PREDICTION OF NET PRIMARY PRODUCTIVITY OF FORESTS IN CHINA IN RESPONSE TO CLIMATE CHANGE

根据中国不同地理区森林生产力和气候环境变量的数据构建了中国森林气候生产力模型,以此为基础研究了气候变化对中国森林生产力的影响。结果表明在所构建的模型中,除海拔高度与净生产力的相关模型外,其它模型均有较高的实用价值,模型的拟合曲线变化,基本反映了中国森林现实生产力的地理分布格局;中国森林生产力的分布格局主要取决于气候环境中的水热条件,水分条件是决定中国大部分地区森林生产力水平和地理分布格局的主导因素;根据7个GCM     

CO2浓度变化和气候变化对中国陆地生态系统净初级生产力及其平衡的影响

本文应用陆地生态系统模型(TEM,4.0)对中国陆地生态系统在目前气候下的净初级生产力,以及在CO2浓度增加和气候变化后的净初级生产力的变化进行了预测。气候变化模型采用三种大气环流模型生成,即：GISS、GFDL和OSU模型。在当前气候条件和CO2浓度(312.5×10-6)下,TEM模型预测中国陆地生态净初级生产力为3,653TgC·a-1(1012gC·a-1)。温带常绿阔叶林是生产力最高的生物区,占有中国净初级生产力的最大比例。NPP的空间格局主要与降水量和温度的空间分布相关联。 中国陆地生态系统的年净初级生产力对CO2浓度和气候的变化敏感。在陆地区域尺度上,其年净初级生产力仅在CO2浓度上升至519×10-6的情况下可增加6.0％(219TgC·a-1)。在气候变化而无CO2浓度变化的条件下,净初级生产力的响应在GISS气候方案下表现为1.5％(54.8TgC·a-1)的降低,在GFDL-q气候方案下表现为8.4％(306.9TgC·a-1)的增加。在气候和CO2浓度均发生变化的情况下,净初级生产力有较大程度的增加,在GISS气候方案下的增加比例为18.7％(683TgC·a-1),在GFDL-q气候方案下增加23.3％(851TgC·a-1)。在空间特征方面,年净初级生产力对气候和CO2浓度变化的响应方式在一个GCM气候方案下变化十分显著。由于三个大气环流模型的不同,使得净初级生产力地理分布的反应格局产生较大差异。CO2浓度升高和气候变化的耦合作用对中国陆地生态系统净初级生产力将产生重大影响。     

中国杉木林生物生产力格局及其数学模型

 根据大量的样地材料,从宏观上阐明了杉木林生物生产力的地理分布格局和水热相关规律,建立的生产力地理分布模型客观地反映了杉木高产林区的地理分布规律。根据限制因子作用律建立了杉木林生物生产力水热优化模型,模型显示杉木林生长最适宜的水热组合环境为：年均气温16～17℃,年降水量1700～1900mm,温暖指数145—150℃月,潜在蒸散量920～930mm,这时杉木林乔木层的生产力达17～18t·hm-2·a-1,全林生产力达21～22t·hm-2·a-1。     

基于区域植被类型评估的气候变化对中国森林生态系统的影响

基于中国知网(CNKI)和学术Google主题词为“气候变化”与“森林”的科技文献,根据全国范围的不同区域植被类型,运用整合分析方法就气候变化对森林生态系统的影响进行了系统评估,结果表明:在观测到的影响中,各个区域植被类型的树木物候、森林生产力与森林火灾方面的影响趋势大体相同,但森林地理分布影响趋势存在一定的差异;在预计的可能影响中,各个区域植被类型的树木物候、森林生产力、森林碳储量、森林火灾方面的影响趋势大体相同,但森林地理分布、森林结构方面的影响存在一定的差异.最后对现有研究的不足及未来研究方向等进行了讨论和展望.     

