Forest Structure Patterns Research Articles

Same, but different: similar states of forest structure in temperate mountain regions of Europe despite different social-ecological forest disturbance regimes

ContextEcosystem services provided by mountain forests are critically linked to forest structure. Social-ecological disturbance regimes (i.e., the rate, frequency, and patch size distribution of disturbances driven by interacting natural and anthropogenic processes) and land use affect forest structure, but their specific impacts are not fully understood.ObjectivesWe examine how differences in disturbance regimes affect patterns of forest structure across three European mountain ranges with similar vegetation types but different land-use histories: the European Alps, the Carpathians, and the Caucasus.MethodsWe related data on horizontal and vertical forest structure, measured by spaceborne lidar (GEDI), with Landsat-derived information on forest disturbances (1986–2020) and topographic, climatic, and anthropogenic predictors.ResultsWe found similar social-ecological disturbance regimes in the Alps and Carpathians (average annual disturbance rates of 0.34% and 0.39%, respectively, and median patch size < 0.5 ha), yet much lower disturbance rates and patch sizes in the Caucasus (0.08% yr−1 and < 0.2 ha). Despite different disturbance regimes, we found similar patterns of forest structure. Two alternative states emerged consistently across all mountain ranges: a tall and closed-canopy state in 74–80% of forests and a low and open-canopy state (< 50% canopy cover) in the rest. While forest structure responded consistently to abiotic drivers such as topography and climate, its association with anthropogenic pressures differed between mountain ranges. Stand-replacing disturbances played an important role in the Carpathians, while forest structure in the Caucasus was related to proximity to settlements, reflecting local forest use.ConclusionsDifferent social-ecological contexts in mountain regions can produce markedly different forest disturbance regimes. Despite these differences, similar states of forest structures emerge, suggesting strong attractors of structure in temperate mountain forests.

Simulating long-term wildfire impacts on boreal forest structure in Central Yakutia, Siberia, since the Last Glacial Maximum

BackgroundWildfires are recognized as an important ecological component of larch-dominated boreal forests in eastern Siberia. However, long-term fire-vegetation dynamics in this unique environment are poorly understood. Recent paleoecological research suggests that intensifying fire regimes may induce millennial-scale shifts in forest structure and composition. This may, in turn, result in positive feedback on intensifying wildfires and permafrost degradation, apart from threatening human livelihoods. Most common fire-vegetation models do not explicitly include detailed individual-based tree population dynamics, but a focus on patterns of forest structure emerging from interactions among individual trees may provide a beneficial perspective on the impacts of changing fire regimes in eastern Siberia. To simulate these impacts on forest structure at millennial timescales, we apply the individual-based, spatially explicit vegetation model LAVESI-FIRE, expanded with a new fire module. Satellite-based fire observations along with fieldwork data were used to inform the implementation of wildfire occurrence and adjust model parameters.ResultsSimulations of annual forest development and wildfire activity at a study site in the Republic of Sakha (Yakutia) since the Last Glacial Maximum (c. 20,000 years BP) highlight the variable impacts of fire regimes on forest structure throughout time. Modeled annual fire probability and subsequent burned area in the Holocene compare well with a local reconstruction of charcoal influx in lake sediments. Wildfires can be followed by different forest regeneration pathways, depending on fire frequency and intensity and the pre-fire forest conditions. We find that medium-intensity wildfires at fire return intervals of 50 years or more benefit the dominance of fire-resisting Dahurian larch (Larix gmelinii (Rupr.) Rupr.), while stand-replacing fires tend to enable the establishment of evergreen conifers. Apart from post-fire mortality, wildfires modulate forest development mainly through competition effects and a reduction of the model’s litter layer.ConclusionWith its fine-scale population dynamics, LAVESI-FIRE can serve as a highly localized, spatially explicit tool to understand the long-term impacts of boreal wildfires on forest structure and to better constrain interpretations of paleoecological reconstructions of fire activity.

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.

