Estimating carbon stock in lowland Papua New Guinean forest: Low density of large trees results in lower than global average carbon stock

Papua New Guinean forests (PNG), sequestering up to 3% of global forest carbon, are a focus of climate change mitigation initiatives, yet few field‐based studies have quantified forest biomass and carbon for lowland PNG forest. We provide an estimate for the 10 770 ha Wanang Conservation Area (WCA) to investigate the effect of calculation methodology and choice of allometric equation on estimates of above‐ground live biomass (AGLB) and carbon. We estimated AGLB and carbon from 43 nested plots at the WCA. Our biomass estimate of 292.2 Mg AGLB ha^?1 (95% CI 233.4–350.6) and carbon at 137.3 Mg C ha^?1 (95% CI 109.8–164.8) is higher than most estimates for PNG but lower than mean global estimates for tropical forest. Calculation method and choice of allometric model do not significantly influence mean biomass estimates; however, the most recently calibrated allometric equation generates estimates 13% higher for lower 95% confidence intervals of mean biomass than previous allometric models – a value often used as a conservative estimate of biomass. Although large trees at WCA (>70 cm diameter at breast height) accounted for 1/5 total biomass, their density was lower than that seen in SE Asian and Australia forests. Lower density of large trees accounts for lower AGLB than in neighbouring forests – as large trees contribute disproportionately to forest biomass. Reduced frequency of larger trees at WCA is explained by the lack of diversity of large dipterocarp species common to neighbouring SE Asian forests and, potentially, higher rates of local disturbance dynamics. PNG is susceptible to the El Niño Southern Oscillation (ENSO) extreme drought events to which large trees are particularly sensitive and, with still over 20% carbon in large trees, differential mortality under increasing ENSO drought stress raises the risk of PNG forest switching from carbon sink to source with reduced long‐term carbon storage capacity.     

Optimal climate for large trees at high elevations drives patterns of biomass in remote forests of Papua New Guinea

Our ability to model global carbon fluxes depends on understanding how terrestrial carbon stocks respond to varying environmental conditions. Tropical forests contain the bulk of the biosphere's carbon. However, there is a lack of consensus as to how gradients in environmental conditions affect tropical forest carbon. Papua New Guinea (PNG) lies within one of the largest areas of contiguous tropical forest and is characterized by environmental gradients driven by altitude; yet, the region has been grossly understudied. Here, we present the first field assessment of aboveground biomass (AGB) across three main forest types of PNG using 193 plots stratified across 3,100‐m elevation gradient. Unexpectedly, AGB had no direct relationship to rainfall, temperature, soil, or topography. Instead, natural disturbances explained most variation in AGB. While large trees (diameter at breast height > 50 cm) drove altitudinal patterns of AGB, resulting in a major peak in AGB (2,200–3,100 m) and some of the most carbon‐rich forests at these altitudes anywhere. Large trees were correlated to a set of climatic variables following a hump‐shaped curve. The set of “optimal” climatic conditions found in montane cloud forests is similar to that of maritime temperate areas that harbor the largest trees in the world: high ratio of precipitation to evapotranspiration (2.8), moderate mean annual temperature (13.7°C), and low intra‐annual temperature range (7.5°C). At extreme altitudes (2,800–3,100 m), where tree diversity elsewhere is usually low and large trees are generally rare or absent, specimens from 18 families had girths >70 cm diameter and maximum heights 20–41 m. These findings indicate that simple AGB‐climate‐edaphic models may not be suitable for estimating carbon storage in forests where optimal climate niches exist. Our study, conducted in a very remote area, suggests that tropical montane forests may contain greater AGB than previously thought and the importance of securing their future under a changing climate is therefore enhanced.     

