Nicholas R. Vaughn

Progressive forest canopy water loss during the 2012–2015 California drought

Significance The state of California has a globally important economy and a population exceeding 38 million. The state relies on its forested watersheds to support numerous services, such as water provisioning, carbon storage, timber products, ecotourism, and recreation. However, secular changes in air temperature, combined with periodic and prolonged drought, pose a compounding challenge to forest health. Here we use new remote-sensing and modeling techniques to assess changes in the canopy water content of California’s forests from 2011 to 2015. Our resulting maps of progressive canopy water stress identify at-risk forest landscapes and watersheds at fine resolution, and offer geographically explicit information to support innovative forest management and policies in preparation for climate change. The 2012–2015 drought has left California with severely reduced snowpack, soil moisture, ground water, and reservoir stocks, but the impact of this estimated millennial-scale event on forest health is unknown. We used airborne laser-guided spectroscopy and satellite-based models to assess losses in canopy water content of California’s forests between 2011 and 2015. Approximately 10.6 million ha of forest containing up to 888 million large trees experienced measurable loss in canopy water content during this drought period. Severe canopy water losses of greater than 30% occurred over 1 million ha, affecting up to 58 million large trees. Our measurements exclude forests affected by fire between 2011 and 2015. If drought conditions continue or reoccur, even with temporary reprieves such as El Niño, we predict substantial future forest change.

Tree Species Detection Accuracies Using Discrete Point Lidar and Airborne Waveform Lidar

Species information is a key component of any forest inventory. However, when performing forest inventory from aerial scanning Lidar data, species classification can be very difficult. We investigated changes in classification accuracy while identifying five individual tree species (Douglas-fir, western redcedar, bigleaf maple, red alder, and black cottonwood) in the Pacific Northwest United States using two data sets: discrete point Lidar data alone and discrete point data in combination with waveform Lidar data. Waveform information included variables which summarize the frequency domain representation of all waveforms crossing individual trees. Discrete point data alone provided 79.2 percent overall accuracy (kappa = 0.74) for all 5 species and up to 97.8 percent (kappa = 0.96) when comparing individual pairs of these 5 species. Incorporating waveform information improved the overall accuracy to 85.4 percent (kappa = 0.817) for five species, and in several two-species comparisons. Improvements were most notable in comparing the two conifer species and in comparing two of the three hardwood species.

Airborne laser-guided imaging spectroscopy to map forest trait diversity and guide conservation

Airborne spectroscopy for forest traits The development of conservation priorities in the tropics is often hampered by the sparseness of ground data on biological diversity and the relative crudeness of larger-scale remote sensing data. Asner et al. developed airborne instrumentation to make large-scale maps of forest functional diversity across 72 million hectares of the Peruvian Andes and Amazon basin (see the Perspective by Kapos). They generated a suite of forest canopy functional trait maps from laser-guided imaging spectroscopy and used them to define distinct forest functional classes. These were then compared with government deforestation and land allocation data, which enabled an analysis of conservation threats and opportunities across the region. Science, this issue p. 385; see also p. 347 Large-scale mapping of tropical forest trait diversity offers an approach for conservation. Functional biogeography may bridge a gap between field-based biodiversity information and satellite-based Earth system studies, thereby supporting conservation plans to protect more species and their contributions to ecosystem functioning. We used airborne laser-guided imaging spectroscopy with environmental modeling to derive large-scale, multivariate forest canopy functional trait maps of the Peruvian Andes-to-Amazon biodiversity hotspot. Seven mapped canopy traits revealed functional variation in a geospatial pattern explained by geology, topography, hydrology, and climate. Clustering of canopy traits yielded a map of forest beta functional diversity for land-use analysis. Up to 53% of each mapped, functionally distinct forest presents an opportunity for new conservation action. Mapping functional diversity advances our understanding of the biosphere to conserve more biodiversity in the face of land use and climate change.

