Impacts of land cover changes on climate trends in Jiangxi province China

Land-use/land-cover (LULC) change is an important climatic force, and is also affected by climate change. In the present study, we aimed to assess the regional scale impact of LULC on climate change using Jiangxi Province, China, as a case study. To obtain reliable climate trends, we applied the standard normal homogeneity test (SNHT) to surface air temperature and precipitation data for the period 1951–1999. We also compared the temperature trends computed from Global Historical Climatology Network (GHCN) datasets and from our analysis. To examine the regional impacts of land surface types on surface air temperature and precipitation change integrating regional topography, we used the observation minus reanalysis (OMR) method. Precipitation series were found to be homogeneous. Comparison of GHCN and our analysis on adjusted temperatures indicated that the resulting climate trends varied slightly from dataset to dataset. OMR trends associated with surface vegetation types revealed a strong surface warming response to land barrenness and weak warming response to land greenness. A total of 81.1 % of the surface warming over vegetation index areas (0–0.2) was attributed to surface vegetation type change and regional topography. The contribution of surface vegetation type change decreases as land cover greenness increases. The OMR precipitation trend has a weak dependence on surface vegetation type change. We suggest that LULC integrating regional topography should be considered as a force in regional climate modeling.     

Reforestation and surface cooling in temperate zones: Mechanisms and implications

Land‐use/cover change (LUCC) is an important driver of environmental change, occurring at the same time as, and often interacting with, global climate change. Reforestation and deforestation have been critical aspects of LUCC over the past two centuries and are widely studied for their potential to perturb the global carbon cycle. More recently, there has been keen interest in understanding the extent to which reforestation affects terrestrial energy cycling and thus surface temperature directly by altering surface physical properties (e.g., albedo and emissivity) and land–atmosphere energy exchange. The impacts of reforestation on land surface temperature and their mechanisms are relatively well understood in tropical and boreal climates, but the effects of reforestation on warming and/or cooling in temperate zones are less certain. This study is designed to elucidate the biophysical mechanisms that link land cover and surface temperature in temperate ecosystems. To achieve this goal, we used data from six paired eddy‐covariance towers over co‐located forests and grasslands in the temperate eastern United States, where radiation components, latent and sensible heat fluxes, and meteorological conditions were measured. The results show that, at the annual time scale, the surface of the forests is 1–2°C cooler than grasslands, indicating a substantial cooling effect of reforestation. The enhanced latent and sensible heat fluxes of forests have an average cooling effect of ?2.5°C, which offsets the net warming effect (+1.5°C) of albedo warming (+2.3°C) and emissivity cooling effect (?0.8°C) associated with surface properties. Additional daytime cooling over forests is driven by local feedbacks to incoming radiation. We further show that the forest cooling effect is most pronounced when land surface temperature is higher, often exceeding ?5°C. Our results contribute important observational evidence that reforestation in the temperate zone offers opportunities for local climate mitigation and adaptation.     

Human modification of the landscape and surface climate in the next fifty years

Human modification of the landscape potentially affects exchanges of energy and water between the terrestrial biosphere and the atmosphere. This study develops a possible scenario for land cover in the year 2050 based on results from the IMAGE 2 (Integrated Model to Assess the Greenhouse Effect) model, which projects land‐cover changes in response to demographic and economic activity. We use the land‐cover scenario as a surface boundary condition in a biophysically‐based land‐surface model coupled to a general circulation model for a 15‐years simulation with prescribed sea surface temperature and compare with a control run using current land cover. To assess the sensitivity of climate to anthropogenic land‐cover change relative to the sensitivity to decadal‐scale interannual variations in vegetation density, we also carry out two additional simulations using observed normalized difference vegetation index (NDVI) from relatively low (1982–83) and high (1989–90) years to describe the seasonal phenology of the vegetation. In the past several centuries, large‐scale land‐cover change occurred primarily in temperate latitudes through conversion of forests and grassland to highly productive cropland and pasture. Several studies in the literature indicate that past changes in surface climate resulting from this conversion had a cooling effect owing to changes in vegetation morphology (increased albedo). In contrast, this study indicates that future land‐cover change, likely to occur predominantly in the tropics and subtropics, has a warming effect governed by physiological rather than morphological mechanisms. The physiological mechanism is to reduce carbon assimilation and consequently latent relative to sensible heat flux resulting in surface temperature increases up to 2 °C and drier hydrologic conditions in locations where land cover was altered in the experiment. In addition, in contrast to an observed decrease in diurnal temperature range (DTR) over land expected with greenhouse warming, results here suggest that future land‐cover conversion in tropics could increase the DTR resulting from decreased evaporative cooling during the daytime. For grid cells with altered land cover, the sensitivity of surface temperature to future anthropogenic land‐cover change is generally within the range induced by decadal‐scale interannual variability in vegetation density in temperate latitudes but up to 1.5 °C warmer in the tropics.     

