, 戴尔阜, 林媚珍Simulating the effect of climate change and human activities on the forest ecosystem in the hilly red soil region of southern China: A case study in Taihe county, Jiangxi province
WUZhuo, DAIErfu, LINMeizhen通讯作者:
收稿日期:2018-05-30
修回日期:2018-09-18
网络出版日期:2018-11-20
版权声明:2018《地理研究》编辑部《地理研究》编辑部
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1 引言
森林作为陆地表层复杂多样的生态系统之一,具有较高的生物生产力和生物量,为人类提供多种多样的生态系统服务[1]。随着“未来地球”计划的推进和人地系统耦合等综合研究的不断发展,森林生态系统的变化特征及其未来演变趋势已经逐渐成为全球变化与区域响应研究的热点问题之一[2,3]。以气候变化和人类活动为主要特征的全球和区域环境变化已经给陆地生态系统带来深刻影响[4],产生诸如热带地区森林面积下降、景观破碎化程度增加、生物多样性丧失、物种分布的空间格局变化等全球或区域性问题[5,6]。而随着人类对土地的需求和人类活动强度的不断加大,这种影响将在未来短期内继续扩大[7]。因此,为理解多系统、多尺度间复杂的相互作用,适应和减缓未来全球变化带来的影响,有必要研究和预估气候变化和人类活动对森林生态系统结构和功能的单独及综合影响。在森林生态系统结构和功能研究中,如何从树种、林分、景观到生态系统的多空间尺度和结合过去、现在、未来的多时间尺度的综合研究日趋重要,仅采用传统实地观测进行森林景观研究已不能满足研究需求,尤其是部分地方野外观测甚至无法实现[8]。森林景观模型的出现帮助****们建立景观结构、功能和过程之间的相互关系,是预测景观变化的有效工具[9]。目前,森林景观模型被广泛应用在全球不同区域来处理气候变化、森林干扰、演替和管理问题。如早期的JABOWA[10]、FORET[11]等研究林分尺度的间隙模型,和后续逐渐开发的以生态系统过程为主的LANDIS[12]、FORMOSAIC模型[13],这些模型重点关注森林景观尺度上的关键生态过程。近期,森林模型逐渐发展到以自然和人为干扰驱动下多尺度、多要素的综合模拟时期,其中LANDIS-II模型在模拟气候变化、森林采伐、土地利用变化等一系列干扰过程中表现出较好的适用性,并被广泛应用在全球范围内的森林管理和模拟研究中[14,15,16]。因此,本研究将采用LANDIS-II模型,利用多模块处理和多模型综合利用,实现气候变化和人类活动驱动下的森林景观动态模拟。
中国南方红壤丘陵区水、热、生物资源丰富,森林生态系统类型多样,作为中国林业生产的重要区域,其人工林的面积和蓄积量分别占全国的63.3%和62.3%[17]。然而近年来过度采伐、毁林开荒等不合理的土地利用,使该地区人工林的发展受到了制约,表现为部分地区森林覆盖率降低、生态系统功能退化和宜林地减少等一系列问题[18,19]。而随着中国城镇化进程的加快,大量林地转变为非林地的趋势仍将存在[20]。如何在目前研究基础上综合考虑气候变化和人类活动对森林生态系统的影响,进而提出具有区域适宜性的结构优化和功能提升对策是目前中国南方红壤丘陵区生态系统管理的迫切需求。本文选择江西省泰和县为研究区,综合利用基于元胞自动机的土地利用模型（CA-Markov）、生态系统过程模型（PnET-II）以及森林直观景观模型（LANDIS-II）,试图建立在景观/区域尺度上森林景观时空变化的空间表征方法,为中国南方人工林地区调整经济发展和森林管理政策,建立相适应的机制与措施提供科学参考。
2 研究方法与数据来源
2.1 研究区概况
泰和县位于江西省中部偏南,吉安地区西南部（26.45°N~26.98°N、114.95°E~115.33°E）,全县总面积为2667 km2。赣江由南往北贯穿而过,在泰和县中部形成河谷平原,并将泰和县分为河东、河西两个部分（图1）。气候类型为中亚热带季风气候,年均气温18.6°C,年平均降水量为1370 mm,雨热同期[21]。境内地貌类型以山地、丘陵为主,地势东西高、中间低,中部地区多分布水稻等经济作物,东西部地区以种植用材林为主。土壤类型以红壤为主,中部平原地区有部分水稻土及紫色土分布[22]。泰和县森林资源丰富,主要植被类型有常绿阔叶林、亚热带针叶林、亚热带竹林等,林地面积达到1680.1 km2,占研究区总面积的62.9%。同时该县承担着重要的人工林生产任务,人工林的面积达到733 km2,占森林总面积的44.9%。从森林覆盖率和主要的森林类型来看,研究区森林十分具有典型性和区域特征。此外,中国科学院千烟洲生态试验站的长期观测数据为本文的模型参数化提供了科学基础与数据支持。
显示原图|下载原图ZIP|生成PPT图1研究区位置及森林类型图
-->Fig. 1Location and forest type of the study area
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2.2 数据预处理与模拟情景
气候变化的影响主要是来自气温、降水、CO2浓度等气候要素的变化。未来气候情景下的月气温和降水数据来自“WCRP的耦合模式比较计划—阶段5的多模式数据集（CMIP5数据）”（http://www.climatechange-data.cn）,该数据集由国家气候中心提供,数据使用国际理论物理研究中心的区域气候模式RegCM4,单向嵌套BCC_CSM1.1全球气候系统模式输出结果,对中国地区进行RCP8.5排放情景下的模拟,数据空间分辨率为0.5°×0.5°。数据结果表明,到2050年泰和县年均温在RCP8.5情景下将达到18.27°C,与2010年实测值增加1.25°C。预估未来的降水量数据受该区域季风气候的影响表现出较为显著的年际波动。CO2浓度数据来源于RCPs数据集（http://tntcat.iiasa.ac.at:8787/RcpDb）,预计到2050年浓度达到540.54 ppm。此外,本文以当前气候状态为控制情景,其数据来自国家气象科学数据共享服务平台（http://data.cma.cn/）吉安站2000-2010年观测的气温、降水平均值。人类活动的干扰主要通过土地利用变化和森林采伐两种主要的方式影响森林景观的动态变化。土地利用数据来自江西省国土资源厅的调查数据,主要包括2000年、2005年、2010年的矢量数据,地类类型：林地、耕地、草地、水域、建设用地和未利用地。森林小班数据来自泰和县林业局提供的森林资源二类调查数据集,主要包括小班内优势树种、地类、龄组、森林起源及用途等,通过ArcGIS软件对2009年泰和县森林资源二类调查数据进行整合处理,得到泰和县全县森林面积为1680.1 km2,其中阔叶林258.5 km2,占15.4%;针叶林1111.2 km2,占66.1%;竹林和经济林共占森林总面积的18.5%。本文仅模拟阔叶林和针叶林对不同干扰情景的响应,竹林和经济林由于生理生态特性和抚育方式的差异将不在模拟中考虑。森林采伐的数据和管理方式来自于泰和县林业局,即满足不同树种达到成熟年龄的前提下,每5年采伐森林管理区域面积的5%进行森林更新。根据以上的干扰特征设置5个情景,具体情景描述如表1所示。
Tab. 1
表1
表1不同情景的特征描述
Tab. 1Characteristic description of different scenarios
| 情景类型 | 无干扰 | 气候变化 | 土地利用 | 采伐 | 综合情景 |
|---|---|---|---|---|---|
| 情景模拟描述 | 仅在当前气候状态下的森林自然演替模拟 | 仅在气候变化RCP8.5情景下的森林演替模拟 | 仅在当前土地利用变化需求下的森林演替模拟 | 仅在当前采伐管理措施下的森林演替模拟 | 气候变化、土地利用、采伐共同作用下的森林演替模拟 |
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2.3 多模型综合模拟方法
