A meta-analysis of management effects on forest carbon storage

ABSTRACT

Forest management can have substantial impacts on ecosystem carbon storage, but those effects can vary significantly with management type and species composition. We used systematic review methodology to identify and synthesize effects of thinning and/or burning, timber harvesting, clear-cut, and wildfire on four components of ecosystem carbon: aboveground vegetation, soil, litter, and deadwood. We performed a meta-analysis on studies from the United States and Canada because those represented 85% of the studies conducted worldwide. We found that the most important variables in predicting effect sizes (ratio of carbon stored in treated stands versus controls) were, in decreasing order of importance, ecosystem carbon component, time since treatment, and age of control. Management treatment was the least important of all the variables we examined, but the trends we found suggest that thinning and/or burning treatments resulted in less carbon loss than wildfire or clear-cut. This finding is consistent with recent modeling studies indicating that forest management is unimportant to long-term carbon dynamics relative to the effects of large-scale natural disturbances (e.g., drought, fire, pest outbreak). However, many data gaps still exist on total ecosystem carbon, particularly in regions other than North America, and in timber production forests and plantations.     

Modeling annual production and carbon fluxes of a large managed temperate forest using forest inventories, satellite data and field measurements

We evaluated annual productivity and carbon fluxes over the Fontainebleau forest, a large heterogeneous forest region of 17,000 ha, in terms of species composition, canopy structure, stand age, soil type and water and mineral resources. The model is a physiological process-based forest ecosystem model coupled with an allocation model and a soil model. The simulations were done stand by stand, i.e., 2992 forest management units of simulation. Some input parameters that are spatially variable and to which the model is sensitive were calculated for each stand from forest inventory attributes, a network of 8800 soil pits, satellite data and field measurements. These parameters are: (1) vegetation attributes: species, age, height, maximal leaf area index of the year, aboveground biomass and foliar nitrogen content; and (2) soil attributes: available soil water capacity, soil depth and soil carbon content. Main outputs of the simulations are wood production and carbon fluxes on a daily to yearly basis. Results showed that the forest is a carbon sink, with a net ecosystem exchange of 371 g C m(-2) year(-1). Net primary productivity is estimated at 630 g C m(-2) year(-1) over the entire forest. Reasonably good agreement was found between simulated trunk relative growth rate (2.74%) and regional production estimated from the National Forest Inventory (IFN) (2.52%), as well as between simulated and measured annual wood production at the forest scale (about 71,000 and 68,000 m(3) year(-1), respectively). Results are discussed species by species.     

Evaluation of the growth function of an empirical forest scenario model

Forests have an important role in the global carbon cycle as carbon pools, sinks and sources, and their quantification has become a relevant task. Empirical models based on national forest inventories are widely used for the assessment of carbon sequestration. However, these models do not treat explicitly all the processes occurring in the ecosystem, as they are mainly based on statistical relations to estimate forest development. Therefore, there is a need for validation of these models to increase confidence in the predictions of future forest development. This study evaluates an empirical single-tree model that was developed in Switzerland (MASSIMO). The accuracy and precision of the growth function of the model is evaluated with data from the National Forest Inventory (NFI) of Liechtenstein. MASSIMO was found to predict the basal area per hectare of the Liechtenstein data very precisely (underestimation of 0.65%). The main differences between observed and predicted diameter increment occur mostly for larger DBH classes, where the increment is underestimated by the model. However, these differences may be related to the precision of the input variables. For example, the explanatory variable stand age is determined with relatively low precision; therefore it shows a high variability. For future model development, either the variable stand age should be estimated more reliably, or stand age should not be an explanatory variable of the growth function.     