Short-Term Temporal Changes in Tree Live Biomass in a Central Amazonian Forest, Brazil

We monitored seventy-two 1 ha permanent plots spread over 64 km² of terra firme forest at Reserva Ducke (Manaus, Amazonas, Brazil) over 2-yr intervals to assess the effects of a soil and topographic gradient on the rate of change in the aboveground tree live biomass (AGLB). AGLB increased significantly over the 2-yr intervals, exhibiting a mean rate of change of 1.65 Mg/ha/yr (bootstrapped 95% CI: 1.15, 2.79). The rate of change varied according to tree size class; understory and sub-canopy trees exhibited higher rates of change. Over the whole period, the rate of change was not related to soil or topographic features of the plots, but there was evidence that the relationships varied depending on the year of measurement. In the plots monitored between 2001 and 2003 we found a significant relationship between AGLB change and the soil textural gradient, but this relationship was not evident in plots monitored between 2002 and 2004. This suggests that both the temporal variation in the soil–biomass change relationship and the size structure of the forest need to be included in models of biomass change in Amazonia. We also noted that the rate of biomass change is sensitive to the equation used to estimate AGLB. Allometric models that incorporate wood-density data provide higher per plot AGLB estimates, but lower rates of change, suggesting that variations in floristic composition have important implications for carbon cycling in diverse tropical forests.
Abstract in Portuguese is available at http://www.blackwell-synergy.com/loi/btp .     

Tree allometry and improved estimation of carbon stocks and balance in tropical forests

Tropical forests hold large stores of carbon, yet uncertainty remains regarding their quantitative contribution to the global carbon cycle. One approach to quantifying carbon biomass stores consists in inferring changes from long-term forest inventory plots. Regression models are used to convert inventory data into an estimate of aboveground biomass (AGB). We provide a critical reassessment of the quality and the robustness of these models across tropical forest types, using a large dataset of 2,410 trees ≥ 5 cm diameter, directly harvested in 27 study sites across the tropics. Proportional relationships between aboveground biomass and the product of wood density, trunk cross-sectional area, and total height are constructed. We also develop a regression model involving wood density and stem diameter only. Our models were tested for secondary and old-growth forests, for dry, moist and wet forests, for lowland and montane forests, and for mangrove forests. The most important predictors of AGB of a tree were, in decreasing order of importance, its trunk diameter, wood specific gravity, total height, and forest type (dry, moist, or wet). Overestimates prevailed, giving a bias of 0.5–6.5% when errors were averaged across all stands. Our regression models can be used reliably to predict aboveground tree biomass across a broad range of tropical forests. Because they are based on an unprecedented dataset, these models should improve the quality of tropical biomass estimates, and bring consensus about the contribution of the tropical forest biome and tropical deforestation to the global carbon cycle. Electronic Supplementary Material Supplementary material is available for this article at     

Distribution of aboveground live biomass in the Amazon basin

The amount and spatial distribution of forest biomass in the Amazon basin is a major source of uncertainty in estimating the flux of carbon released from land‐cover and land‐use change. Direct measurements of aboveground live biomass (AGLB) are limited to small areas of forest inventory plots and site‐specific allometric equations that cannot be readily generalized for the entire basin. Furthermore, there is no spaceborne remote sensing instrument that can measure tropical forest biomass directly. To determine the spatial distribution of forest biomass of the Amazon basin, we report a method based on remote sensing metrics representing various forest structural parameters and environmental variables, and more than 500 plot measurements of forest biomass distributed over the basin. A decision tree approach was used to develop the spatial distribution of AGLB for seven distinct biomass classes of lowland old‐growth forests with more than 80% accuracy. AGLB for other vegetation types, such as the woody and herbaceous savanna and secondary forests, was directly estimated with a regression based on satellite data. Results show that AGLB is highest in Central Amazonia and in regions to the east and north, including the Guyanas. Biomass is generally above 300 Mg ha⁻¹ here except in areas of intense logging or open floodplains. In Western Amazonia, from the lowlands of Peru, Ecuador, and Colombia to the Andean mountains, biomass ranges from 150 to 300 Mg ha⁻¹. Most transitional and seasonal forests at the southern and northwestern edges of the basin have biomass ranging from 100 to 200 Mg ha⁻¹. The AGLB distribution has a significant correlation with the length of the dry season. We estimate that the total carbon in forest biomass of the Amazon basin, including the dead and belowground biomass, is 86 Pg C with ±20% uncertainty.     

