Canopy Complexity Research Articles

Characterizing the structural complexity of the Earth’s forests with spaceborne lidar

Forest structural complexity is a key element of ecosystem functioning, impacting light environments, nutrient cycling, biodiversity, and habitat quality. Addressing the need for a comprehensive global assessment of actual forest structural complexity, we derive a near-global map of 3D canopy complexity using data from the GEDI spaceborne lidar mission. These data show that tropical forests harbor most of the high complexity observations, while less than 20% of temperate forests reached median levels of tropical complexity. Structural complexity in tropical forests is more strongly related to canopy attributes from lower and middle waveform layers, whereas in temperate forests upper and middle layers are more influential. Globally, forests exhibit robust scaling relationships between complexity and canopy height, but these vary geographically and by biome. Our results offer insights into the spatial distribution of forest structural complexity and emphasize the importance of considering biome-specific and fine-scale variations for ecological research and management applications. The GEDI Waveform Structural Complexity Index data product, derived from our analyses, provides researchers and conservationists with a single, easily interpretable metric by combining various aspects of canopy structure.

Relationship between Height and Exposure in Multispectral Vegetation Index Response and Product Characteristics in a Traditional Olive Orchard.

The present research had two aims. The first was to evaluate the effect of height and exposure on the vegetative response of olive canopies' vertical axis studied through a multispectral sensor and on the qualitative and quantitative product characteristics. The second was to examine the relationship between multispectral data and productive characteristics. Six olive plants were sampled, and their canopy's vertical axis was subdivided into four sectors based on two heights (Top and Low) and two exposures (West and East). A ground-vehicle-mounted multispectral proximal sensor (OptRx from AgLeader®) was used to investigate the different behaviours of the olive canopy vegetation index (VI) responses in each sector. A selective harvest was performed, in which each plant and sector were harvested separately. Product characterisation was conducted to investigate the response of the products (both olives and oils) in each sector. The results of Tukey's test (p > 0.05) showed a significant effect of height for the VI responses, with the Low sector obtaining higher values than the Top sector. The olive product showed some height and exposure effect, particularly for the olives' dimension and resistance to detachment, which was statistically higher in the upper part of the canopies. The regression studies highlighted some relationships between the VIs and product characteristics, particularly for resistance to detachments (R2 = 0.44-0.63), which can affect harvest management. In conclusion, the results showed the complexity of the olive canopies' response to multispectral data collection, highlighting the need to study the vertical axis to assess the variability of the canopy itself. The relationship between multispectral data and product characteristics must be further investigated.

No evidence for fractal scaling in canopy surfaces across a diverse range of forest types

Abstract Canopy structural complexity is a key emergent property of forest ecosystems that directly relates to their ability to store carbon, cycle water and nutrients, and provide habitat for biodiversity. However, we lack a general framework for quantifying the structural complexity of forest canopies, and it remains to be seen if there are simple rules that explain the huge variation in canopy structure that we observe across the world's forests. A leading candidate for characterizing differences in structural complexity among forest ecosystems are fractal scaling laws, or measures of statistical self‐similarity. If forest canopies were fractal in nature, their structural attributes could be distilled into a single coefficient—their fractal dimension—which could then be used to directly compare structural differences within and across biomes. To test this idea, we used airborne laser scanning (ALS) data acquired across nine landscapes in Australia that span a huge environmental gradient and include everything from dry shrublands, tropical savannas, dense rainforests, to 90 m tall Mountain Ash forests. Using the ALS data, we built high‐resolution 3D canopy height models of each landscape so that we could quantify how closely they followed fractal scaling laws, based on a comprehensive set of fractal dimension estimators. Across all ecosystem types, fractal scaling assumptions were consistently violated, with clear and systematic differences between real‐world forest canopies and simulated fractal surfaces. However, deviations from fractality did vary predictably among sites, with forests in less arid environments, dominated by tall trees with large crowns, exhibiting a higher degree of self‐similarity across scales. Synthesis: Our study conclusively shows that canopy surfaces are not fractal beyond the scale of individual tree crowns. Nevertheless, we still observed ecologically meaningful and generalisable patterns in forest structure across scales, which closely reflect biophysical and physiological constraints on tree size and architecture. These patterns point the way towards a more general framework for characterizing ecological complexity.

