Crime,weather, and climate change

This paper estimates the impact of climate change on the prevalence of criminal activity in the United States. The analysis is based on a 30-year panel of monthly crime and weather data for 2997 US counties. I identify the effect of weather on monthly crime by using a semi-parametric bin estimator and controlling for state-by-month and county-by-year fixed effects. The results show that temperature has a strong positive effect on criminal behavior, with little evidence of lagged impacts. Between 2010 and 2099, climate change will cause an additional 22,000 murders, 180,000 cases of rape, 1.2 million aggravated assaults, 2.3 million simple assaults, 260,000 robberies, 1.3 million burglaries, 2.2 million cases of larceny, and 580,000 cases of vehicle theft in the United States.     

A tree and climate assessment tool for modelling ecosystem response to climate change

Understanding how vulnerable forest ecosystems are to climate change is a key requirement if sustainable forest management is to be achieved. Modelling the response of species in their regeneration niche to phenological and biophysical processes that are directly influenced by climate is one method for achieving this understanding. A model was developed to investigate species resilience and vulnerability to climate change within its fundamental-regeneration niche. The utility of the developed model, tree and climate assessment (TACA), was tested within the interior Douglas-fir ecosystem in south-central British Columbia. TACA modelled the current potential tree species composition of the ecosystem with high accuracy and modelled significant responses amongst tree species to climate change. The response of individual species suggests that the studied ecosystem could transition to a new ecosystem over the next 100 years. TACA showed that it can be an effective tool for identifying species resilience and vulnerability to changes in climate within the most sensitive stage of development, the regeneration phase. The TACA model was able to identify the degree of change in phenological and biophysical variables that control tree establishment, growth and persistence. The response to changes in one or more of these variables resulted in changes in the climatic suitability of the ecosystem for species and enabled a measure of vulnerability to be quantified. TACA could be useful to forest managers as a decision support tool for adaptation actions and by researchers interested in modelling stand dynamics under climate change.     

Adjustment costs from environmental change

The paper is concerned with the case whereby the distribution of a firm's productivity shocks changes without the knowledge of the firm. Over time the firm learns about the nature and extent of the change in the distribution of the shock and adjusts, incurring adjustment costs in the process. The long-run loss in profits (±) due to the shift in the distribution we term the equilibrium response. The transitory loss in profits, incurred while the firm is learning about the distribution shift, is termed the adjustment cost. The theory is then applied to the problem of measuring adjustment costs in the face of imperfectly observed climate change in agriculture. The empirical part of the paper involves estimating a restricted profit function for agricultural land in a five-state region of the Midwest US as a function of prices, land characteristics, actual weather realizations and expected weather. We then simulate the effect of an unobserved climate shock, where learning about the climate shock is by observing the weather and updating prior knowledge using Bayes Rule. We find adjustment costs to climate change are 1.4% of annual land rents.     

Evaluating and managing wildlife impacts of climate change under uncertainty

Wildlife managers face the daunting task of managing wildlife in light of uncertainty about the nature and extent of future climate change and variability and its potential adverse impacts on wildlife. A conceptual framework is developed for managing wildlife under such uncertainty. The framework uses fuzzy logic to test hypotheses about the extent of the wildlife impacts of past climate change and variability, and fuzzy multiple attribute evaluation to determine best compensatory management actions for adaptively managing the potential adverse impacts of future climate change and variability on wildlife. A compensatory management action is one that can offset some of the potential adverse impacts of climate change and variability on wildlife. Implementation of the proposed framework requires wildlife managers to: (1) select climate impact states, hypotheses about climate impact states, possible management actions for alleviating adverse wildlife impacts of climate change and variability, and future climate change scenarios; (2) choose biological attributes or indicators of species integrity; (3) adjust those attributes for changes in non-climatic variables; (4) define linguistic variables and associated triangular fuzzy numbers for rating both the acceptability of biological conditions under alternative management actions and the relative importance of biological attributes; (5) select minimum or maximum acceptable levels of the attributes and reliability levels for chance constraints on the biological attributes; and (6) define fuzzy sets on the extent of species integrity and biological conditions and select a fuzzy relation between species integrity and biological conditions. A constructed example is used to illustrate a hypothetical application of the framework by a wildlife management team. An overall best compensatory management action across all climate change scenarios is determined using the minimax regret criterion, which is appropriate when the management team cannot assign or is unwilling to assign probabilities to the future climate change scenarios. Application of the framework can be simplified and expedited by incorporating it in a web-based, interactive, decision support tool.     