综合利用土地利用模型、生态系统过程模型以及森林景观模型模拟多干扰下的森林景观动态变化,不同模型的特征描述如表2所示。其中,土地利用变化模拟采用CA-Markov模型,以2005年和2010年江西省国土资源调查的土地利用数据为原始输入,利用IDRISI Selva 17.0软件中的Markov模块、MCE（multi-criteria evaluation）模块以及CA-Markov模块来模拟未来40年研究区的土地利用变化[23]。对于模拟精度验证,将2010年实际的土地利用数据和2010年模拟的土地利用数据进行空间一致性比较,得到Kappa指数为0.8781（>0.8）,表明模拟结果具有较高空间一致性[24]。Tab. 2
表2
表2多模拟模型的特征描述
Tab. 2Characteristic description of different models
| 模拟模型 | 土地利用变化模型（CA-Markov） | 生态系统过程模型（PnET-II） | 森林景观模型（LANDIS-II） |
|---|---|---|---|
| 时间尺度 | 每5年（2010-2050年） | 每5年（2010-2050年） | 每5年（2010-2050年） |
| 空间尺度 | 100 m×100 m | 0.5°×0.5° | 100 m×100 m |
| 本地参数化 | 2005-2010年土地利用转移矩阵 | 气候数据、植被参数、立地 参数 | 初始群落分布、生态区、管理区、演替及干扰参数 |
| 数据来源 | 江西省国土资源调查土地利用数据 | 未来气候情景数据、千烟洲 生态试验站的观测数据、参考文献 | 观测数据、森林小班调查数据、CA-Markov和PnET-II的模拟结果、当地林业管理部门 |
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气候变化影响下的森林生态系统过程模拟利用PnET-II模型,该模型通过集中参数来模拟树种的碳、水循环过程,通过建立土壤和水分要素与树木生长的函数关系,估算森林生态系统最大生产潜力[25,26]。模型输出结果可以为LANDIS-II提供包括物种建立系数（SEP）和地表净初级生产力（ANPP）等关键输入参数。气候数据来自未来气候情景数据和当前气候状态情景数据,其他参数主要来自于千烟洲生态试验站的观测数据、相关文献以及当地的林业管理人员及森林生态学专家。
森林景观模拟采用LANDIS-II模型,该模型是用于模拟森林干扰、演替和管理的空间直观景观模型[27]。模型通过追溯树种年龄级（cohorts）来模拟不同干扰下长时间、大尺度的森林景观动态。输入的初始森林群落数据来源于2009年森林调查小班数据。生态分区图是将研究区划分为若干个自然条件相似的类型区,由于泰和县境内气温、降水差异较小,土壤也以红壤为主,考虑到森林种植和生长与地形有密切的关系,以地貌类型特征作为划分生态区的依据,将研究区划分为5个生态区（图2）。应用模型的演替、采伐以及土地利用模块来实现气候变化和人类活动驱动下的森林景观动态模拟,主要树种的生活史参数来自于文献资料、样地的观测调查数据以及咨询专家得到[28,29,30,31]（表3）。
显示原图|下载原图ZIP|生成PPT图2生态分区图
-->Fig. 2Ecoregions of the study area
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Tab. 3
表3
表3优势树种的物种生活史参数
Tab. 3Life history attributes for dominant species
| 树种 | 拉丁名 | 寿命（年） | 成熟年龄（年） | 萌发率 | 耐阴性 | 种子传播距离（m） |
|---|---|---|---|---|---|---|
| 马尾松 | Pinus massoniana | 200 | 10 | 0.2 | 1 | 200 |
| 湿地松 | Pinus elliottii | 200 | 10 | 0.2 | 1 | 200 |
| 杉木 | Cunninghamia lanceolata | 200 | 10 | 0.6 | 1 | 200 |
| 樟树 | Cinnamomum camphora | 1000 | 15 | 0.5 | 4 | 50 |
| 栲树 | Castanopsis fargesii | 150 | 30 | 0.6 | 5 | 60 |
| 木荷 | Schima superba | 300 | 20 | 0.6 | 5 | 20 |
| 白栎 | Quercus fabri | 120 | 15 | 0.6 | 4 | 20 |
| 青冈 | Cyclobalanopsis multinervis | 200 | 7 | 0.4 | 4 | 20 |
| 苦楝 | Melia azedarach | 80 | 5 | 0.3 | 2 | 200 |
| 拟赤杨 | Alniphyllum fortunei | 120 | 15 | 0.4 | 2 | 250 |
| 桤木 | Alnus cremastogyne | 125 | 5 | 0.4 | 3 | 15 |
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3 结果分析
3.1 森林面积变化分析
森林面积变化的结果表明,阔叶林在无干扰、气候变化、土地利用变化和综合干扰情景下保持增加趋势,而在采伐情景下,阔叶林呈现波动变化,森林面积相对稳定（图3）。到2050年,土地利用和综合情景下的森林面积达到最大,与2010年相比分别增加了37.8%和38.2%;其次为无干扰和气候变化情景,增幅分别为18.1%和18.5%;采伐情景下,森林面积最小,为27434 hm2。从结果可以看出,气候变化对阔叶林面积的影响不大,2010-2030年保持较快增长;土地利用变化使阔叶林面积增加,2035年开始增幅显著提升,说明在地类转换的过程中,部分非林地转变成了林地。采伐使森林面积显著减少,但当前采伐方式仍可保持阔叶林面积稳定。针叶林面积变化与阔叶林相比存在较大差异,到2050年无干扰情景下森林面积达到最大,达到134594 hm2,增加了20.8%;气候变化情景下针叶林面积略低于无干扰情景;土地利用干扰使针叶林面积先升高后下降,与阔叶林不同到2035年森林面积开始减少,到2050年达到126723 hm2;采伐使针叶林面积保持稳定,波动不及阔叶林剧烈;综合情景下针叶林面积有小幅增加,增加了6470 hm2。对于森林总面积,由于针叶林面积占据主导,不同情景下的总面积变化趋势与针叶林基本保持一致,但2035年以后土地利用干扰下的森林面积保持增加,说明阔叶林的面积增加更加显著。
显示原图|下载原图ZIP|生成PPT图32010-2050年不同干扰情景下阔叶林、针叶林和森林总体的面积变化
-->Fig. 3Changes in forest area of broad-leaved forest, coniferous forest and the total forest under various scenarios during 2010 to 2050
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为更直观地辨识不同干扰作用在2010-2050年期间对森林面积的影响差异,制作不同干扰情景下的森林面积箱图（图4）。从结果来看,对于阔叶林,无干扰、气候变化和采伐的面积变化区间不大,而土地利用和综合情景下的面积变化区间较大,说明森林面积变化更加剧烈。与阔叶林相比,针叶林受气候变化的影响更大,而采伐的变化区间最小,说明采伐使针叶林的面积更加稳定。而森林总面积在不同干扰下的变化与针叶林基本一致。
显示原图|下载原图ZIP|生成PPT图42010-2050年不同干扰情景下阔叶林、针叶林和森林景观的面积变化箱图
-->Fig. 4Box plot of changes in forest area of broad-leaved forest, coniferous forest and the total forest landscape under various scenarios during 2010 to 2050
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3.2 森林地上生物量变化分析
