dependent adult recruitment in a low-density tropical tree.

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 of Handroanthus 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 of H. guayacan, which increased significantly in size over the decade of observation.

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.

Chronosequence predictions are robust in a Neotropical secondary forest, but plots miss the mark.

Tropical secondary forests (TSF) are a global carbon sink of 1.6 Pg C/year. However, TSF carbon uptake is estimated using chronosequence studies that assume differently aged forests can be used to predict change in aboveground biomass density (AGBD) over time. We tested this assumption using two airborne lidar datasets separated by 11.5 years over a Neotropical landscape. Using data from 1998, we predicted canopy height and AGBD within 1.1 and 10.3% of observations in 2009, with higher accuracy for forest height than AGBD and for older TSFs in comparison to younger ones. This result indicates that the space-for-time assumption is robust at the landscape-scale. However, since lidar measurements of secondary tropical forest are rare, we used the 1998 lidar dataset to test how well plot-based studies quantify the mean TSF height and biomass in a landscape. We found that the sample area required to produce estimates of height or AGBD close to the landscape mean is larger than the typical area sampled in secondary forest chronosequence studies. For example, estimating AGBD within 10% of the landscape mean requires more than thirty 0.1 ha plots per age class, and more total area for larger plots. We conclude that under-sampling in ground-based studies may introduce error into estimations of the TSF carbon sink, and that this error can be reduced by more extensive use of lidar measurements.

Adult mortality in a low-density tree population using high-resolution remote sensing.

We developed a statistical framework to quantify mortality rates in canopy trees observed using time series from high-resolution remote sensing. By timing the acquisition of remote sensing data with synchronous annual flowering in the canopy tree species Handroanthus guayacan, we made 2,596 unique detections of 1,006 individual adult trees within 18,883 observation attempts on Barro Colorado Island, Panama (BCI) during an 11-yr period. There were 1,057 observation attempts that resulted in missing data due to cloud cover or incomplete spatial coverage. Using the fraction of 123 individuals from an independent field sample that were detected by satellite data (109 individuals, 88.6%), we estimate that the adult population for this species on BCI was 1,135 individuals. We used a Bayesian state-space model that explicitly accounted for the probability of tree detection and missing observations to compute an annual adult mortality rate of 0.2%·yr-1 (SE = 0.1, 95% CI = 0.06-0.45). An independent estimate of the adult mortality rate from 260 field-checked trees closely matched the landscape-scale estimate (0.33%·yr-1 , SE = 0.16, 95% CI = 0.12-0.74). Our proof-of-concept study shows that one can remotely estimate adult mortality rates for canopy tree species precisely in the presence of variable detection and missing observations.

Poleward expansion of mangroves is a threshold response to decreased frequency of extreme cold events.

Regional warming associated with climate change is linked with altered range and abundance of species and ecosystems worldwide. However, the ecological impacts of changes in the frequency of extreme events have not been as well documented, especially for coastal and marine environments. We used 28 y of satellite imagery to demonstrate that the area of mangrove forests has doubled at the northern end of their historic range on the east coast of Florida. This expansion is associated with a reduction in the frequency of "extreme" cold events (days colder than -4 °C), but uncorrelated with changes in mean annual temperature, mean annual precipitation, and land use. Our analyses provide evidence for a threshold response, with declining frequency of severe cold winter events allowing for poleward expansion of mangroves. Future warming may result in increases in mangrove cover beyond current latitudinal limits of mangrove forests, thereby altering the structure and function of these important coastal ecosystems.

Integrating physiological threshold experiments with climate modeling to project mangrove species' range expansion.

Predictions of climate-related shifts in species ranges have largely been based on correlative models. Due to limitations of these models, there is a need for more integration of experimental approaches when studying impacts of climate change on species distributions. Here, we used controlled experiments to identify physiological thresholds that control poleward range limits of three species of mangroves found in North America. We found that all three species exhibited a threshold response to extreme cold, but freeze tolerance thresholds varied among species. From these experiments, we developed a climate metric, freeze degree days (FDD), which incorporates both the intensity and the frequency of freezes. When included in distribution models, FDD accurately predicted mangrove presence/absence. Using 28 years of satellite imagery, we linked FDD to observed changes in mangrove abundance in Florida, further exemplifying the importance of extreme cold. We then used downscaled climate projections of FDD to project that these range limits will move northward by 2.2-3.2 km yr(-1) over the next 50 years.

Winners and losers in the competition for space in tropical forest canopies.

