广西黑叶猴栖息地景观格局破碎化分析及其对种群的影响

黑叶猴(Trachypithecus francoisi)是仅分布于喀斯特石山生境的珍稀濒危灵长类动物。由于非法捕杀和人类活动干扰,其种群数量正在急剧减少。同时,随着森林砍伐和土地开垦的加速,其栖息地严重破碎化。因此,了解栖息地破碎化对黑叶猴种群的影响对于保护这一珍稀濒危物种具有重要意义。基于遥感影像、土地利用数据以及黑叶猴种群调查数据,通过Fragstats软件开展广西黑叶猴栖息地景观破碎化分析,并通过相关性和多元逐步回归分析,探讨了景观格局对广西黑叶猴种群数量的影响。结果表明：(1)广西黑叶猴栖息地呈现破碎化严峻、斑块形状复杂化、斑块团聚程度较弱且分散化的现象;栖息地以林地景观占据重要优势,但人为景观的干扰十分强烈;在不同地区中,生境破碎化程度、人为干扰强度以及景观配置均呈现不同的特征,其中扶绥地区人为干扰最为强烈,德保地区的景观块数破碎化程度较为严重,而龙州地区的人为干扰程度最小,其森林景观最为聚集。(2)蔓延度指数、平均斑块分维指数、林地面积、林地斑块大小、裸岩面积和裸岩面积比重等景观指数与黑叶猴种群数量有显著正向关系,Shannon多样性指数则是显著负向关系;而耕地面积、耕地...     

人工林与天然林破碎化过程差异对比——以美国华盛顿州和密西西比州为例

森林损失和破碎化一直是国际社会普遍关注的重大环境问题之一。根据Forman景观变化包括穿孔、分割、破碎化、收缩和消失5种空间过程的理论,利用ArcGIS Modeler建立森林破碎化过程模型用以明确描述森林景观破碎化的空间过程和生态进程。基于NLCD2001、2006、2011 3期数据,以美国华盛顿州和密西西比州为研究区,利用森林破碎化过程模型,将森林损失斑块分为4种破碎化过程(分割类型因其线状特征被归入破碎化类型),对比分析天然林和人工林的破碎化过程在时空上的差异性。研究表明天然林破碎化斑块多分布于城市/森林、耕地/森林、以及灌木/森林的交界处,而人工林破碎化斑块分布格局较为零散;天然林中破碎化斑块和收缩斑块大多发生在上阶段收缩、破碎化以及穿孔斑块的边缘,而人工林中4种空间过程的承接关系不像天然林那么明显,但两者整体上都呈现相似的"收缩-消失-穿孔/破碎化"变化规律,主要表现为收缩类型占主导然后慢慢消退,穿孔和破碎化逐渐增多占据新的主导。     

黑河中游湿地景观破碎化过程及其驱动力分析

在遥感和GIS技术支持下,基于1975-2010年长时间序列遥感影像,选取斑块密度指数(PD)、景观内部生境面积指数(IA)、斑块平均面积指数(MPS)、斑块形状破碎化指数(FS1、FS2)等具有典型生态意义的景观指数模型,系统分析了黑河中游湿地景观的破碎化过程,并结合灰色关联分析、主成分分析等方法,探讨了影响研究区湿地景观破碎化过程的各驱动因子.结果表明:近35年来,研究区湿地景观破碎化主要表现为斑块平均面积的萎缩,斑块密度的上升以及斑块形状破碎化指数的增大.整个研究时段内,研究区湿地斑块平均面积减少了48.95hm2,斑块密度的上升0.006个/hm2;导致黑河中游湿地景观破碎化发生和发展的驱动力包含自然和人文两个方面.自然因子对湿地景观破碎化进程的影响则主要体现在气温和降水上,而且气温对湿地景观破碎化进程的影响程度明显大于降水.但在1975-2010年间的这一较小时间尺度上,人类活动对湿地景观破碎化的贡献率明显高于自然因子,人类活动能力的增强以及影响范围的不断扩大是引发黑河中游湿地景观破碎化的主因.     

