Forest Structure Variables Research Articles

Comparing forest structure and biodiversity on private and public land: secondary tropical dry forests in Costa Rica

AbstractSecondary forests constitute a substantial proportion of tropical forestlands. These forests occur on both public and private lands and different underlying environmental variables and management regimes may affect post‐abandonment successional processes and resultant forest structure and biodiversity. We examined whether differences in ownership led to differences in forest structure, tree diversity, and tree species composition across a gradient of soil fertility and forest age. We collected soil samples and surveyed all trees in 82 public and 66 private 0.1‐ha forest plots arrayed across forest age and soil gradients in Guanacaste, Costa Rica. We found that soil fertility appeared to drive the spatial structure of public vs. private ownership; public conservation lands appeared to be non‐randomly located on areas of lower soil fertility. On private lands, areas of crops/pasture appeared to be non‐randomly located on higher soil fertility areas while forests occupied areas of lower soil fertility. We found that forest structure and tree species diversity did not differ significantly between public and private ownership. However, public and private forests differed in tree species composition: 11 percent were more prevalent in public forest and 7 percent were more prevalent in private forest. Swietenia macrophylla, Cedrela odorata, and Astronium graveolens were more prevalent in public forests likely because public forests provide stronger protection for these highly prized timber species. Guazuma ulmifolia was the most abundant tree in private forests likely because this species is widely consumed and dispersed by cattle. Furthermore, some compositional differences appear to result from soil fertility differences due to non‐random placement of public and private land holdings with respect to soil fertility. Land ownership creates a distinctive species composition signature that is likely the result of differences in soil fertility and management between the ownership types. Both biophysical and social variables should be considered to advance understanding of tropical secondary forest structure and biodiversity.

Determinants and correlates of above-ground biomass in a secondary hillside rainforest in Central Vietnam

Despite inception of carbon-conservation forestry programs, information about total above-ground woody biomass (TAGB) in Vietnamese secondary lowland rainforests is still scarce. We elucidated major factors influencing local variation of TAGB within an anthropogenically modified hillside forest in Thừa Thien-Huế Province. On forty 400 m2 sized plots all tree species were recorded, and their biomass was calculated using allometric equations. In addition, bio-physical parameters relating to terrain and soils were measured. Effects of bio-physical variables on forest TAGB were assessed using multivariate regression methods. Forest TAGB (average 117 Mg ha−1) was primarily explained by forest structural variables, i.e. tree densities and average heights, in particular presence of large trees. TAGB was largely determined by the biomass of a few species which dominated different forest parts (ridges or hill base); TAGB was hardly influenced by species diversity. Many dominant trees were light-demanding species; these were characterised by scarce rejuvenation and high tree mortality. Bio-physical patterns indicated that previous logging impacts persisted and continued to influence seedling establishment, sapling growth/survival, and—ultimately—species composition. Nutrient patterns were mostly explained by interactions with certain tree species and tree foliage cover, as modulated by terrain and logging impacts. Development trajectories of TAGB over the next 10–20 years could not be predicted easily since (1) many functionally important late-succession species (e.g. dipterocarps) were very scarce; (2) the sizes of initially established light-demanding species appeared to meet limits, including increasing tree mortality; and (3) rejuvenation and species succession differed locally and proceeded along largely unpredictable pathways. Some suggestions for further research are made.

How conspecific primates use their habitats: Surviving in an anthropogenically-disturbed forest in Central Kalimantan, Indonesia