Human impact on forests in early twentieth century Finland

ContextIn northern Europe, changes in forest ecosystem structures are commonly attributed to the ubiquitous impact of modern forestry. However, the starting point for modern forestry was not a pristine forest, but landscapes influenced for centuries by diverse human activities.ObjectivesOur aims were to (1) describe spatial patterns of forest structure and species compositions over large scales in 1920s Finland, and to (2) analyze how these characteristics were influenced by human population and past land-uses.MethodsWe mapped ca. 3000 systematic sample plots measured in the first Finnish National Forest Inventory (1921–1924) and produced a series of maps of large-scale variation in forest characteristics in upland forests. We analyzed forest age and size structures, and species compositions relative to human population and land-use data.ResultsWe found strong geographical and regional gradients in forest age and size structures, and tree species composition. Depending on the variable, these characteristics were at the stand-level best explained by human population density, reflecting the long history of various forest uses. Tree species composition was clearly associated with site productivity, but also with the history of slash-and-burn agriculture and forest grazing.ConclusionsForest landscapes in the early twentieth century Finland exhibited a strong human fingerprint, visible as the abundance of young forests in populated areas, while in remote areas forest characteristics typical of natural forests prevailed. These gradients in human impact a century ago are still reflected as legacies in forest structure, a situation that needs consideration in management and restoration.

Spatial heterogeneity of global forest aboveground carbon stocks and fluxes constrained by spaceborne lidar data and mechanistic modeling.

Forest carbon is a large and uncertain component of the global carbon cycle. An important source of complexity is the spatial heterogeneity of vegetation vertical structure and extent, which results from variations in climate, soils, and disturbances and influences both contemporary carbon stocks and fluxes. Recent advances in remote sensing and ecosystem modeling have the potential to significantly improve the characterization of vegetation structure and its resulting influence on carbon. Here, we used novel remote sensing observations of tree canopy height collected by two NASA spaceborne lidar missions, Global Ecosystem Dynamics Investigation and ICE, Cloud, and Land Elevation Satellite 2, together with a newly developed global Ecosystem Demography model (v3.0) to characterize the spatial heterogeneity of global forest structure and quantify the corresponding implications for forest carbon stocks and fluxes. Multiple-scale evaluations suggested favorable results relative to other estimates including field inventory, remote sensing-based products, and national statistics. However, this approach utilized several orders of magnitude more data (3.77 billion lidar samples) on vegetation structure than used previously and enabled a qualitative increase in the spatial resolution of model estimates achievable (0.25° to 0.01°). At this resolution, process-based models are now able to capture detailed spatial patterns of forest structure previously unattainable, including patterns of natural and anthropogenic disturbance and recovery. Through the novel integration of new remote sensing data and ecosystem modeling, this study bridges the gap between existing empirically based remote sensing approaches and process-based modeling approaches. This study more generally demonstrates the promising value of spaceborne lidar observations for advancing carbon modeling at a global scale.

The Latent Dirichlet Allocation model applied to airborne LiDAR data: A case study on mapping forest degradation associated with fragmentation and fire in the Amazon region

Abstract LiDAR data are being increasingly used to provide a detailed characterization of the vertical profile of forests. This characterization enables the generation of new insights on the influence of environmental drivers and anthropogenic disturbances on forest structure as well as on how forest structure influences important ecosystem functions and services. Unfortunately, extracting information from LiDAR data in a way that enables the spatial visualization of forest structure, as well as its temporal changes, is challenging due to the high dimensionality of these data. We show how the Latent Dirichlet Allocation model applied to LiDAR data (LidarLDA) can be used to identify forest structural types and how the relative abundance of these forest types changes throughout the landscape. The code to fit this model is made available through the open‐source r package LidarLDA in github. We illustrate the use of LidarLDA both with simulated data and data from a large‐scale fire experiment in the Brazilian Amazon region. Using simulated data, we demonstrate that LidarLDA accurately identifies the number of forest types as well as their spatial distribution and absorptance probabilities. For the empirical data, we found that LidarLDA detects both landscape‐level patterns in forest structure as well as the strong interacting effect of fire and forest fragmentation on forest structure based on the experimental fire plots. More specifically, LidarLDA reveals that proximity to forest edge exacerbates the impact of fires, and that burned forests remain structurally different from unburned areas for at least 7 years, even when burned only once. Importantly, LidarLDA generates insights on the 3D structure of forest that cannot be obtained using more standard approaches that just focus on top‐of‐the‐canopy information (e.g. canopy height models based on LiDAR data). By enabling the mapping of forest structure and its temporal changes, we believe that LidarLDA will be of broad utility to the ecological research community.