Forest carbon storage in the northeastern United States: Net effects of harvesting frequency,post-harvest retention,and wood products

Temperate forests are an important carbon sink, yet there is debate regarding the net effect of forest management practices on carbon storage. Few studies have investigated the effects of different silvicultural systems on forest carbon stocks, and the relative strength of in situ forest carbon versus wood products pools remains in question. Our research describes (1) the impact of harvesting frequency and proportion of post-harvest structural retention on carbon storage in northern hardwood-conifer forests, and (2) tests the significance of including harvested wood products in carbon accounting at the stand scale. We stratified Forest Inventory and Analysis (FIA) plots to control for environmental, forest structural and compositional variables, resulting in 32 FIA plots distributed throughout the northeastern U.S. We used the USDA Forest Service's Forest Vegetation Simulator to project stand development over a 160 year period under nine different forest management scenarios. Simulated treatments represented a gradient of increasing structural retention and decreasing harvesting frequencies, including a “no harvest” scenario. The simulations incorporated carbon flux between aboveground forest biomass (dead and live pools) and harvested wood products. Mean carbon storage over the simulation period was calculated for each silvicultural scenario. We investigated tradeoffs among scenarios using a factorial treatment design and two-way ANOVA. Mean carbon sequestration was significantly (α = 0.05) greater for “no management” compared to any of the active management scenarios. Of the harvest treatments, those favoring high levels of structural retention and decreased harvesting frequency stored the greatest amounts of carbon. Classification and regression tree analysis showed that management scenario was the strongest predictor of total carbon storage, though site-specific variables were important secondary predictors. In order to isolate the effect of in situ forest carbon storage and harvested wood products, we did not include the emissions benefits associated with substituting wood fiber for other construction materials or energy sources. Modeling results from this study show that harvesting frequency and structural retention significantly affect mean carbon storage. Our results illustrate the importance of both post-harvest forest structure and harvesting frequency in carbon storage, and are valuable to land owners interested in managing forests for carbon sequestration.     

Distribution of biomass and carbon in even‐aged stands of Norway spruce (Picea abies (L.) Karst.): A case study on spacing and thinning effects in northern Denmark

The main objective of this case study was to explore the possible influence of forest management on the levels and distribution of biomass and carbon (C) in even-aged stands of Norway spruce [Picea abies (L.) Karst.] in Denmark. Data originated from a long-term thinning experiment and an adjacent spacing experiment at stand ages of 58 and 41 years, respectively. Biomass of 16 trees from different thinning and spacing treatments was measured or partly estimated, and soils were sampled for determination of C stocks. All trees in each plot were measured for stem diameter and some for total height, to allow for scaling-up results to stand-level estimates. For trees of similar size, foliage biomass tended to be higher in the spacing experiment, which was located on slightly more fertile land. Foliage biomass increased with increasing thinning grade, but the effect could not be separated from that of tree size. At stand level, foliage biomass tended to increase with increasing spacing as well as with increasing thinning grade. For branchwood, stems and roots (including below-ground stump), the biomass increased with increasing tree size and stand volume at tree and stand level, respectively, but no differences between stands, spacings or thinning grades were observed, apart from that expressed by tree size or stand volume. At stand level, C stocks of all biomass compartments decreased with increasing thinning grade, while the distribution between compartments was hardly influenced. The ratio between above-ground and stem biomass was about 1.21 at stand level, while the ratio between below- and above-ground biomass was about 0.17. Thinning influenced the C stock of the forest floor and mineral soil oppositely, resulting in no effect of thinning on total soil C.     

Effects of harvesting intensity on carbon stocks in eastern Canadian red spruce (Picea rubens) forests: An exploratory analysis using the CBM-CFS3 simulation model

Carbon stocks and stock changes in a chronosequence of 24 red spruce (Picea rubens Sarg.) dominated stands in Nova Scotia, Canada, were compared against predictions from the Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3). Regression analysis of the observed versus simulated total ecosystem C stocks indicates the model's predictions accounted for 81.1% of the variation in the observed biomass data and for 63.2% of the variation in total ecosystem C data; however, the simultaneous F-test for bias was significant. Discrepancy between the observed and simulated total ecosystem C data was primarily caused by differences in dead organic matter C pool estimates, with the model consistently predicting higher soil C throughout stand development. Changes to model parameters were not warranted however, as the field data measured only a portion of the mineral soil profile represented in the model.