Characterizing canopy complexity of natural and restored intertidal oyster reefs (Crassostrea virginica) with a novel laser‐scanning method

The structural complexity of oyster reef canopy plays a major role in promoting biodiversity, balancing the sediment budget, and modulating hydrodynamics in estuarine systems. Although oyster canopy structure is both spatially and temporally heterogeneous, oyster canopies are generally characterized using simple first‐order quantities, like oyster density, which may lack the ability to sufficiently parameterize reef roughness. In this study, a novel laser‐scan approach was used to map the surface of intact reference and restored reefs (restoration age: 1–4 years) during low tide, when the oyster canopy was fully exposed. Measurements were used to estimate hydrodynamically relevant roughness characteristics over the entire reef surface (>140 m2; 0.50 m resolution), providing estimates of the canopy height (hc), standard deviation (), rugosity index (R), and fractal dimension (D). Average canopy heights ranged from 3.6 to 4.9 cm, with canopy height standard deviations between 1.4 and 2.0 cm. Mean rugosity indices and fractal dimensions were relatively low on the youngest (1 year) restored reef (R = 1.28;D = 2.67), with substantial increases observed for more mature reef canopies (4 years:R = 1.56;D = 2.71). Structural complexity was consistently greater on reef margins than in reef interiors. Increases in complexity were linked to restoration age, with older reefs exhibiting more complex oyster canopies. The highest fractal dimension was observed on the intact reference reef, highlighting the importance of sustained reef growth for maintaining higher‐order structural complexity. Results provide spatially explicit surface roughness characterizations for healthy, intertidal oyster reefs, with applications in both restoration science and natural and nature‐based feature design.

Short‐term effects of moderate severity disturbances on forest canopy structure

Abstract Moderate severity disturbances, those that do not result in stand replacement, play an essential role in ecosystem dynamics. Despite the prevalence of moderate severity disturbances and the significant impacts they impose on forest functioning, little is known about their effects on forest canopy structure and how these effects differ over time across a range of disturbance severities and disturbance types. Using longitudinal data from the National Ecological Observatory Network project, we assessed the effects of three moderate severity press disturbances (beech bark disease, hemlock woolly adelgid and emerald ash borer, which are characterized by continuous disturbance and sustained mortality) and three moderate severity pulse disturbances (spring cankerworm moth, spongy moth and ground fire, which are associated with discrete and relatively short mortalities) on temperate forest canopy structure in eastern US. We studied (1) how light detection and ranging (LiDAR)‐derived metrics of canopy structure change in response to disturbance and (2) whether initial canopy complexity offsets impact of disturbances on canopy structure over time. We used a mixed‐effects modelling framework which included a non‐linear term for time to represent changes in canopy structure caused by disturbance, and interactions between time and both disturbance intensity and initial canopy complexity. We discovered that high intensity of both press and pulse disturbances inhibited canopy height growth while low intensity pulse disturbances facilitated it. In addition, high intensity pulse disturbances facilitated increases in the complexity of the canopy over time. Concerning the impact of initial canopy complexity, we found that the initial canopy complexity of disturbed plots altered the effects of moderate disturbances, indicating potential resilience effects. Synthesis. This study used repeated measurements of LiDAR data to examine the effects of moderate disturbances on various dimensions of forest canopy structure, including height, openness, density and complexity. Our study indicates that both press and pulse disturbances can inhibit canopy height growth over time. However, while the impact of press disturbances on other dimensions of canopy structure could not be clearly detected, likely because of compensatory growth, the impact of pulse disturbances over time was more readily apparent using multi‐temporal LiDAR data. Furthermore, our findings suggest that canopy complexity might help to mitigate the impact of moderate disturbances on canopy structures over time. Overall, our research highlights the usefulness of multi‐temporal LiDAR data for assessing the structural changes in forest canopies caused by moderate severity disturbances.

