Variation in above‐ground forest biomass across broad climatic gradients

Aim An understanding of the relationship between forest biomass and climate is needed to predict the impacts of climate change on carbon stores. Biomass patterns have been characterized at geographically or climatically restricted scales, making it unclear if biomass is limited by climate in any general way at continental to global scales. Using a dataset spanning multiple climatic regions we evaluate the generality of published biomass–climate correlations. We also combine metabolic theory and hydraulic limits to plant growth to first derive and then test predictions for how forest biomass should vary with maximum individual tree biomass and the ecosystem water deficit. Location Temperate forests and dry, moist and wet tropical forests across North, Central and South America. Methods A forest biomass model was derived from allometric functions and power‐law size distributions. Biomass and climate were correlated using extensive forest plot (276 0.1‐ha plots), wood density and climate datasets. Climate variables included mean annual temperature, annual precipitation, their ratio, precipitation of the driest quarter, potential and actual evapotranspiration, and the ecosystem water deficit. The water deficit uniquely summarizes water balance by integrating water inputs from precipitation with water losses due to solar energy. Results Climate generally explained little variation in forest biomass, and mixed support was found for published biomass–climate relationships. Our theory indicated that maximum individual biomass governs forest biomass and is constrained by water deficit. Indeed, forest biomass was tightly coupled to maximum individual biomass and the upper bound of maximum individual biomass declined steeply with water deficit. Water deficit similarly constrained the upper bound of forest biomass, with most forests below the constraint. Main conclusions The results suggest that: (1) biomass–climate models developed at restricted geographic/climatic scales may not hold at broader scales; (2) maximum individual biomass is strongly related to forest biomass, suggesting that process‐based models should focus on maximum individual biomass; (3) the ecosystem water deficit constrains biomass, but realized biomass often falls below the constraint; such that (4) biomass is not strongly limited by climate in most forests so that forest biomass may not predictably respond to changes in mean climate.     

Quantifying mortality of tropical rain forest trees using high-spatial-resolution satellite data

Assessment of forest responses to climate change is severely hampered by the limited information on tree death on short temporal and broad spatial scales, particularly in tropical forests. We used 1‐m resolution panchromatic IKONOS and 0.7‐m resolution QuickBird satellite data, acquired in 2000 and 2002, respectively, to evaluate tree death rates at the La Selva Biological Station in old‐growth Tropical Wet Forest in Costa Rica, Central America. Using a calibration factor derived from ground inspection of tree deaths predicted from the images, we calculated a landscape‐scale annual exponential death rate of 2.8%. This corresponds closely to data for all canopy‐level trees in 18 forest inventory plots, each of 0.5 ha, for a mostly‐overlapping 2‐year period (2.8% per year). This study shows that high‐spatial‐resolution satellite data can now be used to measure old‐growth tropical rain forest tree death rates, suggesting many new avenues for tropical forest ecology and global change research.     

The regional variation of aboveground live biomass in old-growth Amazonian forests

The biomass of tropical forests plays an important role in the global carbon cycle, both as a dynamic reservoir of carbon, and as a source of carbon dioxide to the atmosphere in areas undergoing deforestation. However, the absolute magnitude and environmental determinants of tropical forest biomass are still poorly understood. Here, we present a new synthesis and interpolation of the basal area and aboveground live biomass of old‐growth lowland tropical forests across South America, based on data from 227 forest plots, many previously unpublished. Forest biomass was analyzed in terms of two uncorrelated factors: basal area and mean wood density. Basal area is strongly affected by local landscape factors, but is relatively invariant at regional scale in moist tropical forests, and declines significantly at the dry periphery of the forest zone. Mean wood density is inversely correlated with forest dynamics, being lower in the dynamic forests of western Amazonia and high in the slow‐growing forests of eastern Amazonia. The combination of these two factors results in biomass being highest in the moderately seasonal, slow growing forests of central Amazonia and the Guyanas (up to 350 Mg dry weight ha^?1) and declining to 200–250 Mg dry weight ha^?1 at the western, southern and eastern margins. Overall, we estimate the total aboveground live biomass of intact Amazonian rainforests (area 5.76 × 10⁶ km² in 2000) to be 93±23 Pg C, taking into account lianas and small trees. Including dead biomass and belowground biomass would increase this value by approximately 10% and 21%, respectively, but the spatial variation of these additional terms still needs to be quantified.     