Climate-induced changes in the vegetation pattern of China in the 21st century

Quantifying climate-induced changes in vegetation patterns is essential to understanding land–climate interactions and ecosystem changes. In the present study, we estimated various distributional changes of vegetation under different climate-change scenarios in the 21st century. Both hypothetical scenarios and Hedley RCM scenarios show that the transitional vegetation types, such as shrubland and grassland, have higher sensitivity to climatic change compared to vegetation under extreme climatic conditions, such as the evergreen broadleaf forest or desert, barren lands. Mainly, the sensitive areas in China lie in the Tibetan Plateau, Yunnan-Guizhou Plateau, northeastern plain of China and eco-zones between different vegetations. As the temperature increases, mixed forests and deciduous broadleaf forests will shift towards northern China. Grassland, shrubland and wooded grassland will extend to southeastern China. The RCM-project climate changes generally have caused positive vegetation changes; vegetation cover will probably improve 19% relative to baseline, and the forest will expand to 8% relative to baseline, while the desert and bare ground will reduce by about 13%.     

基于MODIS数据的中国三种主要土地类型变化的空间特征分析

人类活动使得土地利用和植被覆盖发生了巨大变化,直接影响着全球气候。本研究通过从2000—2013年对中国三种主要土地利用类型的NDVI变化特征进行了分析,结果表明:(1)14年来,中国三种主要土地利用类型NDVI平均值均有增强的趋势。(2)三种主要土地利用类型中除耕地中的水田,林地中的有林地和草地中的高覆盖草地增长速率不显著外,其他土地类型增长速率均显著。(3)三种土地利用类型均以改善面积大于退化面积,耕地中改善面积占总耕地的64.21%,退化的区域占18.50%;林地改善的区域占总林地的54.21%,退化的区域占20.13%;草地改善的区域占55.53%,退化的区域占18.23%。三种土地类型均有所改善且改善明显的区域主要集中在甘肃以南,陕西以北和东北部分地区。     

A continent under stress: interactions, feedbacks and risks associated with impact of modified land cover on Australia's climate

Global climate change is the major and most urgent global environmental issue. Australia is already experiencing climate change as evidenced by higher temperatures and more frequent and severe droughts. These impacts are compounded by increasing land use pressures on natural resources and native ecosystems. This paper provides a synthesis of the interactions, feedbacks and risks of natural climate variability, climate change and land use/land cover change (LUCC) impacting on the Australian continent and how they vary regionally. We review evidence of climate change and underlying processes resulting from interactions between global warming caused by increased concentration of atmospheric greenhouse gases and modification of the land surface. The consequences of ignoring the effect of LUCC on current and future droughts in Australia could have catastrophic consequences for the nation's environment, economy and communities. We highlight the need for more integrated, long-term and adaptive policies and regional natural resource management strategies that restore the beneficial feedbacks between native vegetation cover and local-regional climate, to help ameliorate the impact of global warming.     