土地利用约束下中国东部南北样带生产力和植被分布对全球变化的响应

对现有的区域植被动态模拟模型进行了改进,使之包含了土地利用分布格局对植被和生态系统相关过程的影响.改进后的模型被用于研究中国东部南北样带(NSTEC)植被和净第一性生产力对未来气候变化的响应.模拟结果显示土地利用格局对未来气候条件下植被分布的变迁和生产力形成过程有非常显著的影响.与没有土地利用约束的情形相比较,土地利用作为限制条件缓减了植被类型之间的竞争,从而减少了模拟的样带区域内常绿阔叶林,但增加了模拟灌木和草地的分布.土地利用约束使得模拟得到的当前条件下的净第一性生产力更为接近实际情况,且未来气候条件下的生产力改变量更为可信.对未来CO2倍增条件下7个大气环流模型预测的气候情景的模拟结果表明:落叶阔叶林将显著增加,但针叶林、灌木和草原的分布将下降.未来气候条件下NSTEC样带的净第一性生产力总量将增加.预测样带北部的净第一性生产力的变化范围大于样带南部.温度变化比降水变化对样带的生产力具有更强的控制.     

土地利用约束下中国东部南北样带生产力和植被分布对全球变化的响应

对现有的区域植被动态模拟模型进行了改进,使之包含了土地利用分布格局对植被和生态系统相关过程的影响。改进后的模型被用地研究中国东部南北样带(NSTEC)植被和净第一性生产力对未来气候变化的响应。模拟结果显示土地利用格局对未来气候条件下植被分布的变迁和生产力形成过程有非常显著的影响。与没有土地利用约束的情形相比较,土地利用作为限制条件缓减了植被类型之间的竞争,从而减少了模拟的样带区域内常绿阔叶林,但增加了模拟灌木和草地的分布。土地利用约束使得模拟得到的当前条件下的净第一性生产力更为接近实际情况,且未来气候条件下的生产力改变量更为可信。对未来CO2倍增条件下7个大气环流模型预测的气候情景的模拟结果表明：落叶阔叶林将显著增加,但针叶林、灌木和草原的分布将下降。未来气候条件下NSTEC样带的净第一性生产力总量将增加。预测样带北部的净第一性生产力的变化范围大于样带南部。温度变化比降水变化对样带的生产力具有更强的控制。     

中国兴安落叶松天然林地理分布及其气候适宜性

准确评估兴安落叶松林潜在分布及其气候适宜性对科学指导森林经营和管理具有重要的现实意义。基于可能影响兴安落叶松林地理分布的8个气候变量:最冷月平均温度(Tc)、最暖月平均温度(Tw)、气温年较差(DTY)、≥5℃积温(GDD5)、年均降水量(P)、秋冬季平均降水量(Paw)、湿润指数(MI)和年辐射量(RAD),利用最大熵模型确定了影响中国兴安落叶松林地理分布的主导气候因子,并构建了兴安落叶松林地理分布与气候的关系模型。结果表明:影响中国兴安落叶松林地理分布的主导气候因子是Tc、DTY、RAD和GDD5,累积贡献率达87.8%,表明热量(温度与辐射)是兴安落叶松林存在与否的决定因素,而水分限制作用相当有限。中国兴安落叶松林主要分布在中、低气候适宜区域,其气候特征为:-28.8℃≤Tc≤-19.5℃;39.0℃≤DTY≤46.2℃;2871.7 MJ·m-2≤RAD≤3519.8 MJ·m-2;1000.0℃·d≤GDD5≤2100.0℃·d。     

基于MaxEnt模型西南地区高山植被对气候变化的响应评估

采用1∶100万的中国植被类型图以及19个气候环境变量数据,基于最大熵(MaxEnt)算法和ArcGIS空间分析模块构建西南地区高山植被地理分布的气候适宜性预测模型,模拟其在基准期(1960—2000年)和不同气候情景下(A2、A1B和B1)的气候适宜性分布格局,并评价其对气候变化的适应性。结果表明:MaxEnt模型分析研究区高山植被地理分布气候适宜性的适用性非常高(AUC=0.93);最暖月均温、最湿季均温、最冷月均温等温度变量是限制其地理分布的主要气候因子;研究区高山植被地理分布的气候适宜区主要集中在西藏自治区、青海省、四川省西部及云南省西北部的部分地区;完全适宜、中度适宜、轻度适宜、不适宜的面积所占总面积比例约为1∶1∶2∶5;1960—2050年研究区高山植被潜在地理分布的气候适宜性面积有不同定程度的减少;未来3种气候变化情景下高山植被地理分布对气候变化的适应性分布格局基本一致,均为不适应区所占总面积比例较大;伴随气候变化,研究区高山植被的适应性减弱,体现在其潜在地理分布对气候变化的适应区分布范围减少;海拔5000—5500m适应性较强,适应区所占面积比例最大(53%左右);3500—4500m适应性最弱,适应区所占面积比例最小(5%左右)。     