Three-dimensional estimation of deciduous forest canopy structure and leaf area using multi-directional, leaf-on and leaf-off airborne lidar data

Airborne laser scanning (ALS) has been widely used to map gap probability and leaf area index (LAI) distribution at plot and landscape scales. As an indirect measurement, most ALS methods to estimate LAI combine waveform or point density information with supporting field measurements such as the leaf angle distribution, gap probability, or direct LAI measures. The development of a more independent estimation approach would facilitate more widespread use of existing ALS data to investigate patterns of forest structure and build realistic 3-D vegetation scenes to simulate remote sensing imagery and energy balance. Here, we develop a data processing workflow (named PVlad) using ALS point cloud apparent reflectance to estimate LAI and voxel-based leaf area density (LAD), aiming to reduce the need for associated field measurements such as the gap probability. The adaptation of the path volume (PV) concept derived from apparent reflectance integrates information from multi-directional ALS pulses, and quantifies the percentage exploration of each voxel for classification and occlusion correction, such that rigorous volumetric sampling approaches can be developed to derive LAI and LAD. The PVlad workflow was applied to discrete-return lidar data (Riegl VQ480i) acquired by NASA Goddard's LiDAR, Hyperspectral and Thermal Imager (G-LiHT) Airborne Imager during leaf-on (summer) and leaf-off (spring) conditions at the Smithsonian Environmental Research Center (SERC). The estimates of LAI and LAD captured structural differences between mature, logged, and intermediate-aged stands over eight deciduous forest plots. The derived LAI values were compared to field litter collection measurements, and the derived LAD vertical distribution was compared to the output of the VoxLAD model using terrestrial laser scan (TLS) field survey data. Using voxel sizes ranging from 0.5 m to 5 m, overall LAI estimation showed linear fitting coefficient bias <0.035 and RMSE<0.5m2/m2 for 1 and 2 m voxel sizes, and vertical LAD distribution showed strong correlation with R≈0.9 and RMSE≈0.028m2/m3 for 0.5 and 1m voxel sizes. For every forest stand, upper-canopy LAD had a low variance for voxel sizes of ≤ 2m. Application of PVlad to the G-LiHT and other similar ALS data archives enables the development of fine-resolution LAI map products, including voxelization of LAD for ecosystem science and radiative transfer simulations of remote sensing imagery or surface energy balance.

Dynamics of Natural Regeneration: Implications for Landscape Restoration in the Atlantic Forest, Brazil

This study aimed to understand post-agricultural natural forest regeneration in the Southern Brazilian Atlantic Forest and its possible role as a cost-effective, passive approach to forest restoration. The study characterized vegetation structure, floristic composition, and the dynamics of secondary forest chronosequences. Data were collected from 159 plots (10 × 10 m each) across forest remnants in Santa Catarina State, covering forest ages that ranged from 2 to 60 years of regeneration after swidden agriculture. Only areas with no signs of degradation were sampled in order to provide a description of vegetation characteristics that could be used to identify and monitor natural regeneration. A total of 11,455 woody plants were identified and classified into 334 species representing 71 families. As the succession process unfolds, the continuous turnover of species makes forests more diverse and structurally complex. Floristic similarity among forest types is observed during the early stages of succession, but decreases over time. Pioneer species dominate young secondary forests, representing about 40% of the basal area up to 10 years of regeneration. Shade-tolerant species start colonizing the sites at early ages; however, they become more important structural elements only after 30 years of succession. The observed patterns of forest structure and species diversity largely conform to the post-agricultural succession seen in many tropical forests. The high species diversity found in this study highlights the importance of natural regeneration as a strategy to restore ecosystems. Floristic data can be used as a reference for choosing suitable species for active restoration, as well as contributing to the design of integrated restoration strategies. We herein reinforce the potential of natural regeneration as part of large-scale restoration programs, which would be particularly attractive to family farmers by the low cost of supplies and labor.