Characterizing riparian vegetation and classifying riparian extent using airborne laser scanning data

Riparian areas are an integral component of the forest hydrologic system. However, systematic management and conservation of riparian vegetation remains a challenge when the extent and nature of riparian vegetation is not easily characterized. Thus, describing riparian vegetation structural attributes and mapping riparian extent is important for stream protection and restoration. This study discriminated riparian and upland vegetation zones in two watersheds on Vancouver Island, Canada, and characterized vegetation attributes ascribed to streamside forest vegetation using fine-scale airborne laser scanning (ALS) data with field-based measurements for controls. Comparison of ALS metrics for riparian and upland vegetation plots indicated metrics of canopy cover, height, and vertical canopy complexity were significantly different. Machine learning was used to model the probability of riparian and upland vegetation zone extent in each watershed and to determine which ALS metrics were the most important for discriminating between these two zones. Separate models were built for each watershed and results indicated that each watershed's model had different ALS metrics that were important for model development, reflecting the different management histories associated with each watershed. Models achieved overall classification accuracies of 65–77% using a 10-fold cross validation. Probability maps were then developed to characterize riparian extent, indicating that the majority of riparian areas in these watersheds were within 20 m of a stream. Additionally, riparian areas were found up to 200 m away from the stream, which is beyond the current provincial regulation widths set for riparian buffers in forested areas in British Columbia, Canada. However, the majority (roughly 75%) of vegetation within existing management buffers was riparian, although this differed by stream classification. We conclude that ALS data provides a potentially useful source of information for determining the characteristics and extent of riparian vegetation.

Airborne laser scanning reveals uniform responses of forest structure to moose (Alces alces) across the boreal forest biome

Abstract The moose Alces alces is the largest herbivore in the boreal forest biome, where it can have dramatic impacts on ecosystem structure and dynamics. Despite the importance of the boreal forest biome in global carbon cycling, the impacts of moose have only been studied in disparate regional exclosure experiments, leading to calls for common analyses across a biome‐wide network of moose exclosures. In this study, we use airborne laser scanning (ALS) to analyse forest canopy responses to moose across 100 paired exclosure‐control experimental plots distributed across the boreal biome, including sites in the United States (Isle Royale), Canada (Quebec, Newfoundland), Norway, Sweden and Finland. We test the hypotheses that canopy height, vertical complexity and above‐ground biomass (AGB) are all reduced by moose and that the impacts vary with moose density, productivity, temperature and pulse disturbances such as logging and insect outbreaks. We find a surprising convergence in forest canopy response to moose. Moose had negative impacts on canopy height, complexity and AGB as expected. The responses of canopy complexity and AGB were consistent across regions and did not vary along environmental gradients. The difference in canopy height between exclosures and open plots was on average 6 cm per year since the start of exclosure treatment (±2.1 SD). This rate increased with temperature, but only when moose density was high. The difference in AGB between moose exclosures and open plots was 0.306 Mg ha−1 year−1 (±0.079). In browsed plots, stand AGB was 32% of that in the exclosures, a difference of 2.09 Mg ha−1. The uniform response allows scaling of the estimate to a biome‐wide impact of moose of the loss of 448 (±115) Tg per year, or 224 Tg of carbon. Synthesis: Analysis of ALS data from distributed exclosure experiments identified a largely uniform response of forest canopies to moose across regions, facilitating scaling of moose impacts across the whole biome. This is an important step towards incorporating the effect of the largest boreal herbivore on the carbon cycling of one of the world's largest terrestrial biomes.

