Interactive Effects of Fire, Soil Climate, and Moss on CO2 Fluxes in Black Spruce Ecosystems of Interior Alaska

Fire is an important control on the carbon (C) balance of the boreal forest region. Here, we present findings from two complementary studies that examine how fire modifies soil organic matter properties, and how these modifications influence rates of decomposition and C exchange in black spruce (Picea mariana) ecosystems of interior Alaska. First, we used laboratory incubations to explore soil temperature, moisture, and vegetation effects on CO₂ and DOC production rates in burned and unburned soils from three study regions in interior Alaska. Second, at one of the study regions used in the incubation experiments, we conducted intensive field measurements of net ecosystem exchange (NEE) and ecosystem respiration (ER) across an unreplicated factorial design of burning (2 year post-fire versus unburned sites) and drainage class (upland forest versus peatland sites). Our laboratory study showed that burning reduced the sensitivity of decomposition to increased temperature, most likely by inducing moisture or substrate quality limitations on decomposition rates. Burning also reduced the decomposability of Sphagnum-derived organic matter, increased the hydrophobicity of feather moss-derived organic matter, and increased the ratio of dissolved organic carbon (DOC) to total dissolved nitrogen (TDN) in both the upland and peatland sites. At the ecosystem scale, our field measurements indicate that the surface organic soil was generally wetter in burned than in unburned sites, whereas soil temperature was not different between the burned and unburned sites. Analysis of variance results showed that ER varied with soil drainage class but not by burn status, averaging 0.9 ± 0.1 and 1.4 ± 0.1 g C m⁻² d⁻¹ in the upland and peatland sites, respectively. However, a more complex general linear model showed that ER was controlled by an interaction between soil temperature, moisture, and burn status, and in general was less variable over time in the burned than in the unburned sites. Together, findings from these studies across different spatial scales suggest that although fire can create some soil climate conditions more conducive to rapid decomposition, rates of C release from soils may be constrained following fire by changes in moisture and/or substrate quality that impede rates of decomposition. Author contributions: JAO: performed research, analyzed data, contributed new methods, wrote the paper; MRT: designed laboratory study, performed research, analyzed data; JWH: designed field study, performed research; KLM: performed research; LEP: performed research, contributed new method; GS: performed research; JCN: performed research.     

比较逻辑斯蒂与地理加权逻辑斯蒂回归模型在福建林火发生的适用性

林火预测预报是科学有效进行林火管理的前提,是林业管理部门和科研工作者的广泛关注的领域。逻辑斯蒂回归(Logistic Regression,LR)是目前国内外广泛应用于森林火灾预测的模型方法,然而近年来有学者发现该方法没有充分考虑林火影响因子的空间相关性和异质性,从而导致模型拟合结果偏差。地理加权逻辑斯蒂回归(Geographically weighted logistic regression,GWR)模型考虑到了模型变量之间的空间相关性,有效提高的模型的拟合能力。为探讨GWLR模型在福建林火预测上的适用性,本研究应用LR和GWLR两种方法分别建立福建省森林火灾与气象因子的预测模型,通过模型拟合能力对比,判断在GWLR的适用性。研究以2000—2005年福建地区森林火灾卫星火点数据和每日气象因子为基础,将全样本分为60%的建模数据和40%的校验数据,并重复5次,建立5个样本组。选择在5个样本组中3个及以上表现显著的变量进入最终模型。研究结果表明GWLR在模型拟合度、模型残差、空间自相关性以及预测准确率等方面均优于LR模型,说明充分考虑模型变量的空间异质性有助于提高模型的预测精度,同时也验证了GWLR在福建地区林火预测上的适应性。此外,模型参数结果显示,"日最高地表气温"、"日最低地表气温"、"日平均风速"、"24小时降水量"、"日最高本站气压"、"日照时数"、"日最高气温"和"日最小相对湿度"8个因子对福建省林火发生有显著影响,研究结论为福建地区林火预测预报提供了新的方法。     