Large-scale climatic and geophysical controls on the leaf economics spectrum

Significance Ecology seeks general principles describing how the biota respond to multiple environmental factors, partly to build a more prognostic science in the face of global climate change. One such principle to emerge is the “leaf economics spectrum” (LES), which relates ecologically important plant nutrients to leaf construction and growth along simple relational axes. However, interrelationships between LES traits have not been tested at large geographic scales. Using airborne imaging spectroscopy and geospatial modeling, we discovered strong climatic and geophysical controls on LES traits and their interrelationships throughout Andean and western Amazonian forest canopies. This finding highlights the need for biogeographically explicit treatment of plant traits, afforded by imaging spectroscopy, in the next generation of biospheric models. Leaf economics spectrum (LES) theory suggests a universal trade-off between resource acquisition and storage strategies in plants, expressed in relationships between foliar nitrogen (N) and phosphorus (P), leaf mass per area (LMA), and photosynthesis. However, how environmental conditions mediate LES trait interrelationships, particularly at large biospheric scales, remains unknown because of a lack of spatially explicit data, which ultimately limits our understanding of ecosystem processes, such as primary productivity and biogeochemical cycles. We used airborne imaging spectroscopy and geospatial modeling to generate, to our knowledge, the first biospheric maps of LES traits, here centered on 76 million ha of Andean and Amazonian forest, to assess climatic and geophysical determinants of LES traits and their interrelationships. Elevation and substrate were codominant drivers of leaf trait distributions. Multiple additional climatic and geophysical factors were secondary determinants of plant traits. Anticorrelations between N and LMA followed general LES theory, but topo-edaphic conditions strongly mediated and, at times, eliminated this classic relationship. We found no evidence for simple P–LMA or N–P trade-offs in forest canopies; rather, we mapped a continuum of N–P–LMA interactions that are sensitive to elevation and temperature. Our results reveal nested climatic and geophysical filtering of LES traits and their interrelationships, with important implications for predictions of forest productivity and acclimation to rapid climate change.

Scale dependence of canopy trait distributions along a tropical forest elevation gradient

Average responses of forest foliar traits to elevation are well understood, but far less is known about trait distributional responses to elevation at multiple ecological scales. This limits our understanding of the ecological scales at which trait variation occurs in response to environmental drivers and change. We analyzed and compared multiple canopy foliar trait distributions using field sampling and airborne imaging spectroscopy along an Andes-to-Amazon elevation gradient. Field-estimated traits were generated from three community-weighting methods, and remotely sensed estimates of traits were made at three scales defined by sampling grain size and ecological extent. Field and remote sensing approaches revealed increases in average leaf mass per unit area (LMA), water, nonstructural carbohydrates (NSCs) and polyphenols with increasing elevation. Foliar nutrients and photosynthetic pigments displayed little to no elevation trend. Sample weighting approaches had little impact on field-estimated trait responses to elevation. Plot representativeness of trait distributions at landscape scales decreased with increasing elevation. Remote sensing indicated elevation-dependent increases in trait variance and distributional skew. Multiscale invariance of LMA, leaf water and NSC mark these traits as candidates for tracking forest responses to changing climate. Trait-based ecological studies can be greatly enhanced with multiscale studies made possible by imaging spectroscopy.

What mediates tree mortality during drought in the southern Sierra Nevada

Severe drought has the potential to cause selective mortality within a forest, thereby inducing shifts in forest species composition. The southern Sierra Nevada foothills and mountains of California have experienced extensive forest dieback due to drought stress and insect outbreak. We used high-fidelity imaging spectroscopy (HiFIS) and light detection and ranging (LiDAR) from the Carnegie Airborne Observatory (CAO) to estimate the effect of forest dieback on species composition in response to drought stress in Sequoia National Park. Our aims were (1) to quantify site-specific conditions that mediate tree mortality along an elevation gradient in the southern Sierra Nevada Mountains, (2) to assess where mortality events have a greater probability of occurring, and (3) to estimate which tree species have a greater likelihood of mortality along the elevation gradient. A series of statistical models were generated to classify species composition and identify tree mortality, and the influences of different environmental factors were spatially quantified and analyzed to assess where mortality events have a greater likelihood of occurring. A higher probability of mortality was observed in the lower portion of the elevation gradient, on southwest- and west-facing slopes, in areas with shallow soils, on shallower slopes, and at greater distances from water. All of these factors are related to site water balance throughout the landscape. Our results also suggest that mortality is species-specific along the elevation gradient, mainly affecting Pinus ponderosa and Pinus lambertiana at lower elevations. Selective mortality within the forest may drive long-term shifts in community composition along the elevation gradient.

Centennial impacts of fragmentation on the canopy structure of tropical montane forest

