The ability to automatically delineate individual tree crowns using remote sensing data opens the possibility to collect detailed tree information over large geographic regions. While individual tree crown delineation (ITCD) methods have proven successful in conifer-dominated forests using Light Detection and Ranging (LiDAR) data, it remains unclear how well these methods can be applied in deciduous broadleaf-dominated forests. We applied five automated LiDAR-based ITCD methods across fifteen plots ranging from conifer- to broadleaf-dominated forest stands at Harvard Forest in Petersham, MA, USA, and assessed accuracy against manual delineation of crowns from unmanned aerial vehicle (UAV) imagery. We then identified tree- and plot-level factors influencing the success of automated delineation techniques. There was relatively little difference in accuracy between automated crown delineation methods (51–59% aggregated plot accuracy) and, despite parameter tuning, none of the methods produced high accuracy across all plots (27—90% range in plot-level accuracy). The accuracy of all methods was significantly higher with increased plot conifer fraction, and individual conifer trees were identified with higher accuracy (mean 64%) than broadleaf trees (42%) across methods. Further, while tree-level factors (e.g., diameter at breast height, height and crown area) strongly influenced the success of crown delineations, the influence of plot-level factors varied. The most important plot-level factor was species evenness, a metric of relative species abundance that is related to both conifer fraction and the degree to which trees can fill canopy space. As species evenness decreased (e.g., high conifer fraction and less efficient filling of canopy space), the probability of successful delineation increased. Overall, our work suggests that the tested LiDAR-based ITCD methods perform equally well in a mixed temperate forest, but that delineation success is driven by forest characteristics like functional group, tree size, diversity, and crown architecture. While LiDAR-based ITCD methods are well suited for stands with distinct canopy structure, we suggest that future work explore the integration of phenology and spectral characteristics with existing LiDAR as an approach to improve crown delineation in broadleaf-dominated stands.
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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.
more » « less- NSF-PAR ID:
- 10376603
- Publisher / Repository:
- Wiley Blackwell (John Wiley & Sons)
- Date Published:
- Journal Name:
- Ecological Applications
- Volume:
- 30
- Issue:
- 7
- ISSN:
- 1051-0761
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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null (Ed.)Maritime forests are threatened by sea-level rise, storm surge and encroachment of salt-tolerant species. On barrier islands, these forested communities must withstand the full force of tropical storms, hurricanes and nor’easters while the impact is reduced for mainland forests protected by barrier islands. Geographic position may account for differences in maritime forest resilience to disturbance. In this study, we quantify two geographically distinct maritime forests protected by dunes on Virginia’s Eastern Shore (i.e., mainland and barrier island) at two time points (15 and 21 years apart, respectively) to determine whether the trajectory is successional or presenting evidence of disassembly with sea-level rise and storm exposure. We hypothesize that due to position on the landscape, forest disassembly will be higher on the barrier island than mainland as evidenced by reduction in tree basal area and decreased species richness. Rate of relative sea-level rise in the region was 5.9 ± 0.7 mm yr−1 based on monthly mean sea-level data from 1975 to 2017. Savage Neck Dunes Natural Area Preserve maritime forest was surveyed using the point quarter method in 2003 and 2018. Parramore Island maritime forest was surveyed in 1997 using 32 m diameter circular plots. As the island has been eroding over the past two decades, 2016 Landsat imagery was used to identify remaining forested plots prior to resurveying. In 2018, only plots that remained forested were resurveyed. Lidar was used to quantify elevation of each point/plot surveyed in 2018. Plot elevation at Savage Neck was 1.93 ± 0.02 m above sea level, whereas at Parramore Island, elevation was lower at 1.04 ± 0.08 m. Mainland dominant species, Acer rubrum, Pinus taeda, and Liquidambar styraciflua, remained dominant over the study period, with a 14% reduction in the total number of individuals recorded. Basal area increased by 11%. Conversely, on Parramore Island, 33% of the former forested plots converted to grassland and 33% were lost to erosion and occur as ghost forest on the shore or were lost to the ocean. Of the remaining forested plots surveyed in 2018, dominance switched from Persea palustris and Juniperus virginiana to the shrub Morella cerifera. Only 46% of trees/shrubs remained and basal area was reduced by 84%. Shrub basal area accounted for 66% of the total recorded in 2018. There are alternative paths to maritime forest trajectory which differ for barrier island and mainland. Geographic position relative to disturbance and elevation likely explain the changes in forest community composition over the timeframes studied. Protected mainland forest at Savage Neck occurs at higher mean elevation and indicates natural succession to larger and fewer individuals, with little change in mixed hardwood-pine dominance. The fronting barrier island maritime forest on Parramore Island has undergone rapid change in 21 years, with complete loss of forested communities to ocean or conversion to mesic grassland. Of the forests remaining, dominant evergreen trees are now being replaced with the expanding evergreen shrub, Morella cerifera. Loss of biomass and basal area has been documented in other low elevation coastal forests. Our results indicate that an intermediate shrub state may precede complete loss of woody communities in some coastal communities, providing an alternative mechanism of resilience.more » « less