Kalimantan (Indonesian Borneo) is a biodiversity hotspot at risk because of severe forest loss, degradation and burning events. Habitat loss and anthropogenic altering of forest structures pose a threat to forest-dependent taxa, including multiple endemic primate species. Conservation management schemes may be enhanced by evaluating how forest-dependent primates use their habitat for fulfilling life-history requirements, the role of natural forest structures thereon, and any corresponding impacts from anthropogenic disturbance and modification of forests. We investigated how forest-structure variables and landscape scale anthropogenic disturbance factors influenced the life-history behaviours (sleeping, ranging and feeding) of two endemic and sympatric primate species, Presbytis rubicunda (red langur) and Hylobates albibarbis (Bornean agile gibbon), in Sabangau tropical peat-swamp forest, Central Kalimantan. We aimed to identify key factors that influence habitat suitability for both species, and determine the influence of similar factors when selecting habitat for various activities such as sleeping, feeding and ranging. GPS locational data for each behaviour were analysed in conjunction with forest-structure parameters present (derived from LiDAR, ALOS-PALSAR), landscape-scale habitat related factors, and proximity to landscape-scale disturbance factors including burned areas. A Maximum Entropy (MaxEnt) algorithm was employed for estimating habitat suitability for the different activities of each species based on the afore-mentioned variables. By using a combination of forest sub-class, structure and disturbance variables within the MaxEnt framework, distribution maps of suitable langur and gibbon sleeping, ranging and feeding habitats were produced. Langurs and gibbons had limited overlaps in terms of feeding, ranging and sleeping habitats. In all cases, landscape-scale variables including those related to landscape scale anthropogenic disturbance had the highest percentage contribution for explaining habitat suitability in comparison to forest-structure variables such as canopy heights (derived using LiDAR data). Additionally, variables influencing habitat selection varied between species; while langur feeding, ranging and sleeping were all influenced by distance from burned forests, gibbon sleeping habitat selection was influenced by distance from the forest edge, and ranging and feeding habitat selection was most affected by distance from burned areas. The insights gained from this study may help inform conservation management of these species and guide forest management strategies accordingly to ensure habitat structure is maintained to facilitate activities by sympatric primate species.

Climate and fragmentation affect forest structure at the southern border of Amazonia

ABSTRACTBackground: The remaining forests in the extensive contact zone between southern Amazonia (seasonal rain forest) and the Cerrado (savanna) biomes are at risk due to intense land-use and climate change.Aims: To explore the vulnerability of these transitional forests to changes in land use and climate, we evaluated the effects of fragmentation and climatic variables on forest structure.Methods: We measured the diameter and height of 14,185 trees with diameter ≥10 cm at 24 forest plots distributed over an area of 25,000 km2. For each plot, we obtained data on contemporary fragmentation and climatic variables.Results: Forest structure variables (height, diameter, height:diameter allometry, biomass) varied significantly both within and among plots. The height, H:D and biomass of trees were positively correlated with annual precipitation and fragment area.Conclusions: The association between forest structure and precipitation indicates that these forests plots are likely to be vulnerable to dry season intensification anticipated for the southern edge of the Amazon. Additionally, the reduction in the fragment area may contribute to reductions in forest biomass and tree height, and consequently ecosystem carbon stocks. Given the likely susceptibility of these forests, urgent conservation action is needed to prevent further habitat degradation.

Forest restoration and hydrological parameters effects on soil water conditions: a structural equation modelling approach

ABSTRACT Although the effects of land use changes on hydrological functioning are widely addressed, issues such as which components of the hydrological system are affected, how and on what time scales are still poorly understood. In this context, we evaluated whether forest restoration improves soil water conditions in a Cerrado area, and whether the combined effects of forest structure and hydrological variables influence soil attributes. For this, we monitored three areas in different stages of natural succession over seven months, and evaluated vegetation structure indicators, hydrological indicators and soil indicators. Vegetation structure variables were analyzed with Principal Components Analysis, and to evaluate the direct and indirect effects among the variables we used structural equations modelling. Each successional stage differed in relation to forest structure, affecting the hydrological processes and causing the improvement of soil attributes with forest development. In the initial stage, throughfall was higher due to the more open vegetation, and the soil was more resistant to penetration. With the development of the vegetation, stemflow and interception also increased. As a result of the structural and hydrological changes, the model indicated that soil moisture was influenced directly by throughfall and stemflow, as well as by soil resistance to penetration and infiltration rates, and indirectly by forest structure, which influenced these variables, except infiltration rates. These results suggest that hydrological variables can be good indicators of forest restoration monitoring, providing a direct link to changes in soil conditions.