LANDIS-II模型已经在该区域之前的工作中得到应用并验证,说明模型具有较好的适用性[32]。从模拟结果可以看出,除采伐外,阔叶林地上总生物量基本不受其他干扰过程的影响,而采伐在2020年开始地上生物量发生一次明显降低之后缓慢提升,地上生物量的变化与森林面积的变化趋势保持一致（图5）。到2050年,阔叶林总生物量在无干扰、气候变化、土地利用和采伐情景下平均增加了约391.3 t,增幅达123.4%,采伐情景下增加了146.3 t;针叶林的生物量在不同干扰情景下均呈现先升高后保持平稳的变化趋势,到2035年变化幅度较小。到2050年,无干扰和气候变化地上生物量基本持平,分别达到1195.4 t和1198.1 t。其次是土地利用干扰情景,总生物量达到1147.5 t,采伐情景下生物量基本保持平稳,到2050年达到842.6 t。从研究区森林总地上生物量来看,整体变化趋势保持增长,2050与2010年增长幅度不同情景对比：气候变化>无干扰>土地利用>综合干扰>采伐。其中,采伐情景下自2020年开始即保持平稳,到2050年,仅增加230.1 t,增幅21.5%。
显示原图|下载原图ZIP|生成PPT图52010-2050年不同干扰情景下阔叶林、针叶林和森林景观的地上生物量变化
-->Fig. 5Changes in forest aboveground biomass of broad-leaved forest, coniferous forest and the total forest under various scenarios during 2010-2050
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3.3 森林地上生物量空间格局变化分析
LANDIS-II模型通过模拟不同干扰情景下的森林生物量,能够输出每5年的森林地上生物量空间分布图,本文仅列出2010年、2030年和2050年五种不同干扰下的森林平均地上生物量,构建模拟时间和干扰情景矩阵（图6）。从2010-2050年,森林生物量总体呈增加趋势,而森林采伐干扰下的生物量增加并不显著。从空间格局来看,平均生物量较高的地区与阔叶林的分布地区较为一致,主要分布在东西部的生态区4的中丘地区,到2050年,最高值位于东部海拔最高的生态区5境内,低值区位于中部平原的针叶林分布区。对比不同干扰情景下森林地上生物量空间格局的差异,森林采伐的生物量分布空间格局更加破碎化,采伐过程主要作用于中部亚热带人工针叶林地区,其生物量绝对值明显低于其他干扰情景,到2050年,几乎未出现高于200 t/hm2的斑块。无干扰、气候变化和土地利用变化的总生物量空间格局差异较小,而综合干扰受采伐的影响中部地区斑块更加破碎,地上生物量值低于无干扰情景。
显示原图|下载原图ZIP|生成PPT图6不同干扰情景下的森林地上生物量空间分布
-->Fig. 6Spatial distribution of total forest aboveground biomass under various scenarios
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4 结论与讨论
4.1 结论
以江西省泰和县为研究区,综合利用基于元胞自动机的土地利用模型（CA-Markov）、生态系统过程模型（PnET-II）以及森林直观景观模型（LANDIS-II）,模拟了五种不同情景下泰和县2010-2050年阔叶林、针叶林和森林景观面积及地上生物量的变化,试图建立在景观/区域尺度上森林景观时空变化的空间表征方法,主要结论如下：（1）气候变化对研究区森林面积影响较小,采伐使森林面积显著减少,而土地利用变化使森林面积的变化更加剧烈;阔叶林和针叶林对人类活动干扰存在一定的响应差异,针叶林受各类干扰的影响更大。
（2）在未来不同干扰情景下,阔叶林、针叶林以及森林总地上生物量都呈现显著增加趋势,但不同干扰情景下的增加幅度有所不同,2050年与2010年森林总地上生物量增长幅度不同情景对比得到：气候变化>无干扰>土地利用>综合干扰>采伐。
（3）森林地上生物量空间格局变化表明,平均生物量较高的地区与阔叶林的分布地区较为一致（位于生态区4或5）,生物量值较低的地区位于中部河谷平原,为针叶人工林主要分布区域（位于生态区2或3）,采伐过程对森林景观格局的影响更加显著。
（4）本文基于森林直观景观模型的空间表征方法有助于景观/区域尺度森林的管理与研究,为南方红壤丘陵区森林结构优化和功能提升提供科学建议。
4.2 讨论
在未来复杂的环境变化下,森林生态系统的结构、功能和演替过程将受到气候变化和人类活动直接和间接的影响[33]。结果表明：针叶林对气候变化的响应更加剧烈,森林采伐显著降低森林面积和生物量,而土地利用变化虽然使森林面积和生物量保持较高,但每个模拟年都会发生林地与非林地之间的相互转换,在综合影响下采伐对针叶林的影响更加显著。对比其他研究,Gustafson等在西伯利亚中南部地区的模拟中发现了类似的结果,他们认为森林组成和生物量对采伐的响应更加剧烈,而气候变化的影响在短期内并不显著[34];而Thompson等在美国马萨诸塞州森林景观模拟结果发现,森林面积的减少主要由于土地利用变化影响,并表现出更多的随机性,其变化也更加复杂剧烈[35]。这些结果与本文结果也基本一致。虽然以上这些模拟结果不能完全反映真实环境的变化过程,但是情景模拟的方式在一定程度上能够有效帮助识别不同森林类型、森林景观对未来可能的气候和人为干扰的响应程度,具有一定的科学意义。对于空间模拟结果的验证,尤其是未来模拟结果的验证一直以来都是生态模拟研究的难点。本研究利用多模型开展综合模拟,模拟结果目前仅能做到逐步验证,通过保证每个模型的相对准确来实现综合集成模拟结果的正确性[36]。而验证也仅能做到对已有数据的验证即模拟初始期的结果与实际结果的比较,如CA-Markov模型将2010年实际的与模拟的土地利用数据进行空间一致性比较,模拟结果得到了有效验证;PnET-II模型的模拟结果与该区域内其他有关生产力的研究结果进行了比较,认为模拟值在不同树种的变化区间内。LANDIS-II模型在之前该区域的研究中已开展了模拟初始年的生物量实测值与模拟值的验证研究,通过随机选取森林二类调查数据中的500个森林小班,对比得到模拟值与实测值之间呈显著的线性相关关系,说明模型结果基本可信。
将多模型耦合与综合应用是从方法上开展地理学综合研究的有效途径[37],但模型的耦合过程也面临着大量的不确定性。首先,模型模拟参数本地化过程的不确定。如本研究的未来气候情景数据是根据单个全球气候模式处理后的区域结果,是一个经过平均化处理的数据集,具有一定的不确定性。但本文所采用的数据空间精度（0.5°×0.5°）基本可以满足研究的空间尺度要求。生态模型参数化是基于森林调查、样地观测和咨询当地的林业专家等途径,由于个体树种具有生理特性的差异,在资料搜集过程中资料的准确性也会产生不确定。其次,模型自身的不确定性。CA-Markov模型是基于当前的土地利用转移矩阵和开发概率来决定未来空间上土地利用类型的变化[38]。土地利用变化过程是受政策影响较为直接的快速变化过程,而政策又会根据环境的变化不断更新变化,其中人类就是最重要的不确定性来源,使得土地利用变化模拟结果存在不确定[39]。但同时该模型也能很好地反映在当前土地利用需求下未来的土地利用空间格局的潜在变化,能够较为真实地反映人类活动下对林地的需求。PnET-II和LANDIS-II模型作为生态模型,设计是基于树种生长与环境变化的数学关系,是对复杂的生态系统的简化过程,因此模型本身也必然存在一定的不确定。但是在景观尺度上这两个模型也具有其自身的优势,能够很好地反映多干扰下森林的空间变化。最后,多模型集成应用过程中的不确定性也是本研究不确定性的重要来源。模型之间的输入输出的数据格式和空间精度转换对模型的无缝连接形成了巨大障碍。每个模型都是以目标结果为导向进行的单独设计,因此在参数、机理、过程以及干扰等多个步骤还难以做到系统间的反馈和模型的耦合。在未来的研究中构建这种综合研究框架下的复杂模型,同时不断将传统的模型检验与评估方法进一步发展并应用于复杂系统模型的检验是未来解决人地复杂关系的重要手段与发展方向。
The authors have declared that no competing interests exist.