Choice of threshold alters projections of species range shifts under climate change

One of the least explored sources of algorithmic uncertainty in bioclimatic envelope models (BEM) is the selection of thresholds to transform modelled probabilities of occurrence (or indices of suitability) into binary predictions of species presence and absence. We investigate the impacts of such thresholds in the specific context of climate change. BEM for European tree species were fitted combining 9 climatic models and emissions scenarios, 7 modelling techniques, and 14 threshold-setting techniques. We quantified sources of uncertainty in projections of turnover, and found that the choice of the modelling technique explained most of the variability (39%), while threshold choice explained 25% of the variability in the results, and their interaction an additional 19%. Choice of future climates explained 9% of total variability among projections. Estimated species range shifts obtained by applying different thresholds and models were grouped by IUCN-based categories of threat. Thresholds had a large impact on the inferred risks of extinction, producing 1.7- to 9.9-fold differences in the proportions of species projected to become threatened by climate change. Results demonstrate that threshold selection has large - albeit often unappreciated - consequences for estimating species range shifts under climate change.     

Effects of climate change on moose populations: Exploring the response horizon through biometric and systems models

Interest in the response of moose to climate change has increased because of the potential role they play in the conservation of woodland caribou, and threatened loss to recreational and economic opportunities. The objective of this study is to develop a plausible, parsimonious, systems-level model of moose population dynamics that will be useful in exploring the response of moose populations to climate projections. The study begins with a statistical model of moose carrying capacity, which is then integrated into a systems-level model that predicts moose density based on explicit causal factors. Scenario analysis was conducted using a variety of assumptions concerning biotic and abiotic interactions, and under the A2 climate scenario all model scenarios predict a decline of moose density at the southern limits of the Ontario distribution and an increase at the northern extents. Predicted declines are a result of lower carrying capacity and higher heat stress, parasite loads and wolf predation. Given the sensitivity of the model to density-dependent factors, the indirect effect of parasites on decreased recruitment may have greater impact on moose than the direct effect of increased death rate. Results indicate that conservation planning for woodland caribou populations should account for possible increases in moose and wolf populations.     

Integrated model projections of climate change impacts on a North American lake

Climate change is likely to impact terrestrial and aquatic ecosystems via numerous physical and biological mechanisms. This study outlines a framework for projecting potential impacts of climate change on lakes using linked environmental models. Impacts of climate drivers on catchment hydrology and thermal balance in Onondaga Lake (New York State) are simulated using mechanistic models HSPF and UFILS4. Outputs from these models are fed into a lake ecosystem model, developed in AQUATOX. Watershed simulations project increases in the magnitude of peak flows and consequent increases in catchment nutrient export as the magnitude of extreme precipitation events increases. This occurs concurrently with a decrease in annual stream discharge as a result of increased evapotranspiration. Simulated lake water temperatures increase by as much as 5 °C during the 2040-2069 time period, accompanied by a prolonging of the duration of summer stratification. Projected changes include shifts in the timing of nutrient cycling between lake sediments and water column. Plankton taxa projected to thrive under climate change include green algae and Bosmina longirostris. Responses for species at higher trophic levels are mixed. Benthic macroinvertebrates may either prosper (zebra mussels) or decline (chironomids), while fish (e.g., gizzard shad) exhibit high seasonal variability without any clear trend.     