Scale dependency of lidar‐derived forest structural diversity

AbstractLidar‐derived forest structural diversity (FSD) metrics—including measures of forest canopy height, vegetation arrangement, canopy cover (CC), structural complexity and leaf area and density—are increasingly used to describe forest structural characteristics and can be used to infer many ecosystem functions. Despite broad adoption, the importance of spatial resolution (grain and extent) over which these structural metrics are calculated remains largely unconsidered. Often researchers will quantify FSD at the spatial grain size of the process of interest without considering the scale dependency or statistical behaviour of the FSD metric employed.We investigated the appropriate scale of inference for eight lidar‐derived spatial metrics—CC, canopy relief ratio, foliar height diversity, leaf area index, mean and median canopy height, mean outer canopy height, and rugosity (RT)‐‐representing five FSD categories—canopy arrangement, CC, canopy height, leaf area and density, and canopy complexity. Optimal scale was determined using the representative elementary area (REA) concept whereby the REA is the smallest grain size representative of the extent. Structural metrics were calculated at increasing canopy spatial grain (from 5 to 1000 m) from aerial lidar data collected at nine different forested ecosystems including sub‐boreal, broadleaf temperate, needleleaf temperate, dry tropical, woodland and savanna systems, all sites are part of the National Ecological Observatory Network within the conterminous United States. To identify the REA of each FSD metric, we used changepoint analysis via segmented or piecewise regression which identifies significant changepoints for both the magnitude and variance of each metric.We find that using a spatial grain size between 25 and 75 m sufficiently captures the REA of CC, canopy arrangement, canopy leaf area and canopy complexity metrics across multiple forest types and a grain size of 30–150 m captures the REA of canopy height metrics. However, differences were evident among forest types with higher REA necessary to characterize CC in evergreen needleleaf forests, and canopy height in deciduous broadleaved forests.These findings indicate the appropriate range of spatial grain sizes from which inferences can be drawn from this set of FSD metrics, informing the use of lidar‐derived structural metrics for research and management applications.

A major Miocene deepwater mud canopy system: The North Sabah–Pagasa Wedge, northwestern Borneo

Abstract Three-dimensional seismic reflection data, well data, and analogues from areas with extensive shale tectonics indicate that the enigmatic deepwater “shale nappe or thrust sheet” region of northern offshore Sabah, Malaysia, now referred to as the North Sabah–Pagasa Wedge (NSPW), is actually a region of major mobile shale activity characterized by mini-basins and mud pipes, chambers, and volcanoes. A short burst of extensive mud volcano activity produced a submarine mud canopy complex composed of ~50 mud volcano centers (each probably composed of multiple mud volcanoes) that cover individual areas of between 4 and 80 km2. The total area of dense mud canopy development is ~1900 km2. During the middle Miocene, the post-collisional NSPW was composed predominantly of overpressured shales that were loaded by as much as 4 km thickness of clastics in a series of mini-basins. Following mini-basin development, there was a very important phase of mud volcanism, which built extensive mud canopies (coalesced mud flows) and vent complexes. The mud canopies affected deposition of the overlying and interfingering deposits, including late middle to early late Miocene deepwater turbidite sandstones, which are reservoirs in some fields (e.g., Rotan field). The presence of the extensive mud volcanoes indicates very large volumes of gas had to be generated within the NSPW to drive the mud volcanism. The Sabah example is only the second mud canopy system to be described in the literature and is the largest and most complex.

Megaherbivore exclusion led to more complex seagrass canopies and increased biomass and sediment Corg pools in a tropical meadow

In some regions of the Caribbean Sea, seagrasses have been negatively affected by sea turtle overgrazing. Seagrass canopy complexity has declined at a long-term monitoring site in Costa Rica. We deployed megaherbivore exclosures for 13 months and found an increase over time in seagrass cover and maximum canopy height to ~ 75% and 20 cm respectively in the exclosures; while they remained steady in controls at < 25% and ~ 5 cm. Following exclusion, above ground biomass was higher in exclosures (320 ± 58 g DW m-2) compared to controls (171 ± 60 g DW m-2). Leaves were longer and wider in the exclosures (8 ± 5 cm and 0.8 ± 0.2 cm) compared to controls (2 ± 2 cm and 0.5 ± 0.1 cm). Above ground biomass Corg pools in exclosures (1.2 ± 0.2 Mg ha-1) were two-times higher than in controls (0.6 ± 0.2 Mg ha-1). Meanwhile, there was no variation between treatments in seagrass shoot density (1,692 ± 803 shoots m-2), below ground biomass (246 ± 103 g DW m-2) and its Corg pool (0.8 ± 0.4 Mg ha-1). Relative sediment level increased up to 4.4 cm within exclosures revealing a net increase in sediment Corg, while surficial sediment Corg percentage was similar between exclosures and controls. Releasing these meadows from megaherbivore grazing therefore led to a clear increase within exclosures of seagrass cover, canopy complexity, above ground biomass, and Corg pools in above ground biomass and sediment. Our study reveals that the decline in canopy complexity over time at this meadow is linked to megaherbivore grazing and has most likely led to a decrease in blue carbon pools. Excessive megaherbivore grazing at this site could lead to a continued decline or potential loss of the meadow, and seagrass conservation and restoration initiatives should include consideration of trophic dynamics.