Macroecological patterns of forest structure and allometric scaling in mangrove forests

AbstractAimMangrove wetlands span broad geographical gradients, resulting in functionally diverse tree communities. We asked whether latitudinal variation, allometric scaling relationships and species composition influence mangrove forest structure and biomass allocation across biogeographical regions and distinct coastal morphologies.LocationGlobal.Time periodPresent.Major taxa studiedMangrove ecosystems.MethodsWe built the largest field‐based dataset on mangrove forest structure and biomass to date (c. 2,800 plots from 67 countries) to address macroecological questions pertaining to structural and functional diversity of mangroves spanning biogeographical and coastal morphology gradients. We used frequentist inference statistics and machine learning models to determine environmental drivers that control biomass allocation within and across mangrove communities globally.ResultsAllometric scaling relationships and forest structural complexity were consistent across biogeographical and coastal morphology gradients, suggesting that mangrove biomass is controlled by regional forcings rather than by latitude or species composition. For instance, nearly 40% of the global variation in biomass was explained by regional climate and hydroperiod, revealing nonlinear thresholds that control biomass accumulation across broad geographical gradients. Furthermore, we found that ecosystem‐level carbon stocks (average 401 ± 48 MgC/ha, covering biomass and the top 1 m of soil) varied little across diverse coastal morphologies, reflecting regional bottom‐up geomorphic controls that shape global patterns in mangrove biomass apportioning.Main conclusionsOur findings reconcile views of wetland and terrestrial forest macroecology. Similarities in stand structural complexity and cross‐site size–density relationships across multiscale environmental gradients show that resource allocation in mangrove ecosystems is independent of tree size and invariant to species composition or latitude. Mangroves follow a universal fractal‐based scaling relationship that describes biomass allocation for several other terrestrial tree‐dominated communities. Understanding how mangroves adhere to these universal allometric rules can improve our ability to account for biomass apportioning and carbon stocks in response to broad geographical gradients.

Big trees drive forest structure patterns across a lowland Amazon regrowth gradient

Degraded Amazonian forests can take decades to recover and the ecological results of natural regeneration are still uncertain. Here we use field data collected across 15 lowland Amazon smallholder properties to examine the relationships between forest structure, mammal diversity, regrowth type, regrowth age, topography and hydrology. Forest structure was quantified together with mammal diversity in 30 paired regrowth-control plots. Forest regrowth stage was classified into three groups: late second-regrowth, early second-regrowth and abandoned pasture. Basal area in regrowth plots remained less than half that recorded in control plots even after 20–25 years. Although basal area did increase in sequence from pasture, early to late-regrowth plots, there was a significant decline in basal area of late-regrowth control plots associated with a decline in the proportion of large trees. Variation in different forest structure responses was explained by contrasting variables, with the proportion of small trees (DBH < 20 cm) most strongly explained by topography (altitude and slope) whereas the proportion of large trees (DBH > 60 cm) was explained by plot type (control vs. regrowth) and regrowth class. These findings support calls for increased efforts to actively conserve large trees to avoid retrogressive succession around edges of degraded Amazon forests.

Spatial patterns of vegetation structure and structural diversity across edges between forested wetlands and upland forest in Atlantic Canada

Forested wetlands are an integral but understudied part of heterogeneous landscapes in Atlantic Canada, although they are known to provide habitat for species at risk. Our objectives were to explore patterns of forest structure across edges between forested wetland and upland forest, to locate changes in vegetation structure and to assess multivariate relationships in vegetation structure. Our study sites were in temperate (Acadian) forested wetland landscapes. We sampled trees and recorded canopy cover every 20 m along 120-m-long transects. We estimated the cover of trees, saplings, shrubs in three height classes, Sphagnum, other bryophytes, lichens, graminoids, ferns, and forbs in contiguous 1 m × 1 m quadrats. We calculated structural diversity using the Shannon index and used wavelet analysis to assess spatial patterns. We found few clear patterns except for lower tree structural diversity at the edge of forested wetlands. Structural diversity was not a reliable measure for distinguishing forested wetland from upland forest. Forested wetlands are an integral part of many forested landscapes in Atlantic Canada, but their detection and differentiation from surrounding ecosystems can be difficult. Policy should err on the side of caution when mapping forested wetlands and include them in wetland protection.