基于IBIS模型的东北森林净第一性生产力模拟

集成生物圈模型(the integrated biosphere simulator, IBIS)作为目前最复杂的基于动态植被模型的陆面生物模型之一,已经成为模拟大尺度(全球区域)的植被地理分布、净第一性生产力和碳平衡以及预测气候变化对陆地生态系统潜在影响的有效工具.应用IBIS模型对2004～2005年大小兴安岭的植被净第一性生产力(net primary productivity, NPP)进行了定量估算,模拟与研究了大小兴安岭森林生态系统植被NPP的空间分布格局以及不同植被类型的NPP季节变化特征,结果表明:大小兴安岭森林植被年均NPP值为494.7 gCm-2 · a-1,年吸收0.06Pg的大气碳.研究区年均NPP的空间分布主要受热量条件的影响,大兴安岭地区基本上呈现出由北向南增加的趋势,小兴安岭地区除单位面积年均NPP大于1.1kgCm-2 · a-1在小兴安岭北部孙吴和逊克地区分布外,基本上呈现出均匀分布的趋势.加强基础数据研究的同时如何根据中国的实际合理确定模型参数,使模型在我国典型生态系统中应用是值得进一步研究的.     

中国北方林生产力变化趋势及其影响因子分析

森林生产力是反映森林固碳能力的重要指标,是进行碳循环研究的重要环节。用模拟生态系统生物地球化学循环的CENTURY模型,模拟中国北方林(兴安落叶松林)近35a来的生产力动态,用3种趋势分析方法,检验了其变化趋势,并用多元线性回归模型分析了中国北方林生产力的年际波动与气温降水年际波动的关系,以及气温和降水对我国北方林生产力的影响程度。结果表明：中国北方林生产力呈增加的趋势,平均年增长率为0．34％;气温与森林生产力呈显著负相关,对森林生产力的贡献因子为4．0977;降水与森林生产力呈弱的正相关,其对森林生产力的贡献因子为0．3902。从而说明近35a来森林生产力的增加除了受气温降水等非生物因素的影响外,还受其它因素的影响;另外说明以气候变暖为标志的全球变化会对森林生产力产生重要的影响。     

Responses of vegetation structure and primary production of a forest transect in eastern China to global change

Aim A regional model of vegetation dynamics was enhanced to include biogeochemical cycling of nitrogen and was then applied to a forest transect in east China (FTEC) in order to investigate the responses of the transect to possible global change. Location Eastern China. Methods Biomass and nitrogen concentration of green and nongreen portions of vegetation, moisture contents of three soil layers, and total and available soil nitrogen are included as state variables in the enhanced model. The model was parameterized and validated against field observations of biomass, productivity, plant and soil nitrogen concentration, nitrogen uptake, a vegetation index derived from satellite remote sensing and digital maps of vegetation and soil distributions along a forest transect in eastern China (FTEC). The model was applied to FTEC in order to investigate the responsive characteristics of the ecosystems to global climatic change. Scenarios of climate change under doubled CO₂ produced by seven general circulation models (GCM) were used to drive the model. Results The simulations indicated that the model is capable of simulating accurately potential vegetation distribution and net primary productivity under contemporary climatic conditions. The simulations for GCM‐projected future climate scenarios with doubled atmospheric CO₂ concentration predicted that broadleaf forests would increase, but conifer forests, shrubs and grasses would decrease; and that deciduous forests would have the largest relative increase, but evergreen shrubs would have the largest decrease. Conclusions The overall effects of doubling CO₂ and climatic changes on FTEC were to produce an increased net primary productivity (NPP) at equilibrium for all seven GCM scenarios. The inclusion of nitrogen dynamics in the model imposes more constraint on the responses of FTEC to climatic change than the previous version of the model without nitrogen dynamics. Temperature exerts a stronger control on NPP than precipitation, as indicated by the negative correlations between NPP and temperature. The southern portion of FTEC, at latitudes less than 33 °N, show much larger increases in annual NPP than in the north. However, the predicted range of NPP increases is much larger in the north than in the south.     