Clear-cut and partial-cut harvesting scenarios for red spruce stands were simulated to examine the impacts of clear-cut and partial-cut harvesting on C stocks. Total ecosystem C increased in the partial-cut stand throughout the 240-year simulation from 308.9 to 327.3 Mg C ha⁻¹, while it decreased in the clear-cut stand to 305.8 Mg C ha⁻¹. Enhanced C sequestration in the partial-cut stand was a consequence of the residual standing biomass providing a continuous source of litterfall and reducing decomposition rates of the forest floor. Choice of harvest system clearly affects forest ecosystem C stocks, but also affects the amount of C removed from forests to meet society's needs. Over the period of the simulation, partial cutting provided 115.6 Mg C ha⁻¹ of merchantable timber, while clear-cutting provided 132.4 Mg C ha⁻¹. Strategies aimed at using forest management to mitigate atmospheric C increases need to assess both the direct impacts on the forest ecosystem and the indirect impacts through product and energy substitution associated with the use and storage of harvested biomass.     

Sustainable Management of Forests for Atmospheric CO2 Depletion

Abstract

The topic of forest sector carbon balance in connection with climate changes currently has both great scientific and political importance for ecological sustainability on a global scale. The concentration of CO2 in the atmosphere has increased by 1-2 ppm per year in the last few decades. The present paper examines the actual and potential role of forest management to deplete atmospheric CO2 concentration, with specific reference to the Italian situation as a case study. Italian carbon emission derived from fossil fuels amounts to 432 Mt/year, of which 65% comes from burning oil. Annual CO2 absorption, estimated by combining the 1985 National Forest Inventory data with selected biomass data, proves to be quite relevant, amounting to more than 10% of the annual Italian CO2 emission. This is a prudent estimate, since no account is taken of the contributions of non-tree vegetation and soil. Current forest management standards are mainly oriented to conservation. Optimisation of forest management specifically purposed also to carbon storage and non-wood products substitution may further enhance the role of Italian forest sector for atmospheric CO2 depletion: in such a view, practical issues (amelioration of existing forest stands; adjustment of harvesting yield to the actual production capacity of forest stands and adjustment of production standards towards high durable wood products; afforestation and tree cropping by means of changes in land use) are addressed within a sustainability framework.     

Potential knowledge gain in large-scale simulations of forest carbon fluxes from remotely sensed biomass and height

Global vegetation models (GVMs) simulate CO₂, water and energy fluxes at large scales, typically no smaller than 10 × 10 km. GVM simulations are thus expected to simulate the average functioning, but not the local variability. The two main limiting factors in refining this scale are (1) the scale at which the pedo-climatic inputs - temperature, precipitation, soil water reserve, etc. - are available to drive models and (2) the lack of geospatial information on the vegetation type and the age of forest stands. This study assesses how remotely sensed biomass or stand height could help the new generation of GVMs, which explicitly represent forest age structure and management, to better simulate this local variability. For the ORCHIDEE-FM model, we find that a simple assimilation of biomass or height brings down the root mean square error (RMSE) of some simulated carbon fluxes by 30-50%. Current error levels of remote sensing estimates do not impact this improvement for large gross fluxes (e.g. terrestrial ecosystem respiration), but they reduce the improvement of simulated net ecosystem productivity, adding 13.5-21% of RMSE to assimilations using the in situ estimates. The data assimilation under study is more effective to improve the simulation of respiration than the simulation of photosynthesis. The assimilation of height or biomass in ORCHIDEE-FM enables the correct retrieval of variables that are more difficult to measure over large areas, such as stand age. A combined assimilation of biomass and net ecosystem productivity could possibly enable the new generation of GVMs to retrieve other variables that are seldom measured, such as soil carbon content.     

