Relation between individual tree mortality and tree characteristics in a polluted and non-polluted environment

Data on individual tree mortality in relatively healthy (Berezinskiy biosphere reserve) and damaged (surroundings of the mineral fertilizer plant 'Achema') even-aged Scots pine (Pinus sylvestris L.) stands are presented. Tree size and competition intensity were found to be the most significant predictors of individual tree mortality in all age groups of the relatively healthy Scots pine stands, however, an essential reduction in the closeness of relations between the tree mortality rate and these variables was determined with the aging of stands. An exponential decrease in tree mortality probability with an increase of tree size is characteristic for trees suffering different competition intensity, however, this decrease becomes much more pronounced as the competition pressure increases. The relations of different tree and stand variables with tree mortality probability have been found to become much weaker in the polluted environment. An exponential increase in tree mortality probability with an increase of crown defoliation was characteristic of damaged Scots pine stands, however, the rate of the increase was different in different age and diameter classes. The impact of crown defoliation on tree mortality rate increased with the aging of stands. At the same defoliation level, individual tree mortality probability was much higher for smaller suppressed trees, however, a relative increase in tree mortality probability along with an increase of crown defoliation was more pronounced for dominant trees. Conclusion: a higher mortality of damaged (defoliated) trees should be considered while assessing losses in forest productivity in a polluted environment.     

Relation Between Individual Tree Mortality and Tree Characteristics in a Polluted and Non-Polluted Environmentx

Data on individual tree mortality in relatively healthy (Berezinskiy biosphere reserve) and damaged (surroundings of the mineral fertilizer plant ‘Achema’) even-aged Scots pine (Pinus sylvestris L.) stands are presented. Tree size and competition intensity were found to be the most significant predictors of individual tree mortality in all age groups of the relatively healthy Scots pine stands, however, an essential reduction in the closeness of relations between the tree mortality rate and these variables was determined with the aging of stands. An exponential decrease in tree mortality probability with an increase of tree size is characteristic for trees suffering different competition intensity, however, this decrease becomes much more pronounced as the competition pressure increases. The relations of different tree and stand variables with tree mortality probability have been found to become much weaker in the polluted environment. An exponential increase in tree mortality probability with an increase of crown defoliation was characteristic of damaged Scots pine stands, however, the rate of the increase was different in different age and diameter classes. The impact of crown defoliation on tree mortality rate increased with the aging of stands. At the same defoliation level, individual tree mortality probability was much higher for smaller suppressed trees, however, a relative increase in tree mortality probability along with an increase of crown defoliation was more pronounced for dominant trees. Conclusion: a higher mortality of damaged (defoliated) trees should be considered while assessing losses in forest productivity in a polluted environment.     

Determining the agricultural ammonia immission using bark bio-monitoring: comparison with passive sampler measurements

Bark samples of spruce, pine and oak trees were collected at two sites in southern Bavaria which are characterized by high agricultural ammonia emissions. The samples were taken using a recently developed bark sampling device which removes a defined layer of the bark. The bark was then analysed for ammonium concentration in order to reflect the environmental ammonia immission. The measured bark concentrations decreased with rising distance between the sample trees and the ammonia source. This applied (i) to measurements inside a closed forest stand ranging from forest edge with high immission to forest interior with much lower immission, and (ii) to the open field where single-standing trees were sampled. Comparing the ammonium concentrations among the three different tree species revealed significant correlations. Thus, it could be shown that old spruce trees are as usable for bark bio-monitoring as the traditionally used pine and oak trees. The ammonium concentrations of the bark were significantly correlated to measurements taken by ammonia passive samplers at the same locations. These results indicate that bark samples may be used for a standardised monitoring of airborne ammonia load. A major advantage of the technique is the determination of the long-term accumulative ammonia load using a single measurement.     

