•Mature and old-growth forests are defined by ecology, policy, and values.•Advanced tree age and relative lack of human impact are common determinants.•However, humans have influenced old forest ...structure and process for millennia.•Forest structure metrics are practical and useful criteria.•Mapping older forests across a landscape accurately is not currently possible.
Mature and old-growth forests are valued for biodiversity, carbon sequestration, habitat, hydrologic function, aesthetics, and spirituality, as well as Tribal and Indigenous histories, cultures, and practices. Over the last 500 years, land use change and industrialization have resulted in global declines in the area of older forests (however defined). The goal of this study was to identify concepts and indicators to define mature and old-growth forests across the vegetation types of the United States in order to quantify their abundance and distribution. Defining old growth has been described as a “wicked problem” that involves values, science, and management; requires multiple disciplines; and can be expressed from many contradictory approaches.
The most common approach to defining mature and old-growth forests is to place them in a successional continuum of increases in tree size, biodiversity, habitat niches, and structural diversity with forest age. Time since severe disturbance, including human impact, is often a consideration, although humans have influenced the development of many forests for millennia. The successional framework is less useful in low-productivity or frequently-disturbed forests, or where current structural diversity under fire suppression may not reflect historic or desired future conditions. In order to classify forests into “old” and “not old”, existing structure-based approaches apply minima of one or more structural or compositional criteria. Site productivity and/or plant association is an element of many definitions.
Once defined, estimating the area of mature and old-growth forest presents challenges. The only comprehensive, consistent field data of US forests is the Forest Inventory and Analysis (FIA) network of >140,000 forested plots. While the 0.067 ha sample area of FIA plots limits the number of structural metrics that might be useful and the plot density cannot capture fine-scale spatial heterogeneity, measurements enable a granular application of multiple structural and compositional criteria by vegetation type at broad spatial extents, and the ability to track change consistently over time. Spatial models integrate field and remotely-sensed data to predict the distribution of structural classes at finer spatial grain, but with substantial error in high-resolution estimates. There does not seem to be a readily-available method to map mature and old-growth stands across a landscape with a high degree of accuracy. Identifying mature and old growth forests in a stand management context will likely require additional measurements, adjustments to criteria at local scales, and incorporation of social and traditional knowledge within a consistent definition framework.
Photo credit: Zane Miller, United States Forest Service.
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•Many burned areas (43%) in Yosemite had forest structure predictive of den habitat.•Cover >2 m, 95th p. height, and 25th p. ...height were most predictive of den habitat.•High den habitat probability occurred most often within low-severity burned areas.
One challenge that land managers face in the southern Sierra Nevada is how to balance conservation of fisher (Pekania pennanti) habitat with the reintroduction of fire. The fisher population in the southern Sierra Nevada is of high conservation priority, due to its small population size, genetic isolation, and the risk of habitat loss due to wildfire and fuel reduction activities. It is unknown whether contemporary forests altered by fire suppression can support fisher habitat following the reintroduction of fire. We examined whether patch-scale forest habitat conditions used by fishers in a landscape with limited recent fire (Dinkey study area) also exist in a landscape with restored fire (Yosemite study area). We developed random forest and logistic regression models using lidar-derived forest structure metrics to distinguish reproductive den presence (n = 261) from randomly-generated “available” points (n = 261) within an estimate of the female population home range. The full logistic regression model correctly classified (under cross-validation) 69.5% of observations and the random forest model correctly classified 74.3%. The parsimonious logistic regression model we selected had comparable accuracy to the full model (correctly classified 68.8% of observations) and included the following variables: cover >2 m, 95th percentile height, and 25th percentile height. Partial dependence plots suggest thresholds at which predicted probability of reproductive den presence exceeds 50%: cover >2 m greater than 60%, 95th percentile height of at least 32 m, and 25th percentile height between 4 m and 14 m. We found that comparable thresholds of forest cover and tree height exist in burned areas in Yosemite; 43.0% of burned pixels had similar lidar-derived forest structural characteristics to those predictive of reproductive dens in Dinkey. Areas with similar forest structures occurred within a range of fire severities and years since the most recent fire, and particularly in low-severity fire conditions (mean differenced normalized burn ratio dNBR value: 128.4). These results are promising for land managers who face the challenge of simultaneously reducing the risk of high-severity fire and conserving fisher habitat, however more research is needed to conclude whether suitable fisher habitat can exist in burned areas at all scales of selection and for all activities of the fisher population.