基于国家森林资源清查数据的不同生物量和碳储量估计方法的对比分析

[目的]通过对不同生物量和碳储量的估计方法进行对比分析,为确定在国家森林资源清查中生物量和碳储量的具体估计方法提供依据。[方法]以广东省2012年森林资源清查的100个杉木林和80个马尾松林的实测样地资料为基础,利用近年来我国建立的主要树种立木生物量模型,对改进IPCC法、生物量模型法和转换因子连续函数法(即方精云法)3种方法按一元和二元模型共6种方案进行了对比;同时,基于改进IPCC法一元和二元模型的生物量估计值,用平均含碳系数法、组分含碳系数法和固定含碳系数(0.5或0.47)法分别对碳储量进行估计。[结果]用二元生物量模型法得到的杉木林和马尾松林样地的总生物量分别为320 Mg和331 Mg,一元生物量模型法的结果分别相差0.9%和6.2%;改进IPCC法的估计结果,采用二元和一元模型时杉木林分别相差-3.6%和-11.9%,马尾松林分别相差-8.5%和-19.6%;而方精云法的估计结果,采用二元和一元模型时杉木林分别相差6.65倍和6.60倍,马尾松林分别相差-14.3%和-18.0%。平均含碳系数法和组分含碳系数法的碳储量估计结果,杉木林仅相差0.2%,马尾松林相差约0.4%;固定含碳系数法的估计结果因树种而异,对杉木林要低估0.6%5.4%,对马尾松林要低估3.3%9.1%。[结论]对生物量的估计,采用生物量模型法准确性最高,而林木水平的生物量模型其预估精度要高于林分水平的模型;IPCC法是基于材积源的通用方法,将其中的缺省参数改进为可变参数模型,可大大提高方法的适应性;方精云法只是基于IPCC法所建立的林分水平模型在大尺度上的一种具体应用方法,其精度要低于林木水平的生物量模型法,不适于中小尺度应用。对碳储量的估计,采用平均含碳系数法与组分含碳系数法差异很小,但采用固定含碳系数法则误差较大。     

Estimating carbon stock in secondary forests: Decisions and uncertainties associated with allometric biomass models

Secondary forests are a major terrestrial carbon sink and reliable estimates of their carbon stocks are pivotal for understanding the global carbon balance and initiatives to mitigate CO₂ emissions through forest management and reforestation. A common method to quantify carbon stocks in forests is the use of allometric regression models to convert forest inventory data to estimates of aboveground biomass (AGB). The use of allometric models implies decisions on the selection of extant models or the development of a local model, the predictor variables included in the selected model, and the number of trees and species for destructive biomass measurements. We assess uncertainties associated with these decisions using data from 94 secondary forest plots in central Panama and 244 harvested trees belonging to 26 locally abundant species. AGB estimates from species-specific models were used to assess relative errors of estimates from multispecies models. To reduce uncertainty in the estimation of plot AGB, including wood specific gravity (WSG) in the model was more important than the number of trees used for model fitting. However, decreasing the number of trees increased uncertainty of landscape-level AGB estimates substantially, while including WSG had limited effects on the accuracy of the landscape-level estimates. Predictions of stand and landscape AGB varied strongly among models, making model choice an important source of uncertainty. Local models provided more accurate AGB estimates than foreign models, but high variability in carbon stocks across the landscape implies that developing local models is only justified when landscape sampling is sufficiently intensive.     

Carbon dynamics of North American boreal forest after stand replacing wildfire and clearcut logging