Tree Diversity and Uses in Coffee Plantations of a Mixe Community in Oaxaca, Mexico

Indigenous communities manage shaded coffee (Coffea arabica) plantations by applying traditional practices which promote and conserve forest structure and tree diversity while providing a wide variety of environmental services, as well as social and cultural functions. We studied coffee production by a Mixe indigenous community in the Mixe mountains region of Oaxaca, Mexico, to identify the relationship between traditional management of coffee plantations and tree diversity conservation through the analysis of forest structure, richness, composition, and tree uses. A total of 85 tree species were recorded in three classified coffee production areas, the majority of which were natives. Seven species use categories were identified. The results demonstrate variations in coffee plantation structure according to topographic conditions, distance to the community, and management practices. Norms, traditions, and customs of the community guide coffee plantation management. The tree diversity registered in coffee plantations and in uncultivated medium tropical deciduous forest contributes to the maintenance of forest diversity. Thus, traditional coffee management promotes biodiversity conservation. In this particular case, the local community conserves medium tropical deciduous forest within its coffee plantations.

Promoting biodiversity values of small forest patches in agricultural landscapes: Ecological drivers and social demand

Small forest patches embedded in agricultural (and peri-urban) landscapes in Western Europe play a key role for biodiversity conservation with a recognized capacity of delivering a wide suite of ecosystem services. Measures aimed to preserve these patches should be both socially desirable and ecologically effective. This study presents a joint ecologic and economic assessment conducted on small forest patches in Flanders (Belgium) and Picardie (N France). In each study region, two contrasted types of agricultural landscapes were selected. Open field (OF) and Bocage (B) landscapes are distinguished by the intensity of their usage and higher connectivity in the B landscapes. The social demand for enhancing biodiversity and forest structure diversity as well as for increasing the forest area at the expenses of agricultural land is estimated through an economic valuation survey. These results are compared with the outcomes of an ecological survey where the influence of structural features of the forest patches on the associated herbaceous diversity is assessed. The ecological and economic surveys show contrasting results; increasing tree species richness is ecologically more important for herbaceous diversity in the patch, but both tree species richness and herbaceous diversity obtain insignificant willingness to pay estimates. Furthermore, although respondents prefer the proposed changes to take place in the region where they live, we find out that social preferences and ecological effectiveness do differ between landscapes that represent different intensities of land use. Dwellers where the landscape is perceived as more “degraded” attach more value to diversity enhancement, suggesting a prioritization of initiatives in these area. In contrast, the ecological analyses show that prioritizing the protection and enhancement of the relatively better-off areas is more ecologically effective. Our study calls for a balance between ecological effectiveness and welfare benefits, suggesting that cost effectiveness studies should consider these approaches jointly.

Assessing how green space types affect ecosystem services delivery in Porto, Portugal

Significant advances have been made in identifying, quantifying and valuing multiple urban ecosystem services (UES), yet this knowledge remains poorly implemented in urban planning and management. One of the reasons for this low implementation is the insufficient thematic and spatial detail in UES research to provide guidance for urban planners and managers. Acknowledging how patterns of UES delivery are related with vegetation structure and composition in urban green areas could help these stakeholders to target structural variables that increase UES provision. This investigation explored how different types of urban green spaces influence UES delivery in Porto, a Portuguese city, and how this variation is affected by a socioeconomic gradient. A stepwise approach was developed using two stratification schemes and a modelling tool to estimate urban forest structure and UES provision. This approach mapped explicit cold and hotspots of UES provision and discriminated the urban forest structural variables that influence UES at the local scale. Results revealed that different types of green spaces affect UES delivery as a direct result of the influence of structural variables of the urban forest. Furthermore, the uneven distribution of green spaces types across socioeconomic strata alters UES delivery across the city. This case study illustrates how a methodology adaptable to other geographic contexts can be used to map and analyze coupled social and ecological patterns, offering novel insights that are simple to understand and apply by urban planners and managers.

Impacts of different land management histories on forest change.