Global patterns and climatic controls of forest structural complexity

The complexity of forest structures plays a crucial role in regulating forest ecosystem functions and strongly influences biodiversity. Yet, knowledge of the global patterns and determinants of forest structural complexity remains scarce. Using a stand structural complexity index based on terrestrial laser scanning, we quantify the structural complexity of boreal, temperate, subtropical and tropical primary forests. We find that the global variation of forest structural complexity is largely explained by annual precipitation and precipitation seasonality (R² = 0.89). Using the structural complexity of primary forests as benchmark, we model the potential structural complexity across biomes and present a global map of the potential structural complexity of the earth´s forest ecoregions. Our analyses reveal distinct latitudinal patterns of forest structure and show that hotspots of high structural complexity coincide with hotspots of plant diversity. Considering the mechanistic underpinnings of forest structural complexity, our results suggest spatially contrasting changes of forest structure with climate change within and across biomes.

Ownership Patterns Drive Multi-Scale Forest Structure Patterns across a Forested Region in Southern Coastal Oregon, USA

Research Highlights: We used airborne lidar to assess the multi-scalar patterns of forest structure across a large (471,000 hectare), multi-owner landscape of the Oregon Coast Range, USA. The results of this study can be used in the development and evaluation of conservation strategies focused on forest management. Background and Objectives: Human management practices reflect policy and economic decisions and shape forest structure through direct management and modification of disturbance regimes. Previous studies have found that land ownership affects forest cover, patch dynamics, structure, and ecosystem function and services. However, prior assessments of forest structure across landscapes and ownerships have been limited by a lack of high-fidelity forest structure measurements across a large spatial extent. We addressed three research questions: (1) What distinct classes of forest structure exist across our study area? (2) How does the distribution and pattern of forest structure vary among types of owners at scales of patches, ownership types, and subregion, and is this independent of property size? and (3) What implications do the fine and sub-regional scale patterns have for landscape configuration goals under recent updates to the Northwest Forest Plan? Materials and Methods: We examined forest structure patterns by identifying six statistically distinct classes of forest structure and then examining their distribution across and within ownership types. We used these structure classes to examine their area within each ownership class, mean patch size, and intermixing at multiple scales. Results and Conclusion: We found that the six different forest structure classes in the study area can be interpreted as two assemblages: production-style forests, principally on private lands, and structurally complex forests, principally on public lands. We found that land ownership objectives resulted in distinct landscape patterns of forest structure as measured by mean structure class patch size and intermixing of different structure class patches. Finally, we found that forest structure differed between public and private lands but differed comparatively little among ownership types within those two broad categories.

Mid-term (2009-2019) demographic dynamics of young beech forest in Albongbunji Basin, Ulleungdo, South Korea

BackgroundThe stem exclusion stage is a stage of forest development that is important for understanding the subsequent understory reinitiation stage and maturation stage during which horizontal heterogeneity is formed. Over the past 11 years (2009–2019), we observed a deciduous broad-leaved forest in the Albongbunji Basin in Ulleungdo, South Korea in its stem exclusion stage, where Fagus engleriana (Engler’s beech) is the dominant species, thereby analyzing the changes in the structure (density and size distributions), function (biomass and species richness), and demographics.ResultsThe mean stem density data presented a bell-shaped curve with initially increasing, peaking, and subsequently decreasing trends in stem density over time, and the mean biomass data showed a sigmoidal pattern indicating that the rate of biomass accumulation slowed over time. Changes in the density and biomass of Fagus engleriana showed a similar trend to the changes in density and biomass at the community level, which is indicative of the strong influence of this species on the changing patterns of forest structure and function. Around 2015, a shift between recruitment and mortality rates was observed. Deterministic processes were the predominant cause of tree mortality in our study; however, soil deposition that began in 2017 in some of the quadrats resulted in an increase in the contribution of stochastic processes (15% in 2019) to tree mortality. The development of horizontal heterogeneity was observed in forest gaps.ConclusionsOur observations showed a dramatic shift between the recruitment and mortality rates in the stem exclusion stage, and that disturbance increases the uncertainty in forest development increases. The minor changes in species composition are likely linked to regional species pool and the limited role of the life-history strategy of species such as shade tolerance and habitat affinity. Our midterm records of ecological succession exhibited detailed demographic dynamics and contributed to the improvement of an ecological perspective in the stem exclusion stage.