Fragmentation poses one of the greatest threats to tropical forests with short-term changes to the structure of forest canopies affecting microclimate, tree mortality, and growth. Yet the long-term effects of fragmentation are poorly understood because (1) most effects require many decades to materialize, but long-term studies are very rare, (2) the effects of edges on forest canopy structure as a function of fragment size are unknown, and (3) edge effects are often confounded by fragment shape. We quantified the long-term (centennial) effects of fragmentation on forest canopy structure using airborne light detection and ranging (LiDAR) of 1060 Hawaiian rain forest fragments ranging in size from 0.02 to 1000 ha, created more than 130 years ago by flowing lava. Along with distance from edge, we developed a metric, minimum span, to gain additional insight into edge effects on three measures of canopy structure: canopy height, height variation, and gap fraction. Fragment size was a strong determinant of the three structural variables. Larger fragments had greater average height, larger variation in height, and smaller gap fraction. Minimum span had a large effect on the depth and magnitude of edge effects for the three structural variables. Locations associated with high span values (those surrounded by more forest habitat) showed little effect of distance to fragment edge. In contrast, locations with low span values (those more exposed to edges) were severely limited in canopy height, showed lower height variation, and were associated with greater gap fraction values. The minimum span attribute allows for a more accurate characterization of edge as well as fragment-level effects, and when combined with high resolution imagery, can improve planning of protected areas for long-term ecological sustainability and biodiversity protection.

An Approach for Foliar Trait Retrieval from Airborne Imaging Spectroscopy of Tropical Forests

Spatial information on forest functional composition is needed to inform management and conservation efforts, yet this information is lacking, particularly in tropical regions. Canopy foliar traits underpin the functional biodiversity of forests, and have been shown to be remotely measurable using airborne 350–2510 nm imaging spectrometers. We used newly acquired imaging spectroscopy data constrained with concurrent light detection and ranging (LiDAR) measurements from the Carnegie Airborne Observatory (CAO), and field measurements, to test the performance of the Spectranomics approach for foliar trait retrieval. The method was previously developed in Neotropical forests, and was tested here in the humid tropical forests of Malaysian Borneo. Multiple foliar chemical traits, as well as leaf mass per area (LMA), were estimated with demonstrable precision and accuracy. The results were similar to those observed for Neotropical forests, suggesting a more general use of the Spectranomics approach for mapping canopy traits in tropical forests. Future mapping studies using this approach can advance scientific investigations and applications based on imaging spectroscopy.

Multiple Scales of Control on the Structure and Spatial Distribution of Woody Vegetation in African Savanna Watersheds

Factors controlling savanna woody vegetation structure vary at multiple spatial and temporal scales, and as a consequence, unraveling their combined effects has proven to be a classic challenge in savanna ecology. We used airborne LiDAR (light detection and ranging) to map three-dimensional woody vegetation structure throughout four savanna watersheds, each contrasting in geologic substrate and climate, in Kruger National Park, South Africa. By comparison of the four watersheds, we found that geologic substrate had a stronger effect than climate in determining watershed-scale differences in vegetation structural properties, including cover, height and crown density. Generalized Linear Models were used to assess the spatial distribution of woody vegetation structural properties, including cover, height and crown density, in relation to mapped hydrologic, topographic and fire history traits. For each substrate and climate combination, models incorporating topography, hydrology and fire history explained up to 30% of the remaining variation in woody canopy structure, but inclusion of a spatial autocovariate term further improved model performance. Both crown density and the cover of shorter woody canopies were determined more by unknown factors likely to be changing on smaller spatial scales, such as soil texture, herbivore abundance or fire behavior, than by our mapped regional-scale changes in topography and hydrology. We also detected patterns in spatial covariance at distances up to 50–450 m, depending on watershed and structural metric. Our results suggest that large-scale environmental factors play a smaller role than is often attributed to them in determining woody vegetation structure in southern African savannas. This highlights the need for more spatially-explicit, wide-area analyses using high resolution remote sensing techniques.

Long-term fragmentation effects on the distribution and dynamics of canopy gaps in a tropical montane forest

Fragmentation alters forest canopy structure through various mechanisms, which in turn drive subsequent changes to biogeochemical processes and biological diversity. Using repeated airborne LiDAR (Light Detection and Ranging) mappings, we investigated the size distribution and dynamics of forest canopy gaps across a topical montane forest landscape in Hawaii naturally fragmented by lava >100 yr ago. The combined effects of long-term isolation were evaluated using edge-proximity patterns in the distribution of gaps identified in year 1 (“existing gaps”). In addition, using the data from year 2, we investigated patterns in the loss of canopy (“new gaps”) and regrowth of canopy (“filled gaps”). The size distributions of the three gap types were modelled using the power-law exponent, λ. We found that fragmentation has resulted in some large changes in gap dynamics, with both the total area of gaps and the relative proportion of large existing gaps increased with distance to fragment edge. In models of power-law distribution scaling, λ estimates decreased to asymptotic values within 20 m of fragment edges for existing gaps. The size distributions of new and filled gaps were surprisingly similar. However, the total area of filled gaps was less than that of new gaps, and this difference was greatest near fragment edges. From these results, we conclude that fragmentation may be capable of continuously altering gap-phase dynamics of a forest for more than a century.