An assessment of tree health and trace element accumulation near a coal-fired generating station, Manitoba, Canada

A forest health assessment was performed in stands dominated by bur oak and trembling aspen to study the potential effects of airborne emissions from a 132 MW coal-fired station. Forty-two stands were sampled within a 16-km radius of the station for both foliar stress symptoms and trace element toxicology. The concentrations of tracer elements (As, Ba, Sr, and V) in the leaf litter were not spatially congruent with airborne emission deposition models (except Ba, which showed elevated levels immediately SE of the station), nor were they at phytotoxic levels. Elemental concentrations were significantly related to soil parameters including organic matter and texture. No patterns were found in forest health along directional or distance gradients from the generating station. Trembling aspen stands demonstrated little decline in general, but three of the 19 bur oak plots, all located on thin sandy soils developed on calcareous till, demonstrated branch dieback. In addition to poor soil conditions, two of these sites also had high water tables, and exhibited tree mortality. The bur oak decline did not appear to be related to emissions from the station, but is suspected to be a result of poor site quality, with urban development as a confounding factor.     

Monitoring of the Phytosanitary State of Navarra's Forests, Spain

Between 1988 and 1993 six surveys on the condition of forests in Navarra (North Spain) were carried out. The results, relating to 408 trees in 17 sampling points, showed that the overall percentage of damaged trees increased from 2.86% in 1988 to 18.6% in 1993, which indicates a general large-scale deterioration of forest condition. Among the most common groups of trees, the most severely affected species were Quercus faginea, Quercus robur and Pinus sylvestris. Furthermore, it was observed that defoliation and discoloration processes did not occur randomly between stand trees, but the trees that were damaged one year (1992) were more predisposed to suffer damage in the next year (1993).     

An integrated methodology for estimation of forest fire-loss using geospatial information

These days, wildfires are prevalent in almost all areas of the world. Researchers have been actively analyzing wildfire damage using a variety of satellite images and geospatial datasets. This paper presents a method for detailed estimation of wildfire losses using various geospatial datasets and an actual case of wildfire at Kang-Won-Do, Republic of Korea in 2005. A set of infrared (IR) aerial images acquired after the wildfire were used to visually delineate the damaged regions, and information on forest type, diameter class, age class, and canopy density within the damaged regions was retrieved from GIS layers of the Korean national forest inventory. Approximate tree heights were computed from airborne LIDAR and verified by ground LIDAR datasets. The corresponding stand volumes were computed using tree volume equations (TVE). The proposed algorithm can efficiently estimate fire loss using the geospatial information; in the present case, the total fire loss was estimated as $5.9 million, which is a more accurate estimate than $4.5 million based on conventional approach. The proposed method can be claimed as a powerful alternative for estimating damage caused by wildfires, because the aerial image interpretation can delineate and analyze damaged regions in a comprehensive and consistent manner; moreover, LIDAR datasets and national forest inventory data can significantly reduce field work.     

Effect of contaminated groundwater on tree growth: A tree-ring analysis

A study was conducted of the effect of contaminated groundwater seepage on tree growth downslope from the F- and H-Area seepage basins of the Department of Energy's Savannah River Site in South Carolina. Trees in wetlands along Four Mile Creek began to show localized stress and mortality in the late 1970s. Extreme winter temperatures and high rainfall were ruled out as potential causal factors of tree stress. Drought was shown to affect trees in both contaminated and uncontaminated zones, but trees in uncontaminated areas exhibited better recovery after drought than trees in contaminated areas. Pollution-mediated alteration of soil acidity and aluminum, sodium, and heavy metal concentrations likely acted to predispose trees to decline, with severe drought acting as the trigger for decline initiation and tree death. Thus, a moderate pollution loading, not sufficient to cause visible damage of itself, may create conditions in which sudden, severe decline could result from natural stresses. This mechanism of forest decline may be common, and should be considered in evaluations of the impact of pollution on wetland forest systems.     