Modelling phytoclimatic versatility as a large scale indicator of adaptive capacity to climate change in forest ecosystems

CLIMPAIR is a new phytoclimatic model, correlative and niche-based, which simultaneously assesses non-linear, non-statistical and dual measurements of proximity/potentiality of a site with respect to a number of climatic ranges of species, defined by convex hulls, within a suitability space. This set of phytoclimatic distances makes it possible to evaluate the degree to which each species is suitable for that site. Considering not only the number of species compatible (expected species richness), but also all those compatible covers presenting a high level of suitability evenness and finally applying an indicator derived from Shannon's classic entropy index to the set of standardized phytoclimatic coordinates in the suitability hyperspace, we can evaluate the phytoclimatic entropy which may be considered as a means of estimating the phytoclimatic versatility of the site. A site with high phytoclimatic entropy would promise versatile future behaviour, characterized by a wide range of possibilities of adaptation to climate change, and hence versatility can be used as an index of resilience and ability of a forest ecosystem to adapt to climate change. The model has been applied to peninsular Spain for 18 forest tree species and 12 climatic variables between the current mean climate (period 1951-1999) and a future climatic scenario (period 2040-2069). The results generally point to a significant decrease in the versatility of forest tree formations in the area studied, which is not homogeneous owing to a dual altitudinal/latitudinal decoupling. The decrease in versatility is greater in Mediterranean biogeographical areas than in Euro-Siberian ones, where in some cases it actually increases. In altitudinal terms, areas at elevations of less than 1500 m tend to become less versatile than areas situated at higher elevations, where versatility increases partly as a result of enrichment of alpine conifer forests with broadleaf species.     

气候变化对亚高山暗针叶林土壤温室气体排放的影响

利用生物地球化学模犁Forest-DNDC模拟气候变化对贡嘎山亚高山暗针叶林土壤温室气体的释放的影响.以位于贡嘎山东坡海拔3 000 m的峨眉冷杉(Abies fabri)中龄林为研究对象,以1999-2006年8年的日气候数据进行平均得到的日平均最高温度、日平均最低温度和日平均降水总最作为基线(Base)气候情景,另外设置了温度+2℃(升)、温度.2℃(T-)、降水量+20%(P+)、降水量-20%(P-)、温度十2℃同时降水量+20%(T+P+)、温度-2℃同时降水量-20%(T-P-)、温度+2℃同时降水量-20%(T+P-)、温度-2℃同时降水量+20%(T-P+)8种气候变化情景.结果显示:贡嘎山峨眉冷杉林土壤CO_2释放随着温度增加而增加,土壤N_2O释放对降水量改变敏感,而土壤NO的释放对温度和降水的改变均比较敏感,二者表现为协同作用.温度+2℃同时降水量+20%(升P+)情景下土壤CO_2释放最高,高于基线情景的36.08%;温度-2℃同时降水量+20%(T-P+)情景下土壤CO_2释放最低,低于基线情景的36.89%.土壤N_2O释放随着降水量的增加而升高,随着降水量减少而降低;温度和降水最同时增加时土壤NO释放均高于单一增加温度或降水量情景,而温度和降水量同时降低时土壤NO释放均低于单一降低温度或降水量情景.     

Exploring the future of European crop production in a liberalised market, with specific consideration of climate change and the regional competitiveness