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A near-monoculture of J. roemerianus is often adjacent to and immediately landward of the A. germinans zone. The transition from the mangrove to the J. roemerianus zone is variable in our study area. An abrupt edge between closed-canopy mangrove and J. roemerianus monoculture may extend for up to several hundred meters in some locations, while other stretches of ecotone present a gradual transition where smaller, widely spaced trees are interspersed into the herbaceous marsh. Juncus roemerianus then extends landward to a high marsh patchwork of succulent halophytes (including Salicornia bigellovi, Sesuvium sp., and Batis maritima), scattered dwarf mangrove, and salt pans, followed in turn by upland vegetation that includes Pinus sp. and Serenoa repens. Field design and sample collection. We established three study sites spaced at approximately 5 km intervals along the western coastline of the central Florida peninsula. The sites consisted of the Salt Springs (28.3298°, -82.7274°), Energy Marine Center (28.2903°, -82.7278°), and Green Key (28.2530°, -82.7496°) sites on the Gulf of Mexico coastline in Pasco County, Florida, USA. At each site, we established three plot pairs, each consisting of one saltmarsh plot and one mangrove plot. Plots were 50 m^2 in size. Plots pairs within a site were separated by 230-1070 m, and the mangrove and saltmarsh plots composing a pair were 70-170 m apart. All plot pairs consisted of directly adjacent patches of mangrove forest and J. roemerianus saltmarsh, with the mangrove forests exhibiting a closed canopy and a tree architecture (height 4-6 m, crown width 1.5-3 m). Mangrove plots were located at approximately the midpoint between the seaward edge (water-mangrove interface) and landward edge (mangrove-marsh interface) of the mangrove zone. Saltmarsh plots were located 20-25 m away from any mangrove trees and into the J. roemerianus zone (i.e., landward from the mangrove-marsh interface). Plot pairs were coarsely similar in geomorphic setting, as all were located on the Gulf of Mexico coastline, rather than within major sheltering formations like Tampa Bay, and all plot pairs fit the tide-dominated domain of the Woodroffe classification (Woodroffe, 2002, "Coasts: Form, Process and Evolution", Cambridge University Press), given their conspicuous semi-diurnal tides. There was nevertheless some geomorphic variation, as some plot pairs were directly open to the Gulf of Mexico while others sat behind keys and spits or along small tidal creeks. Our use of a plot-pair approach is intended to control for this geomorphic variation. Plot center elevations (cm above mean sea level, NAVD 88) were estimated by overlaying the plot locations determined with a global positioning system (Garmin GPS 60, Olathe, KS, USA) on a LiDAR-derived bare-earth digital elevation model (Dewberry, Inc., 2019). The digital elevation model had a vertical accuracy of ± 10 cm (95 % CI) and a horizontal accuracy of ± 116 cm (95 % CI). Soil samples were collected via coring at low tide in June 2011. From each plot, we collected a composite soil sample consisting of three discrete 5.1 cm diameter soil cores taken at equidistant points to 7.6 cm depth. Cores were taken by tapping a sleeve into the soil until its top was flush with the soil surface, sliding a hand under the core, and lifting it up. Cores were then capped and transferred on ice to our laboratory at the University of South Florida (Tampa, Florida, USA), where they were combined in plastic zipper bags, and homogenized by hand into plot-level composite samples on the day they were collected. A damp soil subsample was immediately taken from each composite sample to initiate 1 y incubations for determination of active C and N (see below). The remainder of each composite sample was then placed in a drying oven (60 °C) for 1 week with frequent mixing of the soil to prevent aggregation and liberate water. Organic wetland soils are sometimes dried at 70 °C, however high drying temperatures can volatilize non-water liquids and oxidize and decompose organic matter, so 50 °C is also a common drying temperature for organic soils (Gardner 1986, "Methods of Soil Analysis: Part 1", Soil Science Society of America); we accordingly chose 60 °C as a compromise between sufficient water removal and avoidance of non-water mass loss. Bulk density was determined as soil dry mass per core volume (adding back the dry mass equivalent of the damp subsample removed prior to drying). Dried subsamples were obtained for determination of soil organic matter (SOM), mineral texture composition, and extractable and total carbon (C) and nitrogen (N) within the following week. Sample analyses. A dried subsample was apportioned from each composite sample to determine SOM as mass loss on ignition at 550 °C for 4 h. After organic matter was removed from soil via ignition, mineral particle size