Mapping trees outside forests using high-resolution aerial imagery: a comparison of pixel- and object-based classification approaches

Discrete trees and small groups of trees in nonforest settings are considered an essential resource around the world and are collectively referred to as trees outside forests (ToF). ToF provide important functions across the landscape, such as protecting soil and water resources, providing wildlife habitat, and improving farmstead energy efficiency and aesthetics. Despite the significance of ToF, forest and other natural resource inventory programs and geospatial land cover datasets that are available at a national scale do not include comprehensive information regarding ToF in the United States. Additional ground-based data collection and acquisition of specialized imagery to inventory these resources are expensive alternatives. As a potential solution, we identified two remote sensing-based approaches that use free high-resolution aerial imagery from the National Agriculture Imagery Program (NAIP) to map all tree cover in an agriculturally dominant landscape. We compared the results obtained using an unsupervised per-pixel classifier (independent component analysis—[ICA]) and an object-based image analysis (OBIA) procedure in Steele County, Minnesota, USA. Three types of accuracy assessments were used to evaluate how each method performed in terms of: (1) producing a county-level estimate of total tree-covered area, (2) correctly locating tree cover on the ground, and (3) how tree cover patch metrics computed from the classified outputs compared to those delineated by a human photo interpreter. Both approaches were found to be viable for mapping tree cover over a broad spatial extent and could serve to supplement ground-based inventory data. The ICA approach produced an estimate of total tree cover more similar to the photo-interpreted result, but the output from the OBIA method was more realistic in terms of describing the actual observed spatial pattern of tree cover.     

Evaluating forest management practices using a GIS-based cellular automata modeling approach with multispectral imagery

The objective of this study was to develop an integrated geographic information system (GIS) cellular automata (CA) model for simulating insect-induced tree mortality patterns in order to evaluate the influence of different forest management activities to control insect outbreaks. High-resolution multispectral images were used to determine susceptibility of trees to attack, whereas the GIS-based CA model simulated the effectiveness of clear-cuts and thinning practices for reducing insect-induced tree mortality. The results indicate that thinning susceptible forests should be more effective than clear-cutting for reducing tree loss to insect outbreaks. This study demonstrates the benefits of an integrated approach for understanding and evaluating forest management activities and expresses the need for spatial analysis and modeling for improving forest management practices.     

Inventory methods for trees in nonforest areas in the great plains states

The US Forest Service’s Forest Inventory and Analysis (FIA) program collects information on trees in areas that meet its definition of forest. However, the inventory excludes trees in areas that do not meet this definition, such as those found in urban areas, in isolated patches, in areas with sparse or predominantly herbaceous vegetation, in narrow strips (e.g., shelterbelts), or in riparian areas. In the Great Plains States, little is known about the tree resource in these noninventoried, nonforest areas, and there is a great deal of concern about the potential impact of invasive pests, such as the emerald ash borer. To address this knowledge gap, FIA’s National Inventory and Monitoring Applications Center has partnered with state cooperators and others in a project called the Great Plains Initiative to design and implement an inventory of trees in nonforest areas. The goal of the inventory is to characterize the nonforest tree resource using methods compatible with those of FIA so a holistic understanding of the resource can be obtained by integrating the two surveys. The goal of this paper is to describe the process of designing and implementing the survey, including plot and sample design, and to present some example results from a reporting tool we developed.     

Towards the harmonization between National Forest Inventory and Forest Condition Monitoring. Consistency of plot allocation and effect of tree selection methods on sample statistics in Italy

