基于TM影像、森林资源清查数据和人工神经网络的森林碳空间分布模拟

森林是陆地生态系统中最大的碳库,在全球碳平衡和减缓全球气候变化方面发挥着不可替代的作用。当前主要利用森林资源清查数据和优势树种材积源-生物量的关系进行碳储量估算,在此基础上有效结合遥感影像数据将会更好的满足相关部门对国家和区域森林碳储量计算的需求。利用临安市2004年森林资源清查的930个样地数据和同年度Landsat TM影像数据,提取6个波段灰度值以及与碳储量相关性相对较大的3个波段组合,结合人工神经网络对研究区森林碳储量及其分布进行有效模拟。结果显示,用误差反向传播算法训练神经网络较好的重建了森林碳密度空间分布和变化,森林碳地上部分模拟结果与样地实测值之间的一致性好,全区域模拟结果森林碳平均值为0.98Mg(10.89Mg/hm²),总体森林碳密度模拟结果低于样地平均值约13%,进一步验证了人工神经网络在对大范围森林碳估算与模拟上具有较好的效果,为区域森林碳储量的估测研究提供有效的方法支持。     

Using multi-temporal tree inventory data in eucalypt forestry to benchmark global high-resolution canopy height models. A showcase in Mato Grosso,Brazil

The global monitoring of forest structure worldwide is increasingly being supported by refined and enhanced satellite mission datasets. Forest canopy height is a global metric to characterise and monitor dynamics in forest ecosystems worldwide. Satellite mapping missions as NASA's Global Ecosystem Dynamics Investigation (GEDI) are creating opportunities to refine global forest canopy height models adding forest structural information to time-series satellite imagery. A recent global canopy height model presented by Lang et al., (2022) using GEDI and 10-m Sentinel-2 and the map from Potapov et al., (2020) using GEDI and Landsat are both tested in this study using multi-temporal tree-level data collected over eucalypt plantations in Brazil. Our results at plot-level showed Lang et al., (2022)’s estimates of canopy height came short compared to 2020 maximum and mean tree height records in the plots, 7.6 and 3.6 m, respectively, but adding CHM standard deviation improves the agreement of ground records for maximum tree height. Higher errors were computed for the plots in 2019 using the Potapov's 30-m CHM: 14.2 and 9.5 m, respectively. Averaged stand values were more similar between the three sources tested. We report improvement from the 30-m CHM to the 10-m, but still height saturation problems were observed when accounting for height differences in tall eucalypt trees. As more global products for forest height and biomass are becoming available to users, more validation exercises as presented in this study are needed to assess the suitability of CHM products to forestry needs, and facilitate the uptake and actionability of the next generation of global height and biomass products. We provide recommendations and insights on the use of GEDI laser data for global mapping and on the potential of commercial forestry areas to benchmark the accuracy of satellite mapping missions focusing on tree height estimation in the tropics.     

Landscape-Scale Controls on Aboveground Forest Carbon Stocks on the Osa Peninsula,Costa Rica

Tropical forests store large amounts of carbon in tree biomass, although the environmental controls on forest carbon stocks remain poorly resolved. Emerging airborne remote sensing techniques offer a powerful approach to understand how aboveground carbon density (ACD) varies across tropical landscapes. In this study, we evaluate the accuracy of the Carnegie Airborne Observatory (CAO) Light Detection and Ranging (LiDAR) system to detect top-of-canopy tree height (TCH) and ACD across the Osa Peninsula, Costa Rica. LiDAR and field-estimated TCH and ACD were highly correlated across a wide range of forest ages and types. Top-of-canopy height (TCH) reached 67 m, and ACD surpassed 225 Mg C ha^-1, indicating both that airborne CAO LiDAR-based estimates of ACD are accurate in tall, high-biomass forests and that the Osa Peninsula harbors some of the most carbon-rich forests in the Neotropics. We also examined the relative influence of lithologic, topoedaphic and climatic factors on regional patterns in ACD, which are known to influence ACD by regulating forest productivity and turnover. Analyses revealed a spatially nested set of factors controlling ACD patterns, with geologic variation explaining up to 16% of the mapped ACD variation at the regional scale, while local variation in topographic slope explained an additional 18%. Lithologic and topoedaphic factors also explained more ACD variation at 30-m than at 100-m spatial resolution, suggesting that environmental filtering depends on the spatial scale of terrain variation. Our result indicate that patterns in ACD are partially controlled by spatial variation in geologic history and geomorphic processes underpinning topographic diversity across landscapes. ACD also exhibited spatial autocorrelation, which may reflect biological processes that influence ACD, such as the assembly of species or phenotypes across the landscape, but additional research is needed to resolve how abiotic and biotic factors contribute to ACD variation across high biomass, high diversity tropical landscapes.     