Spatial scale affects novel and disappeared climate change projections in Alaska

The formation of novel and disappeared climates between the last glacial maximum (LGM) and the present is important to consider to understand the expansion and contraction of species niches and distributions, as well as the formation and loss of communities and ecological interactions over time. Our choice in climate data resolution has the potential to complicate predictions of the ecological impacts of climate change, since climate varies from local to global scales and this spatial variation is reflected in climate data. To address this issue, we downscaled LGM and modern (1975–2005) 30‐year averaged climate data to 60‐m resolution for the entire state of Alaska for 10 different climate variables, and then upsampled each variable to coarser resolutions (60 m to 12 km). We modeled the distributions of novel and disappeared climates to evaluate the locations and fractional area of novel and disappeared climates for each of our climate variables and resolutions. Generally, novel and disappeared climates were located in southern Alaska, although there were cases where some disappeared climates existed within coastal and interior Alaska. Climate resolution affected the fractional area of novel and disappeared climates in three patterns: As the spatial resolution of climate became coarser, the fractional area of novel and disappeared climates (a) increased, (b) decreased, or (c) had no explainable relationship. Overall, we found the use of coarser climate data increased the fractional area of novel and disappeared climates due to decreased environmental variability and removal of climate extremes. Our results reinforce the importance of downscaling coarse climate data and suggest that studies analyzing the effects of climate change on ecosystems may overestimate or underestimate their conclusions when utilizing coarse climate data.     

Impacts of climate change on the vegetation of Africa: an adaptive dynamic vegetation modelling approach

Recent IPCC projections suggest that Africa will be subject to particularly severe changes in atmospheric conditions. How the vegetation of Africa and particularly the grassland–savanna–forest complex will respond to these changes has rarely been investigated. Most studies on global carbon cycles use vegetation models that do not adequately account for the complexity of the interactions that shape the distribution of tropical grasslands, savannas and forests. This casts doubt on their ability to reliably simulate the future vegetation of Africa. We present a new vegetation model, the adaptive dynamic global vegetation model (aDGVM) that was specifically developed for tropical vegetation. The aDGVM combines established components from existing DGVMs with novel process‐based and adaptive modules for phenology, carbon allocation and fire within an individual‐based framework. Thus, the model allows vegetation to adapt phenology, allocation and physiology to changing environmental conditions and disturbances in a way not possible in models based on fixed functional types. We used the model to simulate the current vegetation patterns of Africa and found good agreement between model projections and vegetation maps. We simulated vegetation in absence of fire and found that fire suppression strongly influences tree dominance at the regional scale while at a continental scale fire suppression increases biomass in vegetation by a more modest 13%. Simulations under elevated temperature and atmospheric CO₂ concentrations predicted longer growing periods, higher allocation to roots, higher fecundity, more biomass and a dramatic shift toward tree dominated biomes. Our analyses suggest that the CO₂ fertilization effect is not saturated at ambient CO₂ levels and will strongly increase in response to further increases in CO₂ levels. The model provides a general and flexible framework for describing vegetation response to the interactive effects of climate and disturbances.     

Assessing effects of forecasted climate change on the diversity and distribution of European higher plants for 2050

The rapidly increasing atmospheric concentrations of greenhouse gases may lead to significant changes in regional and seasonal climate patterns. Such changes can strongly influence the diversity and distribution of species and, therefore, affect ecosystems and biodiversity. To assess these changes we developed a model, called euromove. The model uses climate data from 1990 to 2050 as compiled from the image 2 model, and determines climate envelopes for about 1400 plant species by multiple logistic regression analysis. The climate envelopes were applied to the projected climate to obtain predictions about plant diversity and distributions by 2050. For each European grid cell, euromove calculates which species would still occur in forecasted future climate conditions and which not. The results show major changes in biodiversity by 2050. On average, 32% of the European plant species that were present in a cell in 1990 would disappear from that cell. The area, in which 32% or more of the 1990 species will disappear, takes up 44% of the modelled European area. Individual responses of the plant species to the forecasted climate change were diverse. In reviewing possible future trends, we found that plant species, in general, would find their current climate envelopes further northeast by 2050, shifting ranges that were comparable with those ranges in other studies.     