In the frame of a process aiming at harmonizing National Forest Inventory (NFI) and ICP Forests Level I Forest Condition Monitoring (FCM) in Italy, we investigated (a) the long-term consistency between FCM sample points (a subsample of the first NFI, 1985, NFI_1) and recent forest area estimates (after the second NFI, 2005, NFI_2) and (b) the effect of tree selection method (tree-based or plot-based) on sample composition and defoliation statistics. The two investigations were carried out on 261 and 252 FCM sites, respectively. Results show that some individual forest categories (larch and stone pine, Norway spruce, other coniferous, beech, temperate oaks and cork oak forests) are over-represented and others (hornbeam and hophornbeam, other deciduous broadleaved and holm oak forests) are under-represented in the FCM sample. This is probably due to a change in forest cover, which has increased by 1,559,200 ha from 1985 to 2005. In case of shift from a tree-based to a plot-based selection method, 3,130 (46.7 %) of the original 6,703 sample trees will be abandoned, and 1,473 new trees will be selected. The balance between exclusion of former sample trees and inclusion of new ones will be particularly unfavourable for conifers (with only 16.4 % of excluded trees replaced by new ones) and less for deciduous broadleaves (with 63.5 % of excluded trees replaced). The total number of tree species surveyed will not be impacted, while the number of trees per species will, and the resulting (plot-based) sample composition will have a much larger frequency of deciduous broadleaved trees. The newly selected trees have—in general—smaller diameter at breast height (DBH) and defoliation scores. Given the larger rate of turnover, the deciduous broadleaved part of the sample will be more impacted. Our results suggest that both a revision of FCM network to account for forest area change and a plot-based approach to permit statistical inference and avoid bias in the tree sample composition in terms of DBH (and likely age and structure) are desirable in Italy. As the adoption of a plot-based approach will keep a large share of the trees formerly selected, direct tree-by-tree comparison will remain possible, thus limiting the impact on the time series comparability. In addition, the plot-based design will favour the integration with NFI_2.     

Implications of differing input data sources and approaches upon forest carbon stock estimation

Site index is an important forest inventory attribute that relates productivity and growth expectation of forests over time. In forest inventory programs, site index is used in conjunction with other forest inventory attributes (i.e., height, age) for the estimation of stand volume. In turn, stand volumes are used to estimate biomass (and biomass components) and enable conversion to carbon. In this research, we explore the implications and consequences of different estimates of site index on carbon stock characterization for a 2,500-ha Douglas-fir-dominated landscape located on Eastern Vancouver Island, British Columbia, Canada. We compared site index estimates from an existing forest inventory to estimates generated from a combination of forest inventory and light detection and ranging (LIDAR)-derived attributes and then examined the resultant differences in biomass estimates generated from a carbon budget model (Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3)). Significant differences were found between the original and LIDAR-derived site indices for all species types and for the resulting 5-m site classes (p?<?0.001). The LIDAR-derived site class was greater than the original site class for 42% of stands; however, 77% of stands were within ±1 site class of the original class. Differences in biomass estimates between the model scenarios were significant for both total stand biomass and biomass per hectare (p?<?0.001); differences for Douglas-fir-dominated stands (representing 85% of all stands) were not significant (p?=?0.288). Overall, the relationship between the two biomass estimates was strong (R ²?=?0.92, p?<?0.001), suggesting that in certain circumstances, LIDAR may have a role to play in site index estimation and biomass mapping.     

Hurricane Katrina-induced forest damage in relation to ecological factors at landscape scale

Forest stand stability to strong winds such as hurricanes has been found to be associated with a number of forest, soil and topography factors. In this study, through applying geographic information system (GIS) and logit regression, we assessed effects of forest characteristics and site conditions on pattern, severity and probability of Hurricane Katrina disturbance to forests in the Lower Pearl River Valley, USA. The factors included forest type, forest coverage, stand density, soil great group, elevation, slope, aspect, and stream buffer zone. Results showed that Hurricane Katrina damaged 60% of the total forested land in the region. The distribution and intensity of the hurricane disturbance varied across the landscape, with the bottomland hardwood forests on river floodplains most severely affected. All these factors had a variety of effects on vulnerability of the forests to the hurricane disturbance and thereby spatial patterns of the disturbance. Soil groups and stand factors including forest types, forest coverage and stand density contributed to 85% of accuracy in modeling the probability of the hurricane disturbance to forests in this region. Besides assessment of Katrina's damage, this study elucidates the great usefulness of remote sensing and GIS techniques combined with statistics modeling in assessment of large-scale risks of hurricane damage to coastal forests.     