基于不同决策树的面向对象林区遥感影像分类比较

面向地理对象影像分析技术(GEOBIA)是影像分辨率越来越高的背景下的产物.如何提高高分辨率影像分类精度和分类效率是影像处理的重要议题之一.本研究对QuickBird影像多尺度分割后的对象进行分类,分析了C5.0、C4.5、CART决策树算法在林区面向对象分类中的效率,并与kNN算法的分类精度进行比较.利用eCognition软件对遥感影像进行多尺度分割,分析得到最佳尺度为90和40.在90尺度下分离出植被和非植被后,在40尺度下提取不同类别植被的光谱、纹理、形状等共21个特征,并利用C5.0、C4.5、CART决策树算法分别对其进行知识挖掘,自动建立分类规则.最后利用建立的分类规则分别对植被区域进行分类,并比较分析其精度.结果表明: 基于决策树的分类精度均高于传统的kNN法.其中,C5.0方法的精度最高,其总体分类精度为90.0%,Kappa系数0.87.决策树算法能有效提高林区树种分类精度,且C5.0决策树的Boosting算法对该分类效果具有最明显的提升.     

黑龙江省大兴安岭森林生物量空间格局及其影响因素

基于样地实测数据和EVI指数,定量分析了黑龙江省大兴安岭森林生物量空间格局,并利用ArcGIS软件的空间分析与统计工具,分析了气候区、海拔、坡度、坡向和植被类型对森林生物量空间格局的影响.结果表明: 黑龙江省大兴安岭森林生物量为350 Tg,空间上呈聚集分布,生物量有巨大的增长空间.森林生物量密度大小顺序为:寒温带湿润区(64.02 t·hm^-2)＞中温带湿润区(60.26 t·hm^-2);各植被类型生物量密度大小顺序为:针阔混交林(65.13 t·hm^-2)＞云冷杉林(63.92 t·hm^-2)＞偃松 落叶松林(63.79 t·hm^-2)＞樟子松林(61.97 t·hm^-2)＞兴安落叶松林(61.40 t·hm^-2)＞落叶阔叶混交林(58.96 t·hm^-2).随海拔和坡度的增大,森林生物量密度先减小后增加,并且阴坡大于阳坡.大兴安岭森林生物量空间格局随气候区、植被类型和地形因子的梯度变化表现出差异性,在区域尺度上估算生物量密度时,需要充分考虑这种空间差异性.     

Carbon pools of an intact forest in Gabon

Quantitative and qualitative loss of tropical forests prompted international policy agendas to slow down forest loss through reducing emissions from deforestation and forest degradation (REDD)+, ensuring carbon offset payments to developing countries. So far, many African countries lack reliable forest carbon data and monitoring systems as required by REDD+. In this study, we estimate the carbon stocks of a naturally forested landscape unaffected by direct human impact. We used data collected from 34 plots randomly distributed across the Mount Birougou National Park (690 km²) in southern Gabon. We used tree‐level data on species, diameter, height, species‐specific wood density and carbon fraction as well as site‐level data on dead wood, soil and litter carbon to calculate carbon content in aboveground, belowground, dead wood, soil and litter as 146, 28, 14, 186 and 7 Mg ha^?1, respectively. Results may serve as a benchmark to assess ecosystem carbon loss/gain for the Massif du Chaillu in Gabon and the Republic of Congo, provide field data for remote sensing and also may contribute to establish national monitoring systems.     

Above-ground biomass estimation in closed canopy Neotropical forests using lidar remote sensing: factors affecting the generality of relationships

Aim Previous studies have developed strong, site‐specific relationships between canopy metrics from lidar (light detecting and ranging) remote sensing data and forest structural characteristics such as above‐ground biomass (AGBM), but the generality of these relationships is unknown. In this study, we examine the generality of relationships between lidar metrics and forest structural characteristics, including AGBM, from two study areas in Central America with different precipitation patterns. Location A series of tropical moist forest sites in Panama and a tropical wet forest in Costa Rica. Methods Canopy metrics (e.g. canopy height) were calculated from airborne lidar data. Basal area, mean stem diameter and AGBM were calculated from measurements taken as a part of ongoing forest dynamics studies in both areas. We examined the generality of relationship between lidar metrics and forest structure, and possible environmental effects (e.g. leaf phenology). Results We found that lidar metrics were strongly correlated (R²: 0.65–0.92) with mean stem diameter, basal area and AGBM in both regions. We also show that the relationships differed between these regions. Deciduousness of canopy trees in the tropical moist forest area accounted for the differences in predictive equations for stem diameter and basal area. The relationships between lidar metrics and AGBM, however, remained significantly different between the two study areas even after adjusting for leaf drop. We attribute this to significant differences in the underlying allometric relationships between stem diameter and AGBM in tropical wet and moist forests. Conclusions Important forest structural characteristics can be estimated reliably across a variety of conditions sampled in these closed‐canopy tropical forests. Environmental factors such as drought deciduousness have an important influence on these relationships. Future efforts should continue to examine climatic factors that may influence the generality of the relationships between lidar metrics and forest structural characteristics and assess more rigorously the generality of field‐derived allometric relationships.     