A comparison of high-throughput imaging methods for quantifying plant growth traits and estimating above-ground biomass accumulation

Image-based estimation of above-ground biomass accumulation is recognized as the predominant asset of breeding programs for accelerating gains in crop adaptation and productivity. High-throughput phenotyping (HTP) has the potential to greatly facilitate genetic improvements by dissecting morphological traits which can serve as accurate predictors of optically sensed plant biomass. Thus, various high-throughput data acquisition methods have been recently developed to quantify desirable phenotypes from images. Novel insights are essential to provide helpful guidelines to breeders for the optimal selection of phenotyping approaches aimed at estimating plant biomass. In this study, three representative HTP data acquisition methods based on two-dimensional (2D) image analysis, Multi View Stereo (MVS)-Structure from Motion (SfM) three-dimensional (3D)-reconstruction and Structured Light (SL) 3D-scanning were compared for estimating fresh (FAGB) and dry above-ground biomass (DAGB) weight of potted plants at early growth stages. Two crop species with contrasting canopy shapes and architectures, namely maize (Zea mais L.) and tomato (Solanum lycopersicum L.), were used as model plants. First, the performances of each sensing approach were tested in the accurate reproduction of the major phenotypic traits and, secondly, in the reliable fresh/dry AGB estimation from the relevant allometric equations calibrated according multi- (six sampling dates, once a week) and mono-temporal (one sampling date at harvest time) datasets. The overall results demonstrated the effectiveness of the tested methods in reproducing the salient features of canopies with increasing architectural complexity, including plants’ height (R2̅ = 0.98, rRMSE̅ = 7.73 % and AIC̅ = 475.07), shoot area (R2̅ = 0.91, rRMSE̅ = 29.53 % and AIC̅ = 1369.77) and convex hull volume (R2̅ = 0.88, rRMSE̅ = 27.32 % and AIC̅ = 818.19). In this context, the shoot area associated with the age of the plant was found to be the most indicative phenotypic determinant for an accurate estimation of FAGB and DAGB. Accordingly, the greater ability of the 2D image analysis in quantifying canopies of elongated plants characterized by thin organs ensured the best estimates of fresh/dry biomass accumulation in maize (0.98 ≤ R2̅ ≤ 0.99 % and 8.98 % ≤ rRMSE̅ ≤ 16.03 %, considering multi- and mono-temporal calibrated models). Contrariwise, the MVS-SfM 3D-reconstruction of more complex canopies with compact habit was advantageous for the accurate prediction of above-ground DAGB and FAGB dynamics in tomato (R2̅ = 0.99 % and 6.70 % ≤ rRMSE̅ ≤ 15.82 %, considering multi- and mono-temporal calibrated models). These findings provide references to carefully select the best suited HTP data acquisition approach for the accurate estimation of biomass accumulation across plants of different canopy complexity, thereby paving the way to break through current phenotyping bottlenecks in breeding applications for current and future food security.

Scale‐dependent responses of understory vegetation to the physical structure of undisturbed tundra shrub patches