Many western North American forest types have experienced considerable changes in ecosystem structure, composition, and function as a result of both fire exclusion and timber harvesting. These two influences co-occurred over a large portion of dry forests, making it difficult to know the strength of either one on its own or the potential for an interaction between the two. In this study, we used contemporary remeasurements of a systematic historical forest inventory to investigate forest change in the Sierra Nevada. The historical data opportunistically spanned a significant land management agency boundary, which protected part of the inventory area from timber harvesting. This allowed for a robust comparison of forest change between logged and unlogged areas. In addition, we assessed the effects of recent management activities aimed at forest restoration relative to the same areas historically, and to other areas without recent management. Based on analyses of 22,007 trees (historical, 9,573; contemporary, 12,434), live basal area and tree density significantly increased from 1911 to the early 2000s in both logged and unlogged areas. Both shrub cover and the proportion of live basal area occupied by pine species declined from 1911 to the early 2000s in both areas, but statistical significance was inconsistent. The most notable difference between logged and unlogged areas was in the density of large trees, which declined significantly in logged areas, but was unchanged in unlogged areas. Recent management activities had a varied impact on the forest structure and composition variables analyzed. In general, areas with no recent management activities experienced the greatest change from 1911 to the early 2000s. If approximating historical forest conditions is a land management goal the documented changes in forest structure and composition from 1911 to the early 2000s indicate that active restoration, including fire use and mechanical thinning, is needed in many areas.

Logistic regression for clustered data from environmental monitoring programs

Large-scale surveys, such as national forest inventories and vegetation monitoring programs, usually have complex sampling designs that include geographical stratification and units organized in clusters. When models are developed using data from such programs, a key question is whether or not to utilize design information when analyzing the relationship between a response variable and a set of covariates. Standard statistical regression methods often fail to account for complex sampling designs, which may lead to severely biased estimators of model coefficients. Furthermore, ignoring that data are spatially correlated within clusters may underestimate the standard errors of regression coefficient estimates, with a risk for drawing wrong conclusions. We first review general approaches that account for complex sampling designs, e.g. methods using probability weighting, and stress the need to explore the effects of the sampling design when applying logistic regression models. We then use Monte Carlo simulation to compare the performance of the standard logistic regression model with two approaches to model correlated binary responses, i.e. cluster-specific and population-averaged logistic regression models. As an example, we analyze the occurrence of epiphytic hair lichens in the genus Bryoria; an indicator of forest ecosystem integrity. Based on data from the National Forest Inventory (NFI) for the period 1993–2014 we generated a data set on hair lichen occurrence on >100,000 Picea abies trees distributed throughout Sweden. The NFI data included ten covariates representing forest structure and climate variables potentially affecting lichen occurrence. Our analyses show the importance of taking complex sampling designs and correlated binary responses into account in logistic regression modeling to avoid the risk of obtaining notably biased parameter estimators and standard errors, and erroneous interpretations about factors affecting e.g. hair lichen occurrence. We recommend comparisons of unweighted and weighted logistic regression analyses as an essential step in development of models based on data from large-scale surveys.

Efficacy of variable density thinning and prescribed fire for restoring forest heterogeneity to mixed-conifer forest in the central Sierra Nevada, CA

Abstract Frequent-fire forests were historically characterized by lower tree density, a higher proportion of pine species, and greater within-stand spatial variability, compared to many contemporary forests where fire has been excluded. As a result, such forests are now increasingly unstable, prone to uncharacteristically severe wildfire or high levels of tree mortality in times of drought stress. While reducing tree density might help to restore resilience, thinning treatments are frequently seen as conflicting with management for other resources such as wildlife habitat, in part because standard thinning prescriptions don’t typically produce the degree of within-stand heterogeneity found in historical forests. In this study, we compare stand structures and heterogeneity produced by two different mechanical thinning treatments and in an unthinned control, all with or without prescribed fire as a follow-up treatment. The “high variability” thinning treatment was designed to produce the spatial variability once found in frequent fire forests and was based on historical data from nearby old-growth stands, while the “low variability” thinning treatment retained a similar number of trees but at a relatively even crown spacing. Stand averages and degree of variation for common forest metrics were calculated and values compared to a historical old-growth reference stand. Both thinning treatments reduced tree density and basal area, and shifted species composition towards historical values. Thinning treatments contained a deficit of trees in both the smallest ( 80 cm) size classes, relative to historical conditions. The high variability thinning treatment increased forest structure variation more than the low variability thinning treatment for most measures and retained a broader distribution of canopy closure values across the treatment units. While prescribed fire also reduced stand density and increased the amount of within-stand heterogeneity (when delayed mortality was included), the magnitude was much less than that produced by thinning. Prescribed fire did not significantly reduce basal area or alter the species composition. Prescribed burning did significantly reduce surface fuel loads, while thinning alone had no effect for most fuel classes. Our results show that high variability thinning coupled with prescribed burning resulted in a forest better aligned with the conditions present in historical frequent-fire forests, which were known to be more resilient to both wildfire and drought.