Simulating climate change impacts on fire frequency and vegetation dynamics in a Mediterranean-type ecosystem

The impacts of climate change on Mediterranean‐type ecosystems may result from complex interactions between direct effects on water stress and subsequent modifications in flammability and fire regime leading to changes in standing biomass and plant species composition. We analysed these interrelations through a simulation approach combining scenarios of climate change developed from GCM results and a multispecies functional model for vegetation dynamics, SIERRA. A fire risk procedure based on weekly estimates of vegetation water stress has been implemented. Using climate data from 1960 to 1997, simulations of a typical maquis woodland community have been performed as baseline and compared with two climate scenarios: a change in the rainfall regime alone, and changes in both rainfall and air temperature. Climate changes are defined by an increase in temperature, particularly in summer, and a change in the rainfall pattern leading to a decrease in low rainfall events, and an increase in intense rainfall events. The results illustrate the lack of drastic changes in the succession process, but highlight modifications in the water budget and in the length of the drought periods. Water stress lower than expected regarding statistics on the current climate is simulated, emphasizing a long‐term new equilibrium of vegetation to summer drought but with a higher sensibility to rare events. Regarding fire frequency, climate changes tend to decrease the time interval between two successive fires from 20 to 16 years for the maquis shrubland and from 72 to 62 years in the forested stages. This increase in fire frequency leads to shrub‐dominated landscapes, which accentuates the yield of water by additional deep drainage and runoff.     

气候变化背景下江西省林火空间预测

林火是森林生态系统中重要的干扰因子之一,深刻地影响森林景观结构和功能。在全球气候化背景下,揭示气候变化对林火空间分布格局的影响,可为林火管理和防火资源分配提供科学指导。因此,基于江西省2001—2015年MODIS火影像数据(MCD14ML)和年均气温、年均降水量、植被、地形、人口密度、距道路距离、距居民点距离7个因子数据,利用增强回归树模型:(1)分析林火发生影响因子的相对重要性及其边际效应;(2)将GFDL-CM3和GISS-E2-R气候变化模式中的年均气温和年均降水量作为未来的气象数据,在3个温室气体排放量情景(RCP2.6、RCP4.5、RCP8.5)下,对2050年(2041—2060的平均值)和2070年(2061—2080的平均值)江西省林火分布进行预测,生成林火发生概率图。并采用受试者工作特征(ROC曲线)和混淆矩阵评估模型预测的精度。研究结果表明:(1)年均气温和海拔与江西省林火发生的相关性较强,年均降水量、居民点距离、人口密度、道路距离与林火发生的相关性较弱,但是与林火发生密切相关的如降水、风速等也应重点关注;(2)训练数据(70%)和验证数据(30%)的AUC值(ROC曲线下面积值)均为0.736,混淆矩阵对火点预测的正确率为67.8%,表明模型能够较好地预测研究区林火的发生;(3)在RCP8.5排放情景中林火发生的增幅最明显,其增幅较大的区域由赣南向赣北移动;(4)未来2050年和2070年林火发生与当前气候(2001—2015年)下相比,赣州市、鹰潭市的增幅较为明显,其他区域不明显。江西省各林业管理部门要加强林火高发区及潜在发生区的森林监测和管理,加大防火宣传力度,提升民众的森林防火意识。     

Evidence of non‐stationary relationships between climate and forest responses: Increased sensitivity to climate change in Iberian forests