Much of the Arctic is experiencing rapid change in the productivity and recruitment of tall, deciduous shrubs. It is well established that shrub expansion can alter tundra ecosystem composition and function; however, less is known about the degree to which variability in the physical structure of shrub patches might mediate these changes. There is also limited information as to how different physical attributes of shrub patches may covary and how they differ with topography. Here, we address these knowledge gaps by measuring the physical structure, abiotic conditions, and understory plant community composition at sampling plots within undisturbed green alder patches at a taiga–tundra ecotone site in the Northwest Territories, Canada. We found surprisingly few associations between most structural variables and abiotic conditions at the plot scale, with the notable exceptions of canopy complexity and snow depth. Importantly, neither patch structure nor abiotic conditions were associated with the vegetation community at the plot scale when among-patch variation was accounted for. However, among-patch variation in plant community composition was significant and represented a gradient in the richness of tundra specialists and Sphagnum moss abundance. This gradient was strongly associated with mean patch snow depth, which was likely controlled at least in part by mean patch canopy complexity. Overall, natural variability in green alder patch structure had less of an association with abiotic conditions than expected, suggesting future changes in physical structure at undisturbed sites may have limited environmental impact at the plot scale. However, at the patch scale, increases in snow depth, likely related to canopy complexity, were negatively associated with tundra specialist richness, potentially due to phenological limitations associated with shortened growing seasons. In summary, our data suggest emergent properties exist at the patch scale that are not apparent at the plot scale such that plot-scale measurements do not represent variation in understory community composition across the landscape. The results presented here will inform future work addressing spatial variability in shrub impacts on ecosystem function and increase our understanding of understory community variation within alder patch habitats at the taiga–tundra ecotone.

Mechanistically-grounded pathways connect remotely sensed canopy structure to soil respiration

Variation in the soil-to-atmosphere C flux, or soil respiration (Rs), is influenced by a suite of biotic and abiotic factors, including soil temperature, soil moisture, and root biomass. However, whether light detection and ranging (lidar)-derived canopy structure is tied to soil respiration through its simultaneous influence over these drivers is not known. We assessed relationships between measures of above- and belowground vegetation density and complexity, and evaluated whether Rs is linked to remotely sensed canopy structure through pathways mediated by established biotic and abiotic mechanisms. Our results revealed that, at the stand-scale, canopy rugosity–a measure of complexity–and vegetation area index were coupled to soil respiration through their effects on light interception, soil microclimate, and fine root mass density, but this connection was stronger for complexity. Canopy and root complexity were not spatially coupled at the stand-scale, with canopy but not root complexity increasing through stand development. Our findings suggest that remotely sensed canopy complexity could be used to infer spatial variation in Rs, and that this relationship is grounded in known mechanistic pathways. The broad spatial inference of soil respiration via remotely sensed canopy complexity requires multi-site observations of canopy structure and Rs, which is possible given burgeoning open data from ecological networks and satellite remote sensing platforms.

Strahler Ordering Analyses on Branching Coral Canopies: Stylophora pistillata as a Case Study

The three-dimensional structural complexities generated by living sessile organisms, such as trees and branching corals, embrace distinct communities of dwelling organisms, many of which are adapted to specific niches within the structure. Thus, characterizing the build-up rules and the canopy compartments may clarify small-scale biodiversity patterns and rules for canopy constituents. While biodiversity within tree canopies is usually typified by the vertical axis that is delineated by its main compartments (understory, trunk, crown), traditional studies of coral canopy dwelling species are evaluated only by viewing the whole coral head as a single homogeneous geometric structure. Here, we employ the Strahler number of a mathematical tree for the numerical measurements of the coral’s canopy complexity. We use the branching Indo-Pacific coral species Stylophora pistillata as a model case, revealing five compartments in the whole coral canopy volume (Understory, Base, Middle, Up, and Bifurcation nods). Then, the coral’s dwellers’ diel distribution patterns were quantified and analyzed. We observed 114 natal colonies, containing 32 dwelling species (11 sessile), totaling 1019 individuals during day observations, and 1359 at night (1–41 individuals/colony). Biodiversity and abundance associated with Strahler numbers, diel richness, abundance, and patterns for compartmental distributions differed significantly between day/night. These results demonstrate that the coral-canopy Strahler number is an applicable new tool for assessing canopy landscapes and canopy associated species biodiversity, including the canopy-compartmental utilization by mobile organisms during day/night and young/adult behaviors.