中国北方温带地区5种锦鸡儿植物的分布模拟

 全面收集中国北方温带干旱－半干旱地区5种主要锦鸡儿植物的地理分布资料, 利用ArcGIS 9.0软件绘制现状分布图, 发现小叶锦鸡儿(Caragana microphylla)、中间锦鸡儿(C. intermedia)和柠条锦鸡儿(C. korshinskii)在空间上呈现出从东到西的地理替代分布格局, 继续向西南方向则分布有藏锦鸡儿(C. tibetica), 向西北方向分布有狭叶锦鸡儿(C. stenophylla), 但它们的分布范围又有一定的重叠。整理5种锦鸡儿分布区内的气象台站长期记录, 选择计算15个具有重要生物学意义的水热指标值; 进而用方差分析、多重比较和因子分析相结合的方法, 研究控制这5种锦鸡儿地理分布的主导驱动因子。结果表明: 控制小叶锦鸡儿和中间锦鸡儿间地理分布差异的主导因子是水分因子, 特别是湿度; 水分因子同样是控制中间锦鸡儿和柠条锦鸡儿间地理分布差异的主导因子, 特别是生长季及年降水量; 控制柠条锦鸡儿和藏锦鸡儿间地理分布差异的主导因子是夏季高温, 控制柠条锦鸡儿和狭叶锦鸡儿地理分布差异的是冬季低温。运用耦合BIOCLIM模型的软件包“DIVA-GIS”模拟预测这5种锦鸡儿的现状潜在分布区及未来气候变化的影响, 结果表明: 现状潜在分布区与实际分布区均有很好的一致性; 在CO₂浓度加倍的未来气候情景下, 5种锦鸡儿植物都会向北大幅度迁移, 在我国的分布范围均缩小, 分布格局发生显著变化。用ROC曲线和Kappa统计值法验证模型表明, BIOCLIM的模拟精度较高。     

北京山区3种暖温带森林生态系统未来碳平衡的模拟与分析

 使用LPJ-GUESS植被动态模型, 在北京山区研究了未来100 a以辽东栎(Quercus liaotungensis)为优势种的落叶阔叶林、以白桦(Betula platyphylla)为主的阔叶林和油松(Pinus tabulaeformis)为优势种的针阔混交林的碳变化, 定量分析了生态系统净初级生产力(NPP)、土壤异养呼吸(R_h)、净生态系统碳交换(NEE)和碳生物量(Carbon biomass)对两种未来气候情景(SRES A2和B2)以及相应大气CO₂浓度变化情景的响应特征。结果表明: 1)未来100 a两种气候情景下3种森林生态系统的NPP和R_h均增加, 并且A2情景下增加的程度更大; 2)由于3种生态系统树种组成的不同, 未来气候情景下各自NPP和R_h增加的比例不同, 导致三者NEE的变化也相异: 100 a后辽东栎林由碳汇转变为弱碳源, 白桦林仍保持为碳汇但功能减弱, 油松林成为一个更大的碳汇; 3) 3种森林生态系统的碳生物量在未来气候情景下均增大, 21世纪末与20世纪末相比: 辽东栎林在A2情景下碳生物量增加的比例为27.6%, 大于B2情景下的19.3%; 白桦林和油松林在B2情景下碳生物量增加的比例分别为34.2%和52.2%, 大于A2情景下的30.8%和28.4%。     

Past climatic fluctuations are associated with morphological differentiation in the cloud forest endemic tree <Emphasis Type="Italic">Ocotea psychotrioides</Emphasis> (Lauraceae)

Pleistocene glacial periods have had a major influence on the geographical patterns of genetic structure of species in tropical montane regions. However, their effect on morphological differentiation among populations of cloud forest plants remains virtually unexplored. Here, we address this question by testing whether geographical patterns of morphological variation in Ocotea psychotrioides can be explained by the intensity of climate change occurring during 130,000 years. For this, we measured vegetative and reproductive traits for 96 individuals from 36 localities registered across the species’ distribution range. Species distribution models and multivariate statistics were used to investigate geographical patterns of morphological variation and test their association with current and past climatic conditions. Leaf size and pubescence in O. psychotrioides showed a latitudinal pattern of clinal variation that does not fit the geographical gradient of increasing leaf size towards lower latitudes observed globally among plants. Instead, the observed clinal variation conforms to a pattern of increasing leaf size towards higher latitudes. However, our analyses showed weak to non-significant association between morphology and current climate. Interestingly, our analyses showed that predicted shifts in the distribution range of O. psychotrioides during the last 130,000 years were accompanied by significant changes in climatic conditions, particularly temperature seasonality and precipitation. Accordingly, climatic instability showed a better fit to the observed patterns of leaf size and pubescence variation than current climate conditions. These results suggest that climatic instability during the Pleistocene glacial periods might play a key role in promoting morphological differentiation among populations of cloud forest plants.     