The Grove of Giants: Tasmania's most carbon-dense forest

The Grove of Giants in the Huon Valley of Tasmania, Australia is renowned for its large trees. A team of tree climbers and citizen scientists undertook a carbon assessment of a 2 hectare plot within the Grove of Giants. The largest 16 trees in the plot (>2.5 m DBH) were measured by tree climbers allowing for accurate estimation of tree volume. Understory trees, coarse woody debris, root biomass and soil carbon were also estimated, making this study the most comprehensive assessment of forest carbon in Tasmania. Total forest carbon was estimated to be 1312 tonnes per hectare. Large trees had the highest carbon stocks, accounting for 44% of the total store. Coarse woody debris represented 19% of the forest's carbon, root biomass was 14%, while the understory trees accounted for 12% and soil carbon for 11%. This is the highest carbon stock recorded in Tasmania and is above the average estimates for temperate forest ecosystems in other parts of the world. Protecting Tasmania's forests, especially mature wet Eucalypt forests, is important to avoid potential greenhouse gas emissions and ensure safe storage of the carbon in the land sector.     

Validating Community-Led Forest Biomass Assessments

The lack of capacity to monitor forest carbon stocks in developing countries is undermining global efforts to reduce carbon emissions. Involving local people in monitoring forest carbon stocks could potentially address this capacity gap. This study conducts a complete expert remeasurement of community-led biomass inventories in remote tropical forests of Papua New Guinea. By fully remeasuring and isolating the effects of 4,481 field measurements, we demonstrate that programmes employing local people (non-experts) can produce forest monitoring data as reliable as those produced by scientists (experts). Overall, non-experts reported lower biomass estimates by an average of 9.1%, equivalent to 55.2 fewer tonnes of biomass ha^-1, which could have important financial implications for communities. However, there were no significant differences between forest biomass estimates of expert and non-expert, nor were there significant differences in some of the components used to calculate these estimates, such as tree diameter at breast height (DBH), tree counts and plot surface area, but were significant differences between tree heights. At the landscape level, the greatest biomass discrepancies resulted from height measurements (41%) and, unexpectedly, a few large missing trees contributing to a third of the overall discrepancies. We show that 85% of the biomass discrepancies at the tree level were caused by measurement taken on large trees (DBH ≥50cm), even though they consisted of only 14% of the stems. We demonstrate that programmes that engage local people can provide high-quality forest carbon data that could help overcome barriers to reducing forest carbon emissions in developing countries. Nonetheless, community-based monitoring programmes should prioritise reducing errors in the field that lead to the most important discrepancies, notably; overcoming challenges to accurately measure large trees.     

Assessment of Aboveground Carbon in Primary and Selectively Harvested Tropical Forest in Papua New Guinea

Papua New Guinea (PNG) has become the focus of climate change mitigation initiatives such as reducing emissions from deforestation and forest degradation, but defensible estimates of forest carbon are lacking. Here we present a methodology for estimating aboveground forest carbon, and apply it to a large Permanent Sample Plot system maintained by Papua New Guinea Forest Research Institute. We report the first estimates of forest carbon in lowland tropical forest in PNG. Average aboveground carbon in stems >10 cm diam. for 115 selectively harvested 1-ha plots in lowland tropical forest was 66.3±3.5 Mg C/ha (95% CI) while for 10 primary forest plots the average was 106.3±16.2 Mg C/ha. We applied ratios based on field observations, in-country studies, and the literature to estimate unmeasured pools of aboveground carbon (stems <10 cm diam., fine litter and coarse woody debris). Total aboveground carbon was estimated at 90.2 and 120.8 Mg C/ha in selectively harvested and primary lowland forest, respectively. Our estimate for primary tropical forest is lower than biome averages for tropical equatorial forest, and we hypothesize that frequent disturbances from fire, frost, landslides, and agriculture are limiting carbon stock development. The methodology and estimates presented here will assist the PNG government in its preparedness for mitigation initiatives, are of interest to communities that are seeking to participate in voluntary carbon markets, and will encourage transparency and consistency in the estimation of forest carbon.     

Deadwood stocks increase with selective logging and large tree frequency in Gabon

