Phenological and structural linkages to seasonality inform productivity relationships in the Amazon Rainforest

Atkins, Jeff W.; Agee, Elizabeth

doi:10.1111/nph.15783

Cited by 5 publications

(4 citation statements)

References 15 publications

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“…Additional investigation is necessary to evaluate the consistency of structural patterns within and among disturbance agents. Additionally, we did not consider the effect of cooccurring or compounding disturbances, nor did we investigate important disturbances such as drought, which will increasingly affect larger areas at greater severities over this century (Adams et al 2012, Gutierrez-Velez et al 2014, McDowell and Allen 2015, Clark 2016, Atkins and Agee 2019, Stovall et al 2019, Stovall et al 2019. Finally, our approach did not standardize for time since disturbance, a difficulty given large agentspecific variation in the timing and duration of defoliation and/or tree mortality.…”

Section: Consistency Of Agent-specific Structural Differentiationmentioning

confidence: 99%

Application of multidimensional structural characterization to detect and describe moderate forest disturbance

et al. 2020

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The study of vegetation community and structural change has been central to ecology for over a century, yet the ways in which disturbances reshape the physical structure of forest canopies remain relatively unknown. Moderate severity disturbances affect different canopy strata and plant species, resulting in variable structural outcomes and ecological consequences. Terrestrial lidar (light detection and ranging) offers an unprecedented view of the interior arrangement and distribution of canopy elements, permitting the derivation of multidimensional measures of canopy structure that describe several canopy structural traits (CSTs) with known links to ecosystem function. We used lidar-derived CSTs within a machine learning framework to detect and describe the structural changes that result from various disturbance agents, including moderate severity fire, ice storm damage, age-related senescence, hemlock woolly adelgid, beech bark disease, and chronic acidification. We found that fire and ice storms primarily affected the amount and position of vegetation within canopies, while acidification, senescence, pathogen, and insect infestation altered canopy arrangement and complexity. Only two of the six disturbance agents significantly reduced leaf area, counter to common assumptions regarding many moderate severity disturbances. While findings are limited in their generalizability due to lack of replication among disturbances, they do suggest that the current limitations of standard disturbance detection methods-such as optical-based remote sensing platforms, which are often above-canopy perspectives-limit our ability to understand the full ecological and structural impacts of disturbance, and to evaluate the consistency of structural patterns within and among disturbance agents. A more broadly inclusive definition of ecological disturbance that incorporates multiple aspects of canopy structural change may potentially improve the modeling, detection, and prediction of functional implications of moderate severity disturbance as well as broaden our understanding of the ecological impacts of disturbance.

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Section: Consistency Of Agent-specific Structural Differentiationmentioning

confidence: 99%

Application of multidimensional structural characterization to detect and describe moderate forest disturbance

et al. 2020

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“…Additionally, we did not consider the effect of co-occurring or compounding disturbances, nor did we investigate important disturbances such as drought, which will increasingly affect larger areas at greater severities over this century (Adams et al 2012, Gutierrez-Velez et al 2014, Clark et al 2016, Atkins and Agee 2019, Smith et al 2019, Stovall et al 2019. Finally, our approach did not standardize for time-since-disturbance, a difficulty given large agent-specific variation in the timing and duration of defoliation and/or tree mortality.…”

Section: Application: the Detection Of Moderate Severity Disturbance mentioning

confidence: 99%

Multidimensional Structural Characterization is Required to Detect and Differentiate Among Moderate Disturbance Agents