Developing Alternative Forest Management Planning Strategies Incorporating Timber, Water and Carbon Values: An Examination of their Interactions

Currently, the integration of carbon and water values of forest ecosystems into forest management planning models has become increasingly important in sustainable forest management. This study focuses on developing a multiple-use forest management planning model to examine the interactions of timber and water production as well as net carbon sequestration in a forest ecosystem. Each forest value is functionally linked to stand structure and quantified economically. A number of forest management planning strategies varying in the amount of water, carbon, and timber targets and flows as constraints are developed and implemented in a linear programming (LP) environment. The outputs of each strategy are evaluated with a number of performance indicators such as standing timber volume, ending forest inventory, area harvested, and net present value (NPV) of water, timber, and carbon over time. Results showed that the cycling time of forest stands for renewal has important implications for timber, water, and carbon values. The management strategies indicated that net carbon sequestration can be attained at a significant cost in terms of foregone timber harvest and financial returns. The standing timber volumes and ending forest inventories were among the most important factors determining whether the forest constitutes a net carbon sink or source. Finally, the interactions among the forest values were generally found to be complementary, yet sometimes contradictory (i.e., negatively affecting each other), depending on the assumed relationship between forest values and stand structure.     

Spatial modeling of forest stand susceptibility to logging operations

The susceptibility of residual, non-harvested, live trees to damage caused by the harvesting of other nearby trees has received moderate attention over the last four decades through observational studies prompted by concerns over ecological and economic consequences of logging operations. We developed models to predict the potential level of damage to residual trees that could be caused by selective timber harvesting. Three machine-learning methods, i.e., classification and regression tree (CART), random forest (RF), and boosted regression tree (BRT), were assessed for this purpose. Through an observational study of a harvested area in the Hyrcanian forests of Iran, we recorded damage to trees >7.5 cm diameter at breast height along transects and grouped them into three types: (1) scars >100 cm², (2) >50% crown removal, and (3) trees leaning >10°. These field observations were associated with the spatially explicit characteristics of the forest stand, i.e., slope angle, slope aspect, altitude, slope length, topographic position index, stand type, stand density, and distance from the nearest roads and skid trails, that were considered as the explanatory variables to the modeling processes. To determine whether the CART, RF, and BRT models performed well in estimating the probability of damage occurrence, they were validated using the Akaike information criterion (AIC) and area under the receiver operating characteristics (AUC) curve. The results revealed that the BRT model with AIC = −276 and AUC = 0.89 generated the most accurate spatially explicit distribution map of stand susceptibility to damage from logging operations, followed by RF (AIC = −263 and AUC = 0.87) and CART (AIC = −23 and AUC = 0.62). We found that the spatial extent of residual stand damage was highly influenced by slope terrain and stand density. Our study has practical implications for reorganizing and planning reduced-impact logging operations and provides forest engineers with insights into the utility of machine learning methods in domains of forestry and forest engineering.     

Foliar injury air pollution surveys of eastern white pine (Pinus strobus L.): A review