参考文献 原文顺序
文献年度倒序
文中引用次数倒序
被引期刊影响因子
| [1] | . 人类活动所引起的温室效应及由此造成的全球气候变化和对全球生态环境的影响正越来越引起人们的关注。作为全球陆地生态系统一个重要组分的森林对未来气候变化的响应更是人们关注的重点。文中系统地论述了未来气候变化对森林生态系统树种组成、林分结构、分布和生产力的潜在响应,提出了今后需要加强的一些研究领域。 . 人类活动所引起的温室效应及由此造成的全球气候变化和对全球生态环境的影响正越来越引起人们的关注。作为全球陆地生态系统一个重要组分的森林对未来气候变化的响应更是人们关注的重点。文中系统地论述了未来气候变化对森林生态系统树种组成、林分结构、分布和生产力的潜在响应,提出了今后需要加强的一些研究领域。 |
| [2] | . . |
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| [6] | . Abstract Ecosystems worldwide are losing some species and gaining others, resulting in an interchange of species that is having profound impacts on how these ecosystems function. However, research on the effects of species gains and losses has developed largely independently of one another. Recent conceptual advances regarding effects of species gain have arisen from studies that have unraveled the mechanistic basis of how invading species with novel traits alter biotic interactions and ecosystem processes. In contrast, studies on traits associated with species loss are fewer, and much remains unknown about how traits that predispose species to extinction affect ecological processes. Species gains and losses are both consequences and drivers of global change; thus, explicit integration of research on how both processes simultaneously affect ecosystem functioning is key to determining the response of the Earth system to current and future human activities. |
| [7] | . 未来地球计划是目前国际上关于全球环境变化前沿研究的综合科学计划,集国际科学理事会(ICSU)所领导的四大科学计划为一体,旨在将自然科学与社会科学结合在一起,并加强决策支持和研究交流,寻求地球系统可持续途径,全球环境变化研究与人类学、社会学合作构建综合集成平台,推进科学研究为社会经济可持续发展服务。本文剖析陆地表层格局特点,分析陆地表层格局的国内外关注焦点及其研究理念的转变与应用领域的拓展。分析表明:陆地表层是未来地球计划关注的重点之一,陆地表层要素与过程相互作用并在人类活动驱动下形成的格局,可作为未来地球计划进一步研究的区域基础框架。未来,陆地表层格局研究应力求方法论的突破,为自然地理学综合研究的发展提供支撑。 . 未来地球计划是目前国际上关于全球环境变化前沿研究的综合科学计划,集国际科学理事会(ICSU)所领导的四大科学计划为一体,旨在将自然科学与社会科学结合在一起,并加强决策支持和研究交流,寻求地球系统可持续途径,全球环境变化研究与人类学、社会学合作构建综合集成平台,推进科学研究为社会经济可持续发展服务。本文剖析陆地表层格局特点,分析陆地表层格局的国内外关注焦点及其研究理念的转变与应用领域的拓展。分析表明:陆地表层是未来地球计划关注的重点之一,陆地表层要素与过程相互作用并在人类活动驱动下形成的格局,可作为未来地球计划进一步研究的区域基础框架。未来,陆地表层格局研究应力求方法论的突破,为自然地理学综合研究的发展提供支撑。 |
| [8] | . Understanding disturbance and recovery of forest landscapes is a challenge because of complex interactions over a range of temporal and spatial scales. Landscape simulation models offer an approach to studying such systems at broad scales. Fire can be simulated spatially using mechanistic or stochastic approaches. We describe the fire module in a spatially explicit, stochastic model of forest landscape dynamics (LANDIS) that incorporates fire, windthrow, and harvest disturbance with species-level succession. A stochastic approach is suited to forest landscape models that are designed to simulate patterns over large spatial and time domains and are not used deterministically to predict individual events. We used the model to examine how disturbance regimes and species dynamics interact across a large (500 000 ha), heterogeneous landscape in northern Wisconsin, USA, with six land types having different species environments, and fire disturbance return intervals varying from 200 to 1000 yr. The model shows that there are feedbacks over time between species, disturbance, and environment, resulting in the re-emergence of patterns that characterized the landscape before extensive alteration. Landscape equilibrium of species composition and age-class structure develops at three scales from the initial, disturbed landscape. Over 100-150 yr, fine-grained successional processes cause gradual disaggregation of the initial pattern of relatively homogenous composition and age classes. Species such as eastern hemlock (Tsuga canadensis), largely removed from the landscape by past human activities, only slowly re-invade. Next, patterns on the various land types diverge, driven by different disturbance regimes and dominant species. Finally, aging of the landscape causes the probabilities of larger and more severe fires to increase, and a coarse-grained pattern develops from the disturbance patches. Influence of adjacent land types is shown as fires spread across land type boundaries, although modified in spread and severity. As found by others, altered landscapes are likely to retain their modified pattern for centuries, suggesting that nonequilibrium conditions between tree species and climate will persist under predicted rates of climate change. The results suggest that this modeling approach can be useful in examining species-level, broad-scale responses of heterogeneous landscapes to changes in landscape disturbance, such as modified management or land-use scenarios, or effects of global change. |
| [9] | . 中国科学院机构知识库(CAS IR GRID)以发展机构知识能力和知识管理能力为目标，快速实现对本机构知识资产的收集、长期保存、合理传播利用，积极建设对知识内容进行捕获、转化、传播、利用和审计的能力，逐步建设包括知识内容分析、关系分析和能力审计在内的知识服务能力，开展综合知识管理。 |
| [10] | . Competition, secondary succession, and changes in vegetation accompanying changes in elevation have been successfully reproduced by a computer simulation of a mixed-species, uneven-aged forest ecosystem of north-eastern United States. As much as the data and understanding allow, this simulation has a conceptual basis. Changes in the state of the simulated forest are a function of the present state plus random components. The program predicts a peak standing crop for the forest approximately 200 years following clearcutting, with a relatively stable, but fluctuating, species composition at subsequent periods. Designed to be used in the Hubbard Brook Ecosystem Study, the program provides output in a form compatible with the original vegetation survey of that study and allows a flexible interaction between the user and the simulator. |
| [11] | . |
| [12] | . This paper provides contextual documentation of the LANDIS model development to provide a framework for the other papers in this special issue. The LANDIS model of forest landscape disturbance and succession was developed since the early 1990s as a research and management tool that optimizes the possible landscape extent (100 s ha to 1000 s km 2), while providing mechanistic detail adequate for a broad range of potential problems. LANDIS is a raster model, and operates on landscapes mapped as cells, containing tree species age classes. Spatial processes, such as seed dispersal, and disturbances such as fire, wind, and harvesting can occur. LANDIS development benefited from the modelling and research progress of the 1960s to the1980s, including the growth of landscape ecology during the 1980s. In the past decade the model has been used by colleagues across North America, as well as in Europe and China. This has been useful to those not able to undertake the cost and effort of developing their own model, and it has provided a growing diverse set of test landscapes for the model. These areas include temperate, southern, and boreal forests of eastern North America, to montane and boreal western forests, coastal California forest and shrub systems, boreal Finnish forests, and montane forests in Switzerland and northeastern China. The LANDIS model continues to be refined and developed. Papers in this special issue document recent work. Future goals include integration within a larger land use change model, and applications to landscape and regional global change projection based on newly incorporated biomass and carbon dynamics. |