Deadwood is a major component of aboveground biomass (AGB) in tropical forests and is important as habitat and for nutrient cycling and carbon storage. With deforestation and degradation taking place throughout the tropics, improved understanding of the magnitude and spatial variation in deadwood is vital for the development of regional and global carbon budgets. However, this potentially important carbon pool is poorly quantified in Afrotropical forests and the regional drivers of deadwood stocks are unknown. In the first large‐scale study of deadwood in Central Africa, we quantified stocks in 47 forest sites across Gabon and evaluated the effects of disturbance (logging), forest structure variables (live AGB, wood density, abundance of large trees), and abiotic variables (temperature, precipitation, seasonality). Average deadwood stocks (measured as necromass, the biomass of deadwood) were 65 Mg ha^?1 or 23% of live AGB. Deadwood stocks varied spatially with disturbance and forest structure, but not abiotic variables. Deadwood stocks increased significantly with logging (+38 Mg ha^?1) and the abundance of large trees (+2.4 Mg ha^?1 for every tree >60 cm dbh). Gabon holds 0.74 Pg C, or 21% of total aboveground carbon in deadwood, a threefold increase over previous estimates. Importantly, deadwood densities in Gabon are comparable to those in the Neotropics and respond similarly to logging, but represent a lower proportion of live AGB (median of 18% in Gabon compared to 26% in the Neotropics). In forest carbon accounting, necromass is often assumed to be a constant proportion (9%) of biomass, but in humid tropical forests this ratio varies from 2% in undisturbed forest to 300% in logged forest. Because logging significantly increases the deadwood carbon pool, estimates of tropical forest carbon should at a minimum use different ratios for logged (mean of 30%) and unlogged forests (mean of 18%).     

Large tree mortality and the decline of forest biomass following Amazonian wildfires

Surface fires in Amazonian forests could contribute as much as 5% of annual carbon emissions from all anthropogenic sources during severe El Niño years. However, these estimates are based on short‐term figures of post‐burn tree mortality, when large thicker barked trees (representing a disproportionate amount of the forest biomass) appear to resist the fires. On the basis of a longer term study, we report that the mortality of large trees increased markedly between 1 and 3 years, more than doubling current estimates of biomass loss and committed carbon emissions from low‐intensity fires in tropical forests.     

菌根真菌影响森林生态系统碳循环研究进展

森林生态系统在全球碳(C)储量中占据极为重要的地位。菌根真菌广泛存在于森林生态系统中,在森林生态系统C循环过程中发挥重要的作用。阐述了不同菌根类型真菌在森林生态系统C循环过程中的功能,对比了温带/北方森林与热带/亚热带森林中菌根真菌介导的C循环研究方面新近取得的研究结果。发现温带和北方森林的外生菌根(EcM)植物对地上生物量C的贡献相对较小,然而是地下C储量的主要贡献者;以丛枝菌根(AM)共生为主的热带/亚热带森林地表生物量占比较高,表明AM植被对热带/亚热带森林地上生物量C的贡献相对较大。我们还就全球变化背景下,菌根真菌及其介导的森林生态系统C汇功能,以及不同菌根类型树种影响C循环的机制等进行了总结。菌根真菌通过影响凋落物分解、土壤有机质形成及地下根系生物量,进而影响整个森林生态系统的C循环功能。菌根介导的森林C循环过程很大程度上取决于(优势)树木的菌根类型和森林土壤中菌根真菌的群落结构。最后指出了当前研究存在的主要问题以及未来研究展望。本文旨在明确菌根真菌在森林生态系统C循环转化过程中的重要生态功能,有助于准确地评估森林生态系统C汇现状,为应对全球变化等提供重要的依据。     

Aboveground Forest Carbon Dynamics in Papua New Guinea: Isolating the Influence of Selective-Harvesting and El Niño

Assessment of forest carbon (C) stock and sequestration and the influence of forest harvesting and climatic variations are important issues in global forest ecology. Quantitative studies of the C balance of tropical forests, such as those in Papua New Guinea (PNG), are also required for forest-based climate change mitigation initiatives. We develop a hierarchical Bayesian model (HBM) of aboveground forest C stock and sequestration in primary, selectively harvested, and El Niño Southern Oscillation (ENSO)-effected lowland tropical forest from 15 years of Permanent Sample Plot (PSP) census data for PNG consisting of 121 plots in selectively harvested forest, and 35 plots in primary forest. Model parameters indicated: C stock in aboveground live biomass (AGLB) of 137 ± 9 (95% confidence interval (CI)) MgC ha^?1 in primary forest, compared with 62 ± 18 MgC ha^?1 for selectively harvested forest (55% difference); C sequestration in primary forest of 0.23 ± 1.70 MgC ha^?1 y^?1, which was lower than in selectively harvested forest, 1.12 ± 3.41 MgC ha^?1 y^?1; ENSO-induced fire resulted in significant C emissions (?6.87 ± 3.94 MgC ha^?1 y^?1). High variability between PSPs in C stock and C sequestration rates necessitated random plot effects for both stock and sequestration. The HBM approach allowed inclusion of hierarchical autocorrelation, providing valid CIs on model parameters and efficient estimation. The HBM model has provided quantitative insights on the C balance of PNG’s forests that can be used as inputs for climate change mitigation initiatives.     