On the impact of canopy model complexity on simulated carbon, water, and solar-induced chlorophyll fluorescence fluxes

Abstract. Lack of direct carbon, water, and energy flux observations at global scales makes it difficult to calibrate land surface models (LSMs). The increasing number of remote-sensing-based products provide an alternative way to verify or constrain land models given their global coverage and satisfactory spatial and temporal resolutions. However, these products and LSMs often differ in their assumptions and model setups, for example, the canopy model complexity. The disagreements hamper the fusion of global-scale datasets with LSMs. To evaluate how much the canopy complexity affects predicted canopy fluxes, we simulated and compared the carbon, water, and solar-induced chlorophyll fluorescence (SIF) fluxes using five different canopy complexity setups from a one-layered canopy to a multi-layered canopy with leaf angular distributions. We modeled the canopy fluxes using the recently developed land model by the Climate Modeling Alliance, CliMA Land. Our model results suggested that (1) when using the same model inputs, model-predicted carbon, water, and SIF fluxes were all higher for simpler canopy setups; (2) when accounting for vertical photosynthetic capacity heterogeneity, differences between canopy complexity levels increased compared to the scenario of a uniform canopy; and (3) SIF fluxes modeled with different canopy complexity levels changed with sun-sensor geometry. Given the different modeled canopy fluxes with different canopy complexities, we recommend (1) not misusing parameters inverted with different canopy complexities or assumptions to avoid biases in model outputs and (2) using a complex canopy model with angular distribution and a hyperspectral radiation transfer scheme when linking land processes to remotely sensed spectra.

Postfire treatments alter forest canopy structure up to three decades after fire

We evaluated the effects of postfire management on forest structure in mixed-conifer forests of northeastern Washington, USA. Postfire treatments were harvest-only, harvest combined with planting, planting-only, and postfire prescribed fire. We used aerial light detection and ranging (LiDAR) to measure vertical and horizontal components of postfire forest structure over a period of 2 to 32 years after fires. We compared treated areas to control areas with similar bioclimatic environments and past fire severity. We used niche overlap statistics to quantify distributions of individual forest structure components and PERMANOVA to assess forest structural response to the presence or absence of treatments, past fire severity, time since treatment, and bioclimatic setting. Harvest alone after fire decreased dominant tree height and reduced vertical canopy complexity and the cover of tall trees. Harvest combined with planting increased dominant tree height, vertical complexity, and cover in lower height strata. Planting and prescribed fires showed little difference in forest structure relative to untreated controls. Overall, the burn severity of the initial fire was the strongest influence on postfire structure, and many aspects of vertical and horizontal forest structure showed little difference with increasing time since fire.

Post-fire landscape evaluations in Eastern Washington, USA: Assessing the work of contemporary wildfires

In the western US, wildfires are modifying the structure, composition, and patterns of forested landscapes at rates that far exceed mechanical thinning and prescribed fire treatments. There are conflicting narratives as to whether these wildfires are restoring landscape resilience to future climate and wildfires. To evaluate the landscape-level work of wildfires, we assessed four subwatersheds in eastern Washington, USA that experienced large wildfires in 2014, 2015, or 2017 after more than a century of fire exclusion and extensive timber harvest. We compared pre- and post-fire landscape conditions to an ecoregion-specific historical (HRV) and future range of variation (FRV) based on empirically established reference conditions derived from a large dataset of historical aerial photo imagery. These four wildfires proved to be a blunt restoration tool, moving some attributes towards more climate-adapted conditions and setting others back. Fires reduced canopy cover and decreased overall tree size and canopy complexity, which moved them into, or slightly outside, the FRV ranges. Moderate- and low-severity fire generally shifted closed-canopy forest structure to open-canopy classes. Patches of high-severity fire shifted patterns of forest, woodland, grassland, and shrubland towards or beyond the HRV ranges and within the FRV ranges by increasing the total area and size of non-forest patches. However, large patches of high-severity fire in dry and moist mixed-conifer forests homogenized landscape patterns beyond FRV ranges towards simplified conditions dominated by non-forest vegetation types. Fires realigned and reconnected landscape patterns with the topo-edaphic template in some cases, but pre-existing fragmentation and spatial mismatches were compounded in many others. Patches of large-tree, closed-canopy forest were reduced by high-severity fire, and the potential to restore more climate-adapted large-tree, open-canopy forest was lost. Re-establishing landscape patterns with desired patch sizes of forest, in particular patches with large trees, will take many decades to centuries and may not occur in drier locations or where seed trees are no longer present. While large wildfires burning during extreme fire weather conditions can move some attributes towards HRV and FRV ranges, intentionally planned mechanical and prescribed-fire treatments that are integrated with strategic wildfire response will better prepare and adapt landscapes for future wildfires and climate.