•Litterfall was measured for 60 months in restoration treatments and forests.•Litterfall components were similar between passive and active restoration.•Litterfall production recovered faster in ...active than in passive restoration.•Litterfall dynamics is a useful indicator of functional recovery and seasonality.
Litterfall is an indicator of ecosystem function and its temporal dynamics can be used to evaluate self-organizing ecosystems on a recovery trajectory following restoration. Few studies have evaluated the recovery trajectories of forest litterfall by simultaneously monitoring forest restoration strategies and reference ecosystems. The general objective of our study was to determine the functional recovery of an abandoned pasture under passive and active restoration, and in secondary (40-year-old) and mature (120-year-old) forest, by analyzing litterfall and its components (leaves, flowers, fruits, woody parts) over a period of five consecutive years. We determined the vegetation structure and tree species composition of these four conditions and compared 1) production of litterfall, leaves, flowers and fruits, 2) leaf litter nutrient inputs (C and N) and, 3) recovery by tree species in leaf litterfall. In five years, litterfall increased from 2.6 to 7.8 Mg ha−1 and from 3.5 to 9.1 Mg ha−1 in the passive and active restoration treatments, respectively, while it increased from 6.0 to 8.6 Mg ha−1 in the secondary forest. In the mature forest, litterfall varied around 10.0 Mg ha−1. The reproductive component increased significantly in restoration (0.3 to 1.5 Mg ha−1) but remained around 0.6 Mg ha−1 in secondary and 1.3 Mg ha−1 in mature forest. Secondary and mature forests both presented correlations to monthly precipitation and maximum and minimum temperatures, indicating strong seasonality. However, litterfall production in the passive and active treatments was continuous throughout the year. Basal area and tree density were higher under active compared to passive restoration. Although the dominant tree species were similar under passive and active restoration, active restoration presented a higher forest species recovery, while the dominance of exotic grass patches persisted under passive restoration. The results suggest that litterfall production can be a useful and accurate indicator with which to evaluate the recovery of ecosystem function, while flower and fruit component can indicate reproductive recovery. Although litterfall production increased rapidly after five years, it did not present a seasonal dynamic. This is probably due to the fact that the species composition still differs from that of the reference systems. Evaluations of cloud forest restoration success should therefore include temporal assessments of vegetation structure and biodiversity recovery in relation to the reference forests in order to establish additional restoration techniques, particularly in the case of passive restoration strategies.
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•Usnea longissima declined in all old sites, with an overall decline of 42% in 37 yr.•The total extinction rate was 0.81, with higher stochastic than deterministic extinction.•The ...lichen was strongly dispersal-limited, with a median effective dispersal of 3.8 m.•The decline was likely driven by air pollution, climate change and denser forests.•The long-term survival of Usnea longissima may be at risk even in protected forests.
Long-term data on spatial dynamics of epiphytic lichens associated with old-growth forests are fundamental for understanding how environmental factors drive their extinction and colonization in heterogeneous landscapes. This study focuses on Usnea longissima, a flagship species for biodiversity conservation. By using a long-term data set (37 yr.) of U. longissima in old Picea abies forests in Skuleskogen National Park, Sweden, we examined changes in the number of host trees, population size (sum of thallus length), extinction, colonization, dispersal, and distribution in a protected landscape. We surveyed the lichen in 1984–1985 by applying a line transect inventory and a total population inventory and tagged 355 occupied trees with an aluminium plate buried in the ground. We repeated the survey in 2021 using a metal detector and recorded GPS-position of host trees, tree and lichen population characteristics. We also measured the structure and age (tree-ring data) of the forest to understand how disturbance history influenced lichen populations. Usnea longissima occurred on 66 of the tagged trees and we recorded 141 new host trees. The number of host trees decreased with 41.7% and the population size with 41.9%. One third of the decline was caused by deterministic extinction (treefalls) and two thirds by stochastic extinction on standing trees. The probability of stochastic extinction on live trees decreased with population size in logistic regression. The decline in the sites with largest populations (35–87% loss) was more influenced by limited colonization than extinction. Colonization was highest in humid north-facing hillslopes with multi-layered forests driven by gap dynamics. The lichen was strongly dispersal-limited, with a median effective horizontal dispersal of only 3.8 m in 37 yr., explaining its strong dependence of long continuity of forest cover. The populations were clustered and had substantial local turnover, yet with stable distribution at landscape scale. The tree-ring index, growth releases and gap recruitments indicate extensive harvesting ∼ 1860–1900, but without major disturbances during the last 70–80 yr. Instead, the decline of U. longissima was probably driven by air pollution, climate change (autumn/winter mortality and heatwaves) and denser forests. Our findings highlight that the long-term survival of this lichen may be at risk even in forests having a strong level of protection.