Trees compete for space in the canopy, but where and how individuals or their component parts win or lose is poorly understood. We developed a stochastic model of three-dimensional dynamics in canopies using a hierarchical Bayesian framework, and analysed 267,533 positive height changes from 1.25 m pixels using data from airborne LiDAR within 43 ha on the windward flank of Mauna Kea. Model selection indicates a strong resident's advantage, with 97.9% of positions in the canopy retained by their occupants over 2 years. The remaining 2.1% were lost to a neighbouring contender. Absolute height was a poor predictor of success, but short stature greatly raised the risk of being overtopped. Growth in the canopy was exponentially distributed with a scaling parameter of 0.518. These findings show how size and spatial proximity influence the outcome of competition for space, and provide a general framework for the analysis of canopy dynamics.

Mapping habitat suitability for at-risk plant species and its implications for restoration and reintroduction.

The conservation of species at risk of extinction requires data to support decisions at landscape to regional scales. There is a need for information that can assist with locating suitable habitats in fragmented and degraded landscapes to aid the reintroduction of at-risk plant species. In addition, desiccation and water stress can be significant barriers to the success of at-risk plant reintroduction programs. We examine how airborne light detection and ranging (LiDAR) data can be used to model microtopographic features that reduce water stress and increase resource availability, providing information for landscape planning that can increase the success of reintroduction efforts for a dryland landscape in Hawaii. We developed a topographic habitat-suitability model (HSM) from LiDAR data that identifies topographic depressions that are protected from prevailing winds (high-suitability sites) and contrasts them with ridges and other exposed areas (low-suitability sites). We tested in the field whether high-suitability sites had microclimatic conditions that indicated better-quality habitat compared to low-suitability sites, whether plant-response traits indicated better growing conditions in high-suitability sites, whether the locations of individuals of existing at-risk plant species corresponded with our habitat-suitability classes, and whether the survival of planted individuals of a common native species was greater in high-suitability, compared to low-suitability, planting sites. Mean wind speed in a high-suitability field site was over five times lower than in a low-suitability site, and soil moisture and leaf wetness were greater, indicating less stress and greater resource availability in high-suitability areas. Plant height and leaf nutrient content were greater in high-suitability areas. Six at-risk species showed associations with high-suitability areas. The survival of planted individuals was less variable among high-suitability plots. These results suggest that plant establishment and survival is associated with the habitat conditions identified by our model. The HSM can improve the survival of planted individuals, reduce the cost of restoration and reintroduction programs through targeted management activities in high-suitability areas, and expand the ability of managers to make landscape-scale decisions regarding land-use, land acquisition, and species recovery.

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.

Remote analysis of biological invasion and the impact of enemy release.

Escape from natural enemies is a widely held generalization for the success of exotic plants. We conducted a large-scale experiment in Hawaii (USA) to quantify impacts of ungulate removal on plant growth and performance, and to test whether elimination of an exotic generalist herbivore facilitated exotic success. Assessment of impacted and control sites before and after ungulate exclusion using airborne imaging spectroscopy and LiDAR, time series satellite observations, and ground-based field studies over nine years indicated that removal of generalist herbivores facilitated exotic success, but the abundance of native species was unchanged. Vegetation cover <1 m in height increased in ungulate-free areas from 48.7% +/- 1.5% to 74.3% +/- 1.8% over 8.4 years, corresponding to an annualized growth rate of lambda = 1.05 +/- 0.01 yr(-1) (median +/- SD). Most of the change was attributable to exotic plant species, which increased from 24.4% +/- 1.4% to 49.1% +/- 2.0%, (lambda = 1.08 +/- 0.01 yr(-1)). Native plants experienced no significant change in cover (23.0% +/- 1.3% to 24.2% +/- 1.8%, lambda = 1.01 +/- 0.01 yr(-1)). Time series of satellite phenology were indistinguishable between the treatment and a 3.0-km2 control site for four years prior to ungulate removal, but they diverged immediately following exclusion of ungulates. Comparison of monthly EVI means before and after ungulate exclusion and between the managed and control areas indicates that EVI strongly increased in the managed area after ungulate exclusion. Field studies and airborne analyses show that the dominant invader was Senecio madagascariensis, an invasive annual forb that increased from < 0.01% to 14.7% fractional cover in ungulate-free areas (lambda = 1.89 +/- 0.34 yr(-1)), but which was nearly absent from the control site. A combination of canopy LAI, water, and fractional cover were expressed in satellite EVI time series and indicate that the invaded region maintained greenness during drought conditions. These findings demonstrate that enemy release from generalist herbivores can facilitate exotic success and suggest a plausible mechanism by which invasion occurred. They also show how novel remote-sensing technology can be integrated with conservation and management to help address exotic plant invasions.

Genome assemblies for two Neotropical trees: Jacaranda copaia and Handroanthus guayacan.