基于“空间形态-破碎化-聚集度”的粤港澳大湾区森林景观格局时空演变

森林景观格局的时空演变研究能够帮助理解区域森林变化过程。传统的景观指数方法多以均值为计算结果且空间信息表达不足，基于形态学方法能够从空间上直观辨别景观类型，综合破碎化和聚集度的定量分析有助于进一步认识森林景观格局的演变特征。以1990、2000、2010、2020年粤港澳大湾区土地利用数据为基础，建立基于“空间形态-破碎化-聚集度”的综合研究框架，开展大湾区森林景观格局的时空演变研究。结果表明：(1)近30年大湾区森林形态以核心区为主，森林面积逐渐减少，而2010—2020年减少速率降低，各类型森林斑块均有所恢复；(2)整体破碎化程度较低，中部破碎化地区表现为先上升后下降的变化趋势；(3)聚集度结果表明，距离森林边界500 m内的森林斑块面积最大，约占研究区总面积的30%,而距离大于4.5 km的非森林斑块面积几乎翻倍增加，应重点关注该区域的森林损失。研究有助于全面理解森林景观格局的变化特征，相关结果可为粤港澳大湾区的森林生态修复工程、国土空间规划以及城市可持续发展提供科学依据。     

黑龙江省森林景观多样性动态

讨论了1949—1981年黑龙江省森林景观多样性的动态。利用1949年和1981年森林资源分布图,选取7个有代表性的度量景观多样性的定量指标：斑块密度、周长-面积分数维、聚集度、斑块散布与毗连指数、Shannon多样性指数、优势度、均匀度,在ESRI’S ARCGIS 8和FRAGSTATS 3．3软件支持下,系统研究了景观元素空间格局的变化。结果表明在近32年的时间进程中,区域森林景观破碎化现象加剧,其中以红松(Pinus koraiensis)林的破碎化最为严重。从斑块多样性、格局多样性和类型多样性的动态变化分析看出,原生的景观斑块类型在数量上不断减少或被异类景观所代替,即景观类型所占景观表面的百分比发生了变化,从而引起景观内部空间格局的改变。整个森林的景观多样性和景观类型分布的均匀性降低,优势度增加。人类不合理的经济活动,如毁林开荒、乱砍滥伐等,改变了景观异质性,从而造成景观多样性的变化。现在应该把对森林的保护和经营提到日程上来。天然林保护工程的实施对于促进林业部门休养生息、培育与保护森林资源,保护生物多样性和改善生态环境等具有重要意义。保护现有森林资源,实行采育结合,实施天然林保护工程,使森林的经营走可持续发展的道路是切实可行的解决办法．     

北京东灵山地区景观格局及破碎化评价

 人类活动已将北京东灵山地区地带性原生暖温带落叶阔叶林破坏殆尽。本项研究基于植被图,在地理信息系统(GIS)支持下,选择多种景观格局指数,从斑块面积、斑块数、斑块周长、分形维数和多样性的角度进行了格局分析和破碎化评价。结果表明,该区景观类型以次生林和灌丛为主,面积分布极不均衡,且多呈小面积零散分布。各森林类型的分布面积、周长和斑块数一般小于灌丛、草地和农田,且边界密度和斑块密度较高,显示出较高程度的破碎化。各景观类型的平均斑块面积和周长遵从分形规律,分形维数1.30,景观整体的斑块边界的褶皱程度较低。景观多样性的Shannon指数,景观组分的类型面积(2.262)<类型周长(2.435)<类型斑块数(2.675),均小于等概率情形(2.940)。上述结果均显示,该区森林景观破碎化程度较高。     

REDD+活动对生物多样性保护的潜在影响

基于《联合国气候变化框架公约》(UNFCCC)对“减少毁林和森林退化引起的碳排放”活动类型(REDD+)的规定和《生物多样性公约》(CBD)对生物多样性保障措施的要求,分析了避免毁林和森林退化、可持续森林管理、森林保护以及造林等减少森林碳排放和增加森林碳储量的REDD+活动类型对生物多样性可能产生的正面和负面影响,并就确保REDD+各种活动对生物多样性发挥积极影响提出了相应的方法和措施.REDD+活动对生物多样性的影响将取决于REDD+活动的规模、类型以及生物多样性安全保障措施的实施.设计REDD+活动时应充分考虑其对生物多样性及其他多重效益的利弊,执行REDD+活动时应采取适当的政策和措施来保护和提高生物多样性,国家政府和当地社区等利益相关者共同协商和进行密切的合作是确保REDD+活动成功实施的关键.为确保我国将来可能实施的REDD+活动有利于生物多样性的保护,国家在构建国家方案、政策措施、机构设置和监测体系时,应从保护目标、机构责任、利益相关群体、实施方案和监测计划等方面制定相应的保障措施.     