Environmental drivers of vascular and non‐vascular epiphyte abundance in tropical pre‐montane cloud forests in Northern Peru

AbstractQuestionsWhat is the role of microclimate relative to easily obtainable measures of forest structure in explaining epiphyte abundance? Do these roles differ between epiphytic plant groups?LocationTropical pre‐montane cloud forests, Alto Mayo watershed, northern Peru.MethodsWe recorded vascular epiphyte abundance, epiphytic bryophyte cover and forest structural features in 36 plots (20 m × 20 m), and measured air temperature and humidity in a subset of 17 plots. We modelled bryophyte cover, total vascular epiphyte abundance and the abundances of the main vascular epiphyte groups separately (bromeliads, aroids, ferns), as a function of forest structure and microclimate using spatial autoregressive models. Three forest structural variables (basal area, tree height and canopy openness) and two microclimatic variables (minimum humidity and maximum temperature) were considered. We constructed all possible combinations of maximum two‐variable models from the five explanatory variables and carried out AIC‐based model selection and variable importance tests with these as input models.ResultsCanopy openness was the most important variable explaining the abundance of the main epiphytic plant groups. It was also strongly correlated with stand microclimate. Therefore, predictions of epiphyte abundance did not improve with the inclusion of microclimatic data in the models. There were some differences among the epiphytic plant groups in their response to microclimate and forest structural features.ConclusionsForest stand microclimate, reflected through canopy openness in particular, was a main determinant of the distributions of all epiphytic plant groups. This implies that easily measurable forest structural variables alone can be used as good predictors of epiphyte abundance. Taxon‐specific differences in responses to microclimate imply that these taxa may also differ in their sensitivity to predicted future changes in temperature and rainfall.

Seasonality of albedo and FAPAR in a boreal forest

Satellite data are continuously used to monitor albedo and fraction of absorbed photosynthetically active radiation (FAPAR), which are key components in determining the energy balance and productivity of forests. However, due to the mismatch between spatial resolution of the satellite data and forest stand size, coarse resolution satellite products cannot capture the fine-scale variations in forest structure. Therefore, forest radiation budget models are important tools in quantifying albedo and FAPAR at stand scale. However, due to the lack of suitable input data, simulations are often restricted to summer conditions only and the seasonal patterns are not considered. We modeled the time series of albedo and FAPAR for an entire growing season for 20 forest plots in the boreal zone in Finland (61°50′N, 24°17′ E) using an exceptional ground reference data set. Canopy gap fractions and the spectra of forest floor were monitored in the plots throughout the growing season. Data on the seasonality of spectra of tree foliage were also available. The modeled albedo and FAPAR were upscaled and compared against albedo and FAPAR derived from MODIS satellite data. We showed that forest radiation budget models capable of adequately taking into account foliage clumping and its effects on multiple scattering are the most appropriate for simulating albedo of boreal coniferous forests. Our results also indicated negative albedo-productivity relations in boreal coniferous forests. In addition, we demonstrated that not only the overall level, but also the seasonal patterns of albedo and FAPAR differ between tree species. Therefore, the use of only peak growing season albedo or FAPAR values when estimating climate impacts of forest management can be misleading.