A thorough review and critical evaluation of field surveys from 1900 to the present of foliar injury to Pinus strobus L. supposedly caused by air pollution was undertaken. Ninety percent of the surveys failed to meet current scientific standards of acceptability. The conduct and peer review of surveys has been poor and the correct injury symptoms have not always been used. Data were obtained for nine that met screening criteria and injury incidence and severity were mapped. Three fourths of the counties in the natural and planted range of eastern white pine have not been scientifically surveyed, so generalizations regarding large-scale spatial patterns of eastern white pine foliar pathological conditions were not possible. However, recent growth and inventory data indicate that growth throughout the natural range regardless of air pollution or other stresses (e.g. blister rust) is excellent, suggesting that regional performance and foliar conditions are unrelated. Sufficient compelling corroborative evidence was found to conclude that a general decline of eastern white pine throughout its range is not a tenable finding.The putative air pollution sensitivity of eastern white pine appears to be based on studies published between 1963 and 1973 on hypersensitive individuals that are no longer being observed in the field. More recent research on eastern white pine has noted a lack of sensitivity and/or high variability of response. The idea that eastern white pine as a species is highly sensitive to air pollution is no longer supported by the available evidence. However, hypersensitive juvenile individuals comprising no more than 8–9% of the total population may still germinate and grow for a brief period of time (because old enough parent trees are still alive) but soon succumb to current levels of ozone and sulfur dioxide in the environment or are suppressed by tolerant neighbors. This phenomenon has been documented anecdotally and is more aptly called tree decline instead of forest decline. An emerging working hypothesis to explain recent reports of unusual eastern white pine tolerance is that sufficient time has elapsed for tree decline to have occurred leading to a gradual elimination of sensitive genotypes from populations.     

Status of the Southern Carpathian forests in the long-term ecological research network

Air pollution, bulk precipitation, throughfall, soil condition, foliar nutrients, as well as forest health and growth were studied in 2006–2009 in a long-term ecological research (LTER) network in the Bucegi Mountains, Romania. Ozone (O₃) was high indicating a potential for phytotoxicity. Ammonia (NH₃) concentrations rose to levels that could contribute to deposition of nutritional nitrogen (N) and could affect biodiversity changes. Higher that 50% contribution of acidic rain (pH?<?5.5) contributed to increased acidity of forest soils. Foliar N concentrations for Norway spruce (Picea abies), Silver fir (Abies alba), Scots pine (Pinus sylvestris), and European beech (Fagus sylvatica) were normal, phosphorus (P) was high, while those of potassium (K), magnesium (Mg), and especially of manganese (Mn) were significantly below the typical European or Carpathian region levels. The observed nutritional imbalance could have negative effects on forest trees. Health of forests was moderately affected, with damaged trees (crown defoliation >25%) higher than 30%. The observed crown damage was accompanied by the annual volume losses for the entire research forest area up to 25.4%. High diversity and evenness specific to the stand type’s structures and local climate conditions were observed within the herbaceous layer, indicating that biodiversity of the vascular plant communities was not compromised.     

Crown condition dynamics of oak in southern Sweden 1988’999

Crown defoliation of oak (Quercus robur and Q. petraea) was analysed in 808 trees during three forest condition surveys (1988, 1993, and 1999) in the southern Sweden. From 1988 to 1999 crown defoliation increased by more than 20%. Changes in crown defoliation were related to the pH in the upper 20–30 cm of the mineral soils, which was closely connected to other measures of soil fertility (cation exchange capacity, CEC and C/N ratio). Trees growing on soils with a high pH (≥4.00, in BaCl₂ filtrate), high CEC and low C/N ratio had significantly lower crown defoliation than trees growing on more acid soils (pH <4.00), indicating that less favourable soil conditions may further enhance oak decline. Age did not differentiate trees with respect to crown defoliation, indicating that decline in crown condition was not due to an age-related increase in crown transparency. Considering only trees younger than 100 years, a significant interaction was observed between changes in crown defoliation and soil pH. Trees younger than 100 years old growing on more acidic soils had a greater increase in crown transparency than trees on more basic soils between 1988 and 1999. Trees ≥100 years old had significantly higher defoliation on more acidic than on more basic soils, however defoliation dynamics of these trees over 1988–99 was not related to soil acidity. Two biotic agents (insect and fungal leaf infections) evaluated in this study did not prove to be important drivers of defoliation dynamics.     