•We explored how small scale-food availability, forest structure and landscape heterogeneity influenced habitat use of by roe deer.•Variables of forest structure like canopy openness, trees species ...richness and vertical complexity influenced roe deer habitat use more than small-scale food abundance, and landscape-scale forest matrix variables such as forest-edge density and forest cover.•Lying deadwood reduced roe deer habitat use, possibly due to physical obstruction of movement.•Manipulating local forest structure may provide a means by which to manipulate roe deer habitat use and thus control where damages occur.
Browsing damages to young trees can have lasting impacts on forest structure. Roe deer (Capreolus capreolus), the most common and widespread large herbivore in central Europe, create a vast majority of this damage. To lessen the impact, it is important to understand the relationship between roe deer and the landscape matrix, and which factors such as food availability and cover will drive the use of habitat by roe deer. In this study, we explored how small scale-food availability (5 × 5 m2), forest structure (100 × 100 m2) and landscape heterogeneity (500 m radius) influenced the use of habitat by roe deer in an intensively managed temperate mountainous mixed forest with implemented retention forestry practices. Using camera-trap detections of roe deer from 130 study plots in the southern Black Forest, monitored for 2.5 years, we found that local forest structure had the strongest influence on roe deer habitat use. Contrary to our expectations, landscape features, such as edge density between forest and non-forest, did not affect roe deer detections, probably because overall anthropogenic pressure is high and homogenous throughout our study system. Small-scale food availability also had little influence, which is likely due to widespread availability throughout the study area. Roe deer were also detected less where there were higher amounts of lying deadwood in autumn, indicating that retention forestry methods may have a negative impact on roe deer habitat use. Since forest structure was the strongest driver of roe deer habitat use, this study supports earlier claims that forests may be managed by affecting roe deer habitat use, thereby browsing damage intensity, through manipulation of food availability and cover.
•Wildlife conservation requires an understanding of animal-environment relationships.•We upscaled GEDI LiDAR metrics leveraging continuous Landsat spectral data.•GEDI forest canopy metrics improved ...models for coyotes, red squirrels, and snowshoe hares.•Carnivores and their prey were influenced by other variables, including snow depth.•We provide an example of integrating spaceborne LiDAR to advance animal ecology.
Animal conservation requires understanding animal-habitat relationships. The integration of novel remote sensing platforms such as Light Detection and Ranging (LiDAR) technology has dramatically improved the resolution of insight when evaluating animal-habitat relationships by characterizing forest structure. However, conventional LiDAR collection (e.g., airborne or terrestrial laser scanning) may be limited by small spatial extents and logistical constraints (e.g., budget) associated with sampling. NASA’s Global Ecosystem Dynamics Investigation (GEDI) mission provides an alternative and complement to conventional LiDAR sampling with globally available waveform LiDAR, which is being collected to characterize vertical and horizontal structure of Earth’s forests. Forest carnivores are wide-ranging species occupying forested ecosystems, and are generally associated with vertical and horizontal forest structure for their survival and reproduction. We evaluated patterns in occurrence and habitat use of forest carnivores, which included Pacific martens (Martes caurina), Rocky Mountain red foxes (Vulpes vulpes macroura), and coyotes (Canis latrans) and patterns in occurrence of their prey; American red squirrels (Tamiasciurus hudsonicus) and snowshoe hares (Lepus americanus). Camera trap data were collected during the 2014–2017 winters in the Greater Yellowstone Ecosystem in Wyoming, USA. Our objectives were to (1) combine GEDI samples with multispectral satellite imagery from Landsat 8 to upscale vertical forest structure metrics; (2) assess the relative importance of environmental characteristics influencing occurrence and habitat use of forest-associated predators and prey; and (3) determine if GEDI-derived variables aided our efforts in characterizing animal-environment relationships. We used Random Forest regression models to upscale GEDI samples across our study area and implemented a multi-tiered approach using generalized linear mixed effect models to simultaneously evaluate animal-environment relationships and how GEDI-derived metrics improved the animal-habitat models. GEDI-derived metrics of relative height and foliage height diversity improved our animal-environment models and were among the strongest covariates (effect sizes were 1.3–1.8 times larger than the next closest) in the coyote, red squirrel, and snowshoe hare models. All five species were influenced to some degree by the frequency of rebaiting a camera trap and varying conditions of snow depth. Collectively, our work indicates forest canopy height and complexity variables significantly improved our ability to assess the importance of forest characteristics on forest carnivores and their prey. Indeed, there is an untapped opportunity to enhance animal ecology and conservation planning with continued integration of GEDI information with freely available satellite data to characterize attributes of forest structure across expansive areas.