广西马山岩溶次生林群落生物量和碳储量

岩溶植被在岩溶生态系统碳循环和全球碳平衡中具有重要的作用。通过对马山县岩溶次生林年龄序列(幼龄林、中龄林和老龄林)3个演替阶段9个样地(20 m×50 m)的系统取样调查,研究了停止人为干扰后岩溶次生林生物量和碳储量的变化。结果表明:沿幼林、中林和老林群落的顺向演替发展,群落生物量显著增加(P0.05),从幼林群落的48.17 t/hm2、到中林群落113.47 t/hm2,再到老林群落242.59 t/hm2。老林生态系统的碳储量较高,平均为236.69 t/hm2,中林和幼林较低且非常相近,分别为225.17 t/hm2和224.76 t/hm2,各次生林生态系统的碳储量差异不显著(P0.05)。土壤碳储量的大小顺序为幼林(198.44 t/hm2)中林(167.39 t/hm2)老林(113.43 t/hm2)。沿群落正向演替,各次生林生态系统中植物碳储量和土壤碳储量的比例发生明显的变化。幼林的土壤碳储量占生态系统碳储量的88.29%,植物碳储量只占11.71%;中林相应为74.34%和25.66%;而老林为47.92%和52.08%。可见,随着岩溶植被的正向演替,土壤碳转变为植物碳的趋势十分明显,这是岩溶森林不同于酸性土森林的一个显著特征。     

Forest Structure and Biomass of a Tropical Seasonal Rain Forest in Xishuangbanna,Southwest China1

Xishuangbanna is a region located at the northern edge of tropical Asia. Biomass estimates of its tropical rain forest have not been published in English literature. We estimated forest biomass and its allocation patterns in five 0.185–1.0 ha plots in tropical seasonal rain forests of Xishuangbanna. Forest biomass ranged from 362.1 to 692.6 Mg/ha. Biomass of trees with diameter at 1.3 m breast height (DBH) ≥ 5 cm accounted for 98.2 percent of the rain forest biomass, followed by shrubs (0.9%), woody lianas (0.8%), and herbs (0.2%). Biomass allocation to different tree components was 68.4–70.0 percent to stems, 19.8–21.8 percent to roots, 7.4–10.6 percent to branches, and 0.7–1.3 percent to leaves. Biomass allocation to the tree sublayers was 55.3–62.2 percent to the A layer (upper layer), 30.6–37.1 percent to the B layer (middle), and 2.7–7.6 percent to the C layer (lower). Biomass of Pometia tomentosa, a dominant species, accounted for 19.7–21.1 percent of the total tree biomass. The average density of large trees (DBH ≥100 cm) was 9.4 stems/ha on two small plots and 3.5 stems/ha on two large plots, illustrating the potential to overestimate biomass on a landscape scale if only small plots are sampled. Biomass estimations are similar to typical tropical rain forests in Southeast Asia and the Neotropics.     

Forest Conversion and Degradation in Papua New Guinea 1972–2002

Quantifying forest change in the tropics is important because of the role these forests play in the conservation of biodiversity and the global carbon cycle. One of the world's largest remaining areas of tropical forest is located in Papua New Guinea. Here we show that change in its extent and condition has occurred to a greater extent than previously recorded. We assessed deforestation and forest degradation in Papua New Guinea by comparing a land-cover map from 1972 with a land-cover map created from nationwide high-resolution satellite imagery recorded since 2002. In 2002 there were 28,251,967 ha of tropical rain forest. Between 1972 and 2002, a net 15 percent of Papua New Guinea's tropical forests were cleared and 8.8 percent were degraded through logging. The drivers of forest change have been concentrated within the accessible forest estate where a net 36 percent were degraded or deforested through both forestry and nonforestry processes. Since 1972, 13 percent of upper montane forests have also been lost. We estimate that over the period 1990–2002, overall rates of change generally increased and varied between 0.8 and 1.8 percent/yr, while rates in commercially accessible forest have been far higher—having varied between 1.1 and 3.4 percent/yr. These rates are far higher than those reported by the FAO over the same period. We conclude that rapid and substantial forest change has occurred in Papua New Guinea, with the major drivers being logging in the lowland forests and subsistence agriculture throughout the country with comparatively minor contributions from forest fires, plantation establishment, and mining.     