Long-term future development of European agriculture within the global market is highly uncertain, but can potentially have large impacts on the future of agricultural businesses, rural communities and amenities such as traditional landscapes and biodiversity. Despite great uncertainties it is of interest to explore the extent of these potential changes. This paper provides an explorative scenario of the European crop production in a liberalised world without European Union (EU) market interventions. The results do not form a prediction or a business as usual scenario, but rather a plausible and salient thought-experiment of a possible future based on the consistent integration of current conceptual and quantitative models.Future scenarios for climate, demography, technology and global demand for agricultural commodities are used to assess the competitiveness of European agriculture. Regional economic competitiveness is determined by combining indicators for the economic strength of farms in a region and population pressure on agricultural land, and subsequently used to determine where agricultural production is likely to sustain under the market liberalisation scenario. The method is illustrated for the 27 EU member state countries for three commodities: wheat, potato and milk (relying on grass).Results include maps of the dominant wheat, potato and milk producing regions across Europe as projected for 2050. They show that due to increased agricultural productivity, less agricultural land will be needed to supply the European demand for food and feed. In addition, production will concentrate in those regions which have a comparative advantage. This potentially leads to a strong polarisation between north-western Europe and southern Europe, which faces negative impacts of climate change and central and northern Europe where agricultural businesses lag in economic strength and farm size. A contrasting policy intervention scenario illustrates how differences in demand and productivity result in an expansion of the agricultural area, especially for the production of wheat.Although the complete liberalisation scenario may seem unlikely, and the underlying assumptions have great uncertainty, the results help identify and map market pressures on agricultural land use across regions in Europe. As such, it stimulates policy debate on the desired future for the European agricultural sector and the trade-offs between economic competitiveness under global market conditions and policy intervention. In addition, it provides a basis for the planning of alternative economic strategies for agriculturally less competitive regions.     

Impacts of climate change/variability on the streamflow in the Yellow River Basin, China

Changes of streamflow reflect combined effects of climate, soil and vegetation in the basin scale. This study was conducted to investigate the response of streamflow to the climate changes/variability in different scales of the Yellow River Basin (YRB). The spatial distribution and temporal trends were explored for precipitation and potential evapotranspiration (PE) during 1961-2000 to illustrate climate change/variability and impacts of climate change/variability on streamflow were explained by investigating the relationship of precipitation, PE and streamflow in the YRB. The results presented that: (i) precipitation and PE exhibited different spatial distribution patterns and temporal trends in different regions, and most stations showed negative trends for precipitation in the basin; (ii) the relationship of streamflow with precipitation and PE showed high nonlinearity, and the magnitudes and patterns of streamflow response to precipitation and PE displayed different patterns varied with the dry conditions in different region or years; and (iii) the precipitation elasticity of streamflow (?_P) was 1.80, 1.08, 1.78 and 1.95 in Lanzhou, Toudaoguai, Huayuankou and Lijin respectively, while the PE elasticity of streamflow (?_ET) was −3.41, −4.40, −4.52 and −4.20 in above four scales, respectively, from which can be seen that streamflow was more sensitive to precipitation in wet region than in arid region and inversely it was more sensitive to PE in arid regions than in wet regions. Furthermore, precipitation elasticity of streamflow calculated from the partial correlation presented a reasonable result to show the combined effect of precipitation and PE on streamflow.     

Uncertainty analysis of climate change mitigation options in the forestry sector using a generic carbon budget model

Industrialized countries agreed on a reduction of greenhouse gas emissions under the Kyoto Protocol. Many countries elected forest management activities and the resulting net balance of carbon emissions and removals of non-CO₂ greenhouse gases by forest management in their climate change mitigation measures. In this paper a generic dynamic forestry model (FORMICA) is presented. It has an empirical basis. Several modules trace C pools relevant for the Kyoto Protocol and beyond: biomass, litter, deadwood and soil, and harvested wood products. The model also accounts for the substitution of fossil fuels by wood products and bioenergy.     

