skip to main content

Title: An experimental approach for crown to whole-canopy defoliation in forests
Canopy defoliation is an important source of disturbance in forest ecosystems that has rarely been represented in large-scale manipulation experiments. Scalable crown to canopy level experimental defoliation is needed to disentangle the effects of variable intensity, timing, and frequency on forest structure, function, and mortality. We present a novel pressure-washing-based defoliation method that can be implemented at the canopy-scale, throughout the canopy volume, targeted to individual leaves or trees, and completed within a timeframe of hours or days. Pressure washing proved successful at producing consistent leaf-level and whole-canopy defoliation, with 10%–20% reduction in leaf area index and consistent leaf surface area removal across branches and species. This method allows for stand-scale experimentation on defoliation disturbance in forested ecosystems and has the potential for broad application. Studies utilizing this standardized method could promote mechanistic understanding of defoliation effects on ecosystem structure and function and development of synthetic understanding across forest types, ecoregions, and defoliation sources.
Authors:
; ; ; ; ;
Award ID(s):
1655095
Publication Date:
NSF-PAR ID:
10327795
Journal Name:
Canadian Journal of Forest Research
Volume:
52
Issue:
2
Page Range or eLocation-ID:
286 to 292
ISSN:
0045-5067
Sponsoring Org:
National Science Foundation
More Like this
  1. Atkins, Jeff (Ed.)
    Abstract Understanding connections between ecosystem nitrogen (N) cycling and invasive insect defoliation could facilitate the prediction of disturbance impacts across a range of spatial scales. In this study we investigated relationships between ecosystem N cycling and tree defoliation during a recent 2015–18 irruption of invasive gypsy moth caterpillars (Lymantria dispar), which can cause tree stress and sometimes mortality following multiple years of defoliation. Nitrogen is a critical nutrient that limits the growth of caterpillars and plants in temperate forests. In this study, we assessed the associations among N concentrations, soil solution N availability and defoliation intensity by L. dispar at the scale of individual trees and forest plots. We measured leaf and soil N concentrations and soil solution inorganic N availability among individual red oak trees (Quercus rubra) in Amherst, MA and across a network of forest plots in Central Massachusetts. We combined these field data with estimated defoliation severity derived from Landsat imagery to assess relationships between plot-scale defoliation and ecosystem N cycling. We found that trees in soil with lower N concentrations experienced more herbivory than trees in soil with higher N concentrations. Additionally, forest plots with lower N soil were correlated with more severe L. dispar defoliation,more »which matched the tree-level relationship. The amount of inorganic N in soil solution was strongly positively correlated with defoliation intensity and the number of sequential years of defoliation. These results suggested that higher ecosystem N pools might promote the resistance of oak trees to L. dispar defoliation and that defoliation severity across multiple years is associated with a linear increase in soil solution inorganic N.« less
  2. BACKGROUND The availability of nitrogen (N) to plants and microbes has a major influence on the structure and function of ecosystems. Because N is an essential component of plant proteins, low N availability constrains the growth of plants and herbivores. To increase N availability, humans apply large amounts of fertilizer to agricultural systems. Losses from these systems, combined with atmospheric deposition of fossil fuel combustion products, introduce copious quantities of reactive N into ecosystems. The negative consequences of these anthropogenic N inputs—such as ecosystem eutrophication and reductions in terrestrial and aquatic biodiversity—are well documented. Yet although N availability is increasing in many locations, reactive N inputs are not evenly distributed globally. Furthermore, experiments and theory also suggest that global change factors such as elevated atmospheric CO 2 , rising temperatures, and altered precipitation and disturbance regimes can reduce the availability of N to plants and microbes in many terrestrial ecosystems. This can occur through increases in biotic demand for N or reductions in its supply to organisms. Reductions in N availability can be observed via several metrics, including lowered nitrogen concentrations ([N]) and isotope ratios (δ 15 N) in plant tissue, reduced rates of N mineralization, and reduced terrestrial Nmore »export to aquatic systems. However, a comprehensive synthesis of N availability metrics, outside of experimental settings and capable of revealing large-scale trends, has not yet been carried out. ADVANCES A growing body of observations confirms that N availability is declining in many nonagricultural ecosystems worldwide. Studies have demonstrated declining wood δ 15 N in forests across the continental US, declining foliar [N] in European forests, declining foliar [N] and δ 15 N in North American grasslands, and declining [N] in pollen from the US and southern Canada. This evidence is consistent with observed global-scale declines in foliar δ 15 N and [N] since 1980. Long-term monitoring of soil-based N availability indicators in unmanipulated systems is rare. However, forest studies in the northeast US have demonstrated decades-long decreases in soil N cycling and N exports to air and water, even in the face of elevated atmospheric N deposition. Collectively, these studies suggest a sustained decline in N availability across a range of terrestrial ecosystems, dating at least as far back as the early 20th century. Elevated atmospheric CO 2 levels are likely a main driver of declines in N availability. Terrestrial plants are now uniformly exposed to ~50% more of this essential resource than they were just 150 years ago, and experimentally exposing plants to elevated CO 2 often reduces foliar [N] as well as plant-available soil N. In addition, globally-rising temperatures may raise soil N supply in some systems but may also increase N losses and lead to lower foliar [N]. Changes in other ecosystem drivers—such as local climate patterns, N deposition rates, and disturbance regimes—individually affect smaller areas but may have important cumulative effects on global N availability. OUTLOOK Given the importance of N to ecosystem