Biomass,carbon density and diversity of tree species in tropical dry deciduous forests in Central India

Tropical dry deciduous forests play a significant role in regulating the biogeochemical cycles. Present study assesses the carbon stock of tropical dry deciduous forests varying in tree density, basal cover, and diversity located in Singrauli district of Madhya Pradesh in Central India. Field sampling was carried out in six forest sites viz., Chitrangi, East Sarai, Gorbi, Renukoot, West Sarai, and Waidhan, of Singrauli. A total of 29 tree species belonging to 18 families were recorded across the forest ranges where tree density, basal area and diversity values varied from 702 (Gorbhi Range) – 1671 (East Sarai range) individuals ha^?1; 15.43 (Renukhund range) – 71.76 m² ha^?1 (Chitrange range) and 0.69 (West Sarai range) – 2.52 (Gorbi range), respectively. Total biomass estimated ranged from 103.32 (Renukhund range) – 453.54 Mg ha^?1 (Chitrange range) while the total tree carbon density varied from 48.97 to 214.97 Mg C ha^?1. The variation in carbon storage in the studied ranges was found dependent on density of trees in different diameter and age classes and tree species diversity. Diospyros melanoxylon, Butea monosperma, Shorea robusta, Senegalia catechu, Spondias pinnata, and Lagerstroemia parviflora were the dominant species at different study sites (forest ranges) and contributed towards higher carbon storage in respective forest ranges. Study endorses field-based approach for carbon estimations based on above and belowground assessments as a more realistic approach to understand sink potential of natural forests.     

Modeling Forest Mortality Caused by Drought Stress: Implications for Climate Change

Climate change is expected to affect forest landscape dynamics in many ways, but it is possible that the most important direct impact of climate change will be drought stress. We combined data from weather stations and forest inventory plots (FIA) across the upper Great Lakes region (USA) to study the relationship between measures of drought stress and mortality for four drought sensitivity species groups using a weight-of-evidence approach. For all groups, the model that predicted mortality as a function of mean drought length had the greatest plausibility. Model tests confirmed that the models for all groups except the most drought tolerant had predictive value. We assumed that no relationship exists between drought and mortality for the drought-tolerant group. We used these empirical models to develop a drought extension for the forest landscape disturbance and succession model LANDIS-II, and applied the model in Oconto county, Wisconsin (USA) to assess the influence of drought on forest dynamics relative to other factors such as stand-replacing disturbance and site characteristics. The simulations showed that drought stress does affect species composition and total biomass, but effects on age classes, spatial pattern, and productivity were insignificant. We conclude that (for the upper Midwest) (1) a drought-induced tree mortality signal can be detected using FIA data, (2) tree species respond primarily to the length of drought events rather than their severity, (3) the differences in drought tolerance of tree species can be quantified, (4) future increases in drought can potentially change forest composition, and (5) drought is a potentially important factor to include in forest dynamics simulations because it affects forest composition and carbon storage.     

Assessing the influence of historic net and gross land changes on the carbon fluxes of Europe

Legacy effects of land cover/use on carbon fluxes require considering both present and past land cover/use change dynamics. To assess past land use dynamics, model‐based reconstructions of historic land cover/use are needed. Most historic reconstructions consider only the net area difference between two time steps (net changes) instead of accounting for all area gains and losses (gross changes). Studies about the impact of gross and net land change accounting methods on the carbon balance are still lacking. In this study, we assessed historic changes in carbon in soils for five land cover/use types and of carbon in above‐ground biomass of forests. The assessment focused on Europe for the period 1950 to 2010 with decadal time steps at 1‐km spatial resolution using a bookkeeping approach. To assess the implications of gross land change data, we also used net land changes for comparison. Main contributors to carbon sequestration between 1950 and 2010 were afforestation and cropland abandonment leading to 14.6 PgC sequestered carbon (of which 7.6 PgC was in forest biomass). Sequestration was highest for old‐growth forest areas. A sequestration dip was reached during the 1970s due to changes in forest management practices. Main contributors to carbon emissions were deforestation (1.7 PgC) and stable cropland areas on peaty soils (0.8 PgC). In total, net fluxes summed up to 203 TgC yr^?1 (98 TgC yr^?1 in forest biomass and 105 TgC yr^?1 in soils). For areas that were subject to land changes in both reconstructions (35% of total area), the differences in carbon fluxes were about 68%. Overall for Europe the difference between accounting for either gross or net land changes led to 7% difference (up to 11% per decade) in carbon fluxes with systematically higher fluxes for gross land change data.     