Impact of climate change on soil moisture dynamics in Brandenburg with a focus on nature conservation areas

Global warming impacts the water cycle not only by changing regional precipitation levels and temporal variability, but also by affecting water flows and soil moisture dynamics. In Brandenburg, increasing average annual temperature and decreasing precipitation in summer have already been observed. For this study, past trends and future effects of climate change on soil moisture dynamics in Brandenburg were investigated, considering regional and specific spatial impacts. Special Areas of Conservation (SACs) were focused on in particular. A decreasing trend in soil water content was shown for the past by analyzing simulation results from 1951 to 2003 using the integrated ecohydrological model SWIM [Krysanova, V., Müller-Wohlfeil, D.-I., Becker, A., 1998. Development and test of a spatially distributed hydrological/water quality model for mesoscale watersheds. Ecol. Model. 106, 261–289]. The trend was statistically significant for some areas, but not for the entire region. Simulated soil water content was particularly low in the extremely dry year 2003. Comparisons of simulated trends in soil moisture dynamics with trends in the average annual Palmer Drought Severity Index for the region showed largely congruent patterns, though the modeled soil moisture trends are characterized by a much higher spatial resolution. Regionally downscaled climate change projections representing the range between wetter and drier realizations were used to evaluate future trends of available soil water. A further decrease of average available soil water ranging from −4% to −15% was projected for all climate realizations up to the middle of the 21st century. An average decrease of more than 25 mm was simulated for 34% of the total area in the dry realization. Available soil water contents in SACs were generally higher and trends in soil moisture dynamics were lower mainly due to their favorable edaphic conditions. Stronger absolute and relative changes in the simulated trends for the past and future were shown for SACs within Brandenburg than for the state as a whole, indicating a high level of risk for many wetland areas. Nonetheless, soil water content in SACs is expected to remain higher than average under climate change conditions as well, and SACs therefore have an important buffer function under the projected climate change. They are thus essential for local climate and water regulation and their status as protected areas in Brandenburg should be preserved.     

温带落叶林的植物物候特征及其对气候变化的响应

植被物候是气候变化对生物圈产生长期或短期影响的重要指示因子。气候变化已经明显改变了许多物种的营养生长和繁殖物候,尤其是在温带地区。研究温带森林物候变化及其对全球变暖的响应,对认识森林物种共存,协同进化以及森林保护和经营等有重要意义。通过概述温带森林下物候研究的进展发现,光照和积温是影响木本植物展叶及繁殖物候的关键因素,林下层树木通过更早展叶,以尽量减少生长季林冠层遮阴对下层树木生长的影响,更早时期开花的树木具有从顶部向四周次第开花的时空格局,林冠层树种开花具有较好的同步性。而草本植物的物候通常受融雪时间和冠层动态的影响更大,并且,温带森林下不同生活史对策的草本植物的物候特征对气候变化的响应也不尽相同,存在明显的季节动态。繁殖物候、光照的季节变化、光合特征、授粉成功之间的联系决定了林下不同繁殖特性的草本植物的繁殖成功率。量化的、多指标、多对象的定位监测是精准物候研究的基础,物候变化的机理和建立可预测的物候模型将是未来研究的重点。     

Neural network modelling for the analysis of forcings/temperatures relationships at different scales in the climate system

A fully non-linear analysis of forcing influences on temperatures is performed in the climate system by means of neural network modelling. Two case studies are investigated, in order to establish the main factors that drove the temperature behaviour at both global and regional scales in the last 140 years. In particular, our neural network model shows the ability to catch non-linear relationships among these variables and to reconstruct temperature records with a high degree of accuracy. In this framework, we clearly show the need of including anthropogenic inputs for explaining the temperature behaviour at global scale and recognise the role of El Niño southern oscillation for catching the inter-annual variability of temperature data. Furthermore, we analyse the relative influence of global forcing and a regional circulation pattern in determining the winter temperatures in Central England, showing that the North Atlantic oscillation represents the driven element in this case study. Our modelling activity and results can be very useful for simple assessments of relationships in the complex climate system and for identifying the fundamental elements leading to a successful downscaling of atmosphere–ocean general circulation models.     