The spatial distribution of forest biomass in the Brazilian Amazon: a comparison of estimates

The amount of carbon released to the atmosphere as a result of deforestation is determined, in part, by the amount of carbon held in the biomass of the forests converted to other uses. Uncertainty in forest biomass is responsible for much of the uncertainty in current estimates of the flux of carbon from land‐use change. In the present contribution several estimates of forest biomass are compared for the Brazilian Amazon, based on spatial interpolations of direct measurements, relationships to climatic variables, and remote sensing data. Three questions were posed: First, do the methods yield similar estimates? Second, do they yield similar spatial patterns of distribution of biomass? And, third, what factors need most attention if we are to predict more accurately the distribution of forest biomass over large areas? The answer to the first two questions is that estimates of biomass for Brazil's Amazonian forests (including dead and belowground biomass) vary by more than a factor of two, from a low of 39 PgC to a high of 93 PgC. Furthermore, the estimates disagree as to the regions of high and low biomass. The lack of agreement among estimates confirms the need for reliable determination of aboveground biomass over large areas. Potential methods include direct measurement of biomass through forest inventories with improved allometric regression equations, dynamic modelling of forest recovery following observed stand‐replacing disturbances, and estimation of aboveground biomass from airborne or satellite‐based instruments sensitive to the vertical structure plant canopies.     

Forestry's fertile crescent: the application of biotechnology to forest trees

Relative to crop plants, the domestication of forest trees is still in its infancy. For example, the domestication of many crop plants was initiated some 10,000 years ago in the so-called 'Fertile Crescent' of the Middle East. By contrast, the domestication of forest trees for the purposes of producing more fibre began in earnest in the last half century. The application of biotechnology to forest trees offers a great potential to hasten the pace of tree improvement for desirable end uses. This review outlines some of the progress that has been made in the application of biotechnology to forest trees, and considers the prospects for biotechnologically based tree improvement in the future.     

Changes in forest productivity across Alaska consistent with biome shift

Global vegetation models predict that boreal forests are particularly sensitive to a biome shift during the 21st century. This shift would manifest itself first at the biome's margins, with evergreen forest expanding into current tundra while being replaced by grasslands or temperate forest at the biome's southern edge. We evaluated changes in forest productivity since 1982 across boreal Alaska by linking satellite estimates of primary productivity and a large tree-ring data set. Trends in both records show consistent growth increases at the boreal-tundra ecotones that contrast with drought-induced productivity declines throughout interior Alaska. These patterns support the hypothesized effects of an initiating biome shift. Ultimately, tree dispersal rates, habitat availability and the rate of future climate change, and how it changes disturbance regimes, are expected to determine where the boreal biome will undergo a gradual geographic range shift, and where a more rapid decline.     

Variation of seasonal litterfall in subtropical montane cloud forests to typhoon severity and environmental factors

Forest litterfall is pivotal for biogeochemical cycles and for assessing the impacts of perturbations on ecosystems. Typhoon occurrence is the primary mechanism for producing litterfall; Taiwan is situated in one of the most frequently disturbed regions. However, no typhoons were recorded in 2018, only occurring three times since 1911. This rare occasion, along with the regular (2017) and extreme typhoon (2016) years, provides an opportunity to investigate the responses of typhoon-prone forest ecosystems to a future climate scenario: Elevated temperatures amplify the intensity but reduce the frequency of typhoons. We compared three years (2016–2018) of summer typhoon season (July–October) mean monthly litterfall (MML) in the subtropical montane cloud forests of northeastern Taiwan, and investigated the relationships between MML/typhoon-induced MML (ΔMML) and 17 biophysical, bioclimatic and topographic attributes. More MML was produced in 2016, caused by strong winds and heavy rainfall. However, there was no statistical difference between 2017 and 2018 since forests may also produce substantial amounts of litterfall in summer without typhoons. The relationship between ΔMML and 17 variables was relatively insensitive to typhoon severity. Variables associated with succession and forest management were crucial for modeling MML in the presence of typhoons, but none of them were pivotal for MML without typhoons. The mean air temperature and elevation (related to forest productivity) were crucial for MML without typhoons; surface curvature may form shelters to prevent extreme typhoon with reduced MML. These outcomes may shed light on future ecosystem dynamics in typhoon-prone forests under a changing climate. Abstract in Mandarin is available with online material.     