functioning, a decline in available N is likely to have far-reaching consequences. Reduced N availability likely constrains the response of plants to elevated CO 2 and the ability of ecosystems to sequester carbon. Because herbivore growth and reproduction scale with protein intake, declining foliar [N] may be contributing to widely reported declines in insect populations and may be negatively affecting the growth of grazing livestock and herbivorous wild mammals. Spatial and temporal patterns in N availability are not yet fully understood, particularly outside of Europe and North America. Developments in remote sensing, accompanied by additional historical reconstructions of N availability from tree rings, herbarium specimens, and sediments, will show how N availability trajectories vary among ecosystems. Such assessment and monitoring efforts need to be complemented by further experimental and theoretical investigations into the causes of declining N availability, its implications for global carbon sequestration, and how its effects propagate through food webs. Responses will need to involve reducing N demand via lowering atmospheric CO 2 concentrations, and/or increasing N supply. Successfully mitigating and adapting to declining N availability will require a broader understanding that this phenomenon is occurring alongside the more widely recognized issue of anthropogenic eutrophication. Intercalibration of isotopic records from leaves, tree rings, and lake sediments suggests that N availability in many terrestrial ecosystems has steadily declined since the beginning of the industrial era. Reductions in N availability may affect many aspects of ecosystem functioning, including carbon sequestration and herbivore nutrition. Shaded areas indicate 80% prediction intervals; marker size is proportional to the number of measurements in each annual mean. Isotope data: (tree ring) K. K. McLauchlan et al. , Sci. Rep. 7 , 7856 (2017); (lake sediment) G. W. Holtgrieve et al. , Science 334 , 1545–1548 (2011); (foliar) J. M. Craine et al. , Nat. Ecol. Evol. 2 , 1735–1744 (2018)« less
  3. The capacity of forests to resist structural change and retain material legacies–the biotic and abiotic resources that persist through disturbance–is crucial to sustaining ecosystem function after disturbance. However, the role of forest structure as both a material legacy and feature supporting carbon (C) cycling stability following disturbance has not been widely investigated. We used a large-scale disturbance manipulation to ask whether legacies of lidar-derived canopy structures drive 3-year primary production responses to disturbance. As part of the Forest Resilience Threshold Experiment (FoRTE) in northern Michigan, USA we simulated phloem-disrupting disturbances producing a range of severities and affecting canopy trees of different sizes. We quantified the legacies of forest structure using two approaches: one measuring the change in structure and primary production from pre-to post-disturbance and the second estimating resistance as log transformed ratios of control and treatment values. We found that total aboveground wood net primary production (ANPP w ) was similar across disturbance severities as legacy trees rapidly increased rates of primary production. Experiment-wide, the disturbance had limited effects on change in mean structural complexity values; however, high variance underscored large differences in the magnitude and direction of complexity's response at the plot-scale. Plot-scale structural complexity, but not vegetationmore »area index (VAI), resistance strongly predicted ANPP w resistance while temporal VAI and structural complexity changes did not. We conclude that the presence of material legacies in the form of forest structure may affect primary production stability following disturbance and that how legacies are quantified may affect the interpretation of disturbance response.« less
  4. 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.
  5. Improving high-resolution (meter-scale) mapping of snow-covered areas in complex and forested terrains is critical to understanding the responses of species and water systems to climate change. Commercial high-resolution imagery from Planet Labs, Inc. (Planet, San Francisco, CA, USA) can be used in environmental science, as it has both high spatial (0.7–3.0 m) and temporal (1–2 day) resolution. Deriving snow-covered areas from Planet imagery using traditional radiometric techniques have limitations due to the lack of a shortwave infrared band that is needed to fully exploit the difference in reflectance to discriminate between snow and clouds. However, recent work demonstrated that snow cover area (SCA) can be successfully mapped using only the PlanetScope 4-band (Red, Green, Blue and NIR) reflectance products and a machine learning (ML) approach based on convolutional neural networks (CNN). To evaluate how additional features improve the existing model performance, we: (1) build on previous work to augment a CNN model with additional input data including vegetation metrics (Normalized Difference Vegetation Index) and DEM-derived metrics (elevation, slope and aspect) to improve SCA mapping in forested and open terrain, (2) evaluate the model performance at two geographically diverse sites (Gunnison, Colorado, USA and Engadin, Switzerland), and (3) evaluate the modelmore »performance over different land-cover types. The best augmented model used the Normalized Difference Vegetation Index (NDVI) along with visible (red, green, and blue) and NIR bands, with an F-score of 0.89 (Gunnison) and 0.93 (Engadin) and was found to be 4% and 2% better than when using canopy height- and terrain-derived measures at Gunnison, respectively. The NDVI-based model improves not only upon the original band-only model’s ability to detect snow in forests, but also across other various land-cover types (gaps and canopy edges). We examined the model’s performance in forested areas using three forest canopy quantification metrics and found that augmented models can better identify snow in canopy edges and open areas but still underpredict snow cover under forest canopies. While the new features improve model performance over band-only options, the models still have challenges identifying the snow under trees in dense forests, with performance varying as a function of the geographic area. The improved high-resolution snow maps in forested environments can support studies involving climate change effects on mountain ecosystems and evaluations of hydrological impacts in snow-dominated river basins.« less