Climate and forest structure are considered major drivers of forest demography and productivity. However, recent evidence suggests that the relationships between climate and tree growth are generally non‐stationary (i.e. non‐time stable), and it remains uncertain whether the relationships between climate, forest structure, demography and productivity are stationary or are being altered by recent climatic and structural changes. Here we analysed three surveys from the Spanish Forest Inventory covering c. 30 years of information and we applied mixed and structural equation models to assess temporal trends in forest structure (stand density, basal area, tree size and tree size inequality), forest demography (ingrowth, growth and mortality) and above‐ground forest productivity. We also quantified whether the interactive effects of climate and forest structure on forest demography and above‐ground forest productivity were stationary over two consecutive time periods. Since the 1980s, density, basal area and tree size increased in Iberian forests, and tree size inequality decreased. In addition, we observed reductions in ingrowth and growth, and increases in mortality. Initial forest structure and water availability mainly modulated the temporal trends in forest structure and demography. The magnitude and direction of the interactive effects of climate and forest structure on forest demography changed over the two time periods analysed indicating non‐stationary relationships between climate, forest structure and demography. Above‐ground forest productivity increased due to a positive balance between ingrowth, growth and mortality. Despite increasing productivity over time, we observed an aggravation of the negative effects of climate change and increased competition on forest demography, reducing ingrowth and growth, and increasing mortality. Interestingly, our results suggest that the negative effects of climate change on forest demography could be ameliorated through forest management, which has profound implications for forest adaptation to climate change.     

Evaluating the responses of forest ecosystems to climate change and CO2 using dynamic global vegetation models

The climate has important influences on the distribution and structure of forest ecosystems, which may lead to vital feedback to climate change. However, much of the existing work focuses on the changes in carbon fluxes or water cycles due to climate change and/or atmospheric CO₂, and few studies have considered how and to what extent climate change and CO₂ influence the ecosystem structure (e.g., fractional coverage change) and the changes in the responses of ecosystems with different characteristics. In this work, two dynamic global vegetation models (DGVMs): IAP‐DGVM coupled with CLM3 and CLM4‐CNDV, were used to investigate the response of the forest ecosystem structure to changes in climate (temperature and precipitation) and CO₂ concentration. In the temperature sensitivity tests, warming reduced the global area‐averaged ecosystem gross primary production in the two models, which decreased global forest area. Furthermore, the changes in tree fractional coverage (ΔF_tree; %) from the two models were sensitive to the regional temperature and ecosystem structure, i.e., the mean annual temperature (MAT; °C) largely determined whether ΔF_tree was positive or negative, while the tree fractional coverage (F_tree; %) played a decisive role in the amplitude of ΔF_tree around the globe, and the dependence was more remarkable in IAP‐DGVM. In cases with precipitation change, F_tree had a uniformly positive relationship with precipitation, especially in the transition zones of forests (30% < F_tree < 60%) for IAP‐DGVM and in semiarid and arid regions for CLM4‐CNDV. Moreover, ΔF_tree had a stronger dependence on F_tree than on the mean annual precipitation (MAP; mm/year). It was also demonstrated that both models captured the fertilization effects of the CO₂ concentration.     

Human Impacts on the Fire Regime of Interior Alaska: Interactions among Fuels, Ignition Sources, and Fire Suppression

Wildfire is the major natural agent of disturbance in interior Alaska. We examined the magnitude of human impact on fire by comparing fire regime between individual 1-km² grid cells designated for fire suppression with lands where fires are allowed to burn naturally. Two-thirds of interior Alaska has an essentially natural fire regime, with few human ignitions, negligible suppression activity, and many large lightning-caused fires. In the 17% of land that is designated for fire suppression due to its proximity to communities and roads, there was a 50% reduction in the proportion of area burned from 1992–2001, relative to areas without suppression. The remaining 16% of land serves as a buffer, receives some suppression, and has an intermediate fire regime. Even though there were 50 times more fires and the fire season began two months earlier in lands designated for suppression, most of these fires were lit by people and remained small because fires tended to occur at times and places less favorable for fire spread and were more accessible to fire fighters compared to lands not designated for suppression. Even in the absence of fire suppression, human-caused fires were less likely to exceed 400 ha compared to lightning-caused fires. Fire suppression reduced area burned in all fuel types but was somewhat more effective in less flammable (non-forest) vegetation. Alaska’s fire policy of focusing suppression efforts on a small proportion of the fire-prone region maximizes the ecological and social benefits associated with fire-dependent ecosystem services, while minimizing the social and ecological costs of suppression. Application of this policy to other areas would require well-informed managers and stakeholders to make difficult decisions about the relative costs and benefits of fire across ecologically and culturally variable landscapes.     