composition was determined using a combination of wet sieving and density separation in 49 mM (3 %) sodium hexametaphosphate ((NaPO_3)_6) following procedures in Kettler et al. (2001, Soil Science Society of America Journal 65, 849-852). The percentage of dry soil mass composed of silt and clay particles (hereafter, fines) was calculated as the mass lost from dispersed mineral soil after sieving (0.053 mm mesh sieve). Fines could have been slightly underestimated if any clay particles were burned off during the preceding ignition of soil. An additional subsample was taken from each composite sample to determine extractable N and organic C concentrations via 0.5 M potassium sulfate (K_2SO_4) extractions. We combined soil and extractant (ratio of 1 g dry soil:5 mL extractant) in plastic bottles, reciprocally shook the slurry for 1 h at 120 rpm, and then gravity filtered it through Fisher G6 (1.6 μm pore size) glass fiber filters, followed by colorimetric detection of nitrite (NO_2^-) + nitrate (NO_3^-) and ammonium (NH_4^+) in the filtrate (Hood Nowotny et al., 2010,Soil Science Society of America Journal 74, 1018-1027) using a microplate spectrophotometer (Biotek Epoch, Winooski, VT, USA). Filtrate was also analyzed for dissolved organic C (referred to hereafter as extractable organic C) and total dissolved N via combustion and oxidation followed by detection of the evolved CO_2 and N oxide gases on a Formacs HT TOC/TN analyzer (Skalar, Breda, The Netherlands). Extractable organic N was then computed as total dissolved N in filtrate minus extractable mineral N (itself the sum of extractable NH_4-N and NO_2-N + NO_3-N). We determined soil total C and N from dried, milled subsamples subjected to elemental analysis (ECS 4010, Costech, Inc., Valencia, CA, USA) at the University of South Florida Stable Isotope Laboratory. Median concentration of inorganic C in unvegetated surface soil at our sites is 0.5 % of soil mass (Anderson, 2019, Univ. of South Florida M.S. thesis via methods in Wang et al., 2011, Environmental Monitoring and Assessment 174, 241-257). Inorganic C concentrations are likely even lower in our samples from under vegetation, where organic matter would dilute the contribution of inorganic C to soil mass. Nevertheless, the presence of a small inorganic C pool in our soils may be counted in the total C values we report. Extractable organic C is necessarily of organic C origin given the method (sparging with HCl) used in detection. Active C and N represent the fractions of organic C and N that are mineralizable by soil microorganisms under aerobic conditions in long-term soil incubations. To quantify active C and N, 60 g of field-moist soil were apportioned from each composite sample, placed in a filtration apparatus, and incubated in the dark at 25 °C and field capacity moisture for 365 d (as in Lewis et al., 2014, Ecosphere 5, art59). Moisture levels were maintained by frequently weighing incubated soil and wetting them up to target mass. Daily CO_2 flux was quantified on 29 occasions at 0.5-3 week intervals during the incubation period (with shorter intervals earlier in the incubation), and these per day flux rates were integrated over the 365 d period to compute an estimate of active C. Observations of per day flux were made by sealing samples overnight in airtight chambers fitted with septa and quantifying headspace CO_2 accumulation by injecting headspace samples (obtained through the septa via needle and syringe) into an infrared gas analyzer (PP Systems EGM 4, Amesbury, MA, USA). To estimate active N, each incubated sample was leached with a C and N free, 35 psu solution containing micronutrients (Nadelhoffer, 1990, Soil Science Society of America Journal 54, 411-415) on 19 occasions at increasing 1-6 week intervals during the 365 d incubation, and then extracted in 0.5 M K_2SO_4 at the end of the incubation in order to remove any residual mineral N. Active N was then quantified as the total mass of mineral N leached and extracted. Mineral N in leached and extracted solutions was detected as NH_4-N and NO_2-N + NO_3-N via colorimetry as above. This incubation technique precludes new C and N inputs and persistently leaches mineral N, forcing microorganisms to meet demand by mineralizing existing pools, and thereby directly assays the potential activity of soil organic C and N pools present at the time of soil sampling. Because this analysis commences with disrupting soil physical structure, it is biased toward higher estimates of active fractions. Calculations. Non-mobile C and N fractions were computed as total C and N concentrations minus the extractable and active fractions of each element. This data package reports surface-soil constituents (moisture, fines, SOM, and C and N pools and fractions) in both gravimetric units (mass constituent / mass soil) and areal units (mass constituent / soil surface area integrated through 7.6 cm soil depth, the depth of sampling). Areal concentrations were computed as X × D × 7.6, where X is the gravimetric concentration of a soil constituent, D is soil bulk density (g dry soil / cm^3), and 7.6 is the sampling depth in cm.more » « less
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Abstract Light is a key resource for tree performance and hence, tree species partition spatial and temporal gradients in light availability. Although light distribution drives tree performance and species replacement during secondary forest succession, we yet lack understanding how light distribution changes with tropical forest development.