FLiES-SIF version 1.0: three-dimensional radiative transfer model for estimating solar induced fluorescence

Abstract. Global terrestrial ecosystems control the atmospheric CO2 concentration through gross primary production (GPP) and ecosystem respiration processes. Chlorophyll fluorescence is one of the energy release pathways of excess incident light in the photosynthetic process. Over the last 10 years, extensive studies have revealed that canopy-scale Sun-induced chlorophyll fluorescence (SIF), which potentially provides a direct pathway to link leaf-level photosynthesis to global GPP, can be observed from satellites. SIF is used to infer photosynthetic capacity of plant canopy; however, it is not clear how the leaf-level SIF emission contributes to the top-of-canopy directional SIF. Plant canopy radiative transfer models are useful tools to understand the mechanism of anisotropic light interactions such as scattering and absorption in plant canopies. One-dimensional (1-D) plane-parallel layer models (e.g., the Soil Canopy Observation, Photochemistry and Energy fluxes (SCOPE) model) have been widely used and are useful to understand the general mechanisms behind the temporal and seasonal variations in SIF. However, a 1-D model does not explain the complexity of the actual canopy structures. Three-dimensional models (3-D) have a potential to delineate the realistic directional canopy SIFs. Forest Light Environmental Simulator for SIF (FLiES-SIF) version 1.0 is a 3-D Monte Carlo plant canopy radiative transfer model to understand the biological and physical mechanisms behind the SIF emission from complex forest canopies. The FLiES-SIF model is coupled with leaf-level fluorescence and a physiology module so that users are able to simulate how the changes in environmental and leaf traits as well as canopy structure affect the observed SIF at the top of the canopy. The FLiES-SIF model was designed as three-dimensional model, yet the entire modules are computationally efficient: FLiES-SIF can be easily run by moderate-level personal computers with lower memory demands and public software. In this model description paper, we focused on the model formulation and simulation schemes, and showed some sensitivity analysis against several major variables such as view angle and leaf area index (LAI). The simulation results show that SIF increases with LAI then saturated at LAI&gt;2–4 depending on the spectral wavelength. The sensitivity analysis also shows that simulated SIF radiation may decrease with LAI at a higher LAI domain (LAI&gt;5). These phenomena are seen in certain Sun and view angle conditions. This type of nonlinear and nonmonotonic SIF behavior towards LAI is also related to spatial forest structure patterns. FLiES-SIF version 1.0 can be used to quantify the canopy SIF in various view angles including the contribution of multiple scattering which is the important component in the near-infrared domain. The potential use of the model is to standardize the satellite SIF by correcting the bidirectional effect. This step will contribute to the improvement of the GPP estimation accuracy through SIF.

Characterizing over Four Decades of Forest Disturbance in Minnesota, USA

Spatial information about disturbance driven patterns of forest structure and ages across landscapes provide a valuable resource for all land management efforts including cross-ownership collaborative forest treatments and restoration. While disturbance events in general are known to impact stand characteristics, the agent of change may also influence recovery and the supply of ecosystem services. Our study utilizes the full extent of the Landsat archive to identify the timing, extent, magnitude, and agent, of the most recent fast disturbance event for all forested lands within Minnesota, USA. To account for the differences in the Landsat sensors through time, specifically the coarser spatial, spectral, and radiometric resolutions of the early MSS sensors, we employed a two-step approach, first harmonizing spectral indices across the Landsat sensors, then applying a segmentation algorithm to fit temporal trends to the time series to identify abrupt forest disturbance events. We further incorporated spectral, topographic, and land protection information in our classification of the agent of change for all disturbance patches. After allowing two years for the time series to stabilize, we were able to identify the most recent fast disturbance events across Minnesota from 1974–2018 with a change versus no-change validation accuracy of 97.2% ± 1.9%, and higher omission (14.9% ± 9.3%) than commission errors (1.6% ± 1.9%) for the identification of change patches. Our classification of the agent of change exhibited an overall accuracy of 96.5% ± 1.9% with classes including non-disturbed forest, land conversion, fire, flooding, harvest, wind/weather, and other rare natural events. Individual class errors varied, but all class user and producer accuracies were above 78%. The unmatched nature of the Landsat archive for providing comparable forest attribute and change information across more than four decades highlights the value of the totality of the Landsat program to the larger geospatial, ecological research, and forest management communities.