Microhabitat Factors Associated with Occupancy of Songbirds in Suburban Forest Fragments in the Eastern United States

Forests in the eastern United States have become fragmented by urban development and agriculture, creating a landscape of remnant forest patches. Many bird species rely on these fragments for breeding habitat, but habitat selection in these patches is not well-understood. Our objective was to examine the effects of forest structure, native plants, and invertebrate biomass on the occupancy of an assemblage of common Eastern songbird species in suburban forest fragments. We collected data at 98 plots in remnant forest patches in Delaware and Maryland. Avian point counts were conducted three times per season between 15 May–7 August 2009–2010. We estimated occupancy probability, while accounting for imperfect detection, for nine common songbird species in order to understand how they are influenced by invertebrate biomass and vegetation characteristics. We ranked competing models using Akaike Information Criteria (AIC). Occupancy of six of our 10 candidate species was affected by forest structure, native plant density, or invertebrate biomass. Species we identified to have occupancy relationships with forest structure variables in suburban forest fragments appear to align well with habitat relationships that have been previously identified for the species in more forested areas. This supports that managing for structural characteristics associated with these species in more heavily forested areas could improve habitat quality for these species in suburban forest fragments as well. Occupancy of only one species we examined was related to native plants, suggesting vegetation structure, rather than composition, was a more important factor in occupancy.

Quantifying downed coarse woody material and residual forest basal area following retention harvesting in northeastern Minnesota using Landsat sensor data

Retention harvesting shows great promise for restoring and maintaining forest structural and compositional diversity. However, economical, comprehensive monitoring is needed to advance understanding of the effectiveness of these management strategies through time. We investigate multitemporal winter Landsat sensor data (capturing snow ground cover at 7.6 cm and 106.7 cm depths) as a tool for discriminating between and providing regional estimates of both residual forest basal area (BA) and downed coarse woody material (DCWM) volume following retention harvesting in Minnesota, USA. Measurements from 34 ground plots were used with Landsat predictor variables to estimate these two biophysical forest parameters. According to similar studies, results for DCWM volume estimation are considered adequate, with an R2adj = 0.54 and absolute RMSE (RMSEa) = 19.02 m3·ha−1. Residual forest BA estimates were similar: total BA R2adj = 0.55 (RMSEa = 1.85 m2·ha−1), hardwood BA R2adj = 0.67 (RMSEa = 1.23 m2·ha−1), and conifer BA R2adj = 0.52 (RMSEa = 0.94 m2·ha−1). Use of winter Landsat imagery was key to quantifying these important forest biophysical parameters — a tool that carries the potential to transform our understanding of the impact of human and natural disturbance regimes on northern forest ecosystems.

Effects of forest structure on natural regeneration of Excentrodendron hsienmu population in Southwest Guangxi, China.

The effects of forest vertical structural variables (crown index, tree height, and large and small tree proportions) and density variables (basal area, adult tree density, shrub density, shrub coverage, and Excentrodendron hsienmu proportion in the forest canopy) on the natural rege-neration of the typical E. hsienmu populations in the karst mountains of Southwest Guangxi, China were studied. The results showed that the average regeneration density of E. hsienmu populations was 1742-3861 trees·hm-2 and relatively low. Forest vertical structure and density variables did not significantly affect the number of E. hsienmu seedlings, but significantly affected seedling ground diameter and height to some extent. Among the vertical structure variables, a significant nega tive correlation was observed between crown index and seedling height, but the association between crown index and seedling ground diameter was not significant. The large tree proportion and tree height were significantly negatively correlated with both seedling ground diameter and height. However, the proportion of small trees was significantly positively related to both seedling ground diameter and height. Among the density variables, adult tree density showed a significant positive correlation with both seedling ground diameter and height. A significant negative association was observed between the proportion of E. hsienmu and seedling ground diameter. Multiple regression analysis indicated that the model based on stand structure factors showed a poor fitness with regard to the number of E. hsienmu seedlings (P>0.05), and the quantitative distribution of E. hsienmu seedlings was affected to some extent by vertical structural variables. The stand structure factor model fitted well for the diameter and height of the seedlings (P<0.01). Seedling ground diameter was mainly affected by adult tree density, and seedling height was mainly determined by the combined effects of adult tree density and basal area.

