Local forest structure variability increases resilience to wildfire in dry western U.S. coniferous forests.

A 'resilient' forest endures disturbance and is likely to persist. Resilience to wildfire may arise from feedback between fire behaviour and forest structure in dry forest systems. Frequent fire creates fine-scale variability in forest structure, which may then interrupt fuel continuity and prevent future fires from killing overstorey trees. Testing the generality and scale of this phenomenon is challenging for vast, long-lived forest ecosystems. We quantify forest structural variability and fire severity across >30 years and >1000 wildfires in California's Sierra Nevada. We find that greater variability in forest structure increases resilience by reducing rates of fire-induced tree mortality and that the scale of this effect is local, manifesting at the smallest spatial extent of forest structure tested (90 × 90 m). Resilience of these forests is likely compromised by structural homogenisation from a century of fire suppression, but could be restored with management that increases forest structural variability

Estimating Tropical Forest Structure Using a Terrestrial Lidar

Forest structure comprises numerous quantifiable biometric components and characteristics, which include tree geometry and stand architecture. These structural components are important in the understanding of the past and future trajectories of these biomes. Tropical forests are often considered the most structurally complex and yet least understood of forested ecosystems. New technologies have provided novel avenues for quantifying biometric properties of forested ecosystems, one of which is LIght Detection And Ranging (lidar). This sensor can be deployed on satellite, aircraft, unmanned aerial vehicles, and terrestrial platforms. In this study we examined the efficacy of a terrestrial lidar scanner (TLS) system in a tropical forest to estimate forest structure. Our study was conducted in January 2012 at La Selva, Costa Rica at twenty locations in a predominantly undisturbed forest. At these locations we collected field measured biometric attributes using a variable plot design. We also collected TLS data from the center of each plot. Using this data we developed relative vegetation profiles (RVPs) and calculated a series of parameters including entropy, Fast Fourier Transform (FFT), number of layers and plant area index to develop statistical relationships with field data.We developed statistical models using a series of multiple linear regressions, all of which converged on significant relationships with the strongest relationship being for mean crown depth (r2 = 0.88, p \u3c 0.001, RMSE = 1.04 m). Tree density was found to have the poorest significant relationship (r2 = 0.50, p \u3c 0.01, RMSE = 153.28 n ha-1). We found a significant relationship between basal area and lidar metrics (r2 = 0.75, p \u3c 0.001, RMSE = 3.76 number ha-1). Parameters selected in our models varied, thus indicating the potential relevance of multiple features in canopy profiles and geometry that are related to field-measured structure. Models for biomass estimation included structural canopy variables in addition to height metrics. Our work indicates that vegetation profiles from TLS data can provide useful information on forest structure

Forest-Structure Analysis in the Paraguayan Chaco, combining Sentinel and GEDI data

Tropical forest ecosystems have been identified as one of the most diverse regions in the world. Offering extensive ecosystem services such as climate regulation and rich biodiversity has raised increasing concerns about their future and protection. Latest studies conducted at a global scale have defined Argentina, Brazil, and Paraguay as the countries with the highest rates of deforestation in South America. With an area of about 250 000 km², the Paraguayan Chaco covers about one fourth of the Great American Chaco which spreads out over Argentina, Bolivia and Paraguay. The Paraguayan Chaco comprises not only a great variety of ecosystems such as savannahs, shrublands, grasslands and wetlands but also holds the largest dry forest area on earth. Furthermore, the ecoregion has been acknowledged as an important carbon sink on a global scale. Nevertheless, uninterrupted deforestation activities between 1987 and 2012 resulted in the loss of 27 % of its original cover. The constant expansion of agricultural crops, cattle ranching, and illegal logging have severely fragmented the Paraguayan Chaco transforming the last forest remnants into isolated patches, jeopardizing not only their continuity but also the biodiversity comprised within. In this context, this study focuses on the assessment of the annual forest cover between 2016 and 2020 using Sentinel-1 and -2 on the one hand and estimating forest structure parameters with data from the Global Ecosystem Dynamics Investigation (GEDI) on the other. Annual forest / non-forest masks generated through machine learning algorithms show a continuous annual decrease of the forest cover. Between the years 2016 and 2020 9 % of the natural forest cover was lost, resulting in 12 500 km² (Figure 1a)). Regarding forest structure, more than 7.2 million valid lidar shots have been analysed to determine forest height, vertical Plant-Area-Volume�Density, Foliage-Height-Diversity-Index (FHDI) and Plant-Area-Index (PAI). Preliminary results exhibit that more than 55 % of the forest height is between 3 to 9 meters (Figure 1b)) and heights greater than 15 meters are mainly located in the North-East of the Paraguayan Chaco. Additionally, vegetation density appears to be rather sparse which is described by mean values of total canopy cover (17 %) and PAI (0.44 m²/m²). On the other hand, highest vegetation densities and closed forest canopies are observed in the North and North-East (Chaco Biosphere Reserve) where most of the protected areas and indigenous reserves are located. Overall continuous expansion of the agricultural frontier, illegal logging activities, and the constant demand for natural goods threaten the continuity of the tropical forest. To meet these challenges, there is an urgent need to develop methods and approaches in the field of remote sensing observations. This would simplify the implementation of environmental laws and conservation programs orientated toward protecting the last remnants of natural forest on the continent. Countries with large, forested areas such as Paraguay should be taking advantage of the latest natural resources available to halt and monitor deforestation activities in the country. With upcoming data from GEDI and fusion products of optical and lidar sensors, global forest structure data will improve estimates of above-ground biomass models to better quantify global carbon fluxes, further highlight drastic losses of forests and promote environmental-sound land use