The influence of climate change on the distribution of indigenous forest in KwaZulu-Natal, South Africa

Aims (1) To define the physical correlates of indigenous forest in KwaZulu-Natal province and develop a model, based on climatic parameters, to predict the potential distribution of forest subtypes in the province. (2) To explore the impact of palaeoclimatic change on forest distribution, providing an insight into the regional-scale/historical forces shaping the pattern and composition of present-day forest communities. (3) To investigate potential future shifts in forest distribution associated with projected climate change. Location KwaZulu-Natal province, South Africa. Methods A BIOCLIM-type approach is adopted. Bioclimatic ‘profiles’ for eight different forest subtypes are defined from a series of grid overlays of current forest distribution against nineteen climatic and geographical variables, using ArcInfo GIS grid-based processing. A principal components analysis is performed on a selection of individual forests to identify those variables most significant in distinguishing different forest subtypes. Five models are developed to predict the distribution of forest subtypes from their bioclimatic profiles. Maps of the potential distribution of forest subtypes predicted by these models under current climatic conditions are produced, and model accuracy assessed. One model is applied to two palaeoclimatic scenarios, the Last Glacial Maximum (LGM) (≈18,000 BP ) and the Holocene altithermal (≈7000 BP ), and to projected future climate under a doubling in global atmospheric carbon dioxide. Results Seven variables; altitude, mean annual temperature, annual rainfall range, potential evaporation, annual temperature range, mean annual precipitation and mean winter rainfall, are most important in distinguishing different forest subtypes. Under the most accurate model, the potential present-day distribution of all forest subtypes is more extensive than is actually observed, but is supported by recent historical evidence. During the LGM, Afromontane forest occupied a much reduced and highly fragmented area in the mid-altitude region currently occupied by scarp forest. During the Holocene altithermal, forest expanded in area, with a mixing of Afromontane and Indian Ocean coastal belt forest elements along the present-day scarp forest belt. Under projected climatic conditions, forest shifts in altitude and latitude and occupies an area similar to its current potential and more extensive than its actual current distribution. Main conclusions Biogeographical history and present physical diversity play a major role in the evolution and persistence of the diversity of forest in KwaZulu-Natal. It is important to adopt a long-term and regional perspective to forest ecology, biogeography, conservation and management. The area and altitudinal and latitudinal distribution of forest subtypes show considerable sensitivity to climate change. The isolation of forest by anthropogenic landscape change has limited its radiation potential and ability to track environmental change. Long-term forest preservation requires reserves in climatically stable areas, or spanning altitudinal or latitudinal gradients allowing for forest migration, along with innovative matrix management strategies. Dune, sand, swamp, riverine and lowland forest subtypes are most at risk. Scarp forests are highlighted as former refugia and important for the future conservation of forest biodiversity.     

美味猕猴桃地理分布模拟与气候变化影响分析

为了解气候变化对美味猕猴桃(Actinidia deliciosa)地理分布的影响,结合气候情景,采用Maxent预测美味猕猴桃的适生区的变化趋势。结果表明,基准气候和未来情景下构建的美味猕猴桃分布模型的AUC值均达到极好的标准。基准气候条件下,美味猕猴桃在中国的适生区为22°~38°N,96°~122°E,总面积为3.367 9×106 km2,高适生区位于秦岭-巴山、四川盆地东部、云贵高原东部、武陵山-巫山、武夷山脉。RCP4.5和RCP8.5情景下,美味猕猴桃在中国的高适生区面积将显著减少,中适生区面积则呈增加趋势,两种情景下高、中质心均向偏南或低纬度方向移动,RCP8.5情景下质心的迁移轨迹最长,变动范围最大。Maxent模型的准确预测对于优化猕猴桃产业结构具有重要指导意义。     