中国北方草地与农牧交错带植被的NDVI-Ts空间的年内变化特征

利用多时相或时序植被指数(normalize difference vegetation index,NDVI)数据进行地表覆盖研究已取得了大量成果。随着陆地表面温度(1and surface temperature,TS)遥感反演精度的不断提高,将Ts与NDVI结合起来进行地表植被动态变化的监测已成为可能。本文主要包括以下三部分内容：1)介绍了基于卫星遥感数据的NDVI、Ts和Ts／NDVI计算方法。2)讨论NDVI、Ts和Ts／NDVI数据对植被覆盖信息表达的差异,并分析了中国北方草地与农牧交错带植被在NDVI-TS空间的年内变化特征。3)利用信息熵和平均梯度,定量分析了NDVI、Ts和Ts／NDVI数据在信息表达丰富度方面的差异,并对在不同地表植被覆盖下,Ts／NDVI数据对信息提高程度的敏感性进行了讨论。     

中国北方草地与农牧交错带植被的NDVI-Ts空间的年内变化特征

利用多时相或时序植被指数(normalize difference vegetation index,NDVI)数据进行地表覆盖研究已取得了大量成果.随着陆地表面温度(1and surface temperature,Ts)遥感反演精度的不断提高,将Ts与NDVI结合起来进行地表植被动态变化的监测已成为可能.本文主要包括以下三部分内容:1)介绍了基于卫星遥感数据的NDVI、Ts和Ts/NDVI计算方法.2)讨论NDVI、Ts和Ts/NDVI数据对植被覆盖信息表达的差异,并分析了中国北方草地与农牧交错带植被在NDVI-Ts空间的年内变化特征.3)利用信息熵和平均梯度,定量分析了NDVI、Ts和 Ts/NDVI数据在信息表达丰富度方面的差异,并对在不同地表植被覆盖下,Ts/NDVI数据对信息提高程度的敏感性进行了讨论.     

土地利用/覆盖变化对中国不同季节气温的影响

近几十年中国地区土地利用/覆盖变化(LUCC)较大,在区域气候模拟中尤其需要使用更加准确的土地利用/覆盖数据。基于模式原有的USGS和新开发的LUC90两种土地利用/覆盖资料,利用区域环境集成模拟系统(RIEMS2.0)分别进行连续10a模拟,分析LUCC对中国不同季节气温的影响。结果表明:1)采用LUC90资料后,中国及东北、华北、华南夏季平均气温增加,但只有东北模拟与观测值的偏差减小,且通过显著性检验(P0.01)。中国及东北、华南冬季平均气温增加,并且模拟与观测值的偏差减少。中国及华北和华南对冬季气温年际变率的模拟改善好于夏季。2)土地利用/覆盖变化通过影响潜热通量的变化和净吸收辐射通量的变化来影响不同季节气温的变化。冬季净辐射通量变化对气温变化的贡献较夏季大,而夏季潜热通量变化对气温变化的贡献较冬季大。雨养农田转变森林、草地、灌溉农田过程造成通量变化,其对气温变化的影响也存在不同分区季节的差异。     

2000-2019年四川省植被恢复成效与影响因素

国家实施天然林资源保护工程与退耕还林等生态建设工程,为构筑长江上游生态屏障、促进长江流域经济可持续发展做出了突出贡献;评估退耕还林等生态工程实施后植被恢复成效及影响因素是促进区域植被恢复优化与生态环境改善的关键一步。基于MODIS MOD13Q1数据,应用Theil Sen斜率与Mann-Kendall趋势检验、“基线”评价方法、时空地理加权回归模型等量化不同时间尺度的植被时空变化、恢复成效和恢复机制。结果表明(1)植被覆盖状况良好,截止2019年底,四川省91%的区域植被出现增长,四川盆地东北部、四川省南部地区以及东南部乌蒙山、川西北高原地区植被覆盖较高;成都市内以及周围市区植被覆盖率较低。(2)植被恢复成效时空差异显著,占全省面积98.68%的区域植被恢复成效明显,高值区面积占比71.47%,集中于除成都平原外的四川省绝大部分区域。(3)气候变化对植被变化的影响以不显著为主,气温、降水对四川省植被恢复影响微弱,海拔和>35°坡度面积比等地理环境因子则以弱抑制作用为主。(4)在相对平稳的气候背景下,人均财政支出、耕地面积与人均GDP所代表的社会经济因素是植被恢复成效改善的重要影...     