Ancient Amazonian populations left lasting impacts on forest structure

Amazonia contains a vast expanse of contiguous tropical forest and is influential in global carbon and hydrological cycles. Whether ancient Amazonia was highly disturbed or modestly impacted, and how ancient disturbances have shaped current forest ecosystem processes, is still under debate. Amazonian Dark Earths (ADEs), which are anthropic soil types with enriched nutrient levels, are one of the primary lines of evidence for ancient human presence and landscape modifications in settings that mostly lack stone structures and which are today covered by vegetation. We assessed the potential of using moderate spatial resolution optical satellite imagery to predict ADEs across the Amazon Basin. Maximum entropy modeling was used to develop a predictive model using locations of ADEs across the basin and satellite‐derived remotely sensed indices. Amazonian Dark Earth sites were predicted to be primarily along the main rivers and in eastern Amazonia. Amazonian Dark Earth sites, when compared with randomly selected forested sites located within 50 km of ADE sites, were less green canopies (lower normalized difference vegetation index) and had lower canopy water content. This difference was accentuated in two drought years, 2005 and 2010. This is contrary to our expectation that ADE sites would have nutrient‐rich soils that support trees with greener canopies and forests on ADE soils being more resilient to drought. Biomass and tree height were lower on ADE sites in comparison with randomly selected adjacent sites. Our results suggested that ADE‐related ancient human impact on the forest is measurable across the entirety of the 6 million km2 of Amazon Basin using remotely sensed data

Terrestrial Laser Scanning to Detect Liana Impact on Forest Structure

Tropical forests are currently experiencing large-scale structural changes, including an increase in liana abundance and biomass. Higher liana abundance results in reduced tree growth and increased tree mortality, possibly playing an important role in the global carbon cycle. Despite the large amount of data currently available on lianas, there are not many quantitative studies on the influence of lianas on the vertical structure of the forest. We study the potential of terrestrial laser scanning (TLS) in detecting and quantifying changes in forest structure after liana cutting using a small scale removal experiment in two plots (removal plot and non-manipulated control plot) in a secondary forest in Panama. We assess the structural changes by comparing the vertical plant profiles and Canopy Height Models (CHMs) between pre-cut and post-cut scans in the removal plot. We show that TLS is able to detect the local structural changes in all the vertical strata of the plot caused by liana removal. Our study demonstrates the reproducibility of the TLS derived metrics for the same location confirming the applicability of TLS for continuous monitoring of liana removal plots to study the long-term impacts of lianas on forest structure. We therefore recommend to use TLS when implementing new large scale liana removal experiments, as the impact of lianas on forest structure will determine the aboveground competition for light between trees and lianas, which has important implications for the global carbon cycle

Forest floor vegetation in Sweden

In boreal forests, dwarf-shrubs (Vaccinium spp.) often dominate the forest floor and are key-stone species in ecosystems due to their importance for nutrient cycling and as a major food source for herbivores. Forestry affects the vegetation both directly through management and indirectly by altering the forest structure. Forest fertilization with N at the end of the rotation period is a common practice in Swedish boreal forests. Even higher timber production can be achieved if fertilization with multi-nutrient fertilizer is applied early in the rotation period, but the effects on forest floor vegetation have not been studied. The objectives of this thesis were to increase knowledge regarding how 1) intensive fertilization in young forest affects forest floor vegetation; 2) background deposition of N influences the effects of N addition; and 3) to relate observed changes in common species abundances to changes in forest structure. Fertilization decreased the abundance of many common forest plant species while only few species increased (I). Surprisingly, also species known as nitrophilous decreased in abundance. Paper I shows that the decrease in availability of light induced by fertilization is a crucial factor behind this change. Consequently, fertilization reduced both species richness, species diversity and the between site (β) diversity (II). In areas where the background N deposition was low (4 kg ha-1 yr-1), the effects of N addition were larger than in areas with intermediate (16 kg ha-1 yr-1) deposition (III). Key-stone species among the forest floor vegetation of boreal Sweden (e.g. Vaccinium myrtillus) were found to decrease in abundance (IV). These species are strongly dependent on aspects of forest structure, such as forest density and age, and likewise, temporal changes in species abundance coincided with corresponding changes in forest structure (IV). In conclusion, in large parts of Sweden the prevailing forest management is incompatible with a productive forest floor vegetation possessing a high diversity of plant species, and this situation will only be exacerbated by more intensive use of fertilization regimes. To avoid associated cascading effects from the decreased abundance of key-stone species, forestry intensity needs to be relaxed on the landscape level which would likely result in a considerable loss of timber production. Compensation for this loss through intensified forestry on other areas would indicate the need for altered forest zoning