Modelling carbon and nitrogen dynamics in forest ecosystems of Central Russia under different climate change scenarios and forest management regimes

The individual-based stand-level model EFIMOD was used for large-scale simulations using standard data on forest inventories as model inputs. The model was verified for the case-study of field observations, and possible sources of uncertainties were analysed. The approach developed kept the ability for fine-tuning to account for spatial discontinuity in the simulated area. Several forest management regimes were simulated as well as forest wildfires and climate changes. The greatest carbon and nitrogen accumulations were observed for the regime without cuttings. It was shown that cuttings and wildfires strongly influence the processes of carbon and nitrogen accumulations in both soil and forest vegetation. Modelling also showed that the increase in annual average temperatures resulted in the partial relocation of carbon and nitrogen stocks from soil to plant biomass. However, forest management, particularly harvesting, has a greater effect on the dynamics of forest ecosystems than the prescribed climate change.     

Linking species- and ecosystem-level impacts of climate change in lakes with a complex and a minimal model

To study the interaction between species- and ecosystem-level impacts of climate change, we focus on the question of how climate-induced shifts in key species affect the positive feedback loops that lock shallow lakes either in a transparent, macrophyte-dominated state or, alternatively, in a turbid, phytoplankton-dominated state. We hypothesize that climate warming will weaken the resilience of the macrophyte-dominated clear state. For the turbid state, we hypothesize that climate warming and climate-induced eutrophication will increase the dominance of cyanobacteria. Climate change will also affect shallow lakes through a changing hydrology and through climate change-induced eutrophication. We study these phenomena using two models, the full ecosystem model PCLake and a minimal dynamic model of lake phosphorus dynamics. Quantitative predictions with the complex model show that changes in nutrient loading, hydraulic loading and climate warming can all lead to shifts in ecosystem state. The minimal model helped in interpreting the non-linear behaviour of the complex model. The main output parameters of interest for water quality managers are the critical nutrient loading at which the system will switch from clear to turbid and the much lower critical nutrient loading – due to hysteresis – at which the system switches back. Another important output parameter is the chlorophyll-a level in the turbid state. For each of these three output parameters we performed a sensitivity analysis to further understand the dynamics of the complex model PCLake. This analysis showed that our model results are most sensitive to changes in temperature-dependence of cyanobacteria, planktivorous fish and zooplankton. We argue that by combining models at various levels of complexity and looking at multiple aspects of climate changes simultaneously we can develop an integrated view of the potential impact of climate change on freshwater ecosystems.     

Evaluating the effects of future climate change and elevated CO2 on the water use efficiency in terrestrial ecosystems of China

Water use efficiency (WUE) is an important variable used in climate change and hydrological studies in relation to how it links ecosystem carbon cycles and hydrological cycles together. However, obtaining reliable WUE results based on site-level flux data remains a great challenge when scaling up to larger regional zones. Biophysical, process-based ecosystem models are powerful tools to study WUE at large spatial and temporal scales. The Integrated BIosphere Simulator (IBIS) was used to evaluate the effects of climate change and elevated CO₂ concentrations on ecosystem-level WUE (defined as the ratio of gross primary production (GPP) to evapotranspiration (ET)) in relation to terrestrial ecosystems in China for 2009-2099. Climate scenario data (IPCC SRES A2 and SRES B1) generated from the Third Generation Coupled Global Climate Model (CGCM3) was used in the simulations. Seven simulations were implemented according to the assemblage of different elevated CO₂ concentrations scenarios and different climate change scenarios. Analysis suggests that (1) further elevated CO₂ concentrations will significantly enhance the WUE over China by the end of the twenty-first century, especially in forest areas; (2) effects of climate change on WUE will vary for different geographical regions in China with negative effects occurring primarily in southern regions and positive effects occurring primarily in high latitude and altitude regions (Tibetan Plateau); (3) WUE will maintain the current levels for 2009-2099 under the constant climate scenario (i.e. using mean climate condition of 1951-2006 and CO₂ concentrations of the 2008 level); and (4) WUE will decrease with the increase of water resource restriction (expressed as evaporation ratio) among different ecosystems.     