Modelling climate response to historical land cover change

In order to estimate the effect of historical land cover change (deforestation) on climate, we perform a set of experiments with a climate system model of intermediate complexity – CLIMBER-2. We focus on the biophysical effect of the land cover change on climate and do not explicitly account for the biogeochemical effect. A dynamic scenario of deforestation during the last millennium is formulated based on the rates of land conversion to agriculture. The deforestation scenario causes a global cooling of 0.35 °C with a more notable cooling of the northern hemisphere (0.5 °C). The cooling is most pronounced in the northern middle and high latitudes, especially during the spring season. To compare the effect of deforestation on climate with other forcings, climate responses to the changing atmospheric CO₂ concentration and solar irradiance are also analysed. When all three factors are taken into account, dynamics of northern hemisphere temperature during the last 300 years within the model are generally in agreement with the observed (reconstructed) temperature trend. We conclude that the impact of historical land cover changes on climate is comparable with the impact of the other climate forcings and that land cover forcing is important for reproducing historical climate change.     

Climate and CO2 controls on global vegetation distribution at the last glacial maximum: analysis based on palaeovegetation data, biome modelling and palaeoclimate simulations

The global vegetation response to climate and atmospheric CO₂ changes between the last glacial maximum and recent times is examined using an equilibrium vegetation model (BIOME4), driven by output from 17 climate simulations from the Palaeoclimate Modelling Intercomparison Project. Features common to all of the simulations include expansion of treeless vegetation in high northern latitudes; southward displacement and fragmentation of boreal and temperate forests; and expansion of drought‐tolerant biomes in the tropics. These features are broadly consistent with pollen‐based reconstructions of vegetation distribution at the last glacial maximum. Glacial vegetation in high latitudes reflects cold and dry conditions due to the low CO₂ concentration and the presence of large continental ice sheets. The extent of drought‐tolerant vegetation in tropical and subtropical latitudes reflects a generally drier low‐latitude climate. Comparisons of the observations with BIOME4 simulations, with and without consideration of the direct physiological effect of CO₂ concentration on C₃ photosynthesis, suggest an important additional role of low CO₂ concentration in restricting the extent of forests, especially in the tropics. Global forest cover was overestimated by all models when climate change alone was used to drive BIOME4, and estimated more accurately when physiological effects of CO₂ concentration were included. This result suggests that both CO₂ effects and climate effects were important in determining glacial‐interglacial changes in vegetation. More realistic simulations of glacial vegetation and climate will need to take into account the feedback effects of these structural and physiological changes on the climate.     