Impacts of climate change on fire activity and fire management in the circumboreal forest

Forest fires are a significant and natural element of the circumboreal forest. Fire activity is strongly linked to weather, and increased fire activity due to climate change is anticipated or arguably has already occurred. Recent studies suggest a doubling of area burned along with a 50% increase in fire occurrence in parts of the circumboreal by the end of this century. Fire management agencies' ability to cope with these increases in fire activity is limited, as these organizations operate with a narrow margin between success and failure; a disproportionate number of fires may escape initial attack under a warmer climate, resulting in an increase in area burned that will be much greater than the corresponding increase in fire weather severity. There may be only a decade or two before increased fire activity means fire management agencies cannot maintain their current levels of effectiveness.     

气候变化对东北主要地带性植被类型分布的影响

准确地划分地带性主要植被类型分布的适宜区域,可为区域植被恢复与重建、生物多样性保护等工作提供有益的理论参考。在检验1961—2013年东北地区气候变化突变点的基础上,基于东北地区主要植被类型热量指标,研究气候变化对该区域主要植被类型适宜分布区域的影响,并利用2000年和2013年土地类型覆盖数据(MCD12Q1),对推算的适宜分布区域进行验证,结果表明:大兴安岭气温突变点为1982年,其它地区为1988年,东北地区各生态地理区年降水量没有明显的突变点。气温突变点后适宜在东北地区生长的主要植被种类没有变化,但各植被类型的分布区域均有所改变,其中高山冻原、亚高山矮曲林、寒温带针叶林和温带针阔叶混交林适宜分布区域面积减小,暖温带落叶阔叶林和温带草原面积增大。气温突变点前后各植被类型适宜分布区的地理中心均发生了不同程度的移动,其中移动距离最大的是南部地区的亚高山矮曲林,向东北方向移动了135.44km。与主要植被类型实际分布相对比,证明气候变化对研究区植被类型分布可能已经产生了影响。     

Assessing the response of area burned to changing climate in western boreal North America using a Multivariate Adaptive Regression Splines (MARS) approach

Fire is a common disturbance in the North American boreal forest that influences ecosystem structure and function. The temporal and spatial dynamics of fire are likely to be altered as climate continues to change. In this study, we ask the question: how will area burned in boreal North America by wildfire respond to future changes in climate? To evaluate this question, we developed temporally and spatially explicit relationships between air temperature and fuel moisture codes derived from the Canadian Fire Weather Index System to estimate annual area burned at 2.5° (latitude × longitude) resolution using a Multivariate Adaptive Regression Spline (MARS) approach across Alaska and Canada. Burned area was substantially more predictable in the western portion of boreal North America than in eastern Canada. Burned area was also not very predictable in areas of substantial topographic relief and in areas along the transition between boreal forest and tundra. At the scale of Alaska and western Canada, the empirical fire models explain on the order of 82% of the variation in annual area burned for the period 1960–2002. July temperature was the most frequently occurring predictor across all models, but the fuel moisture codes for the months June through August (as a group) entered the models as the most important predictors of annual area burned. To predict changes in the temporal and spatial dynamics of fire under future climate, the empirical fire models used output from the Canadian Climate Center CGCM2 global climate model to predict annual area burned through the year 2100 across Alaska and western Canada. Relative to 1991–2000, the results suggest that average area burned per decade will double by 2041–2050 and will increase on the order of 3.5–5.5 times by the last decade of the 21st century. To improve the ability to better predict wildfire across Alaska and Canada, future research should focus on incorporating additional effects of long‐term and successional vegetation changes on area burned to account more fully for interactions among fire, climate, and vegetation dynamics.     