Relationship Between Crown Condition and Tree Diameter Growth in Southern Swedish Oaks

We studied correlation between crown conditions and tree-ring widths in 260 trees of pedunculate oak (Quercus robur L.) growing on 33 sites in southern Sweden. The tree-ring increment over 1998-2002 was highest in trees with healthy crowns, intermediate in trees with moderately declined crowns, and lowest in trees with heavily declining crowns. The time period with significant correlation between crown status and tree-ring increment varied between 10 years (given autocorrelation in tree-ring chronologies preserved) and 4 years (autocorrelation removed). In pairwise comparisons of three crown classes, differences in tree-ring increment between trees with healthy crowns and trees with heavily declining crowns were the most pronounced, Fisher LSD P value staying below 0.05 over 13 years (autocorrelation preserved ) or 4 years (autocorrelation removed). Over two 5-year periods (1993-1997 vs. 1998-2002) the cumulative increment increased significantly for trees with healthy crowns, did not change in trees with moderately declining crowns, and significantly decreased in trees with heavily declining crowns. For trees with healthy crowns, this dynamics may represent growth recovery after 1992 drought. Instead, oaks with defoliation above 60% appear to reach a threshold in their ability to recover growth. At sites on nutrient-poor soils cumulative increments over 1998-2002 differed significantly among trees with different crown condition and no differences were observed at sites on nutrient-rich soils. Analyses and interpretation of the oak growth trends as recovered from tree-ring chronologies may be improved by controlling for the crown status of the trees sampled, e.g., by using sampling strategy that would represent the average crown and growth conditions of the sites.     

Large-scale carbon stock assessment of woody vegetation in tropical dry deciduous forest of Sathanur reserve forest,Eastern Ghats,India

Tropical dry forests are one of the most widely distributed ecosystems in tropics, which remain neglected in research, especially in the Eastern Ghats. Therefore, the present study was aimed to quantify the carbon storage in woody vegetation (trees and lianas) on large scale (30, 1 ha plots) in the dry deciduous forest of Sathanur reserve forest of Eastern Ghats. Biomass of adult (≥10 cm DBH) trees was estimated by species-specific allometric equations using diameter and wood density of species whereas in juvenile tree population and lianas, their respective general allometric equations were used to estimate the biomass. The fractional value 0.4453 was used to convert dry biomass into carbon in woody vegetation of tropical dry forest. The mean aboveground biomass value of juvenile tree population was 1.86 Mg/ha. The aboveground biomass of adult trees ranged from 64.81 to 624.96 Mg/ha with a mean of 245.90 Mg/ha. The mean aboveground biomass value of lianas was 7.98 Mg/ha. The total biomass of woody vegetation (adult trees + juvenile population of trees + lianas) ranged from 85.02 to 723.46 Mg/ha, with a mean value of 295.04 Mg/ha. Total carbon accumulated in woody vegetation in tropical dry deciduous forest ranged from 37.86 to 322.16 Mg/ha with a mean value of 131.38 Mg/ha. Adult trees accumulated 94.81% of woody biomass carbon followed by lianas (3.99%) and juvenile population of trees (1.20%). Albizia amara has the greatest biomass and carbon stock (58.31%) among trees except for two plots (24 and 25) where Chloroxylon swietenia contributed more to biomass and carbon stock. Similarly, Albizia amara (52.4%) showed greater carbon storage in juvenile population of trees followed by Chloroxylon swietenia (21.9%). Pterolobium hexapetalum (38.86%) showed a greater accumulation of carbon in liana species followed by Combretum albidum (33.04%). Even though, all the study plots are located within 10 km radius, they show a significant spatial variation among them in terms of biomass and carbon stocks which could be attributed to variation in anthropogenic pressures among the plots as well as to changes in tree density across landscapes. Total basal area of woody vegetation showed a significant positive (R ² = 0.978; P = 0.000) relationship with carbon storage while juvenile tree basal area showed the negative relationship (R ² = 0.4804; P = 0.000) with woody carbon storage. The present study generates a large-scale baseline data of dry deciduous forest carbon stock, which would facilitate carbon stock assessment at a national level as well as to understand its contribution on a global scale.