西藏林芝地区森林碳储量、碳密度及其分布

利用林芝地区第六次二类森林资源清查数据,运用材积源生物量法和平均生物量法,结合不同树种的分子式含碳率,估算了林芝地区森林及其组分的碳储量、碳密度,并分析其分布特征.结果表明: 2004年,林芝地区森林碳储量为2.43×10⁸ t,森林平均碳密度为76.01 t·hm^-2,其中,林分碳储量>灌木林碳储量>疏林碳储量>散生木碳储量>竹林碳储量>四旁树碳储量,各林分类型碳储量在2.51×10⁵～1.27×10⁸ t,共计占总森林碳储量的92.0%,各林分类型的平均碳密度为103.16 t·hm^-2,其中冷杉林的碳储量和碳密度均最高.在区域分布上,森林碳储量由西北向东南递增,森林平均碳密度由西南向东北递增.林分碳储量以成、过熟林碳储量为主,而过熟林的碳密度在各龄级中最高.随着过熟林的增加,林芝地区森林碳储量将增加;但随着过熟林的死亡和分解,林芝地区森林碳储量将有减小趋势.     

Modeling the impact of liana infestation on the demography and carbon cycle of tropical forests

There is mounting empirical evidence that lianas affect the carbon cycle of tropical forests. However, no single vegetation model takes into account this growth form, although such efforts could greatly improve the predictions of carbon dynamics in tropical forests. In this study, we incorporated a novel mechanistic representation of lianas in a dynamic global vegetation model (the Ecosystem Demography Model). We developed a liana‐specific plant functional type and mechanisms representing liana–tree interactions (such as light competition, liana‐specific allometries, and attachment to host trees) and parameterized them according to a comprehensive literature meta‐analysis. We tested the model for an old‐growth forest (Paracou, French Guiana) and a secondary forest (Gigante Peninsula, Panama). The resulting model simulations captured many features of the two forests characterized by different levels of liana infestation as revealed by a systematic comparison of the model outputs with empirical data, including local census data from forest inventories, eddy flux tower data, and terrestrial laser scanner‐derived forest vertical structure. The inclusion of lianas in the simulations reduced the secondary forest net productivity by up to 0.46 t_C ha^?1 year^?1, which corresponds to a limited relative reduction of 2.6% in comparison with a reference simulation without lianas. However, this resulted in significantly reduced accumulated above‐ground biomass after 70 years of regrowth by up to 20 t_C/ha (19% of the reference simulation). Ultimately, the simulated negative impact of lianas on the total biomass was almost completely cancelled out when the forest reached an old‐growth successional stage. Our findings suggest that lianas negatively influence the forest potential carbon sink strength, especially for young, disturbed, liana‐rich sites. In light of the critical role that lianas play in the profound changes currently experienced by tropical forests, this new model provides a robust numerical tool to forecast the impact of lianas on tropical forest carbon sinks.     

Allometric constraints and competition enable the simulation of size structure and carbon fluxes in a dynamic vegetation model of tropical forests (LM3PPA‐TV)

Tropical forests are a key determinant of the functioning of the Earth system, but remain a major source of uncertainty in carbon cycle models and climate change projections. In this study, we present an updated land model (LM3PPA‐TV) to improve the representation of tropical forest structure and dynamics in Earth system models (ESMs). The development and parameterization of LM3PPA‐TV drew on extensive datasets on tropical tree traits and long‐term field censuses from Barro Colorado Island (BCI), Panama. The model defines a new plant functional type (PFT) based on the characteristics of shade‐tolerant, tropical tree species, implements a new growth allocation scheme based on realistic tree allometries, incorporates hydraulic constraints on biomass accumulation, and features a new compartment for tree branches and branch fall dynamics. Simulation experiments reproduced observed diurnal and seasonal patterns in stand‐level carbon and water fluxes, as well as mean canopy and understory tree growth rates, tree size distributions, and stand‐level biomass on BCI. Simulations at multiple sites captured considerable variation in biomass and size structure across the tropical forest biome, including observed responses to precipitation and temperature. Model experiments suggested a major role of water limitation in controlling geographic variation forest biomass and structure. However, the failure to simulate tropical forests under extreme conditions and the systematic underestimation of forest biomass in Paleotropical locations highlighted the need to incorporate variation in hydraulic traits and multiple PFTs that capture the distinct floristic composition across tropical domains. The continued pressure on tropical forests from global change demands models which are able to simulate alternative successional pathways and their pace to recovery. LM3PPA‐TV provides a tool to investigate geographic variation in tropical forests and a benchmark to continue improving the representation of tropical forests dynamics and their carbon storage potential in ESMs.     