Boreal forest carbon (C) storage and sequestration is a critical element for global C management and is largely disturbance driven. The disturbance regime can be natural or anthropogenic with varying intensity and frequency that differ temporally and spatially the boreal forest. The objective of this review was to synthesize the literature on C dynamics of North American boreal forests after most common disturbances, stand replacing wildfire and clearcut logging. Forest ecosystem C is stored in four major pools: live biomass, dead biomass, organic soil horizons, and mineral soil. Carbon cycling among these pools is inter-related and largely determined by disturbance type and time since disturbance. Following a stand replacing disturbance, (1) live biomass increases rapidly leading to the maximal biomass stage, then stabilizes or slightly declines at old-growth or gap dynamics stage at which late-successional tree species dominate the stand; (2) dead woody material carbon generally follows a U-shaped pattern during succession; (3) forest floor carbon increases throughout stand development; and (4) mineral soil carbon appears to be more or less stable throughout stand development. Wildfire and harvesting differ in many ways, fire being more of a chemical and harvesting a mechanical disturbance. Fire consumes forest floor and small live vegetation and foliage, whereas logging removes large stems. Overall, the effects of the two disturbances on C dynamics in boreal forest are poorly understood. There is also a scarcity of literature dealing with C dynamics of plant coarse and fine roots, understory vegetation, small-sized and buried dead material, forest floor, and mineral soil.     

Mapping tree aboveground biomass and carbon in Omo Forest Reserve Nigeria using Landsat 8 OLI data

Protected areas in Nigeria are important ecosystems for carbon storage. The aim of this study was to estimate and map tree aboveground biomass (TAGB) and carbon (TAGC) within a tropical forest in Nigeria. Stepwise regression analysis was implemented to develop models for predicting TAGB in the forest stand, by integrating field TAGB data with Landsat 8 OLI data. Spectral variables used in the analysis include spectral bands, vegetation indices, tasseled cap indices and principal components. Model validation was performed using independent sample plots. The results showed that incorporating more than one category of spectral variables improved the prediction of TAGB. The best-fit model was applied to map the spatial distribution of TAGB and TAGC. The TAGC was estimated as 52.3% of TAGB, based on the average carbon content of tree species derived in this study. Average TAGB and TAGC estimates for the forest stand were 373.1 ± 165.4 t ha^?1 and 194 ± 82.7 t ha^?1, respectively. Reliable estimates of TAGB and TAGC for the forest reserve were obtained. This study provides important information required to manage the forest stand for optimal carbon sequestration.     

Additive prediction of aboveground biomass for Pinus radiata (D. Don) plantations

A general and two country-specific systems of additive equations were developed to predict aboveground biomass of Pinus radiata plantations from stand variables that are routinely measured in inventory plots and predicted by conventional growth and yield models. The data for this work consisted of 319 plot-based biomass estimates that were derived from individual tree biomass equations developed in situ. These plot-based biomass estimates were compiled from studies reported in the forestry and ecological literature since 1960 and also from personal communications. They represent more than 60 sites worldwide with a majority in Australia and New Zealand. The systems of additive biomass equations developed from these data provide an alternative and addition to the current methods of estimating the aboveground biomass of P. radiata plantations. They also provide a direct linkage between forest inventory measures, outputs from conventional growth and yield models and biomass and carbon stock estimates at the same spatial scale. This direct linkage provides a new basis for scaling to a remote sensing image from which biomass and carbon stocks across the landscape can be mapped. Comparisons of prediction accuracies between this approach and other methods such as scaling up from individual tree biomass estimates and biomass expansion factors highlighted considerable methodological differences in the estimates of aboveground biomass and associated uncertainties over a range of stand age and conditions. These differences should be carefully evaluated before adopting a particular method to estimate aboveground biomass and carbon stocks of P. radiata plantations at a local, regional or national scale.     

Species substitution for carbon storage: Sessile oak versus Corsican pine in France as a case study

Species choice is potentially an important management decision for increasing carbon stocks in forest ecosystems. The substitution of a slow-growing hardwood species (Quercus petraea) by a fast-growing conifer plantation (Pinus nigra subsp. laricio) was studied in central France. Simulations of carbon stocks in tree biomass were conducted using stand growth models Fagacées for sessile oak and PNL for Corsican pine. The changes in soil carbon were assessed using the Century model and data from two European soil monitoring networks: 16 km × 16 km grid and RENECOFOR. Carbon in wood products was assessed with life cycle analysis and lifespan of final products. However, only carbon stocks and their variation were accounted for: effects of energy-consuming materials or fossil fuel substitution are excluded from the analysis. To compare the growth of these two types of forest stands, an important part of the study was to assess the productivity of both species at the same site, using National Forest Inventory data.     