A global climate niche for giant trees

Rainforests are among the most charismatic as well as the most endangered ecosystems of the world. However, although the effects of climate change on tropical forests resilience is a focus of intense research, the conditions for their equally impressive temperate counterparts remain poorly understood, and it remains unclear whether tropical and temperate rainforests have fundamental similarities or not. Here we use new global data from high precision laser altimetry equipment on satellites to reveal for the first time that across climate zones ‘giant forests’ are a distinct and universal phenomenon, reflected in a separate mode of canopy height (~40 m) worldwide. Occurrence of these giant forests (cutoff height > 25 m) is negatively correlated with variability in rainfall and temperature. We also demonstrate that their distribution is sharply limited to situations with a mean annual precipitation above a threshold of 1,500 mm that is surprisingly universal across tropical and temperate climates. The total area with such precipitation levels is projected to increase by ~4 million km² globally. Our results thus imply that strategic management could in principle facilitate the expansion of giant forests, securing critically endangered biodiversity as well as carbon storage in selected regions.     

Fire-mediated dieback and compositional cascade in an Amazonian forest

The only fully coupled land-atmosphere global climate model predicts a widespread dieback of Amazonian forest cover through reduced precipitation. Although these predictions are controversial, the structural and compositional resilience of Amazonian forests may also have been overestimated, as current vegetation models fail to consider the potential role of fire in the degradation of forest ecosystems. We examine forest structure and composition in the Arapiuns River basin in the central Brazilian Amazon, evaluating post-fire forest recovery and the consequences of recurrent fires for the patterns of dominance of tree species. We surveyed tree plots in unburned and once-burned forests examined 1, 3 and 9 years after an unprecedented fire event, in twice-burned forests examined 3 and 9 years after fire and in thrice-burned forests examined 5 years after the most recent fire event. The number of trees recorded in unburned primary forest control plots was stable over time. However, in both once- and twice-burned forest plots, there was a marked recruitment into the 10-20cm diameter at breast height tree size classes between 3 and 9 years post-fire. Considering tree assemblage composition 9 years after the first fire contact, we observed (i) a clear pattern of community turnover among small trees and the most abundant shrubs and saplings, and (ii) that species that were common in any of the four burn treatments (unburned, once-, twice- and thrice-burned) were often rare or entirely absent in other burn treatments. We conclude that episodic wildfires can lead to drastic changes in forest structure and composition, with cascading shifts in forest composition following each additional fire event. Finally, we use these results to evaluate the validity of the savannization paradigm.     

Local neighborhood effects on long-term survival of individual trees in a neotropical forest

The survival of approximately 235 000 individual tropical trees and saplings in the 50 ha permanent plot on Barro Colorado Island (BCI), Panama was analyzed over a 13-year interval (1982–1995) as a function of four biotic neighborhood variables: (i) total stem density; (ii) conspecific density; (iii) relative plant size; and (iv) relative species richness. These neighborhood variables were measured in annular rings of width 2.5 m, extending 30 m from a given focal plant, and in one more distant annulus at 47.5–50 m. Because survival was spatially autocorrelated, a Gibbs sampler and a Monte Carlo Markov chain method were used for fitting an autologistic regression model to obtain unbiased estimates of parameter variances for hypothesis testing. After pooling all species at the community level, results showed that all four variables had significant and often strong effects on focal plant survival. Three of the four variables had negative effects on focal plant survival; relative plant size was the only variable with a positive effect (18% increase in the survival odds ratio). The variables with a negative effect on the survival odds ratio, in order of their effect strength in the nearest annulus, were: stem density (a 70% reduction in the survival odds ratio), conspecific density (50% reduction) and species richness (13% reduction). A guild-level analysis revealed considerable heterogeneity among guilds in their responses to these variables. For example, survival of gap species showed a much larger positive response to relative plant size than did survival of shade-tolerant species. Survival of shrub species was positively affected by conspecific density, but canopy tree survival was negatively affected. Conspecific density negatively affected survival of rare species much more strongly than survival of common species. The neighborhood effects of conspecific density disappear within approximately 12–15 m of the focal plant. Although locally strong, the rapid spatial decay of these effects raises unanswered questions about their quantitative contribution to the maintenance of tree diversity on landscape scales in the BCI forest.