典型红壤侵蚀景观的时空变化——以福建长汀为例

基于典型红壤侵蚀区——福建长汀县1988、2000和2007年遥感影像和数字高程模型,获取侵蚀景观类型数据,并利用空间数学模型分析了1988—2007年研究区侵蚀景观格局的变化.结果表明:1988—2007年,研究区不同强度的侵蚀景观类型具有互相转移的特点,主要表现为由侵蚀强度较重的景观向侵蚀强度较轻的景观转移,同时存在少量侵蚀强度较轻景观向侵蚀强度较重景观转移的情形,研究区侵蚀景观空间质心的变化不大,河田镇一直是研究区侵蚀核心区域;研究期间,景观水平的景观格局指数变化反映出研究区景观的低异质性、低破碎化和规则化趋势;斑块水平的景观格局指数变化反映出低侵蚀强度、易治理的斑块整体好转,且合并变大,而高侵蚀强度、难治理的斑块则局部好转而破碎化.     

基于模拟景观的城市森林景观格局指数选取

基于现实的沈阳城市森林景观,模拟了4个景观格局梯度,并选取了1个与之相应的现实景观格局梯度,分析了28个景观格局指数在各梯度对景观破碎化和景观斑块形状复杂性的反映,从而筛选出描述这两种景观格局特征的适宜景观格局指数.结果表明：斑块密度（PD）和平均斑块面积（AREA_MN）在城市森林景观破碎化方面表现出较规律的变化趋势,斑块密度随破碎化程度的增加而增加,平均斑块面积随破碎化程度的增加而减小;面积加权平均周长面积比（PARA_AM）在描述景观斑块形状复杂性方面与景观格局梯度相吻合,且随斑块形状复杂性的增加而增加,能够较为准确地描述景观斑块形状的复杂性.     

长白山森林景观边界动态变化研究

通过野外调查、遥感和地理信息系统相结合的方法来研究长白山森林景观边界的动态变化规律,并通过相关性分析,探讨了长白山森林景观破碎化过程和景观边界指数变化的关系。首先对遥感影像进行计算机分类,其次,构建了描述景观边界的指标体系,再次,从景观边界的长度、密度、对比度、形状和多样性5个方面,对长白山森林景观边界的动态在景观类型尺度和景观尺度上进行分析。结果表明,在20多年的时问内,苔原面积减少了3694．8hm^2,云冷杉林的面积减少了130482．03hm^2,阔叶红松林面积增加了41610．4hm^2,岳桦林面积增加了66978hm^2．由于森林砍伐和毁林造田以及其它人类活动(如旅游)的影响,长白山森林景观的破碎化程度趋于增加,景观边界形状趋于复杂景观破碎化过程和景观边界指数变化的相关性分析证实了可以用景观形状指数(LSI)、对比度加权边界密度(CWEI))、边界加权总长度(TEGT)、加权景观形状指数(LSI-WGT)的变化来指示森林景观的破碎化程度。景观边界形状指数的大小还可以用来反映人类活动对景观的影响程度。最后,针对目前长白山森林景观破碎化程度趋于增大的情况,建议采取积极措施,防止长白山森林景观的进一步破碎化,以便更好地保护天然林。     

Traditional shifting agriculture: tracking forest carbon stock and biodiversity through time in western Panama