基于森林清查资料的河南省森林植被碳储量动态变化

利用1994—1998年、1999—2003年、2004—2008年、2009—2013年河南省4期森林资源清查数据,运用生物量转换因子连续函数法和平均生物量法,估算了1998—2013年河南省森林植被的碳储量和碳密度变化。研究结果表明,河南省森林植被碳储量由1998年的45.57 Tg增加到2013年的107.98 Tg,年均碳汇量为4.16 Tg/a。乔木林碳储量和碳密度分别由1998年的33.54 Tg和22.39 Mg/hm~2增加到2013年的97.11 Tg和31.80 Mg/hm~2。乔木林碳储量在所有植被类型中占主体,4个森林清查时期乔木林碳储量占森林植被总碳储量的比例分别为73.60%、79.22%、85.63%和89.93%。2013年森林清查时,乔木林中杨树和栎类碳储量最大,分别占总碳储量的37.61%和25.22%,各龄组乔木林碳密度大小顺序依次为成熟林近熟林中龄林过熟林幼龄林。阔叶林面积、碳储量、碳密度均高于针叶林,阔叶林是河南省森林碳汇的主要贡献者。人工林面积、碳储量、碳密度增加幅度都要高于天然林,人工林碳储量由1998年的9.62 Tg增加到2013年的55.67 Tg,占乔木林碳储量总增量的77.15%,人工林碳密度由1998年的17.86 Mg/hm~2提高到2013年的32.01 Mg/hm~2,人工林在河南省森林碳汇中逐步发挥重要的作用,逐渐成为河南省森林碳汇的主体,随着人工林生长为具有较高碳密度的成熟林,河南省乔木林将具有较大的碳汇潜力。     

全球森林土壤微生物生物量碳氮磷化学计量的季节动态

土壤微生物生物量在森林生态系统中充当具有生物活性的养分积累和储存库。土壤微生物转化有机质为植物提供可利用养分, 与植物的相互作用维系着陆地生态系统的生态功能。同时, 土壤微生物也与植物争夺营养元素, 在季节交替过程和植物的生长周期中呈现出复杂的互利-竞争关系。综合全球数据对温带、亚热带和热带森林土壤微生物生物量碳(C)、氮(N)、磷(P)含量及其化学计量比值的季节动态进行分析, 发现温带和亚热带森林的土壤微生物生物量C、N、P含量均呈现夏季低、冬季高的格局。热带森林四季的土壤微生物生物量C、N、P含量都低于温带和亚热带森林, 且热带森林土壤微生物生物量C含量、N含量在秋季相对最低, 土壤微生物生物量P含量四季都相对恒定。温带森林的土壤微生物生物量C:N在春季显著高于其他两个森林类型; 热带森林的土壤微生物生物量C:N在秋季显著高于其他2个森林类型。温带森林土壤微生物生物量N:P和C:P在四季都保持相对恒定, 而热带森林土壤微生物生物量N:P和C:P在夏季高于其他3个季节。阔叶树的土壤微生物生物量C含量、N含量、N:P、C:P在四季都显著高于针叶树; 而针叶树的土壤微生物生物量P含量在四季都显著高于阔叶树。在春季和冬季时, 土壤微生物生物量C:N在阔叶树和针叶树之间都没有显著差异; 但是在夏季和秋季, 针叶树的土壤微生物生物量C:N显著高于阔叶树。对于土壤微生物生物量的变化来说, 森林类型是主要的显著影响因子, 季节不是显著影响因子, 暗示土壤微生物生物量的季节波动是随着植物其内在固有的周期变化而变化。植物和土壤微生物密切作用表现出来的对养分的不同步吸收是保留养分和维持生态功能的一种权衡机制。