This study aims to evaluate how changes in forest structure lead to changes in vertical and horizontal light heterogeneity during tropical forest succession.
We described successional patterns in light using a chronosequence approach in which we compared 14 Mexican secondary forest stands that differ in age (8–32 years) since agricultural abandonment. For each stand, we measured vertical light profiles in 16 grid cells, and structural parameters (diameter at breast height, height and crown dimensions) for each tree.
During succession, we found a rapid increase in stand size (basal area, crown area and length) and stand differentiation (i.e. a gradual leaf distribution along the forest profile), which leads to fast changes in light conditions and more light heterogeneity. The inflection points of the vertical light gradient (i.e. the absolute height at which 50% relative light intensity is attained) rapidly moved towards higher heights in the first 20 years, indicating that larger amounts of light are intercepted by canopy trees. Light attenuation rate (i.e. the rate of light extinction) decreased during succession due to slower accumulation of the crown area with height. Understorey light intensity and heterogeneity slightly decreased during succession because of an increase in crown size and a decrease in lateral gap frequency. Understorey relative light intensity was 1.56% at 32 years after abandonment.
Synthesis . During succession, light conditions changed linearly, which should lead to a continuous and constant replacement of species. Especially in later successional stages, stronger vertical light gradients can limit the regeneration of light‐demanding pioneer species and increase the proportion of shade‐tolerant late‐successional species under the canopy. These changes in light conditions were largely driven by the successional changes in forest structure, as basal area strongly determined the height where most light is absorbed, whereas crown area, and to a lesser extent crown length, determined light distribution. -
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Abstract Forest tree communities are largely structured by interactions between phenotypes and their environments. Functional traits have been popularized as providing key insights into plant functional tradeoffs. Similarly, tree crown—stem diameter and tree height—stem diameter allometric relationships are likely to be strongly coordinated with functional trait tradeoff axes. Specifically, species with functional traits indicative of conservative strategies (i.e., dense wood, heavy seeds) should be related to tree architectures that have lower heights and wider crowns for a given stem diameter. For example, shade‐tolerant species in tropical forests are typically characterized as having dense wood, large seeds, and relatively broad crowns at early ontogenetic stages. Here, we focus on 14 dominant dicot tree species in a tropical forest. We utilized hierarchical Bayesian models to characterize species‐specific height and crown size allometric parameters. We sampled from the posterior distributions for these parameters and correlated them with six functional traits. We also characterize the expected height and crown size for a series of reference stem diameters to quantify the relationship between traits and tree architecture across size classes. We find little interspecific variation in allometric slopes, but clear variation in allometric intercepts. Allometeric height intercepts were negatively correlated with wood density and crown size intercepts were positively related to wood density and seed mass and negatively related to leaf percent phosphorus. Thus, interspecific variation in tree architecture is generated by interspecific variation in allometric intercepts and not slopes. These intercepts could be predicted using a handful of functional traits where conservative traits were indicative of trees that are relatively short and have larger crown sizes. This demonstrates a coordination of tropical tree life histories that can be characterized simultaneously with functional traits and tree allometries.