Fine‐scale forest variability and biodiversity in the boreal mixedwood forest

Local spatial variation in species distributions is driven by a mix of abiotic and biotic factors, and understanding such hierarchical variation is important for conservation of biodiversity across larger scales. We sought to understand how variation in species composition of understory vascular plants, spiders, and carabid beetles is associated with concomitant spatial variation in forest structure on a 1‐ha permanent plot in a never‐cut mixedwood forest in central Alberta (Canada). Using correlations among dendrograms produced by cluster analysis we associated data about mapped distribution of all living and dead stems &gt; 1 cm diameter at breast height with distributions of the three focal taxa sampled from regular grids across the plot. Variation in each of these species assemblages were significantly associated with several forest structure variables at various spatial scales, but the scale of the associations varied among assemblages. Variation in species richness and abundance was explained mostly by changes in basal area of trees across the plot; however, other variables (e.g. snag density and tree density) were also important, depending on assemblage. We conclude that fine‐scale habitat variation is important in structuring spatial distribution of the species of the forest floor, even within a relatively homogeneous natural forest. Thus, assessments that ignore within‐stand heterogeneity and management that ignores its maintenance will have limited utility as conservation measures for these taxa, which are major elements of forest biodiversity.

Spatial heterogeneity of biomass and forest structure of the Amazon rain forest: Linking remote sensing, forest modelling and field inventory

AbstractAimEstimating the current spatial variation of biomass in the Amazon rain forest is a challenge and remains a source of substantial uncertainty in the assessment of the global carbon cycle. Precise estimates need to consider small‐scale variations of forest structures resulting from local disturbances, on the one hand, and require large‐scale information on the state of the forest that can be detected by remote sensing, on the other hand. In this study, we introduce a novel method that links a forest gap model and a canopy height map to derive the biomass distribution of the Amazon rain forest.LocationAmazon rain forest.MethodsAn individual‐based forest model was applied to estimate the variation of aboveground biomass across the Amazon rain forest. The forest model simulated individual trees; hence, it allowed the direct comparison of simulated and observed canopy heights from remote sensing. The comparison enabled the detection of disturbed forest states and the derivation of a simulation‐based biomass map at 0.16 ha resolution.ResultsSimulated biomass values ranged from 20 to 490 t (dry mass)/ha across 7.8 Mio km2 of Amazon rain forest. We estimated a total aboveground biomass stock of 76 GtC, with a coefficient of variation of 45%. We found mean differences of only 15% when comparing biomass values of the map with 114 field inventories. The forest model enables the derivation of additional estimates, such as basal area and stem density.Main conclusionsLinking a canopy height map with an individual‐based forest model captures the spatial variation of biomass in the Amazon rain forest at high resolution. The study demonstrates how this linkage allows for quantifying the spatial variation in forest structure caused by tree‐level to regional‐scale disturbances. It thus provides a basis for large‐scale analyses on the heterogeneous structure of tropical forests and their carbon cycle.

Relationship between some wild mammals and forest structural diversity parameters

Relationship between some wild mammals and forest structural diversity parameters

Use of airborne lidar data to improve plant species richness and diversity monitoring in lowland and mountain forests.

We explored the potential of airborne laser scanner (ALS) data to improve Bayesian models linking biodiversity indicators of the understory vegetation to environmental factors. Biodiversity was studied at plot level and models were built to investigate species abundance for the most abundant plants found on each study site, and for ecological group richness based on light preference. The usual abiotic explanatory factors related to climate, topography and soil properties were used in the models. ALS data, available for two contrasting study sites, were used to provide biotic factors related to forest structure, which was assumed to be a key driver of understory biodiversity. Several ALS variables were found to have significant effects on biodiversity indicators. However, the responses of biodiversity indicators to forest structure variables, as revealed by the Bayesian model outputs, were shown to be dependent on the abiotic environmental conditions characterizing the study areas. Lower responses were observed on the lowland site than on the mountainous site. In the latter, shade-tolerant and heliophilous species richness was impacted by vegetation structure indicators linked to light penetration through the canopy. However, to reveal the full effects of forest structure on biodiversity indicators, forest structure would need to be measured over much wider areas than the plot we assessed. It seems obvious that the forest structure surrounding the field plots can impact biodiversity indicators measured at plot level. Various scales were found to be relevant depending on: the biodiversity indicators that were modelled, and the ALS variable. Finally, our results underline the utility of lidar data in abundance and richness models to characterize forest structure with variables that are difficult to measure in the field, either due to their nature or to the size of the area they relate to.