Atkins¹,

Bond‐Lamberty²,

Fahey³

et al. 2019

Preprint

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The study of vegetation community and structural change has been central to ecology for over a century, yet how disturbances reshape the physical structure of forest canopies remains relatively unknown. Moderate severity disturbance including fire, ice storms, insect and pathogen outbreaks, affects different canopy strata and plant species, which may give rise to variable structural outcomes and ecological consequences. Terrestrial lidar (light detection and ranging) offers an unprecedented view of the interior arrangement and distribution of canopy elements, permitting the derivation of multidimensional measures of canopy structure that describe several canopy structural traits with known linkages to ecosystem functioning. We used lidar-derived canopy structural measured within a machine learning framework to detect and differentiate among various disturbance agents, including moderate severity fire, ice storm damage, age-related senescence, hemlock woolly adelgid, beech bark disease, and chronic acidification. We found that disturbance agents such as fire and ice storms primarily affected the amount and position of vegetation within canopies, while acidification, pathogen and insect infestation, and senescence altered canopy arrangement and complexity. Only two of the six disturbance agents significantly reduced leaf area, indicating that this commonly quantified canopy feature is insufficient to characterize many moderate severity disturbances. Rather, measures of canopy structure, including those that describe multidimensional change, are needed to characterize disturbance at moderate severities because structural changes from these events are spatially and quantitatively variable. Our findings suggest that standard disturbance detection methods, such as optical based remote sensing platforms, may currently be limited in their ability to detect, differentiate, and characterize disturbance. Further, we conclude that a more broadly inclusive definition of ecological disturbance that incorporates multiple aspects of canopy structure change will improve the modeling, detection, and prediction of functional implications of moderate severity disturbance.

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“…Advances in remote sensing, specifically light detection and ranging (LiDAR), have enabled mapping of forest structure and complexity with unprecedented precision, at plot‐level to regional scales (LaRue et al 2020). Ecological applications of LiDAR have broadened our understanding of resource acquisition (Stark et al 2015, Atkins et al 2018 b ), allocation strategies (Stovall et al 2017, 2018 a , b , Stovall and Shugart 2018), use efficiencies (Hardiman et al 2013), drought response (Atkins and Agee 2019, Smith et al 2019, Stovall et al 2019, 2020), productivity (Gough et al 2019), and disturbance history (Fahey et al 2015, Atkins et al 2020). However, recent studies of forest structural complexity either focus on broad, landscape‐ to continental‐scale patterns (LaRue et al 2018, Atkins et al 2018 b , Gough et al 2019, Fahey et al 2019), or are limited to characterizations of stand‐scale phenomena (Hardiman et al 2018, Hickey et al 2019), without fully considering how forest complexity varies at the stand to regional scale in response to ecological gradients.…”

Section: Introductionmentioning

confidence: 99%

Vegetation structural complexity and biodiversity in the Great Smoky Mountains

2021

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Vegetation structural complexity and biodiversity tend to be positively correlated, but understanding of this relationship is limited in part by structural metrics tending to quantify only horizontal or vertical variation, and that do not reflect internal structure. We developed new metrics for quantifying internal vegetation structural complexity using terrestrial LiDAR scanning and applied them to 12 NEON forest plots across an elevational gradient in Great Smoky Mountains National Park, USA. We asked (1) How do our newly developed structure metrics compare to traditional metrics? (2) How does forest structure vary with elevation in a high-biodiversity, high topographic complexity region? (3) How do forest structural metrics vary in the strength of their relationships with vascular plant biodiversity? Our new measures of canopy density (Depth) and structural complexity (σDepth), and their canopy height-normalized counterparts, were sensitive to structural variations and effectively summarized horizontal and vertical dimensions of structural complexity. Forest structure varied widely across plots spanning the elevational range of GRSM, with taller, more structurally complex forests at lower elevation. Vascular plant biodiversity was negatively correlated with elevation and more strongly positively correlated with vegetation structure variables. The strong correlations we observed between canopy structural complexity and biodiversity suggest that structural complexity metrics could be used to assay plant biodiversity over large areas in concert with airborne and spaceborne platforms.

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Phenological and structural linkages to seasonality inform productivity relationships in the Amazon Rainforest

Abstract: This article is a Commentary on Smith et al., 222: 1284–1297.

Cited by 5 publications

References 15 publications

Application of multidimensional structural characterization to detect and describe moderate forest disturbance

Application of multidimensional structural characterization to detect and describe moderate forest disturbance

Multidimensional Structural Characterization is Required to Detect and Differentiate Among Moderate Disturbance Agents

Vegetation structural complexity and biodiversity in the Great Smoky Mountains

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