林火干扰对大兴安岭主要林分类型地上生物量预测的影响模拟研究

林火干扰是北方森林最主要的自然干扰之一,对北方森林地上生物量影响是一个长期的过程。因此,在预测地上生物量动态变化时需要考虑林火的影响。运用空间直观景观模型LANDIS PRO,模拟大兴安岭林区林火对不同树种地上生物量预测的影响。选取研究区5种主要树种林分(兴安落叶松、樟子松、云杉、白桦和山杨),以无干扰情景为参考预案,在验证模型模拟结果的基础上,模拟林火在短期(0—50a)、中期(50—150a)和长期(150—300a)对地上生物量的定量化影响,及其对不同立地类型地上生物量的动态变化。结果表明:(1)基于森林调查数据参数化的2000年森林景观模拟结果能够较好地代表2000年真实森林景观,模拟的2010年森林林分密度和胸高断面积与2010年森林调查数据无显著性差异(P0.05),当前林火干扰机制模拟结果能够较好地与样地调查数据匹配,说明林火模拟能够代表当前研究区林火发生情况;(2)与无干扰预案相比,整个模拟时期内景观水平上林火减少了1.7—5.9 t/hm2地上生物量;(3)与无干扰预案相比,林火预案下主要树种生物量在短期、中期和长期变化显著(P0.05);(4)在不同模拟时期,林火显著地改变了地上生物量空间分布,其中以亚高山区地上生物量降低最为明显。研究可为长期森林管理以及森林可持续发展提供参考。     

六盘山森林植被碳密度空间分布特征及其成因

深入了解干旱缺水地区森林植被碳密度的空间分布特征是定量评价森林固碳能力、合理协调林水矛盾的重要基础。然而,目前有关干旱缺水地区的植被碳密度的研究仅限于典型样地上的碳储量、碳密度的比较,对区域尺度上森林植被碳密度的空间分布特征了解较少。为此,利用宁夏六盘山自然保护区2005年森林资源一类清查数据,计算了森林植被碳密度,并分析了其与林分结构特征和环境因子的关系。结果表明,六盘山的森林植被碳密度(t/hm2)平均为26.17(0.67—120.63),其中天然次生林为30.2(7.6—120.6),显著高于人工林的15.7(0.67—66.7)。森林植被碳密度随林龄增加而线性增大,天然林和人工林的平均增速分别为1.11和2.48 t hm-2a-1,而且,部分未成熟林的林分植被碳密度已接近甚至超过全国同类森林类型成熟林的植被碳密度平均值。随林分密度增加,森林植被碳密度增大,但在林分密度1000株/hm2后,森林植被碳密度不再增大,达到其最大值,其中,天然林为75.4 t/hm2,人工林为34.6 t/hm2;林冠郁闭度对森林植被碳密度的影响与林分密度相似,森林植被碳密度增长的郁闭度拐点为0.5。水分条件是影响六盘山森林植被碳密度的重要因素,森林植被碳密度(t/hm2)由700 mm以上地点的32.5(7.6—120.6)下降至年降水量500—600 mm地点的10.9(0.67—42.9),而且随年降水量减少,最大森林植被碳密度所对应的海拔高度呈增加趋势,如在年降水量为700、600—700和600 mm的地区,最大碳密度所在海拔高度分别为1900—2100、2100—2300和2300—2500 m。综上所述,研究区森林植被还有较大的固碳潜力,从提高森林固碳功能角度来看,林分郁闭度不宜超过0.5。     

Diversity, biomass and distribution pattern of Sargassum beds in the South West lagoon of New Caledonia (South Pacific)