There is concern in the scientific community and among forest managers about potential reductions in the provisioning of forest ecosystem services due to the loss of tree species diversity. Many ...studies have shown how species diversity influences forest functioning, especially productivity, but the influence of structural diversity, such as tree size heterogeneity, has received much less attention. This study focused on understanding the relationship between stand productivity and several structural characteristics of spruce-fir-beech mountain forest stands in Europe. We used a dataset of 89 long-term plots in spruce-fir-beech forests distributed along the European mountains where the three species, Norway spruce (Picea abies (L.) Karst.), silver fir (Abies alba Mill.) and European beech (Fagus sylvatica L.), represent at least 75% of the basal area. Site-dependent conditions were accounted for in a linear mixed-effect basic model, which related the stand productivity with the morphological, climatic and pedological characteristics. The influence of tree species diversity, tree size heterogeneity, species size dominance, and species overlapping in the size distribution on stand productivity was analysed by adding variables to the basic model one by one and evaluating the change in the Akaike's Information Criterion (AIC). The variables that resulted in significant reductions in the AIC, and that were not correlated with each other, were used to build a model to estimate stand productivity. The model showed that in spruce-fir-beech mixed mountain forests (i) when Norway spruce, silver fir and European beech are evenly present within the size distribution (high evenness) the productivity decreases, (ii) the stand productivity increases when the diameter distribution is skewed to the right (higher numbers of smaller individuals), (iii) the stand productivity increases as the proportion of basal area that is spruce increases, and (iv) stand productivity increases with the variability in diameter. We discuss the implications of our results for the management of spruce-fir-beech mountain forest in Europe and for preserving and increasing the stand productivity of these mixed forests.
Characterization of tropical forest trees has been limited to field-based techniques focused on measurement of diameter of the cylindrical part of the bole, with large uncertainty in measuring large ...trees with irregular shapes, and other size attributes such as total tree height and the crown size. Here, we introduce a methodology to decompose lidar point cloud data into 3D clusters corresponding to individual tree crowns (ITC) that enables the estimation of many biophysical variables of tropical forests such as tree height, crown area, crown volume, and tree number density. The ITC-based approach was tested using airborne high-resolution lidar data collected over the 50-ha Center for Tropical Forest Science (CTFS) plot in the Barro Colorado Island, Panama. The lack of tree height and crown size measurements in the field prohibits the direct validation of the ITC metrics. We assess the reliability of our method by comparing the aboveground biomass (AGB) estimated using ground and lidar individual tree measurements at multiple spatial scales, namely 1ha, 2.25ha, 4ha, and 6.25ha. We examined four different lidar-derived AGB models, with three based on individual tree height, crown volume, and crown area, and one with mean top canopy height (TCH) calculated at the plot level using the lidar canopy height model. Results show that the predictive power of all models based on ITC size and TCH increases with decreasing spatial resolution from 16.9% at 1ha for the worst model to 5.0% at 6.25ha for the best model. The TCH-based model performed slightly better than ITC-based models except at higher spatial scales (~4ha) and when errors due to edge effects associated with tree crowns were reduced. Unlike the TCH models that change regionally depending on forest type and structure allometry, the ITC-based models are derived as a function of individual tree allometry and can be extended globally to all tropical forests. The method for lidar detection of individual crown size overcome some limitations of ground-based inventories such as 1) it is able to access crowns of large trees and 2) it enables the assessment of directional changes in tree density, canopy architecture and forest dynamics over large and inaccessible areas to support robust tropical ecological studies.
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•We extract tropical rain forest individual trees using lidar data.•Our model provides estimates on tree density, tree height, crown area and volume.•Individual tree metrics feed allometric equations to calculate tropical tree biomass.•We calculate the first biomass maps without the need for massive ground measurements•Biomass variability is validated over the 50-ha CTFS plot in Barro Colorado Island.