Reducing emissions from deforestation and forest degradation (REDD+) requires developing countries to quantify greenhouse gas emissions and removals from forests in a manner that is robust, transparent, and as accurate as possible. Although shifting cultivation is a dominant practice in several developing countries, there is still very limited information available on how to monitor this land‐use practice for REDD+ as little is known about the areas of shifting cultivation or the net carbon balance. In this study, we propose and test a methodology to monitor the effect of the shifting cultivation on above‐ground carbon stocks. We combine multiyear remote sensing information, taken from a 12‐year period, with an in‐depth community forest carbon stock inventory in Palo Seco Forest Reserve, western Panama. Using remote sensing, we were able to separate four forest classes expressing different forest‐use intensity and time‐since‐intervention, which demonstrate expected trends in above‐ground carbon stocks. The addition of different interventions observed over time is shown to be a good predictor, with remote sensing variables explaining 64.2% of the variation in forest carbon stocks in cultivated landscapes. Multitemporal and multispectral medium‐resolution satellite imagery is shown to be adequate for tracking land‐use dynamics of the agriculture‐fallow cycle. The results also indicate that, over time, shifting cultivation has a transitory effect on forest carbon stocks in the study area. This is due to the rapid recovery of forest carbon stocks, which results in limited net emissions. Finally, community participation yielded important additional benefits to measuring carbon stocks, including transparency and the valorization of local knowledge for biodiversity monitoring. Our study provides important inputs regarding shifting cultivation, which should be taken into consideration when national forest monitoring systems are created, given the context of REDD+ safeguards.     

A large‐scale field assessment of carbon stocks in human‐modified tropical forests

Tropical rainforests store enormous amounts of carbon, the protection of which represents a vital component of efforts to mitigate global climate change. Currently, tropical forest conservation, science, policies, and climate mitigation actions focus predominantly on reducing carbon emissions from deforestation alone. However, every year vast areas of the humid tropics are disturbed by selective logging, understory fires, and habitat fragmentation. There is an urgent need to understand the effect of such disturbances on carbon stocks, and how stocks in disturbed forests compare to those found in undisturbed primary forests as well as in regenerating secondary forests. Here, we present the results of the largest field study to date on the impacts of human disturbances on above and belowground carbon stocks in tropical forests. Live vegetation, the largest carbon pool, was extremely sensitive to disturbance: forests that experienced both selective logging and understory fires stored, on average, 40% less aboveground carbon than undisturbed forests and were structurally similar to secondary forests. Edge effects also played an important role in explaining variability in aboveground carbon stocks of disturbed forests. Results indicate a potential rapid recovery of the dead wood and litter carbon pools, while soil stocks (0–30 cm) appeared to be resistant to the effects of logging and fire. Carbon loss and subsequent emissions due to human disturbances remain largely unaccounted for in greenhouse gas inventories, but by comparing our estimates of depleted carbon stocks in disturbed forests with Brazilian government assessments of the total forest area annually disturbed in the Amazon, we show that these emissions could represent up to 40% of the carbon loss from deforestation in the region. We conclude that conservation programs aiming to ensure the long‐term permanence of forest carbon stocks, such as REDD+, will remain limited in their success unless they effectively avoid degradation as well as deforestation.     

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.     

A methodology to estimate national REDD+ reference levels using the Zero-Sum-Gains DEA approach

REDD+ reference levels directly impact the benefits which a country may receive. However, the existing “Compensation Reduction” (CR) and “Compensated Successful Efforts” (CSE) are only considered from a unilateral perspective of outputs or inputs. The combination of these two approaches is considered to estimate the REDD+ reference levels through the Zero-Sum-Gains Data Envelopment Analysis in this paper. The agricultural labor force and agricultural land area are used as input variables, and the gross agricultural production and carbon emissions from deforestation are considered as output variables. The REDD+ reference levels of 89 countries are calculated and classified through the Zero-Sum-Gains DEA model. The results demonstrate that the REDD+ reference levels are estimated efficiently through the Zero-Sum-Gains DEA model, and all countries with deforestation are in the Zero-Sum-Gains DEA frontier, indicating the overall Pareto optimality has been achieved. The empirical results also indicate that the use of Zero-Sum-Gains DEA model is more beneficial for Latin American and the Caribbean, while the countries that may see a revenue drop in REDD+ are in Africa, Asia and Oceania. Consequently, the final REDD+ reference levels should take into account both efficiency and fairness by selecting the appropriate fairness-efficiency weighting factor.     