Assessing biome boundary shifts under climate change scenarios in India

Climate change and its cascading impacts are being increasingly recognized as a major challenge across the globe. Climate is one of the most critical factors affecting biomes and their distribution. The present study assessed shifts in biome types of India using the conceptual framework of Holdridge life zone (HLZ) model, minimum distance classifier and climatic datasets to assess the distribution pattern of potential biomes under climate change scenarios in India. Modelling was conducted on the entire region of India using various combinations; (i) current climate scenario, and, (ii) increased temperature and precipitation scenario. The geographical analysis identifies nineteen (19) HLZs in the Indian sub-continent; seven (7) biomes and nineteen (19) sub-biomes. The overall accuracy and kappa coefficient of the biome map prepared for current climate scenario was 82.73% and 0.75, respectively. With the changes in increasing temperature and precipitation scenario, the modelling results predict significant decrease in the area cover for tropical deserts (plains), tropical desert scrubs (lower montane), tropical moist forests (lower montane) and tropical wet forests (lower montane). Along with these changes, there have been substantial increases in the area cover for tropical dry forests (plains) and tropical very dry forests (plains), especially in central and southern India. The results show shifts from very dry tundra (alvar) to dry tundra (alpine) and moist tundra (alpine) and in some places tropical moist forests (sub-alpine) as well. In central India, decrease in tropical moist forests (lower montane) has been observed, while an increase in the area cover of tropical rain forests (plains) in northeastern India has been observed. It is important to understand the impacts and vulnerabilities of projected climate change on forest ecosystems so that better management and conservation strategies can be adopted for biodiversity and forest dependent communities. The knowledge of impact mechanisms will identify adaptation strategies for some conditions which will help in decreasing the susceptibility to anticipated climate change in the forest sector.     

Climate warming feedback from mountain birch forest expansion: reduced albedo dominates carbon uptake

Expanding high‐elevation and high‐latitude forest has contrasting climate feedbacks through carbon sequestration (cooling) and reduced surface reflectance (warming), which are yet poorly quantified. Here, we present an empirically based projection of mountain birch forest expansion in south‐central Norway under climate change and absence of land use. Climate effects of carbon sequestration and albedo change are compared using four emission metrics. Forest expansion was modeled for a projected 2.6 °C increase in summer temperature in 2100, with associated reduced snow cover. We find that the current (year 2000) forest line of the region is circa 100 m lower than its climatic potential due to land‐use history. In the future scenarios, forest cover increased from 12% to 27% between 2000 and 2100, resulting in a 59% increase in biomass carbon storage and an albedo change from 0.46 to 0.30. Forest expansion in 2100 was behind its climatic potential, forest migration rates being the primary limiting factor. In 2100, the warming caused by lower albedo from expanding forest was 10 to 17 times stronger than the cooling effect from carbon sequestration for all emission metrics considered. Reduced snow cover further exacerbated the net warming feedback. The warming effect is considerably stronger than previously reported for boreal forest cover, because of the typically low biomass density in mountain forests and the large changes in albedo of snow‐covered tundra areas. The positive climate feedback of high‐latitude and high‐elevation expanding forests with seasonal snow cover exceeds those of afforestation at lower elevation, and calls for further attention of both modelers and empiricists. The inclusion and upscaling of these climate feedbacks from mountain forests into global models is warranted to assess the potential global impacts.     

Increased evapotranspiration demand in a Mediterranean climate might cause a decline in fungal yields under global warming

Wild fungi play a critical role in forest ecosystems, and its recollection is a relevant economic activity. Understanding fungal response to climate is necessary in order to predict future fungal production in Mediterranean forests under climate change scenarios. We used a 15‐year data set to model the relationship between climate and epigeous fungal abundance and productivity, for mycorrhizal and saprotrophic guilds in a Mediterranean pine forest. The obtained models were used to predict fungal productivity for the 2021–2080 period by means of regional climate change models. Simple models based on early spring temperature and summer–autumn rainfall could provide accurate estimates for fungal abundance and productivity. Models including rainfall and climatic water balance showed similar results and explanatory power for the analyzed 15‐year period. However, their predictions for the 2021–2080 period diverged. Rainfall‐based models predicted a maintenance of fungal yield, whereas water balance‐based models predicted a steady decrease of fungal productivity under a global warming scenario. Under Mediterranean conditions fungi responded to weather conditions in two distinct periods: early spring and late summer–autumn, suggesting a bimodal pattern of growth. Saprotrophic and mycorrhizal fungi showed differences in the climatic control. Increased atmospheric evaporative demand due to global warming might lead to a drop in fungal yields during the 21st century.