Regional variation in interior Alaskan boreal forests is driven by fire disturbance, topography, and climate

AbstractHigh latitude regions are warming rapidly with important ecological and societal consequences. Utilizing two landscape‐scale data sets from interior Alaska, we compared patterns in forest structure in two regions with differing fire disturbance, topography, and summer climate norms. Our goal was to evaluate a set of hypotheses concerning possible warming‐driven changes in forest structure suggested by recent literature. We found essentially consistent habitat associations for the tree flora across two disparate study areas concomitant with considerable differences in observed patterns of forest structure and composition. Our results confirmed expected increases in broadleaved species occupancy and abundance in the warmer, more fire‐affected study region along with considerably higher tree occupancy and abundance in high elevation areas there. However, contrary to our predictions, we found no evidence of expected reductions in conifer occupancy or increases in non‐fire related tree mortality. Instead, both individual and combined tree species occupancy, density, abundance, and richness were considerably higher in the warmer, more fire‐influenced region, except in the warmest, driest areas (steep and south‐facing slopes at low elevation). Our comparison of two landscape‐scale data sets suggests that changes in tree distribution and forest structure in interior Alaska will proceed unevenly, governed by a mosaic of site‐dependent influences wherein forest community composition and species dominance will shift along different trajectories and at different rates according to variation in underlying landscape attributes. Although there were clear differences in forest structure between the two areas that were likely attributable to differences in growing season warmth and fire disturbance, we found scant support for the concept of an incipient, ongoing biome shift in interior Alaska resulting from impending diminution of boreal forest cover over the short to medium term. Indeed, we suggest that (depending on severity of disturbance dynamics and the rapidity of future warming) cooler areas of interior Alaska's forest may reasonably be expected to sustain marginal increases in forest cover with additional warming, at least in certain topographic positions (such as poorly drained basins and cool treeline sites) and/or geographic regions, prior to any landscape‐scale diminution of forest cover due to warming.

Direct and Cascading Effects of Landscape Structure on Tropical Forest and Non-forest Frugivorous Birds

Global biodiversity is increasingly threatened by land-use change, but the direct and indirect drivers of species diversity in human-modified tropical landscapes are poorly known. Forest-dependent species are expected to be particularly sensitive to changes in landscape composition (e.g., forest loss) and configuration (e.g., increase of forest edges), both directly and indirectly through cascading landscape effects on local patterns of forest structure and resource availability. In contrast, non-forest-dependent species are probably more strongly related to landscape changes than to local forest patterns, as these species are able to use resources not only from the forest, but also from other landscape elements over larger spatial scales. We tested these hypotheses using structural equation modeling. In particular, we sampled 20 landscapes (115 ha each) from the Brazilian Atlantic rainforest to assess the effect of landscape-scale forest cover and amount of forest edges on the diversity of frugivorous birds, both directly and indirectly through the effect that these landscape variables may have on vegetation complexity and fruit biomass. We separately assessed the response of forest-dependent and non-forest-dependent frugivores to infer potential mechanisms underlying bird assemblages in fragmented landscapes. The diversity of forest-dependent birds mainly decreased with the simplification of vegetation complexity in more deforested landscapes, but increased with increasing fruit biomass in more forested landscapes (indirect effects). Both patterns were significant, thus supporting a strong bottom-up control, i.e., local habitat simplification and resource scarcity in highly deforested landscapes limits the maintenance of forest-dependent birds. Conversely, but as expected, non-forest-dependent birds were more strongly and directly related to landscape-scale patterns. In particular, landscapes with higher forest edge amount showed higher bird species diversity, probably because the increasing length of ecotones and interspersion/juxtaposition of different habitat types in landscapes with more forest edges can increase resource availability and foraging efficiency of non-forest-dependent birds. As the seed dispersal services offered by forest-dependent species cannot be ecologically compensated for by the proliferation of non-forest-dependent species, preventing forest loss is imperative to maintain forest-dependent birds and forest regeneration in this vanishing biodiversity hotspot.