| [13] | . A forest is embedded in heterogeneous landscape mosaics and interacts with the surrounding environment through processes such as seed dispersal. Previous forest models, however, have either ignored such interactions or made unrealistic assumptions. We developed a landscape model (FORMOSAIC) that explicitly considers not only the dynamics of a focal forest but also ecological impacts of adjacent areas on the focal forest. FORMOSAIC is hierarchically structured, spatially explicit, multi-scale, stochastic, and individual-based. It integrates information of tree position, regeneration, growth, death, spatial interaction, and environmental factors. Data for parameterizing FORMOSAIC were mainly from a 50 ha permanent study plot in the Pasoh forest reserve (Malaysia), which contained over 800 tree species and more than 330 000 trees with diameter at breast height (dbh) 1.0 cm. Model simulation results agreed well with independent field census data in terms of species richness, species composition, tree abundance, and basal area at two spatial scales. Sensitivity analysis indicated that minimum harvest size was the most sensitive parameter. Species richness was particularly sensitive to the duration of seed immigration from species-rich surrounding forests. For tree abundance and basal area, the second most sensitive parameters varied at two spatial scales. Through uncertainty analysis we found that many parameters had scale-dependent and non-linear relationships with species richness, tree abundance, and basal area. There also existed significant interactive effects between parameters. The model could be a useful tool for addressing important issues such as fragmentation and deforestation in forest management for species diversity and timber production from a landscape perspective. |
| [14] | . 应用空间直观景观模型 LANDIS-II模拟了陕西黄龙山森林景观在不考虑风、火、病虫害及采伐等干扰因素前提下300a(2004—2304年)的自然演替进行动态,采用景 观格局统计软件APACK计算了林区内优势树种所占的面积百分比以及反映物种分布格局的聚集度指数,分析了各个树种在模拟的时间尺度上龄级组成的变化趋 势。结果表明:油松是针叶树中的优势种,辽东栎是阔叶树中的优势种;在演替后期油松取代辽东栎成为所占面积比例最大的优势树种;油松和辽东栎的相对聚集度 较其它几类树种小;随着模拟年代的推进,树种年龄结构发生显著变化,呈现出复杂多样的异龄林空间分布格局。 . 应用空间直观景观模型 LANDIS-II模拟了陕西黄龙山森林景观在不考虑风、火、病虫害及采伐等干扰因素前提下300a(2004—2304年)的自然演替进行动态,采用景 观格局统计软件APACK计算了林区内优势树种所占的面积百分比以及反映物种分布格局的聚集度指数,分析了各个树种在模拟的时间尺度上龄级组成的变化趋 势。结果表明:油松是针叶树中的优势种,辽东栎是阔叶树中的优势种;在演替后期油松取代辽东栎成为所占面积比例最大的优势树种;油松和辽东栎的相对聚集度 较其它几类树种小;随着模拟年代的推进,树种年龄结构发生显著变化,呈现出复杂多样的异龄林空间分布格局。 |
| [15] | . Abstract In the past three decades, our global climate has been experiencing unprecedented warming. This warming has and will continue to significantly influence the structure and function of forest ecosystems. While studies have been conducted to explore the possible responses of forest landscapes to future climate change, the representative concentration pathways (RCPs) scenarios under the framework of the Coupled Model Intercomparison Project Phase 5 (CMIP5) have not been widely used in quantitative modeling research of forest landscapes. We used LANDIS-II, a forest dynamic landscape model, coupled with a forest ecosystem process model (PnET-II), to simulate spatial interactions and ecological succession processes under RCP scenarios, RCP2.6, RCP4.5 and RCP8.5, respectively. We also modeled a control scenario of extrapolating current climate conditions to examine changes in distribution and aboveground biomass (AGB) among five different forest types for the period of 2010 2100 in Taihe County in southern China, where subtropical coniferous plantations dominate. The results of the simulation show that climate change will significantly influence forest distribution and AGB. (i) Evergreen broad-leaved forests will expand into Chinese fir and Chinese weeping cypress forests. The area percentages of evergreen broad-leaved forests under RCP2.6, RCP4.5, RCP8.5 and the control scenarios account for 18.25%, 18.71%, 18.85% and 17.46% of total forest area, respectively. (ii) The total AGB under RCP4.5 will reach its highest level by the year 2100. Compared with the control scenarios, the total AGB under RCP2.6, RCP4.5 and RCP8.5 increases by 24.1%, 64.2% and 29.8%, respectively. (iii) The forest total AGB increases rapidly at first and then decreases slowly on the temporal dimension. (iv) Even though the fluctuation patterns of total AGB will remain consistent under various future climatic scenarios, there will be certain responsive differences among various forest types. |
| [16] | . Ecosystem carbon carrying capacity (CCC) is determined by prevailing climate and natural disturbance regimes, conditions that are projected to change significantly. The interaction of changing climate and its effects on disturbance regimes is expected to affect forest regeneration and growth, which may diminish forest carbon (C) stocks and uptake. We modeled landscape C dynamics over 590 years along the latitudinal gradient of the U.S. Sierra Nevada Mountains under climate and area burned by large wildfires projected by late 21stcentury. We assumed climate and wildfire stabilize at late-21stcentury conditions (2090 2100) to facilitate analysis of lags between warming and changing CCC. We show that compared with historical (1980 2010) climate and wildfire conditions, projected scenarios would drive a significant decrease of up to 73% in mean total ecosystem carbon (TEC) by the end of the 590-year simulation. Tree regeneration failure due to intensified growing season dryness and increased area burned would substantially decrease forested area, transitioning the system from C sink to source. Our results demonstrate the potential for a lower CCC in the system due to extensive vegetation type conversion from forest to non-forest types, and suggest a decline in the contribution of Sierra Nevada forests to U.S. C sink. |