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).     

喀斯特流域径流对植被和气候变化的多尺度响应

植被覆盖和气候变化对径流的影响可能具有尺度依赖性,而在生态环境脆弱和地质结构复杂的西南喀斯特区开展研究较少。为此,以喀斯特地貌广泛发育的西江流域为研究区,选取郁江、红水河、浔江和梧州4个流域,利用Mann-Kendall趋势检验对4个流域年径流深、NDVI、降水量、潜在蒸散发和气温(1982—2015)的变化趋势进行了分析,运用多元经验模态分解(MEMD)量化了流域径流深与植被和气候因子在不同尺度上的相关性,并预测了年径流深,旨在研究喀斯特流域径流对植被和气候变化的多尺度响应。结果表明,径流深仅有红水河流域呈显著下降趋势(P<0.05)。其中郁江流域径流深主要表征尺度为3年和5年,红水河流域径流深主要表征尺度为10年和22年,浔江和梧州流域径流深主要表征尺度为3年和22年。径流深与植被和气候因子的关系具有尺度依赖性,在不同尺度下,4个流域径流深与降水量和潜在蒸散发始终呈显著相关性(P<0.05),而径流深与NDVI和气温的多尺度关系在某些表征尺度上并不显著。利用MEMD法对径流深的预测效果(R²=0.81—0.86)要优于基于原始数据的多元逐步回归方法...     

浙江省植被NDVI动态及其对气候的响应

利用GIMMS和MODIS两种归一化植被指数(NDVI)资料反演了1982—2010年浙江植被覆盖状况,结合同期研究区63个气象站点的气温、降水和湿润指数等气候指标,分析了该地区植被年际变化、月际变化及其对气候要素的响应特征。结果表明:(1)研究期间,浙江气候总体呈暖干化趋势,植被覆盖缓慢下降,主要是由于森林植被遭破坏,农业生产活动受抑制影响所致,其中NDVI显著减少的地区约占全省陆域面积的29.1%,主要发生在6—11月;(2)降水量及干湿程度对浙江植被NDVI年变化起着决定性作用。植被与气候要素年变化相关分析发现,NDVI与湿润指数关系较降水、气温更为密切,两者相关及偏相关系数均通过0.05水平的置信度检验,这表明在年际尺度上,湿度的增加增大了植被的生长势,有利于植被生长;(3)植被与气候要素月变化分析表明冬季的热量供给是影响浙江植被生长的重要因子,而植被变化对夏季降水和干湿程度的最大响应为滞后两个月;(4)农业生产水平的提高使得农作物种植区NDVI有所增加,人类活动对浙江植被覆盖的影响不可忽视。     

东北地区植被物候对气候变化的响应

使用1982—2003年GIMMS-NDVI数据和气候数据,借助GIS空间分析和统计分析方法,分析了东北地区不同植被物候期与气候变化的关系。结果表明:22年东北地区年均温度以升高趋势为主,年降水量以减少趋势为主;针叶林、针阔叶混交林、阔叶林、草甸和沼泽植被生长季开始日期提前受春季温度升高影响显著(P<0.05)。春季降水对植被生长季开始日期变化影响较小,仅对针叶林生长季开始日期的推迟有显著的影响(P<0.05)。植被生长季结束日期受温度变化影响较小,仅草原植被生长季结束日期提前受秋季温度降低影响显著(P<0.05)。降水对东北地区植被生长季结束日期的变化影响高于温度。随着秋季降水量的减少,针阔叶混交林、草原和农田植被生长季结束日提前(P<0.05)。草丛生长季结束日期提前受夏季降水减少的影响显著(P<0.05);农田生长季结束日期提前亦受夏季和9月降水量减少的显著影响(P<0.05)。阔叶林和沼泽植被生长季延长受春季温度升高影响显著(P<0.05);灌丛植被生长季缩短受春季降水量减少影响显著(P<0.05);草丛和农田植被生长季延长受夏季降水量增加影响显著(P<0.05)。