Sargassum (Phaeophyceae, Fucales) is a genus of worldwide distribution recently recognised to proliferate in several regions of the South Pacific. In New Caledonia, species of this genus naturally structure one of the major lagoon habitats but their extent, composition and biomass remain largely unknown. To fill these gaps in our knowledge over large areas, we applied a combination of remote sensing and in situ methods applied to the Neo Caledonian South West Lagoon. Space borne high resolution Landsat (30-m resolution) and Quickbird (2.4-m resolution) images of the Neo Caledonian South West lagoon were used to estimate the spatial extent of the different beds of interest. Species composition was determined for 11 Sargassum beds and seasonal variations were investigated for four representative beds over an 18 month period using quadrats and transects. Relationships between surface cover and biomass were estimated from seasonal field data sets. Finally, four methods requiring variable levels of sampling effort were designed to estimate the total biomass at the scale of each bed, considering (or not) the specific composition, and spatial and temporal variations. Seven Sargassaceae species were identified. Mean surface cover (24.4–51.6%) and total biomass [3.4–1,461.9 t dry matter (DM)] varied widely between beds. Overall, biomass temporal variations were not significantly different, but species-level variations seemed to be bed-specific. The extent of the 11 beds was 9 km²; their total biomass was estimated and compared using each of the four methods, and the most precise method provided an estimate of 2,900 t DM. This study demonstrates a way of characterising Sargassum beds, efficiently and on a large scale, using a combination of remotely sensed and in situ data. These methods should be useful for possible future biomonitoring of Sargassum beds in New Caledonia, and in other areas worldwide.     

Quantifying variation in forest disturbance,and its effects on aboveground biomass dynamics,across the eastern United States

The role of tree mortality in the global carbon balance is complicated by strong spatial and temporal heterogeneity that arises from the stochastic nature of carbon loss through disturbance. Characterizing spatio‐temporal variation in mortality (including disturbance) and its effects on forest and carbon dynamics is thus essential to understanding the current global forest carbon sink, and to predicting how it will change in future. We analyzed forest inventory data from the eastern United States to estimate plot‐level variation in mortality (relative to a long‐term background rate for individual trees) for nine distinct forest regions. Disturbances that produced at least a fourfold increase in tree mortality over an approximately 5 year interval were observed in 1–5% of plots in each forest region. The frequency of disturbance was lowest in the northeast, and increased southwards along the Atlantic and Gulf coasts as fire and hurricane disturbances became progressively more common. Across the central and northern parts of the region, natural disturbances appeared to reflect a diffuse combination of wind, insects, disease, and ice storms. By linking estimated covariation in tree growth and mortality over time with a data‐constrained forest dynamics model, we simulated the implications of stochastic variation in mortality for long‐term aboveground biomass changes across the eastern United States. A geographic gradient in disturbance frequency induced notable differences in biomass dynamics between the least‐ and most‐disturbed regions, with variation in mortality causing the latter to undergo considerably stronger fluctuations in aboveground stand biomass over time. Moreover, regional simulations showed that a given long‐term increase in mean mortality rates would support greater aboveground biomass when expressed through disturbance effects compared with background mortality, particularly for early‐successional species. The effects of increased tree mortality on carbon stocks and forest composition may thus depend partly on whether future mortality increases are chronic or episodic in nature.     

青藏高原典型人工林幼树生物量模型构建

森林生物量计算是全球碳储量估算的基础,现已纳入全球国家森林清单项目。普遍的森林碳汇计量采用的材积源生物量法针对胸径5 cm以上的树木,幼树(胸径<6 cm,树高>0.3 m)的碳汇量并未被完整计入其中,导致生态系统碳汇能力被低估。基于青藏高原137株5种典型人工林幼树的实测生物量数据,以地径代替胸径作为预测变量,采用加权广义最小二乘法建立独立生物量模型,选择比例总量直接控制及代数和控制2种结构形式的相容性生物量模型,并通过加权非线性似乎不相关回归进行方程组估算,建立了整株及各组分的相容性生物量方程。结果表明: 二元相容性模型优于一元以及独立模型,对整株生物量来说,R²达到0.90～0.99,两种相容性模型对于不同树种来说各有优势但精度差距可以忽略,从林业生产实践角度考虑,比例总量直接控制生物量模型更有实践意义,从遥感技术的变量提取角度考虑,本研究构建了更适于遥感估算的幼树生物量模型,其整体上拟合精度高,可以准确地进行类似气候环境中的幼树整株和各组分生物量的估算。     