| [17] | . Planted forests are expanding throughout the world, and now account for 7% of global forest cover and provide more than 60% of global industrial round wood. Negative ecological and social impacts of the establishment of planted forests and the challenges of their multi-purpose management have also given rise to concern. China has been playing an important role in global expansion of planted forests while reducing emission from deforestation and forest degradation. This article attempts to conduct an overall analysis and review of the current status, challenges and future perspectives of planted forests in China to obtain a better understanding on how to manage planted forests for multiple uses under a changing environment. Data from several national forest inventories and other sources, as well as new empirical data, were used for a statistical analysis on the dynamics of planted forests in China. Planted forests in China have undergone a continuous expansion in the past 20 years, which has significantly contributed to an increase in total forest cover and timber supply as well as other ecosystem services like carbon sequestration. The three key driving forces for this expansion were government programmes, and market and technology development. However, the predominance of very few tree species in the plantations, uneven spatial distribution, skewed age-class distribution, and low volumes in growing stock, coupled with increasing complexity of multiple purpose forestry management under a changing environment, have generated several major challenges confronting planted forests in China. A strategic transition in the management of Chinese planted forests is needed, with a shifting emphasis from area expansion to stand productivity and quality enhancement, from traditional timber production to multi-purpose management for forest goods and services, and from monoculture plantations to biodiversity rich mixed forests. A landscape-design approach and adaptive management practices should be put in place to meet the diversified demands of stakeholders for different goods and ecosystem services while enhancing forest resilience under the changing climate. |
| [18] | . 南方森林对于中国林业乃至整个国民经济的持续发展和人民生活水平的提高发挥了重要作用,其生态系统功能在维持生态环境与社会经济呵持续发展中极其重要.目前,中国南方森林生态系统存在林种和林龄结构不合理、人工林面积大但森林质量不高、森林灾害严重、水土流失现象严重、生物多样性减少、生态系统功能退化、林地流失严重等问题.针对上述问题,必须健全林业的金融和税收扶持政策,完善林业贴息贷款、森林保险保费补贴、森林经营补助、免缴税费等政策,促进林业产业化发展,积极推进适地适树造林政策,因地制宜优化林种结构,提高森林生物多样性,强化森林资源保护管理,实行依法治林,增强森林灾害防控,确保森林健康发展,提高森林经营水平,改善森林质量,提升林业科技进步贡献率,拓展专业技术队伍素质,以确保南方森林生态系统持续稳定健康发展. . 南方森林对于中国林业乃至整个国民经济的持续发展和人民生活水平的提高发挥了重要作用,其生态系统功能在维持生态环境与社会经济呵持续发展中极其重要.目前,中国南方森林生态系统存在林种和林龄结构不合理、人工林面积大但森林质量不高、森林灾害严重、水土流失现象严重、生物多样性减少、生态系统功能退化、林地流失严重等问题.针对上述问题,必须健全林业的金融和税收扶持政策,完善林业贴息贷款、森林保险保费补贴、森林经营补助、免缴税费等政策,促进林业产业化发展,积极推进适地适树造林政策,因地制宜优化林种结构,提高森林生物多样性,强化森林资源保护管理,实行依法治林,增强森林灾害防控,确保森林健康发展,提高森林经营水平,改善森林质量,提升林业科技进步贡献率,拓展专业技术队伍素质,以确保南方森林生态系统持续稳定健康发展. |
| [19] | . |
| [20] | . 土地利用变化通过改变生态系统结构对植被生物量产生很大影响.采用土地利用动态模型模拟了沿历史趋势情景(未来土地利用面积变化由1988—2005年的历史趋势推衍而来)和规划情景下(未来土地利用面积变化基于国家尺度上的土地利用规划来制定)中国至2030年土地利用变化的时空分布格局，基于此格局并结合密度法估算了植被生物量空间分布.模拟结果表明：沿历史趋势情景下，森林面积将减少，但随着林龄的增长，森林生物量密度增加，至2030年中国植被生物量为14619 Tg，比2005年增加了251.19 Tg；规划情景下，森林面积将增加，至2030年中国植被生物量为15468 Tg，比2005年增加了1100 Tg.在规划情景下，由于人工林面积较大，林龄普遍较低，导致至2030年植被生物量密度低于沿历史趋势情景，因此规划情景下中国植被作为碳汇的潜力更大. . 土地利用变化通过改变生态系统结构对植被生物量产生很大影响.采用土地利用动态模型模拟了沿历史趋势情景(未来土地利用面积变化由1988—2005年的历史趋势推衍而来)和规划情景下(未来土地利用面积变化基于国家尺度上的土地利用规划来制定)中国至2030年土地利用变化的时空分布格局，基于此格局并结合密度法估算了植被生物量空间分布.模拟结果表明：沿历史趋势情景下，森林面积将减少，但随着林龄的增长，森林生物量密度增加，至2030年中国植被生物量为14619 Tg，比2005年增加了251.19 Tg；规划情景下，森林面积将增加，至2030年中国植被生物量为15468 Tg，比2005年增加了1100 Tg.在规划情景下，由于人工林面积较大，林龄普遍较低，导致至2030年植被生物量密度低于沿历史趋势情景，因此规划情景下中国植被作为碳汇的潜力更大. |
| [21] | . Despite the significance of interannual variation of soil respiration () for understanding long-term soil carbon dynamics, factors that control the interannual variation of have not been sufficiently investigated. Interannual variation of was studied using a 6-year data set collected in a subtropical plantation dominated by an exotic species, slash pine (Engelm.), in China. The results showed that seasonal variation of was significantly affected by soil temperature and soil water content (SWC). in the dry season (July–October) was constrained by seasonal drought. Mean annual was estimated to be 73602± 3002g02C·m·year, with a range of 706–79002g02C·m·year. Although this forest was characterized by a humid climate with high precipitation (146902mm·year), the interannual variation of was attributed to the changes of annual mean SWC (= 0.66, = 0.03), which was affected by annual rainfall frequency (= 0.80, 02< 0.01) and not rainfall amount (= 0.84). Consequently, precipitation pattern indirectly controlled the interannual variation of by affecting soil moisture in this subtropical forest. In the context of climate change, interannual variation of in subtropical ecosystems is expected to increase because of the predicted changes of precipitation regime. |
| [22] | |
| [23] | . In the context of rapid urbanization, accurate assessment of urban growth has become increasingly necessary for understanding environmental impacts and supporting urban planning toward a sustainable development. In this paper, we present an integrated system dynamics and cellular automata model not only in socio-economic driving forces analysis but also in urban spatial pattern evaluation. Shanghai city in China is selected as a case to fulfill the tasks. The major findings are summarized as follows: (1) the integrated model is proved to be competent in monitoring and projecting the dynamics of urban growth. (2) From 2000 to 2020, the urban area of Shanghai is predicted to increase at an annual rate of 3%, and amount 1474 km 2 in 2020. Spatially, the newly increased urban land is most likely to expand around the vicinity of city center or sub-centers, and mainly along a west–east axis and a north–south axis. Road network planning plays an important role in directing the development of newly urbanized land. |
| [24] | . |