MODERATE SEVERITY DISTURBANCE HAS SIMILAR EFFECTS ON THE PRODUCTION OF THREE FORESTS NESTED WITHIN THE UPPER GREAT LAKES LANDSCAPE

Moderate severity disturbances, which only kill a subset of canopy trees (e.g., via insects, pathogens, and windthrow), are increasingly widespread, and can alter forest structure and production. Whether moderate severity disturbance similarly affects the net primary production (NPP) of different forest stands within inherently heterogeneous landscapes, however, is unknown. We experimentally disturbed three, 2-ha stands varying in forest structure and primary production, reducing stand basal area 38 to 66 % by stem girdling all mature early successional aspen (Populus) and birch (Betula). For nearly a decade, we examined how the forest stands restructured and recovered, and linked post-recovery physical and biological structure with light absorption and wood NPP. Disturbance significantly altered the structure of all stands and prompted a similar decade-long pattern of primary production decline and recovery. All stands exhibited an initial reduction in wood NPP, recovering to, or exceeded pre-disturbance levels within eight years. Following the recovery of wood NPP, more biologically diverse forest canopies with higher leaf area indexes captured more light, and, subsequently, had higher rates of wood NPP. We provide limited support that disturbance may enhance long-term primary production through its effects on canopy structural reorganization. We conclude that, while the forests examined responded similarly to disturbance, improved understanding of different forest ecosystems’ response to disturbance remains critical to informing carbon management decisions across diverse landscape mosaics

Quantitative analysis of the links between forest structure and land surface albedo on a global scale

Forests are critical in regulating climate by altering the Earth's surface albedo. Therefore, there is an urgent need to enhance our knowledge about the effects of forest structure on albedo. Here, we present a global assessment of the links between forest structure and albedo at a 1-km spatial resolution using generalized additive models (GAMs). We used remotely sensed data to obtain variables representing forest structure, including forest density, leaf area index, and tree cover, during the peak growing season in 2005 with pure forest pixels that cover similar to 7% of the Earth's surface. Furthermore, we estimated black-sky albedo at a solar zenith angle of 38 degrees using the most recent collection of the moderate resolution imaging spectroradiometer (MODIS; version 6) at shortwave, near-infrared, and visible spectral regions. In addition, for the first time, we mapped the magnitude of the relationship between forest structure and albedo at each pixel with a 0.5-degree spatial resolution. Our results suggested that forest structure may modulate albedo in most of the sub-biomes. The response of shortwave albedo was always positive to the leaf area index and negative to the tree cover (except for deciduous broadleaf forests in mediterranean and temperate regions), while the response to forest density varied across space in 2005. The spatial map affirmed that the links between forest structure and albedo vary over geographical locations. In sum, our study emphasized the importance of forest structure in the surface albedo regulation. This paper provides the first spatially explicit evidence of the magnitude of relationships between forest structure and albedo on a global scale.Peer reviewe

Estimating forest structure in a tropical forest using field measurements, a synthetic model and discrete return lidar data

Tropical forests are huge reservoirs of terrestrial carbon and are experiencing rapid degradation and deforestation. Understanding forest structure proves vital in accurately estimating both forest biomass and also the natural disturbances and remote sensing is an essential method for quantification of forest properties and structure in the tropics. Our objective is to examine canopy vegetation profiles formulated from discrete return LIght Detection And Ranging (lidar) data and examine their usefulness in estimating forest structural parameters measured during a field campaign. We developed a modeling procedure that utilized hypothetical stand characteristics to examine lidar profiles. In essence, this is a simple method to further enhance shape characteristics from the lidar profile. In this paper we report the results comparing field data collected at La Selva, Costa Rica (10° 26′ N, 83° 59′ W) and forest structure and parameters calculated from vegetation height profiles and forest structural modeling. We developed multiple regression models for each measured forest biometric property using forward stepwise variable selection that used Bayesian information criteria (BIC) as selection criteria. Among measures of forest structure, ranging from tree lateral density, diameter at breast height, and crown geometry, we found strong relationships with lidar canopy vegetation profile parameters. Metrics developed from lidar that were indicators of height of canopy were not significant in estimating plot biomass (p-value = 0.31, r2 = 0.17), but parameters from our synthetic forest model were found to be significant for estimating many of the forest structural properties, such as mean trunk diameter (p-value = 0.004, r2 = 0.51) and tree density (p-value = 0.002, r2 = 0.43). We were also able to develop a significant model relating lidar profiles to basal area (p-value = 0.003, r2 = 0.43). Use of the full lidar profile provided additional avenues for the prediction of field based forest measure parameters. Our synthetic canopy model provides a novel method for examining lidar metrics by developing a look-up table of profiles that determine profile shape, depth, and height. We suggest that the use of metrics indicating canopy height derived from lidar are limited in understanding biomass in a forest with little variation across the landscape and that there are many parameters that may be gleaned by lidar data that inform on forest biometric properties