•We derived 19 structural attributes from 45 northern hardwood-conifer forest plots.•Forest structure varies markedly, despite a shared land use history.•Structural complexity positively correlates ...with carbon storage.•The results will inform management to improve carbon storage.
Elements of forest structure are fundamentally associated with an array of ecosystem services and habitat characteristics. However, forest structure varies, in particular, through interactions with natural and human disturbances. Both variation in structural characteristics and associated relationships with ecosystem service outcomes have been poorly explored in mature, secondary forests redeveloped since 19th century agricultural abandonment in the eastern United States. Our study addressed this uncertainty focusing on carbon storage as an important climate regulation service. We conducted an inventory of 45 plots sharing similar land use history (i) to identify differences in forest structure, and (ii) to investigate links between stand structure and aboveground carbon storage. We derived 19 structural attributes and used these in Agglomerative Hierarchical Clustering (AHC) to categorize structurally different groups. Subsequently, we analyzed carbon density in each cluster and employed a random forest algorithm to derive partial effects of structural attributes on carbon storage.
We found a distinctive disparity in forest structure inferred from two hardwood-dominated and one softwood-dominated clusters. Nine variables (cavity tree density, conifer ratio, foliage height index, gap area, live basal area, species diversity, variation in heights and diameters, and vertical shrub cover) explained significant differences between these clusters. Carbon storage varied markedly, and was highest in the softwood cluster. Structural complexity was overall positively associated with carbon storage, whereas this effect was more distinctive in hardwood compared to softwood-dominated forests. In particular, five variables exhibited a positive (conifer ratio, diameter variation, dead basal area, large live trees, and live basal area), one a negative (live tree density), and two (dead tree density and species diversity) a mixed relationship with carbon storage. Despite only moderate variation in climatic conditions across the investigated plots, we found a strong sensitivity of carbon storage to mean annual temperature. In contrast, annual precipitation and topography had no effect on carbon storage. The link between structural complexity and carbon storage suggests a high potential to actively increase forest carbon density. Based on our findings, a variety of options are available to enhance forest structure, and thus to improve carbon storage in managed forest ecosystems. These include, for instance, increasing the variability in tree dimensions and fostering large live trees which may improve niche complementarity. Increasing structural complexity in managed forest stands may thus improve buffering of potentially negative impacts of climate change on carbon stocks.
•We examined impacts of a hydroelectric dam on igapó forests in the Brazilian Amazon.•Tree species composition changed in distinct ways depending on the topography.•Dominance of a few flood-adapted ...species increased in lower topographies.•Higher topographies showed higher floristic similarity with upland forest.•Assessment of future hydroelectric dams should incorporate downstream impacts.
The monomodal flood pulse of major Amazonian rivers is a seasonal phenomenon that determines ecological and biogeochemical processes in adjacent floodplain forests. River damming transforms the pattern of downstream flood pulses and provides a natural disturbance to which the native biota might be poorly adapted. Severe modifications of the flood pulse were recorded in the Uatumã River after the installation of the Balbina dam, Central Amazonia. Flood pulse regulation increased mortality of flood-adapted species in the black-water floodplain (igapó) forest. No previous studies have investigated impacts of flood pulse regulation on the species composition and forest structure of igapó forests. Therefore, we examined species composition and forest structure of igapó forests along a regulated river in comparison to a pristine tributary, the Abacate River, evaluating soil texture characteristics and flood duration. In order to assess potential encroachment of species less sensitive to flood alteration, we also inventoried adjacent non-flooded upland forest in each river section. A quantitative inventory of all trees with diameter at breast height (DBH) ≥5 cm was carried out in low-igapó, high-igapó and adjacent upland forests, totaling one half-hectare in each river. In both rivers investigated, the clay fraction of the soil was significantly related to tree height. Flood duration was correlated to DBH and basal area, with the largest trees found in low-igapó forests which are exposed to long-term flooding. Species composition, richness and diversity significantly responded to flood duration. Species richness was highest in upland forests and lowest in low-igapó forest. In the pristine river, tree species composition exhibited a turnover of species along the flooding gradient. In the regulated river, flood intensification in the low-igapó forest increased dominance of a few flood-adapted species, which produced floristic dissimilarity to all forest types investigated. On the other hand, high-igapó forest showed higher floristic similarity with upland forest due to flood suppression that contributed to encroachment of species commonly described in secondary upland forests. Our results emphasize the urgent need for Brazilian environmental regulatory agencies to incorporate downstream impacts in the environmental assessments of dam projects in the Amazon Basin.