| [25] | . PnET is a simple, lumped-parameter, monthly-time-step model of carbon and water balances of forests built on two principal relationships: 1) maximum photosynthetic rate is a function of foliar nitrogen concentration, and 2) stomatal conductance is a function of realized photosynthetic rate. Monthly leaf area display and carbon and water balances are predicted by combining these with standard equations describing light attenuation in canopies and photosynthetic response to diminishing radiation intensity, along with effects of soil water stress and vapor pressure deficit (VPD). PnET has been validated against field data from 10 well-studied temperate and boreal forest ecosystems, supporting our central hypothesis that aggregation of climatic data to the monthly scale and biological data such as foliar characteristics to the ecosystem level does not cause a significant loss of information relative to long-term, mean ecosystem responses. Sensitivity analyses reveal a diversity of responses among systems to identical alterations in climatic drivers. This suggests that great care should be used in developing generalizations as to how forests will respond to a changing climate. Also critical is the degree to which the temperature responses of photosynthesis and respiration might acclimate to changes in mean temperatures at decadal time scales. An extreme climate change simulation (+3 C maximum temperature, -25% precipitation with no change in minimum temperature or radiation, direct effects of increased atmospheric CO鈧 ignored) suggests that major increases in water stress, and reductions in biomass production (net carbon gain) and water yield would follow such a change. |
| [26] | . 利用光化学植被指数（PRI）反演区域尺度植被光能利用效率（LUE）的动态变化特征是当前生态系统生产力遥感研究的一个重要方向。基于2014年4月-2015年3月在广东省肇庆市鼎湖山森林生态试验站开展了植被冠层光谱和涡度相关通量同步观测,探讨亚热带常绿针阔混交林LUE与PRI的相关性及其调控因素。研究表明：（1）亚热带常绿针阔混交林LUE-PRI存在显著相关关系,但其相关性存在较大的季节性差异,冬季的相关性（R~2=0.40,P〈0.01）明显优于夏季（R~2=0.04,P〈0.01）;（2）削弱植被自身的色素含量以及观测区内部的冠层结构、土壤背景、观测和光照条件影响后的？PRI难以有效表征亚热带常绿针阔混交林的LUE动态变化（表征程度为10%左右）;（3）植被吸收的光合有效辐射（PAR）对LUE-PRI关系影响较大,饱和水汽压差（VPD）和日均温（Ta）对LUE-PRI相关性的影响较弱。需要进一步分析森林冠层结构、物候变化等因素对两者关系的影响,提高PRI作为亚热带森林LUE动态变化指示器的精度。 . 利用光化学植被指数（PRI）反演区域尺度植被光能利用效率（LUE）的动态变化特征是当前生态系统生产力遥感研究的一个重要方向。基于2014年4月-2015年3月在广东省肇庆市鼎湖山森林生态试验站开展了植被冠层光谱和涡度相关通量同步观测,探讨亚热带常绿针阔混交林LUE与PRI的相关性及其调控因素。研究表明：（1）亚热带常绿针阔混交林LUE-PRI存在显著相关关系,但其相关性存在较大的季节性差异,冬季的相关性（R~2=0.40,P〈0.01）明显优于夏季（R~2=0.04,P〈0.01）;（2）削弱植被自身的色素含量以及观测区内部的冠层结构、土壤背景、观测和光照条件影响后的？PRI难以有效表征亚热带常绿针阔混交林的LUE动态变化（表征程度为10%左右）;（3）植被吸收的光合有效辐射（PAR）对LUE-PRI关系影响较大,饱和水汽压差（VPD）和日均温（Ta）对LUE-PRI相关性的影响较弱。需要进一步分析森林冠层结构、物候变化等因素对两者关系的影响,提高PRI作为亚热带森林LUE动态变化指示器的精度。 |
| [27] | . We introduce LANDIS-II, a landscape model designed to simulate forest succession and disturbances. LANDIS-II builds upon and preserves the functionality of previous LANDIS forest landscape simulation models. LANDIS-II is distinguished by the inclusion of variable time steps for different ecological processes; our use of a rigorous development and testing process used by software engineers; and an emphasis on collaborative features including a flexible, open architecture. We detail the variable time step logic and provide an overview of the system architecture. Finally, we demonstrate model behavior and sensitivity to variable time steps through application to a large boreal forest landscape. We simulated pre-industrial forest fire regimes in order to establish base-line conditions for future management. Differing model time steps substantially altered our estimates of pre-industrial forest conditions. Where disturbance frequency is relatively high or successional processes long, the variable time steps may be a critical element for successful forest landscape modeling. |
| [28] | |
| [29] | . . |
| [30] | . <FONT face=Verdana>利用基于生理生态学过程的EALCO模型，探讨了千烟洲中亚热带人工针叶林生态系统对未来气候变化的响应.结果表明:CO<SUB>2</SUB>浓度、温度和降水的变化对该人工林生态系统碳水通量<BR>影响的程度不同，其中CO<SUB>2</SUB>浓度＞温度＞降水.CO<SUB>2</SUB>浓度是生态系统总光合生产力(GPP)<BR>的主要驱动因子，温度与CO<SUB>2</SUB>浓度均是控制生态系统呼吸的主要环境因子，温度的升高使<BR>植物地上部分呼吸明显增加，而CO<SUB>2</SUB>浓度升高则对土壤呼吸影响较大.温度升高使蒸散(ET)<BR>增加，而CO<SUB>2</SUB>浓度升高则使ET减少.在未来气候变化情景(2100年)下，该人工林生态系统的<BR>净初级生产力将增加22%，说明其仍具有较强的固碳潜力.<BR></FONT> . <FONT face=Verdana>利用基于生理生态学过程的EALCO模型，探讨了千烟洲中亚热带人工针叶林生态系统对未来气候变化的响应.结果表明:CO<SUB>2</SUB>浓度、温度和降水的变化对该人工林生态系统碳水通量<BR>影响的程度不同，其中CO<SUB>2</SUB>浓度＞温度＞降水.CO<SUB>2</SUB>浓度是生态系统总光合生产力(GPP)<BR>的主要驱动因子，温度与CO<SUB>2</SUB>浓度均是控制生态系统呼吸的主要环境因子，温度的升高使<BR>植物地上部分呼吸明显增加，而CO<SUB>2</SUB>浓度升高则对土壤呼吸影响较大.温度升高使蒸散(ET)<BR>增加，而CO<SUB>2</SUB>浓度升高则使ET减少.在未来气候变化情景(2100年)下，该人工林生态系统的<BR>净初级生产力将增加22%，说明其仍具有较强的固碳潜力.<BR></FONT> |
| [31] | . 植被净初级生产力（NPP）对气候变化的响应研究是全球变化研究的核心内容之一。在区域尺度上研究NPP年际间的空间变化规律,探究气候因子与植被生长的关系,是应对气候变化区域响应、探讨区域生态过程的科学基础。基于SPOT VEGETATION NDVI植被指数数据、气候和植被分类数据,利用光能利用率模型（CASA）估算了中国南方红壤丘陵区泰和县1998-2012年植被NPP,分析了NPP时空分布特征及其与气候因子的相关性。结果表明：1 1998-2012年泰和县植被年均NPP为762 g C/m2·a,不同植被类型差异明显,空间上表现出东西高、中间低的分布特征;2 1998-2012年泰和县植被NPP总体呈增长趋势,年际波动较大,平均值为2.21×106g C/a;3研究区NPP与年降水量呈不显著正相关关系,与年均气温呈显著负相关关系,表明温度是影响该地区植被NPP的主要气候因子。 . 植被净初级生产力（NPP）对气候变化的响应研究是全球变化研究的核心内容之一。在区域尺度上研究NPP年际间的空间变化规律,探究气候因子与植被生长的关系,是应对气候变化区域响应、探讨区域生态过程的科学基础。基于SPOT VEGETATION NDVI植被指数数据、气候和植被分类数据,利用光能利用率模型（CASA）估算了中国南方红壤丘陵区泰和县1998-2012年植被NPP,分析了NPP时空分布特征及其与气候因子的相关性。结果表明：1 1998-2012年泰和县植被年均NPP为762 g C/m2·a,不同植被类型差异明显,空间上表现出东西高、中间低的分布特征;2 1998-2012年泰和县植被NPP总体呈增长趋势,年际波动较大,平均值为2.21×106g C/a;3研究区NPP与年降水量呈不显著正相关关系,与年均气温呈显著负相关关系,表明温度是影响该地区植被NPP的主要气候因子。 |
| [32] | . 以土地利用变化和气候变化为特征的全球和区域环境变化及其影响已经成为国际社会和公众关注的焦点,同时也是土地科学、全球变化科学和全球生态学关注的关键问题。由于土地、气候和森林生态系统之间存在着复杂而密切的关系,土地利用变化和气候变化将不可避免地对森林结构和功能产生重要影响。如何采用合理的适应措施降低这些变化可能带来的损失,是目前全球变化研究亟待解决的问题之一。因此,研究土地利用和气候变化对森林的单独及综合影响具有重要的科学意义。本文综合利用基于主体的土地利用模型(ABM/LUCC)、生态系统过程模型(PnET-Ⅱ)以及森林景观动态模型(LANDIS-Ⅱ)构建了综合模拟研究框架,选择森林类型多样且具有长期观测数据积累的江西省泰和县为研究区,模拟并对比了土地利用和气候变化组合情景下未来森林地上总生物量的变化差异。结果表明:(1)土地利用变化对泰和县森林地上总生物量的影响比气候变化所带来的影响更加显著。研究区森林地上总生物量在有土地利用变化干扰的情景下与RCP 2.6、RCP 4.5和RCP 8.5单独的气候情景下相比分别减少33.13%、32.92%和32.42%;(2)尽管未来气候变化可能有利于森林地上总生物量的积累,但土地利用变化将使森林地上总生物量显著减少,并将抵消气候变化带来的正效应;(3)本文提出的综合模拟研究框架可以很好地模拟土地利用和气候变化对森林生态系统的影响,可为提升和优化人工林结构和功能、开展可持续森林管理提供科学建议。 . 以土地利用变化和气候变化为特征的全球和区域环境变化及其影响已经成为国际社会和公众关注的焦点,同时也是土地科学、全球变化科学和全球生态学关注的关键问题。由于土地、气候和森林生态系统之间存在着复杂而密切的关系,土地利用变化和气候变化将不可避免地对森林结构和功能产生重要影响。如何采用合理的适应措施降低这些变化可能带来的损失,是目前全球变化研究亟待解决的问题之一。因此,研究土地利用和气候变化对森林的单独及综合影响具有重要的科学意义。本文综合利用基于主体的土地利用模型(ABM/LUCC)、生态系统过程模型(PnET-Ⅱ)以及森林景观动态模型(LANDIS-Ⅱ)构建了综合模拟研究框架,选择森林类型多样且具有长期观测数据积累的江西省泰和县为研究区,模拟并对比了土地利用和气候变化组合情景下未来森林地上总生物量的变化差异。结果表明:(1)土地利用变化对泰和县森林地上总生物量的影响比气候变化所带来的影响更加显著。研究区森林地上总生物量在有土地利用变化干扰的情景下与RCP 2.6、RCP 4.5和RCP 8.5单独的气候情景下相比分别减少33.13%、32.92%和32.42%;(2)尽管未来气候变化可能有利于森林地上总生物量的积累,但土地利用变化将使森林地上总生物量显著减少,并将抵消气候变化带来的正效应;(3)本文提出的综合模拟研究框架可以很好地模拟土地利用和气候变化对森林生态系统的影响,可为提升和优化人工林结构和功能、开展可持续森林管理提供科学建议。 |
| [33] | . |