Coupling dynamic models of climate and vegetation

Numerous studies have underscored the importance of terrestrial ecosystems as an integral component of the Earth's climate system. This realization has already led to efforts to link simple equilibrium vegetation models with Atmospheric General Circulation Models through iterative coupling procedures. While these linked models have pointed to several possible climate–vegetation feedback mechanisms, they have been limited by two shortcomings: (i) they only consider the equilibrium response of vegetation to shifting climatic conditions and therefore cannot be used to explore transient interactions between climate and vegetation; and (ii) the representations of vegetation processes and land-atmosphere exchange processes are still treated by two separate models and, as a result, may contain physical or ecological inconsistencies. Here we present, as a proof concept, a more tightly integrated framework for simulating global climate and vegetation interactions. The prototype coupled model consists of the GENESIS (version 2) Atmospheric General Circulation Model and the IBIS (version 1) Dynamic Global Vegetation Model. The two models are directly coupled through a common treatment of land surface and ecophysiological processes, which is used to calculate the energy, water, carbon, and momentum fluxes between vegetation, soils, and the atmosphere. On one side of the interface, GENESIS simulates the physics and general circulation of the atmosphere. On the other side, IBIS predicts transient changes in the vegetation structure through changes in the carbon balance and competition among plants within terrestrial ecosystems. As an initial test of this modelling framework, we perform a 30 year simulation in which the coupled model is supplied with modern CO₂ concentrations, observed ocean temperatures, and modern insolation. In this exploratory study, we run the GENESIS atmospheric model at relatively coarse horizontal resolution (4.5° latitude by 7.5° longitude) and IBIS at moderate resolution (2° latitude by 2° longitude). We initialize the models with globally uniform climatic conditions and the modern distribution of potential vegetation cover. While the simulation does not fully reach equilibrium by the end of the run, several general features of the coupled model behaviour emerge. We compare the results of the coupled model against the observed patterns of modern climate. The model correctly simulates the basic zonal distribution of temperature and precipitation, but several important regional biases remain. In particular, there is a significant warm bias in the high northern latitudes, and cooler than observed conditions over the Himalayas, central South America, and north-central Africa. In terms of precipitation, the model simulates drier than observed conditions in much of South America, equatorial Africa and Indonesia, with wetter than observed conditions in northern Africa and China. Comparing the model results against observed patterns of vegetation cover shows that the general placement of forests and grasslands is roughly captured by the model. In addition, the model simulates a roughly correct separation of evergreen and deciduous forests in the tropical, temperate and boreal zones. However, the general patterns of global vegetation cover are only approximately correct: there are still significant regional biases in the simulation. In particular, forest cover is not simulated correctly in large portions of central Canada and southern South America, and grasslands extend too far into northern Africa. These preliminary results demonstrate the feasibility of coupling climate models with fully dynamic representations of the terrestrial biosphere. Continued development of fully coupled climate-vegetation models will facilitate the exploration of a broad range of global change issues, including the potential role of vegetation feedbacks within the climate system, and the impact of climate variability and transient climate change on the terrestrial biosphere.     

黄河流域植被时空变化及其对气候要素的响应

在气候变化和人类活动的双重作用下,黄河流域生态环境不断发生变化。探讨植被生长动态对于实施生态保护政策至关重要。利用Advanced Very High Resolution Radiometer(AVHRR) Leaf Area Index(LAI)遥感资料,结合气候要素数据,分析1981—2017年黄河流域植被覆盖的时空分布特征,探讨气候要素对其变化的影响及贡献率。研究结果表明：(1)时序上,黄河流域植被覆盖呈显著增长趋势,夏季植被覆盖的增长幅度和年际波动最大,冬季植被覆盖呈缓慢平稳增长,波动最小。(2)空间上,植被覆盖显著提高的区域占整个区域的52.1%,主要分布在中东部平原;显著降低的区域占4%,主要分布在北部和西部高原山地;生态脆弱的区域植被覆盖率大多有不同程度的提高,但生态环境良好的部分区域植被覆盖率降低。(3)时序上,黄河流域植被覆盖与气温具有显著的正相关关系。春夏冬三季的植被覆盖与气温呈显著正相关,与降水呈不显著关系;秋季的植被覆盖与气温和降水量均呈显著正相关;春秋冬三季的植被覆盖与太阳辐射呈不显著负相关,夏季的植被覆盖与太阳辐射呈不显著正相关。春夏秋冬四季的气温对植被覆...     

应用遥感技术研究土地利用/土地覆盖变化及其对土壤侵蚀过程的影响--以印度北部Pali Gad山地流域为例

应用遥感技术评估了印度北部Pali Gad山地流域过去几十年里土地利用／土地覆盖变化及其造成的土壤侵蚀程度,并基于摩根参数模型（Morgan Parametric Model）的方法来测定土壤的侵蚀程度;结果表明,由于不同的坡向受到太阳光照的不同可以引起土地覆盖的变迁;海拔和坡度已不再是阻碍人们获取自然资源的因素,人们的活动范围正转移到更高的海拔和更陡峭的坡度;揭示了土地利用／土地覆盖变化对土壤侵蚀进程有着直接的影响。     