Direct and cascading effects of landscape structure on tropical forest and non-forest frugivorous birds.

Global biodiversity is increasingly threatened by land-use change, but the direct and indirect drivers of species diversity in human-modified tropical landscapes are poorly known. Forest-dependent species are expected to be particularly sensitive to changes in landscape composition (e.g., forest loss) and configuration (e.g., increase of forest edges), both directly and indirectly through cascading landscape effects on local patterns of forest structure and resource availability. In contrast, non-forest-dependent species are probably more strongly related to landscape changes than to local forest patterns, as these species are able to use resources not only from the forest, but also from other landscape elements over larger spatial scales. We tested these hypotheses using structural equationmodeling. In particular, we sampled 20 landscapes (115ha each) from the Brazilian Atlantic rainforest to assess the effect of landscape-scale forest cover and amount of forest edges on the diversity of frugivorous birds, both directly and indirectly through the effect that these landscape variables may have on vegetation complexity and fruit biomass. We separately assessed the response of forest-dependent and non-forest-dependent frugivores to infer potential mechanisms underlying bird assemblages in fragmented landscapes. The diversity of forest-dependent birds mainly decreased with the simplification of vegetation complexity in more deforested landscapes, but increased with increasing fruit biomass in more forested landscapes (indirect effects). Both patterns were significant, thus supporting a strong bottom-up control, i.e., local habitat simplification and resource scarcity in highly deforested landscapes limits the maintenance of forest-dependent birds. Conversely, but as expected, non-forest-dependent birds were more strongly and directly related to landscape-scale patterns. In particular, landscapes with higher forest edge amount showed higher bird species diversity, probably because the increasing length of ecotones and interspersion/juxtaposition of different habitat types in landscapes with more forest edges can increase resource availability and foraging efficiency of non-forest-dependent birds. As the seed dispersal services offered by forest-dependent species cannot be ecologically compensated for by the proliferation of non-forest-dependent species, preventing forest loss is imperative to maintain forest-dependent birds and forest regeneration in this vanishing biodiversity hotspot.

Floristic diversity and composition of the Biteyu forest in the Gurage mountain chain (Ethiopia): implications for forest conservation

The Afromontane forests of Ethiopia have been under a serious degradation threat. Assessment of floristic diversity and species composition in Biteyu forest of Gurage mountain chain in the central Ethiopia was conducted to examine the pattern of forest structure. Thirty plots of 30 m × 30 m were used to record the vegetation and environmental data using systematic sampling technique. The local name, plant scientific names, DBH, height, species abundance and percentage canopy cover of plant species were recorded. Shannon diversity index and Sorensen’s coefficients was used for comparison among communities and similar forests in the country. Threats to the forest biodiversity in Biteyu were determined by counting cattle interference and wood stumps as disturbance indicators. Relative Euclidean Distance measures by using Ward’s method (linkage) was applied for cluster analysis. Environmental variables were also recorded in each plot. Woody species population structure, basal area and importance value index were analyzed using spreadsheet programs. Data on species distribution and environmental variables in the forest were analyzed by canonical correspondence analysis. A total of 190 species in 154 genera under 73 families were identified. Twenty species were found to be endemic taxa to the Flora Area. Only three plant community types were identified from the cluster analysis due to the high human influence. The Sorensen’s coefficient showed the resemblance of the Biteyu forest with other Dry Evergreen Afromontane forests in the country. Moreover, altitude and slope strongly affect the species composition and structure of Biteyu forest. Given the high anthropogenic influence, high endemism, high dependence of the local community on the forest resources, forest conservation and restoration measures should be done by stakeholders.