The potential ecological costs and cobenefits of REDD: a critical review and case study from the Amazon region

The United Nations climate treaty may soon include a mechanism for compensating tropical nations that succeed in reducing carbon emissions from deforestation and forest degradation, source of nearly one fifth of global carbon emissions. We review the potential for this mechanism [reducing emissions from deforestation and degradation (REDD)] to provoke ecological damages and promote ecological cobenefits. Nations could potentially participate in REDD by slowing clear‐cutting of mature tropical forest, slowing or decreasing the impact of selective logging, promoting forest regeneration and restoration, and expanding tree plantations. REDD could also foster efforts to reduce the incidence of forest fire. Potential ecological costs include the accelerated loss (through displaced agricultural expansion) of low‐biomass, high‐conservation‐value ecosystems, and substitution of low‐biomass vegetation by monoculture tree plantations. These costs could be avoided through measures that protect low‐biomass native ecosystems. Substantial ecological cobenefits should be conferred under most circumstances, and include the maintenance or restoration of (1) watershed functions, (2) local and regional climate regimes, (3) soils and biogeochemical processes, (4) water quality and aquatic habitat, and (5) terrestrial habitat. Some tools already being developed to monitor, report and verify (MRV) carbon emissions performance can also be used to measure other elements of ecosystem function, making development of MRV systems for ecological cobenefits a concrete possibility. Analysis of possible REDD program interventions in a large‐scale Amazon landscape indicates that even modest flows of forest carbon funding can provide substantial cobenefits for aquatic ecosystems, but that the functional integrity of the landscape's myriad small watersheds would be best protected under a more even spatial distribution of forests. Because of its focus on an ecosystem service with global benefits, REDD could access a large pool of global stakeholders willing to pay to maintain carbon in forests, thereby providing a potential cascade of ecosystem services to local stakeholders who would otherwise be unable to afford them.     

Quantifying small‐scale deforestation and forest degradation in African woodlands using radar imagery

Carbon emissions from tropical land‐use change are a major uncertainty in the global carbon cycle. In African woodlands, small‐scale farming and the need for fuel are thought to be reducing vegetation carbon stocks, but quantification of these processes is hindered by the limitations of optical remote sensing and a lack of ground data. Here, we present a method for mapping vegetation carbon stocks and their changes over a 3‐year period in a > 1000 km² region in central Mozambique at 0.06 ha resolution. L‐band synthetic aperture radar imagery and an inventory of 96 plots are combined using regression and bootstrapping to generate biomass maps with known uncertainties. The resultant maps have sufficient accuracy to be capable of detecting changes in forest carbon stocks of as little as 12 MgC ha^?1 over 3 years with 95% confidence. This allows characterization of biomass loss from deforestation and forest degradation at a new level of detail. Total aboveground biomass in the study area was reduced by 6.9 ± 4.6% over 3 years: from 2.13 ± 0.12 TgC in 2007 to 1.98 ± 0.11 TgC in 2010, a loss of 0.15 ± 0.10 TgC. Degradation probably contributed 67% (96.9 ± 91.0 GgC) of the net loss of biomass, but is associated with high uncertainty. The detailed mapping of carbon stock changes quantifies the nature of small‐scale farming. New clearances were on average small (median 0.2 ha) and were often additions to already cleared land. Deforestation events reduced biomass from 33.5 to 11.9 MgC ha^?1 on average_. Contrary to expectations, we did not find evidence that clearances were targeted towards areas of high biomass. Our method is scalable and suitable for monitoring land cover change and vegetation carbon stocks in woodland ecosystems, and can support policy approaches towards reducing emissions from deforestation and degradation (REDD).     

Land-use Change Modeling in a Brazilian Indigenous Reserve: Construction of a Reference Scenario for the Suruí REDD Project

Interactions of indigenous peoples with the surrounding non-indigenous society are often the main sources of social and environmental changes in indigenous lands. In the case of the Suruí in Brazilian Amazonia’s “arc of deforestation,” these influences are leading to deforestation and logging that threaten both the forest and the sustainability of the group’s productive systems. The Suruí tribal leadership has initiated a proposal for an economic alternative based on Reducing Emissions from Deforestation and Degradation (REDD). This has become a key case in global discussions on indigenous participation in REDD. The realism of the baseline scenario that serves as a reference for determining the amount of deforestation and emissions avoided by the proposed project is critical to assuring the reality of the carbon benefits claimed. Here we examine the SIMSURUI model, its input parameters and the implications of the Suruí Forest Carbon Project for indigenous participation in climate mitigation efforts.     