A diameter growth index method for standardization of forest data inventoried at different dates

A model of tree diameter growth during the growth season was developed to standardize the forest data from different inventory dates. A diameter growth index is defined and its relation with the number of growing days is established. Parameters characterizing this relationship are estimated using accurate tree ring width measurements and other stand and tree related variables from the Swedish National Forest Inventory data for 1989. The residual analyses show that the model is an effective expression of the actual growth and the results are consistent with an earlier used tree growth model. Some climatic data are tested for model improvement, but no essential improvement is gained given the data available.     

A non-linear model to predict crown recession of Norway spruce (<Emphasis Type="Italic">Picea abies</Emphasis> [L.] Karst.) in Austria

In this study, a non-linear model was developed that predicts the five-year change of height to crown base (HCB) of Norway spruce (Picea abies [L.] Karst.). Data were available from the Austrian National Forest Inventory and comprised 2,419 trees from 1,637 permanent sample plots measured during 1981 and 2002. The dynamic model explained 36% of the variation in the observed change of HCB. It is well behaved and meets biological expectations. Based on five independent data sets, the predictive ability of the new dynamic model was compared to an already existing static crown ratio model. For this comparison, the models were applied as follows: the new ∆ HCB model was used to predict the change in HCB directly. For the semi-dynamic method, the static model was applied at the end and at the start of the growth period to obtain two estimates of HCB. The difference of these two estimates was then added to the initial HCB. For the static method, the model was only applied at the end of the prediction period to obtain the new estimate of HCB. Except for one plot, the new ∆ HCB model yielded the smallest BIAS and the highest precision, followed by the semi-dynamic and the static method. Because the independent data sets cover a broad range of age classes and thinning regimes, the validation results also indicate that the new ∆ HCB is robust and the effect of stand management is adequately represented.     

National inventories of down and dead woody material forest carbon stocks in the United States: Challenges and opportunities

Concerns over the effect of greenhouse gases and consequent international agreements and regional/national programs have spurred the need for comprehensive assessments of forest ecosystem carbon stocks. Down and dead woody (DDW) materials are a substantial component of forest carbon stocks; however, few surveys of DDW carbon stocks have been conducted at national-scales around the world. This study uses the DDW survey of the United States as a case study to examine the challenges of inventorying DDW at a national scale, reviews how dead wood carbon pools are currently estimated in the National Greenhouse Gas Inventory (NGHGI), and suggests opportunities for improving such inventories. The US currently estimates national DDW carbon stocks using models with standing live tree attributes as predictor variables, calibrated using preliminary DDW field estimates. In recent years, implementation of a national DDW inventory has resulted in inventory-based DDW estimates. National field-based DDW estimates follow the national patterns of DDW carbon dispersion seen in earlier model-based estimates. Although the current DDW inventory provides fairly repeatable measurements within a statistically defensible national sample design for producing national estimates of DDW carbon stocks, improving numerous aspects of the DDW survey would may improve the accuracy and precision of C estimates reported in the NGHGI.     

Impacts of initial stand density and thinning regimes on energy wood production and management-related CO<Subscript>2</Subscript> emissions in boreal ecosystems