Land‐use change outweighs projected effects of changing rainfall on tree cover in sub‐Saharan Africa

Global change will likely affect savanna and forest structure and distributions, with implications for diversity within both biomes. Few studies have examined the impacts of both expected precipitation and land use changes on vegetation structure in the future, despite their likely severity. Here, we modeled tree cover in sub‐Saharan Africa, as a proxy for vegetation structure and land cover change, using climatic, edaphic, and anthropic data (R² = 0.97). Projected tree cover for the year 2070, simulated using scenarios that include climate and land use projections, generally decreased, both in forest and savanna, although the directionality of changes varied locally. The main driver of tree cover changes was land use change; the effects of precipitation change were minor by comparison. Interestingly, carbon emissions mitigation via increasing biofuels production resulted in decreases in tree cover, more severe than scenarios with more intense precipitation change, especially within savannas. Evaluation of tree cover change against protected area extent at the WWF Ecoregion scale suggested areas of high biodiversity and ecosystem services concern. Those forests most vulnerable to large decreases in tree cover were also highly protected, potentially buffering the effects of global change. Meanwhile, savannas, especially where they immediately bordered forests (e.g. West and Central Africa), were characterized by a dearth of protected areas, making them highly vulnerable. Savanna must become an explicit policy priority in the face of climate and land use change if conservation and livelihoods are to remain viable into the next century.     

中国西北地区植被NPP多时间尺度变化及其对气候变化的响应

净初级生产力(NPP)是评估植被生长的重要参数,也是评价区域生态环境质量的重要指标。以"一带一路"枢纽地区西北六省为研究区,基于多年连续的GIMMS NDVI资料和气象数据,利用CASA模型,估算了西北六省34年NPP值,利用MK和EEMD方法,揭示了NPP变化的非线性特征,并探究不同时间尺度植被NPP变化对气候变化的响应。研究结果发现:(1)1982—2015年生长季植被NPP总体呈增加趋势,线性增长率为0.718 gCm~(-2) a~(-1);大多数研究区植被NPP短时间内将保持现有变化趋势,尤其是青藏高原、塔里木盆地边缘和内蒙古南部一带。(2)1982—2015年植被NPP以3年周期变化和长期增加趋势为主。其中陕西的南部,甘肃、新疆、宁夏和青海的北部以及内蒙古中部和北部以3年周期变化为主导,而陕西的北部,甘肃、新疆、宁夏的南部以及内蒙古东部以长期变化为主。不同植被类型NPP变化差异明显:针叶林、阔叶林以及混交林以3年周期波动为主,而灌木、草地和农田以3年周期波动和长期增长趋势为主。(3)NPP与气温和降水之间的相关性随着时间尺度的增大逐渐显著。在3年时间尺度上,大多数研究区NPP与气温和降水的相关性很小(P0.05)。6年时间尺度上,NPP与降水量呈正相关的区域向南略有扩散,其中青海南部高寒草甸NPP与降水的相关性由负相关转为正相关。在长期趋势上,NPP与气温和降水量具有非常显著的相关关系,且呈正相关的区域大于负相关的区域。本研究发现多时间尺度能够更好的分析NPP时空特征以及不同时间尺度NPP对气候变化的响应,有助于揭示全球气候变化背景下植被NPP对气候变化的非线性响应机制,评价气候变化的生态坏境风险,为西北六省区域可持续发展和生态环境保护提供理论依据。     

The global distribution of cultivable lands: current patterns and sensitivity to possible climate change