Modelling the impact of thermal adaptation of soil microorganisms and crop system on the dynamics of organic matter in a tropical soil under a climate change scenario

No consensus currently exists about how climate change should affect the status of soil organic matter (SOM) in the tropics. In this study, we analyse the impact of climate change on the underlying mechanisms controlling SOM dynamics in a ferralsol under two contrasting tropical crops: maize (C4 plant) and banana (C3 plant). We model the effect of microbial thermal adaptation on carbon (C) mineralisation at the crop system scale and introduce it in the model STICS, which was previously calibrated for the soil-crop systems tested in this study. Microbial thermal adaptation modelling is based on a reported theory for thermal acclimation of plant and soil respiration. The climate is simulated from 1950 to 2099 for the tropical humid conditions of Guadeloupe (French Antilles), using the ARPEGE model and the IPCC emission scenario A1B. The model predicts increases of 3.4 °C for air temperature and 1100 mm yr⁻¹ for rainfall as a response to an increase of 375 ppm for atmospheric carbon dioxide concentration in the 2090-2099 decade compared with the 1950-1959 decade. The results of the STICS model indicate that the crop affects the response of SOM to climate change by controlling the change in several variables involved in C dynamics: C input, soil temperature and soil moisture. SOM content varies little until 2020, and then it decreases faster for maize than for banana. The decrease is weakened under the hypothesis of thermal adaptation, and this effect is greater for maize (−180 kg C ha⁻¹ yr⁻¹ without adaptation and −140 kg C ha⁻¹ yr⁻¹ with adaptation) than for banana (−60 kg C ha⁻¹ yr⁻¹ and −40 kg C ha⁻¹ yr⁻¹, respectively). The greater SOM loss in maize is mainly due to the negative effect of warming on maize growth decreasing C input from residues. Climate change has a small effect on banana growth, and SOM loss is linked to its effect on C mineralisation. For both crops, annual C mineralisation increases until 2040, and then it decreases continuously. Thermal adaptation reduces the initial increase in mineralisation, but its effect is lower on the final decrease, which is mainly controlled by substrate limitation. No stabilisation in SOM status is attained at the end of the analysed period because C mineralisation is always greater than C input. Model predictions indicate that microbial thermal adaptation modifies, but does not fundamentally change the temporal pattern of SOM dynamics. The vegetation type (C3 or C4) plays a major role in SOM dynamics in this tropical soil because of the different impact of climate change on crop growth and then on C inputs.     

黄河源区植被生长季NDVI时空特征及其对气候变化的响应

利用黄河源区MODIS/NDVI数据、1∶100万植被类型图和气象资料,分析了该区不同植被类型生长季NDVI时空特征以及与气候因子的关系。结果表明,1）2000—2011年,黄河源区植被生长呈改善趋势,生长季NDVI年际变化率每10 a为＋2.75%,高寒草原、高寒草甸、高寒灌丛生长季NDVI年际变化率分别为每10 a＋2.84%、＋2.65%、＋2.77%。2）黄河源区植被改善面积占全区总面积的29.39%,主要分布在卡日曲和玛曲上游、扎曲流域、布青山南麓、扎陵湖北部和鄂陵湖周边地区。植被退化面积仅占全区总面积的0.98%,主要分布在约古宗列曲东南部山地和卡日曲北部山地。受水热条件控制,植被改善表现为：①植被改善面积南坡大于北坡;②植被改善面积随海拔升高先增加后减小;③植被改善面积随坡度增加迅速减小。3）黄河源区植被生长季NDVI与同期气温和降水分别存在显著正相关性,其中高寒草原和高寒草甸生长受降水影响更为明显,而高寒灌丛生长受气温影响更为明显。气候的暖湿化趋势可能是促使黄河源区植被生长改善的主要原因。