| [34] | . Multiple global changes such as timber harvesting in areas not previously disturbed by cutting and climate change will undoubtedly affect the composition and spatial distribution of boreal forests, which will, in turn, affect the ability of these forests to retain carbon and maintain biodiversity. To predict future states of the boreal forest reliably, it is necessary to understand the complex interactions among forest regenerative processes (succession), natural disturbances (e.g., fire, wind, and insects), and anthropogenic disturbances (e.g., timber harvest). We used a landscape succession and disturbance model (LANDIS-II) to study the relative effects of climate change, timber harvesting, and insect outbreaks on forest composition, biomass (carbon), and landscape pattern in south-central Siberia. We found that most response variables were more strongly influenced by timber harvest and insect outbreaks than by the direct effects of climate change. Direct climate effects generally increased tree productivity and modified probability of establishment, but indirect effects on the fire regime generally counteracted the direct effects of climate on forest composition. Harvest and insects significantly changed forest composition, reduced living aboveground biomass, and increased forest fragmentation. We concluded that: (1) Global change is likely to significantly change forest composition of south-central Siberian landscapes, with some changes taking ecosystems outside the historic range of variability. (2) The direct effects of climate change in the study area are not as significant as the exploitation of virgin forest by timber harvest and the potential increased outbreaks of the Siberian silk moth. (3) Novel disturbance by timber harvest and insect outbreaks may greatly reduce the aboveground living biomass of Siberian forests and may significantly alter ecosystem dynamics and wildlife populations by increasing forest fragmentation. |
| [35] | . Land use and climate change have complex and interacting effects on naturally dynamic forest landscapes. To anticipate and adapt to these changes, it is necessary to understand their individual and aggregate impacts on forest growth and composition. We conducted a simulation experiment to evaluate regional forest change in Massachusetts, USA over the next 50 years (2010 2060). Our objective was to estimate, assuming a linear continuation of recent trends, the relative and interactive influence of continued growth and succession, climate change, forest conversion to developed uses, and timber harvest on live aboveground biomass (AGB) and tree species composition. We examined 20 years of land use records in relation to social and biophysical explanatory variables and used regression trees to create "probability-of-conversion" and "probability-of-harvest" zones. We incorporated this information into a spatially interactive forest landscape simulator to examine forest dynamics as they were affected by land use and climate change. We conducted simulations in a fullfactorial design and found that continued forest growth and succession had the largest effect on AGB, increasing stores from 181.83 Tg to 309.56 Tg over 50 years. The increase varied from 49% to 112% depending on the ecoregion within the state. Compared to simulations with no climate or land use, forest conversion reduced gains in AGB by 23.18 Tg (or 18%) over 50 years. Timber harvests reduced gains in AGB by 5.23 Tg (4%). Climate change (temperature and precipitation) increased gains in AGB by 17.3 Tg (13.5%). Pinus strobus and Acer rubrum were ranked first and second, respectively, in terms of total AGB throughout all simulations. Climate change reinforced the dominance of those two species. Timber harvest reduced Quercus rubra from 10.8% to 9.4% of total AGB, but otherwise had little effect on composition. Forest conversion was generally indiscriminate in terms of species removal. Under the na茂ve assumption that future land use patterns will resemble the recent past, we conclude that continued forest growth and recovery will be the dominant mechanism driving forest dynamics over the next 50 years, and that while climate change may enhance growth rates, this will be more than offset by land use, primarily forest conversion to developed uses. |
| [36] | . Validation of the long-term biomass predictions of forest landscape models (FLMs) has always been a challenging task. Using the space-for-time substitution method, forest biomass curves over stand age were generated from a forest survey dataset (FSD) in the Lesser Khingan Mountains area ( LKM ), Northeastern China and compared with long-term biomass predictions of LANDIS-II model. The results showed that mean forest age and mean biomass of the LKM in 2000 were 51.6 years and 84.2Mgha 611 , respectively. Significant linear correlations were found between FSD derived biomass and simulated biomass in the aggradation phase for the entire LKM and most subregions. However, a considerable difference in the mean maximum biomass (53.45Mgha 611 ) existed between from FSD and simulation during the post-aggradation phase. The space-for-time substitution method has potential in validating time series biomass predictions of FLMs in aggradation phase when only limited forest inventory data is available. |
| [37] | . . |
| [38] | . . |
| [39] | . Analyzing the process of land use and cover changes during long periods of time and predicting the future changes is highly important and useful for the land use managers. In this study, the land use maps in the Ardabil plain in north-west part of Iran for four periods (1989, 1998, 2009 and 2013) are extracted and analyzed through remote sensing technique, using the land-sat satellite images. Then, the future land use changes are simulated for 2030 using integrated CA-Markov model according to the scenario of continuing current management process. The results show that in the period between 1989 and 2009, i.e. since two-thirds of the plain was declared restricted till all of it was declared thus, the study area has experienced a total of about 58645.08 ha changes. After the whole plain was restricted (since 2009 till 2014), the changes have been estimated to be 22466.88 ha. The prediction also indicates that the changes will equal 8908.83 ha by 2030. Agricultural lands and human-built environment constitute the majority of changes and are increasing continuously. The obtained Kappa values for the model accuracy assessment (higher than 0.8) indicated the model capability to predict future Land use/cover changes in the study area. Thus, analyzing Land use and cover changes trends from past to near future using CA-Markov model can play a significant role in land use policy making, planning, and managing of the restricted plains especially in the proposed study area. |