Aim This study makes quantitative global estimates of land suitability for cultivation based on climate and soil constraints. It evaluates further the sensitivity of croplands to any possible changes in climate and atmospheric CO₂ concentrations. Location The location is global, geographically explicit. Methods The methods used are spatial data synthesis and analysis and numerical modelling. Results There is a cropland ‘reserve’ of 120%, mainly in tropical South America and Africa. Our climate sensitivity analysis indicates that the southern provinces of Canada, north‐western and north‐central states of the United States, northern Europe, southern Former Soviet Union and the Manchurian plains of China are most sensitive to changes in temperature. The Great Plains region of the United States and north‐eastern China are most sensitive to changes in precipitation. The regions that are sensitive to precipitation change are also sensitive to changes in CO₂, but the magnitude is small compared to the influence of direct climate change. We estimate that climate change, as simulated by global climate models, will expand cropland suitability by an additional 16%, mainly in the Northern Hemisphere high latitudes. However, the tropics (mainly Africa, northern South America, Mexico and Central America and Oceania) will experience a small decrease in suitability due to climate change. Main conclusions There is a large reserve of cultivable croplands, mainly in tropical South America and Africa. However, much of this land is under valuable forests or in protected areas. Furthermore, the tropical soils could potentially lose fertility very rapidly once the forest cover is removed. Regions that lie at the margins of temperature or precipitation limitation to cultivation are most sensitive to changes in climate and atmospheric CO₂ concentration. It is anticipated that climate change will result in an increase in cropland suitability in the Northern Hemisphere high latitudes (mainly in developed nations), while the tropics will lose suitability (mainly in developing nations).     

Mountain vegetation change quantification using surface landscape metrics in Lancang watershed,China

Land cover and vegetation change are among the most important aspects of environmental change. Vegetation change can be quantified by landscape pattern indices (LPI). Landscape indices are routinely calculated using planar land use/land cover (LU/LC) maps, obtained by the projection of a non-flat landscape surface into a two-dimensional Cartesian space. Especially in mountainous areas, quantification on planar maps can lead to underestimation of vegetation and land cover changes. Hoechstetter et al. (2008) developed a method to compute LPIs in a surface structure by calculating landscape patch surface area and surface perimeter from digital elevation models (DEM). As yet there have been no applications of these surface landscape indices on land use/land cover and vegetation change quantification. The objectives of this study are to (1) choose a LPI method (surface metrics pattern analysis or common planimetric metrics pattern analysis) for vegetation change quantification; and (2) employ the selected surface LPI method to assess vegetation pattern change in two mountainous areas of the Lancang watershed, Yunnan Province, China. The results show that the surface approach to estimate changes of class area (CA), mean patch area (MPA), and mean Euclidean Near-Neighbor distance (MENN) may obtain more accurate results for quantifying vegetation change in steep mountain areas. Forest fragmentation increased significantly over time in the two different mountainous study areas. The patches of two land cover classes, (i) agricultural land and (ii) low density forest and tall shrubs, became more aggregated in the northern (temperate) study area. In the southern (tropical) study area, rubber plantations increased considerably in size and became more aggregated.     

Vegetation-atmosphere interactions and their role in global warming during the latest Cretaceous

Forest vegetation has the ability to warm Recent climate by its effects on albedo and atmospheric water vapour, but the role of vegetation in warming climates of the geologic past is poorly understood. This study evaluates the role of forest vegetation in maintaining warm climates of the Late Cretaceous by (1) reconstructing global palaeovegetation for the latest Cretaceous (Maastrichtian); (2) modelling latest Cretaceous climate under unvegetated conditions and different distributions of palaeovegetation; and (3) comparing model output with a global database of palaeoclimatic indicators. Simulation of Maastrichtian climate with the land surface coded as bare soil produces high-latitude temperatures that are too cold to explain the documented palaeogeographic distribution of forest and woodland vegetation. In contrast, simulations that include forest vegetation at high latitudes show significantly warmer temperatures that are sufficient to explain the widespread geographic distribution of high-latitude deciduous forests. These warmer temperatures result from decreased albedo and feedbacks between the land surface and adjacent oceans. Prescribing a realistic distribution of palaeovegetation in model simulations produces the best agreement between simulated climate and the geologic record of palaeoclimatic indicators. Positive feedbacks between high-latitude forests, the atmosphere, and ocean contributed significantly to high-latitude warming during the latest Cretaceous, and imply that high-latitude forest vegetation was an important source of polar warmth during other warm periods of geologic history.