Accelerating the development of structural complexity: lidar analysis supports restoration as a tool in coastal Pacific Northwest forests

A century of land-use changes and intensive plantation-style forestry in the Pacific Northwest have resulted in a substantial deficit of structurally complex late-successional forests, which serve key ecological and social functions. Restoration treatments can theoretically accelerate the development of structural complexity in simplified forest stands, but our understanding of the short-term effects of such treatments on forest structure and gap patterns is still emerging. In this study, we used a bi-temporal airborne lidar dataset to assess short-term (10 years post-treatment) effects of restoration treatments on the structural complexity of forest stands in the Ellsworth Creek Preserve in southwestern Washington. We also compared forest structure and gap patterns between treated stands and existing late-successional areas within the preserve. Restoration treatments in older stands (60- to 80-years old) resulted in a greater increase in the mean and variability of both vertical and horizontal structural complexity and a considerable increase in the density of canopy gaps, indicating accelerated development towards increased structural complexity. Treatments in the younger stands (20- to 30-years old) primarily accelerated the development of vertical canopy complexity. Older treated stands within the preserve will require natural growth in canopy height, increased regeneration density, and filling in and diversification of canopy gaps to reach the structural complexity of late-successional forests in the preserve, but accelerating these developments may require additional restoration-focused treatments. Forest managers in the region should consider restoration treatments as a viable option for improving short-term structural complexity in simplified forest stands. We also encourage long-term management and monitoring plans that continue to address the deficit of late-successional forests in the region.

Fire-derived phosphorus fertilization of African tropical forests

Central African tropical forests face increasing anthropogenic pressures, particularly in the form of deforestation and land-use conversion to agriculture. The long-term effects of this transformation of pristine forests to fallow-based agroecosystems and secondary forests on biogeochemical cycles that drive forest functioning are poorly understood. Here, we show that biomass burning on the African continent results in high phosphorus (P) deposition on an equatorial forest via fire-derived atmospheric emissions. Furthermore, we show that deposition loads increase with forest regrowth age, likely due to increasing canopy complexity, ranging from 0.4 kg P ha−1 yr−1 on agricultural fields to 3.1 kg P ha−1 yr−1 on old secondary forests. In forest systems, canopy wash-off of dry P deposition increases with rainfall amount, highlighting how tropical forest canopies act as dynamic reservoirs for enhanced addition of this essential plant nutrient. Overall, the observed P deposition load at the study site is substantial and demonstrates the importance of canopy trapping as a pathway for nutrient input into forest ecosystems.

Airborne laser scanning reveals increased growth and complexity of boreal forest canopies across a network of ungulate exclosures in Norway

AbstractLarge herbivores are often classed as ecosystem engineers, and when they become scarce or overabundant, this can alter ecosystem states and influence climate forcing potentials. This realization has spurred a call to integrate large herbivores in earth system models. However, we lack a good understanding of their net effects on climate forcing, including carbon and energy exchange. A possible solution to this lies in harmonizing data across the myriad of large herbivore exclosure experiments around the world. This is challenging due to differences in experimental designs and field protocols. We used airborne laser scanning (ALS) to describe the effect of herbivore removal across 43 young boreal forest stands in Norway and found that exclusion caused the canopy height to increase from 1.7 ± 0.2 to 2.5 ± 0.2 m (means ± se), and also causing a marked increase in vertical complexity and above‐ground biomass. We then go on to discuss some of the issues with using ALS; we propose ALS as an approach for studying the effects of multiple large herbivore exclosure experiments simultaneously, and producing area‐based estimates on canopy structure and forest biomass in a cheap, efficient, standardized and reproducible way. We suggest that this is a vital next step towards generating biome‐wide predictions for the effects of large herbivores on forest ecosystem structure which can both inform both local management goals and earth system models.