An official website of the United States government
Abstract AimCanopy structural complexity, which describes the degree of heterogeneity in vegetation density, is strongly tied to a number of ecosystem functions, but the community and structural characteristics that give rise to variation in complexity at site to subcontinental scales are poorly defined. We investigated how woody plant taxonomic and phylogenetic diversity, maximum canopy height, and leaf area index (LAI) relate to canopy rugosity, a measure of canopy structural complexity that is correlated with primary production, light capture, and resource‐use efficiency. LocationOur analysis used 122 plots distributed across 10 ecologically and climatically variable forests spanning a > 1,500 km latitudinal gradient within the National Ecological Observatory Network (NEON) of the USA. Time period2016–2018. Taxa studiedWoody plants. MethodsWe used univariate and multivariate modelling to examine relationships between canopy rugosity, and community and structural characteristics hypothesized to drive site and subcontinental variation in complexity. ResultsSpatial variation in canopy rugosity within sites and across the subcontinent was strongly and positively related to maximum canopy height (r2 = .87 subcontinent‐wide), with the addition of species richness in a multivariate model resolving another 2% of the variation across the subcontinent. Individually, woody plant species richness and phylogenetic diversity (r2 = .17 to .44, respectively) and LAI (r2 = .16) were weakly to moderately correlated with canopy rugosity at the subcontinental scale, and inconsistently explained spatial variation in canopy rugosity within sites. Main conclusionsWe conclude that maximum canopy height is a substantially stronger predictor of complexity than diversity or LAI within and across forests of eastern North America, suggesting that canopy volume places a primary constraint on the development of structural complexity. Management and land‐use practices that encourage and sustain tall temperate forest canopies may support greater complexity and associated increases in ecosystem functioning.
more »
« less
Structural heterogeneity predicts ecological resistance and resilience to wildfire in arid shrublands
Abstract ContextDynamic feedbacks between physical structure and ecological function drive ecosystem productivity, resilience, and biodiversity maintenance. Detailed maps of canopy structure enable comprehensive evaluations of structure–function relationships. However, these relationships are scale-dependent, and identifying relevant spatial scales to link structure to function remains challenging. ObjectivesWe identified optimal scales to relate structure heterogeneity to ecological resistance, measured as the impacts of wildfire on canopy structure, and ecological resilience, measured as native shrub recruitment. We further investigated whether structural heterogeneity can aid spatial predictions of shrub recruitment. MethodsUsing high-resolution imagery from unoccupied aerial systems (UAS), we mapped structural heterogeneity across ten semi-arid landscapes, undergoing a disturbance-mediated regime shift from native shrubland to dominance by invasive annual grasses. We then applied wavelet analysis to decompose structural heterogeneity into discrete scales and related these scales to ecological metrics of resilience and resistance. ResultsWe found strong indicators of scale dependence in the tested relationships. Wildfire effects were most prominent at a single scale of structural heterogeneity (2.34 m), while the abundance of shrub recruits was sensitive to structural heterogeneity at a range of scales, from 0.07 – 2.34 m. Structural heterogeneity enabled out-of-site predictions of shrub recruitment (R2 = 0.55). The best-performing predictive model included structural heterogeneity metrics across multiple scales. ConclusionsOur results demonstrate that identifying structure–function relationships requires analyses that explicitly account for spatial scale. As high-resolution imagery enables spatially extensive maps of canopy heterogeneity, models for scale dependence will aid our understanding of resilience mechanisms in imperiled arid ecosystems.
more »
« less
- Award ID(s):
- 2207158
- PAR ID:
- 10509482
- Publisher / Repository:
- Springer Science + Business Media
- Date Published:
- Journal Name:
- Landscape Ecology
- Volume:
- 39
- Issue:
- 6
- ISSN:
- 1572-9761
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Abstract Plant functional diversity is strongly connected to photosynthetic carbon assimilation in terrestrial ecosystems. However, many of the plant functional traits that regulate photosynthetic capacity, including foliar nitrogen concentration and leaf mass per area, vary significantly between and within plant functional types and vertically through forest canopies, resulting in considerable landscape‐scale heterogeneity in three dimensions. Hyperspectral imagery has been used extensively to quantify functional traits across a range of ecosystems but is generally limited to providing information for top of canopy leaves only. On the other hand, lidar data can be used to retrieve the vertical structure of forest canopies. Because these data are rarely collected at the same time, there are unanswered questions about the effect of forest structure on the three ‐dimensional spatial patterns of functional traits across ecosystems. In the United States, the National Ecological Observatory Network's Airborne Observation Platform (NEON AOP) provides an opportunity to address this structure‐function relationship by collecting lidar and hyperspectral data together across a variety of ecoregions. With a fusion of hyperspectral and lidar data from the NEON AOP and field‐collected foliar trait data, we assessed the impacts of forest structure on spatial patterns of N. In addition, we examine the influence of abiotic gradients and management regimes on top‐of‐canopy percent N and total canopy N (i.e., the total amount of N [g/m2] within a forest canopy) at a NEON site consisting of a mosaic of open longleaf pine and dense broadleaf deciduous forests. Our resulting maps suggest that, in contrast to top of canopy values, total canopy N variation is dampened across this landscape resulting in relatively homogeneous spatial patterns. At the same time, we found that leaf functional diversity and canopy structural diversity showed distinct dendritic patterns related to the spatial distribution of plant functional types.more » « less