Developing Cost-Effective Field Assessments of Carbon Stocks in Human-Modified Tropical Forests

Across the tropics, there is a growing financial investment in activities that aim to reduce emissions from deforestation and forest degradation, such as REDD+. However, most tropical countries lack on-the-ground capacity to conduct reliable and replicable assessments of forest carbon stocks, undermining their ability to secure long-term carbon finance for forest conservation programs. Clear guidance on how to reduce the monetary and time costs of field assessments of forest carbon can help tropical countries to overcome this capacity gap. Here we provide such guidance for cost-effective one-off field assessments of forest carbon stocks. We sampled a total of eight components from four different carbon pools (i.e. aboveground, dead wood, litter and soil) in 224 study plots distributed across two regions of eastern Amazon. For each component we estimated survey costs, contribution to total forest carbon stocks and sensitivity to disturbance. Sampling costs varied thirty-one-fold between the most expensive component, soil, and the least, leaf litter. Large live stems (≥10 cm DBH), which represented only 15% of the overall sampling costs, was by far the most important component to be assessed, as it stores the largest amount of carbon and is highly sensitive to disturbance. If large stems are not taxonomically identified, costs can be reduced by a further 51%, while incurring an error in aboveground carbon estimates of only 5% in primary forests, but 31% in secondary forests. For rapid assessments, necessary to help prioritize locations for carbon- conservation activities, sampling of stems ≥20cm DBH without taxonomic identification can predict with confidence (R² = 0.85) whether an area is relatively carbon-rich or carbon-poor—an approach that is 74% cheaper than sampling and identifying all the stems ≥10cm DBH. We use these results to evaluate the reliability of forest carbon stock estimates provided by the IPCC and FAO when applied to human-modified forests, and to highlight areas where cost savings in carbon stock assessments could be most easily made.     

Will Passive Protection Save Congo Forests?

Central Africa’s tropical forests are among the world’s largest carbon reserves. Historically, they have experienced low rates of deforestation. Pressures to clear land are increasing due to development of infrastructure and livelihoods, foreign investment in agriculture, and shifting land use management, particularly in the Democratic Republic of Congo (DRC). The DRC contains the greatest area of intact African forests. These store approximately 22 billion tons of carbon in aboveground live biomass, yet only 10% are protected. Can the status quo of passive protection — forest management that is low or nonexistent — ensure the preservation of this forest and its carbon? We have developed the SimCongo model to simulate changes in land cover and land use based on theorized policy scenarios from 2010 to 2050. Three scenarios were examined: the first (Historical Trends) assumes passive forest protection; the next (Conservation) posits active protection of forests and activation of the national REDD+ action plan, and the last (Agricultural Development) assumes increased agricultural activities in forested land with concomitant increased deforestation. SimCongo is a cellular automata model based on Bayesian statistical methods tailored for the DRC, built with the Dinamica-EGO platform. The model is parameterized and validated with deforestation observations from the past and runs the scenarios from 2010 through 2050 with a yearly time step. We estimate the Historical Trends trajectory will result in average emissions of 139 million t CO₂ year^-1 by the 2040s, a 15% increase over current emissions. The Conservation scenario would result in 58% less clearing than Historical Trends and would conserve carbon-dense forest and woodland savanna areas. The Agricultural Development scenario leads to emissions of 212 million t CO₂ year^-1 by the 2040s. These scenarios are heuristic examples of policy’s influence on forest conservation and carbon storage. Our results suggest that 1) passive protection of the DRC’s forest and woodland savanna is insufficient to reduce deforestation; and 2): enactment of a REDD+ plan or similar conservation measure is needed to actively protect Congo forests, their unique ecology, and their important role in the global carbon cycle.