Quantifying tree carbon stock in historically conserved Seminary Hills urban forest of Nagpur,India

Urban forests help regulating flow of ecosystem services and are efficient to sequester atmospheric carbon. Tree carbon stock in urban forests and green spaces can help improving human well-being. Nagpur being one of the fastest growing urban agglomerate in India that has faced rapid loss of green spaces in last three decades. Present study assessed tree biomass carbon storage potential of a historically conserved large (67.41 ha) Seminary Hills Reserve forest of Nagpur. A total of 150 quadrats of 100 m² were laid to understand the vegetation structure and tree biomass storage. Overall structure and composition of the forest was assessed while, non-destructive biomass estimation was carried out using tree volume eqs. A total of 27 tree species belonging to 12 plant families were observed from the forest with only 6 tree species being dominant and remaining 21 being rare in occurrence. The maximum tree carbon storage was observed in dominant tree species of Hardwickia binata (76.30 t C ha^?1) followed by 17.04 t C ha^?1 in Tectona grandis and 1.19 t C ha^?1 in Boswellia serrata. Carbon stock in other co-dominant species was reported in Terminalia bellirica (76.57 kg C ha^?1), Gardenia resinifera (1118.6 g C ha^?1) and Terminalia arjuna (84.8 g C ha^?1). Total carbon stock of dominant tree species present in Seminary Hills urban forest was 94.53 ± 39.6 t C ha^?1. The study intends to bring focus ecosystem benefits from Urban Forests in growing urban sprawls of India and the need to include their vital role in urban planning.     

A Changing Number of Alternative States in the Boreal Biome: Reproducibility Risks of Replacing Remote Sensing Products

Publicly available remote sensing products have boosted science in many ways. The openness of these data sources suggests high reproducibility. However, as we show here, results may be specific to versions of the data products that can become unavailable as new versions are posted. We focus on remotely-sensed tree cover. Recent studies have used this public resource to detect multi-modality in tree cover in the tropical and boreal biomes. Such patterns suggest alternative stable states separated by critical tipping points. This has important implications for the potential response of these ecosystems to global climate change. For the boreal region, four distinct ecosystem states (i.e., treeless, sparse and dense woodland, and boreal forest) were previously identified by using the Collection 3 data of MODIS Vegetation Continuous Fields (VCF). Since then, the MODIS VCF product has been updated to Collection 5; and a Landsat VCF product of global tree cover at a fine spatial resolution of 30 meters has been developed. Here we compare these different remote-sensing products of tree cover to show that identification of alternative stable states in the boreal biome partly depends on the data source used. The updated MODIS data and the newer Landsat data consistently demonstrate three distinct modes around similar tree-cover values. Our analysis suggests that the boreal region has three modes: one sparsely vegetated state (treeless), one distinct ‘savanna-like’ state and one forest state, which could be alternative stable states. Our analysis illustrates that qualitative outcomes of studies may change fundamentally as new versions of remote sensing products are used. Scientific reproducibility thus requires that old versions remain publicly available.     

Carbon stocks in the Guinea savanna of Ghana: estimates from three protected areas

Savannas are widespread in sub‐Saharan Africa (SSA) and play a major role in the global carbon balance. Extensive quantification of savanna carbon stocks in SSA will therefore contribute to better accounting of the global carbon budget in the era of climate change. In this study, we investigated the spatial distribution of carbon stocks of different soil fractions and aboveground biomass within three forest reserves in the Guinea savanna zone of Ghana. Soil carbon stocks (SCSs) ranged from 4.80 to 12.61 Mg C/ha in surface soils (0–10 cm depth). Higher SCSs were associated with the silt +clay fraction than microaggregates and small macroaggregates in all three reserves. Relative to the dominant tree species (Vitellaria paradoxa), the highest SCSs were recorded under the sub‐canopy (SC), drip line (DL), and interspace (2 * SC + DL) zones for the Klupene, Sinsablegbinni, and Kenikeni forest reserves, respectively. The highest tree carbon stock was 60.01 Mg C/ha in Kenikeni. Sinsablegbinni had an average stock of 26.74 Mg C/ha and had the highest tree density. Average carbon capture by a single tree ranged from 0.04 to 0.34 Mg C. Aboveground grass carbon stock ranged from 0.08 to 0.47 Mg C/ha, while the belowground carbon stock ranged from 0.03 to 0.44 Mg C/ha. Accumulation of carbon in the aboveground grass biomass was greater at Klupene with low forest cover.     