-
Abstract Neotropical xerophytic forest ecosystems evolved with fires that shaped their resilience to disturbance events. However, it is unknown whether forest resilience to fires persists under a new fire regime influenced by anthropogenic disturbance and climate change. We asked whether there was evidence for a fire severity threshold causing an abrupt transition from a forest to an alternative shrub thicket state in the presence of typical postfire management. We studied a heterogeneous wildfire event to assess medium‐term effects (11 years) of varying fire severity in a xerophytic Caldén forest in central Argentina. We conducted vegetation surveys in patches that were exposed to low (LFS), medium (MFS), and high (HFS) fire severities but had similar prefire woody canopy cover. Satellite images were used to quantify fire severity using a delta Normalized Burning Ratio (dNBR) and to map prefire canopy cover. Postfire total woody canopy cover was higher in low and medium than high severity patches, but the understory woody component was highest in HFS patches. The density of woody plants was over three times higher under HFS than MFS and LFS due to the contribution of small woody plants to the total density. Unlike LFS and MFS patches, the small plants in HFS patches were persistent, multistem shrubs that resulted from the resprouting of top‐killedProsopis caldeniatrees and, more importantly, from young shrubs that probably established after the wildfire. Our results suggest that the Caldén forest is resilient to fires of low to moderate severities but not to high‐severity fires. Fire severities with dNBR values > ~600 triggered an abrupt transition to a shrub thicket state. Postfire grazing and controlled‐fire treatments likely contributed to shrub dominance after high‐severity wildfire. Forest to shrub thicket transitions enable recurring high‐severity fire events. We propose that repeated fires combined with grazing can trap the system in a shrub thicket state. Further studies are needed to determine whether the relationships between fire and vegetation structure examined in this case study represent general mechanisms of irreversible state changes across the Caldenal forest region and whether analogous threshold relationships exist in other fire‐prone woodland ecosystems.more » « less
-
Abstract Estimating and monitoring plant population size is fundamental for ecological research, as well as conservation and restoration programs. High‐resolution imagery has potential to facilitate such estimation and monitoring. However, remotely sensed estimates typically have higher uncertainty than field measurements, risking biased inference on population status.We present a model that accounts for false negative (missed plants) and false positive (misclassified or double‐counted plants) error in counts from high‐resolution imagery via integration with ground data. We apply it to estimate the abundance of a foundational shrub species in post‐wildfire landscapes in the western United States. In these landscapes, plant recruitment is crucial for ecological recovery but locally patchy, motivating the use of spatially extensive measurements from unoccupied aerial systems (UAS). Integrating >16 ha of UAS imagery with >700 georeferenced field plots, we fit our model to generate insights into the prevalence and drivers of observation errors associated with classification algorithms used to distinguish individual plants, relationships between abundance and landscape context, and to generate spatially explicit maps of shrub abundance.Raw counts of plant abundance in high‐resolution imagery resulted in substantial false negative and false positive observation errors. The probability of detecting (p) adult plants (0.25 m tall) varied between sites within 0.52 < < 0.82, whereas the detection of smaller plants (<0.25 m) was lower, 0.03 < < 0.3. On average, we estimate that 19% of all detected plants were false positive errors, which varied spatially in relation to topographic predictors. Abundance declined toward the interior of previous wildfires and was positively associated with terrain roughness.Our study demonstrates that integrated models accounting for imperfect detection improve estimates of plant population abundance derived from inherently imperfect UAS imagery. We believe such models will further improve inference on plant population dynamics—relevant to restoration, wildlife habitat and related objectives—and echo previous calls for remote sensing applications to better differentiate between ecological and observational processes.more » « less
-
Structural diversity is a key feature of forest ecosystems that influences ecosystem functions from local to macroscales. The ability to measure structural diversity in forests with varying ecological composition and management history can improve the understanding of linkages between forest structure and ecosystem functioning. Terrestrial LiDAR has often been used to provide a detailed characterization of structural diversity at local scales, but it is largely unknown whether these same structural features are detectable using aerial LiDAR data that are available across larger spatial scales. We used univariate and multivariate analyses to quantify cross-compatibility of structural diversity metrics from terrestrial versus aerial LiDAR in seven National Ecological Observatory Network sites across the eastern USA. We found strong univariate agreement between terrestrial and aerial LiDAR metrics of canopy height, openness, internal heterogeneity, and leaf area, but found marginal agreement between metrics that described heterogeneity of the outermost layer of the canopy. Terrestrial and aerial LiDAR both demonstrated the ability to distinguish forest sites from structural diversity metrics in multivariate space, but terrestrial LiDAR was able to resolve finer-scale detail within sites. Our findings indicated that aerial LiDAR could be of use in quantifying broad-scale variation in structural diversity across macroscales.more » « less