The lack of genomic resources for tropical canopy trees is impeding several research avenues in tropical forest biology. We present genome assemblies for two Neotropical hardwood species, Jacaranda copaia and Handroanthus (formerly Tabebuia) guayacan, that are model systems for research on tropical tree demography and flowering phenology. For each species, we combined Illumina short-read data with in vitro proximity-ligation (Chicago) libraries to generate an assembly. For Jacaranda copaia, we obtained 104X physical coverage and produced an assembly with N50/N90 scaffold lengths of 1.020/0.277 Mbp. For H. guayacan, we obtained 129X coverage and produced an assembly with N50/N90 scaffold lengths of 0.795/0.165 Mbp. J. copaia and H. guayacan assemblies contained 95.8% and 87.9% of benchmarking orthologs, although they constituted only 77.1% and 66.7% of the estimated genome sizes of 799 and 512 Mbp, respectively. These differences were potentially due to high repetitive sequence content (>59.31% and 45.59%) and high heterozygosity (0.5% and 0.8%) in each species. Finally, we compared each new assembly to a previously sequenced genome for Handroanthus impetiginosus using whole-genome alignment. This analysis indicated extensive gene duplication in H. impetiginosus since its divergence from H. guayacan.

Impact of a tropical forest blowdown on aboveground carbon balance.

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.

Chlorophyll a fluorescence illuminates a path connecting plant molecular biology to Earth-system science.

For decades, the dynamic nature of chlorophyll a fluorescence (ChlaF) has provided insight into the biophysics and ecophysiology of the light reactions of photosynthesis from the subcellular to leaf scales. Recent advances in remote sensing methods enable detection of ChlaF induced by sunlight across a range of larger scales, from using instruments mounted on towers above plant canopies to Earth-orbiting satellites. This signal is referred to as solar-induced fluorescence (SIF) and its application promises to overcome spatial constraints on studies of photosynthesis, opening new research directions and opportunities in ecology, ecophysiology, biogeochemistry, agriculture and forestry. However, to unleash the full potential of SIF, intensive cross-disciplinary work is required to harmonize these new advances with the rich history of biophysical and ecophysiological studies of ChlaF, fostering the development of next-generation plant physiological and Earth-system models. Here, we introduce the scale-dependent link between SIF and photosynthesis, with an emphasis on seven remaining scientific challenges, and present a roadmap to facilitate future collaborative research towards new applications of SIF.

Convergent structural responses of tropical forests to diverse disturbance regimes.

Size frequency distributions of canopy gaps are a hallmark of forest dynamics. But it remains unknown whether legacies of forest disturbance are influencing vertical size structure of landscapes, or space-filling in the canopy volume. We used data from LiDAR remote sensing to quantify distributions of canopy height and sizes of 434,501 canopy gaps in five tropical rain forest landscapes in Costa Rica and Hawaii. The sites represented a wide range of variation in structure and natural disturbance history, from canopy gap dynamics in lowland Costa Rica and Hawaii, to stages and types of stand-level dieback on upland Mauna Kea and Kohala volcanoes. Large differences in vertical canopy structure characterized these five tropical rain forest landscapes, some of which were related to known disturbance events. Although there were quantitative differences in the values of scaling exponents within and among sites, size frequency distributions of canopy gaps followed power laws at all sites and in all canopy height classes. Scaling relationships in gap size at different heights in the canopy were qualitatively similar at all sites, revealing a remarkable similarity despite clearly defined differences in species composition and modes of prevailing disturbance. These findings indicate that power-law gap-size frequency distributions are ubiquitous features of these five tropical rain forest landscapes, and suggest that mechanisms of forest disturbance may be secondary to other processes in determining vertical and horizontal size structure in canopies.

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.

The GEDI Simulator: A Large-Footprint Waveform Lidar Simulator for Calibration and Validation of Spaceborne Missions.

NASA's Global Ecosystem Dynamics Investigation (GEDI) is a spaceborne lidar mission which will produce near global (51.6°S to 51.6°N) maps of forest structure and above-ground biomass density during its 2-year mission. GEDI uses a waveform simulator for calibration of algorithms and assessing mission accuracy. This paper implements a waveform simulator, using the method proposed in Blair and Hofton (1999; https://doi.org/10.1029/1999GL010484), and builds upon that work by adding instrument noise and by validating simulated waveforms across a range of forest types, airborne laser scanning (ALS) instruments, and survey configurations. The simulator was validated by comparing waveform metrics derived from simulated waveforms against those derived from observed large-footprint, full-waveform lidar data from NASA's airborne Land, Vegetation, and Ice Sensor (LVIS). The simulator was found to produce waveform metrics with a mean bias of less than 0.22 m and a root-mean-square error of less than 5.7 m, as long as the ALS data had sufficient pulse density. The minimum pulse density required depended upon the instrument. Measurement errors due to instrument noise predicted by the simulator were within 1.5 m of those from observed waveforms and 70-85% of variance in measurement error was explained. Changing the ALS survey configuration had no significant impact on simulated metrics, suggesting that the ALS pulse density is a sufficient metric of simulator accuracy across the range of conditions and instruments tested. These results give confidence in the use of the simulator for the pre-launch calibration and performance assessment of the GEDI mission.