长白落叶松林龄序列上的生物量及碳储量分配规律

由于多年来的过量采伐和重采轻育,伊春东折棱河林场人工长白落叶松林分质量普遍下降,森林生态功能严重衰退。结合对该研究地同一立地类型的人工长白落叶松林(Larix ologensis)林木各组分生物量垂直分配规律的分析,研究了其生物量在年龄序列上的分布及分配规律,为提高其林分生物量及碳储量采取相应的抚育管理措施提供一定的理论基础。结果表明,处于中龄、近熟及成熟林中的林木树干、树皮及活枝生物量所占比例受年龄影响较小,而叶生物量随林龄增大呈现明显递减变化;不同年龄长白落叶松的垂直分布规律基本一致:其树皮及树干生物量随树高增大呈现递减规律,其活枝及叶生物量主要集中分布于树冠中部,而其死枝生物量未呈现明显分布规律;长白落叶松根系生物量随着林分年龄的增大,其粗根、中根及细根所占比例呈现递减规律,而其大根所占比例随年龄的增大基本呈增大趋势。通过统计分析得出,长白落叶松生物量与林分蓄积的最优模型为:W=0.4909M+9.6624(R²=0.8893),进而估算得出:研究区域幼龄长白落叶松林分生物量为1273.72 t/hm²,碳储量为656.98 t/hm²;中龄长白落叶松林分生物量为15480.13 t/hm²,碳储量为7984.65 t/hm²;近熟、成熟龄长白落叶松林分生物量为7684.41 t/hm²,碳储量为3963.62 t/hm²。随林分结构的改善以及中龄、近熟及成熟林分的不断增加,生物量及碳储量会相应增加。     

Observation of Trends in Biomass Loss as a Result of Disturbance in the Conterminous U.S.: 1986–2004

The critical role of forests in the global carbon cycle is well known, but significant uncertainties remain about the specific role of disturbance, in part because of the challenge of incorporating spatial and temporal detail in the characterization of disturbance processes. In this study, we link forest inventory data to remote sensing data to derive estimates of pre- and post-disturbance biomass, and then use near-annual remote sensing observations of forest disturbance to characterize biomass loss associated with disturbance across the conterminous U.S. between 1986 and 2004. Nationally, year-to-year variability in the amount of live aboveground carbon lost as a result of disturbance ranged from a low of 61 T _g C (±16) in 1991 to a high of 84 T _g C (±33) in 2003. Eastern and western forest strata were relatively balanced in terms of their proportional contribution to national-level trends, despite eastern forests having more than twice the area of western forests. In the eastern forest stratum, annual biomass loss tracked closely with the area of disturbance, whereas in the western forest stratum, annual biomass loss showed more year-to-year variability that did not directly correspond to the area of disturbance, suggesting that the biomass density of forests affected by disturbance in the west was more spatially and temporally variable. Eastern and western forest strata exhibited somewhat opposing trends in biomass loss, potentially corresponding to the implementation of the Northwest Forest Plan in the mid 1990s that resulted in a shift of timber harvesting from public lands in the northwest to private lands in the south. Overall, these observations document modest increases in disturbance rates and associated carbon consequences over the 18-year period. These changes are likely not significant enough to weaken a growing forest carbon sink in the conterminous U.S. based largely on increased forest growth rates and biomass densities.     