An ecosystem model (Sima) was utilised to investigate the impact of forest management (by changing both the initial stand density and basal area thinning thresholds from current recommendations) on energy wood production (at energy wood thinning and final felling) and management-related carbon dioxide (CO₂) emissions for the energy wood production in Finnish boreal conditions (62°39′ N, 29°37′ E). The simultaneous effects of energy wood, timber and C stocks in the forest ecosystem (live and dead biomass) were also assessed. The analyses were carried out at stand level during a rotation period of 80 years for Scots pine (Pinus sylvestris L.) and Norway spruce (Picea abies L. Karst.) growing in different fertility sites. Generally, the results showed that decreased basal area thinning thresholds, compared with current thinning, reduced energy wood (logging residues) and timber production, as well as carbon stocks in the forest ecosystem. Conversely, increased thinning thresholds increased energy wood production (ca. 1–27%) at both energy wood thinning and final felling and reduced CO₂ emissions (ca. 2–6%) related to the production chain (e.g. management operations), depending on the thinning threshold levels, initial stand density, species and site. Increased thinning thresholds also enhanced timber production and carbon stocks in the forest ecosystem. Additionally, increased initial stand density enhanced energy wood production for energy wood thinning for both species, but this reduced energy wood production at final felling for Scots pine and Norway spruce. This study concluded that increases in both initial stand density and thinning thresholds, compared with the current level, could be useful in energy wood, timber and carbon stocks enhancement, as well as reducing management-related CO₂ emissions for energy wood production. Only 2.4–3.3% of input of the produced energy (energy wood) was required during the whole production chain, depending on the management regime, species and sites. However, a comprehensive substitution analysis of wood-based energy, in respect to environmental benefits, would also require the inclusion of CO₂ emissions related to ecosystem processes (e.g. decomposition).     

Reliable data on fine-root turnover from sequential soil coring in an old carbon budget for a 14-year-old Scots pine from the late 1970s: Comments on Majdi et al., Scandinavian Journal of Forest Research 22: 299–303

Abstract

Comprehensive data from different research workers were included in the compilation of a carbon budget for a 14-year-old Scots pine (Pinus sylvestris) in the late 1970s, within the SWECON project (the Swedish Coniferous Forest Project). In a recent paper in the Scandinavian Journal of Forest Research, the authors published a surprisingly high turnover rate of fine roots (7.4 year^?1), maintaining that they had used our old SWECON data from our sequential soil coring. However, a close examination of our original data suggests a turnover of fine-root biomass of 2.3 and for fine-root standing crop (biomass+necromass) of 2.0 year^?1. Supporting evidence is available from other forest sites suggesting that our turnover rates were correctly estimated. Certain errors may exist in different parts of our old carbon budget, e.g. some measurements were carried out for different parts of the tree, while others were attributed to the whole stand. The sequential soil coring technique still remains the best technique available for fine-root growth and turnover estimates in forest stands.     

Predicting breeding bird occurrence by stand- and microhabitat-scale features in even-aged stands in the Central Appalachians

Spatial scale is an important consideration when managing forest wildlife habitat, and models can be used to improve our understanding of these habitats at relevant scales. Our objectives were to determine whether stand- or microhabitat-scale variables better predicted bird metrics (diversity, species presence, and abundance) and to examine breeding bird response to clearcut size and age in a highly forested landscape. In 2004-2007, vegetation data were collected from 62 even-aged stands that were 3.6-34.6 ha in size and harvested in 1963-1990 on the Monongahela National Forest, WV, USA. In 2005-2007, we also surveyed birds at vegetation plots. We used classification and regression trees to model breeding bird habitat use with a suite of stand and microhabitat variables. Among stand variables, elevation, stand age, and stand size were most commonly retained as important variables in guild and species models. Among microhabitat variables, medium-sized tree density and tree species diversity most commonly predicted bird presence or abundance. Early successional and generalist bird presence, abundance, and diversity were better predicted by microhabitat variables than stand variables. Thus, more intensive field sampling may be required to predict habitat use for these species, and management may be needed at a finer scale. Conversely, stand-level variables had greater utility in predicting late-successional species occurrence and abundance; thus management decisions and modeling at this scale may be suitable in areas with a uniform landscape, such as our study area. Our study suggests that late-successional breeding bird diversity can be maximized long-term by including harvests >10 ha in size into our study area and by increasing tree diversity. Some harvesting will need to be incorporated regularly, because after 15 years, the study stands did not provide habitat for most early successional breeding specialists.