Relationships Between Soil Microorganisms, Plant Communities, and Soil Characteristics in Chinese Subtropical Forests

We analyzed the influence of above- and belowground factors on the soil microbial community in a Chinese subtropical forest, one of the most diverse biomes in the northern hemisphere. Soil samples were taken at different depths from four replicate comparative study plots in each of three forest age classes (young 10–40?years, medium 40–80?years, old ≥80?years). Microbial biomass and community structure were then determined using phospholipid fatty acid (PLFA) analysis, and basal respiration and microbial biomass carbon (C_mic) were determined by substrate-induced respiration. These data were then related to plant community and soil variables using non-metric multidimensional scaling analysis and post-hoc permutational correlations. We found that microbial lipid composition and abundance were not related to forest age class. Instead, microbial lipid composition and abundance were related to factors reflecting primary production, i.e., percent litter cover, percent dead wood cover, and percent tree layer cover. Specifically, the relative abundance (mol fraction) of indicators for arbuscular mycorrhizal fungi, Gram-positive and Gram-negative bacteria were positively significantly correlated with percent litter cover. We also found that the biomass of all microbial groups and total PLFA were negatively significantly related to percent deadwood cover. In addition, $ {\text{pH}}_{{{\text{H}}_{ 2} {\text{O}}}} $ was the only soil parameter that was correlated significantly to microbial biomass. Our results indicate that overarching ecological factors such as plant productivity and soil pH are important factors influencing the soil microbial community, both in terms of biomass and of community composition in this subtropical ecosystem.     

Simulating Carbon Stocks and Fluxes of an African Tropical Montane Forest with an Individual-Based Forest Model

Tropical forests are carbon-dense and highly productive ecosystems. Consequently, they play an important role in the global carbon cycle. In the present study we used an individual-based forest model (FORMIND) to analyze the carbon balances of a tropical forest. The main processes of this model are tree growth, mortality, regeneration, and competition. Model parameters were calibrated using forest inventory data from a tropical forest at Mt. Kilimanjaro. The simulation results showed that the model successfully reproduces important characteristics of tropical forests (aboveground biomass, stem size distribution and leaf area index). The estimated aboveground biomass (385 t/ha) is comparable to biomass values in the Amazon and other tropical forests in Africa. The simulated forest reveals a gross primary production of 24 t_cha^-1yr^-1. Modeling above- and belowground carbon stocks, we analyzed the carbon balance of the investigated tropical forest. The simulated carbon balance of this old-growth forest is zero on average. This study provides an example of how forest models can be used in combination with forest inventory data to investigate forest structure and local carbon balances.     

Tree Biomass Allocation and Its Model Additivity for Casuarina equisetifolia in a Tropical Forest of Hainan Island,China

Casuarina equisetifolia is commonly planted and used in the construction of coastal shelterbelt protection in Hainan Island. Thus, it is critical to accurately estimate the tree biomass of Casuarina equisetifolia L. for forest managers to evaluate the biomass stock in Hainan. The data for this work consisted of 72 trees, which were divided into three age groups: young forest, middle-aged forest, and mature forest. The proportion of biomass from the trunk significantly increased with age (P<0.05). However, the biomass of the branch and leaf decreased, and the biomass of the root did not change. To test whether the crown radius (CR) can improve biomass estimates of C. equisetifolia, we introduced CR into the biomass models. Here, six models were used to estimate the biomass of each component, including the trunk, the branch, the leaf, and the root. In each group, we selected one model among these six models for each component. The results showed that including the CR greatly improved the model performance and reduced the error, especially for the young and mature forests. In addition, to ensure biomass additivity, the selected equation for each component was fitted as a system of equations using seemingly unrelated regression (SUR). The SUR method not only gave efficient and accurate estimates but also achieved the logical additivity. The results in this study provide a robust estimation of tree biomass components and total biomass over three groups of C. equisetifolia.     

Influence of Tree Species Composition and Community Structure on Carbon Density in a Subtropical Forest

We assessed the impact of species composition and stand structure on the spatial variation of forest carbon density using data collected from a 4-ha plot in a subtropical forest in southern China. We found that 1) forest biomass carbon density significantly differed among communities, reflecting a significant effect of community structure and species composition on carbon accumulation; 2) soil organic carbon density increased whereas stand biomass carbon density decreased across communities, indicating that different mechanisms might account for the accumulation of stand biomass carbon and soil organic carbon in the subtropical forest; and 3) a small number of tree individuals of the medium- and large-diameter class contributed predominantly to biomass carbon accumulation in the community, whereas a large number of seedlings and saplings were responsible for a small proportion of the total forest carbon stock. These findings demonstrate that both biomass carbon and soil carbon density in the subtropical forest are sensitive to species composition and community structure, and that heterogeneity in species composition and stand structure should be taken into account to ensure accurate forest carbon accounting.