不同密度柚木人工林林下植被及土壤理化性质的研究

研究不同密度柚木人工林对林下植被及土壤理化性质的影响,为柚木人工林营建与可持续经营提供理论依据。以广东揭阳14~16年生不同林分密度（650、900、1 050、1 200和1 450 株·hm^-2）柚木人工林为研究对象,通过样方调查植被的种名、株数、高度及盖度等,并采集0~20和20~40 cm土样进行理化性质分析,对林下植被物种多样性指数及其土壤理化性质进行主成分分析评价,来评价不同林分密度下柚木人工林的立地质量。结果表明：随着林分密度增加,柚木人工林林下植被盖度整体表现出降低趋势,草本优势物种由阳生性到中生性,逐渐向阴生性的过渡,林下植被Shannon-Wiener指数、Simpson优势度指数、丰富度指数和均匀度指数表现出先增加后减少的趋势;相同密度下,表层土土壤理化性质优于下层土,随着林分密度增大,土壤理化性质整体呈现出先改善后退化的变化过程,不同林分密度间柚木人工林土壤毛管孔隙度、非毛管孔隙度、速效K、速效P、全P、交换性酸和交换性Al等指标差异性显著（P<0.05）;基于林下植被物种多样性和土壤理化性质主成分分析,不同林分密度柚木人工林物种多样性和土壤理化性质综合得分由大到小依次是：1 050 株·hm^-2（4.82）、900 株·hm^-2（1.58）、650 株·hm^-2（-1.30）、1 200 株·hm^-2（-1.81）、1 450 株·hm^-2（-3.29）。因此,说明适宜的林分密度（1 050 株·hm^-2）有利于保持较好的林下植被物种多样性和土壤理化性质,在柚木人工林经营的过程中,可以根据实际情况合理调整林分的密度。     

配比施肥对带状采伐毛竹林林下植被多样性的影响

毛竹是具有经济、生态等综合价值的重要物种,带状采伐为一种新型的高效的可机械化经营模式,在伐后自然恢复过程中,施肥是加快林分恢复的重要措施。2019年选取大年毛竹纯林,在带状采伐后选取N∶P₂O₅∶K₂O为2∶1∶1、3.5∶1∶2、5∶1∶2.5(A1、A2、A3)3种施肥配比和450、600、750 kg·hm^-2(B1、B2、B3)3种施肥量进行二因素三水平施肥试验,探究林下植被多样性对养分输入的响应。结果表明：(1)采伐当年,林下植被多样性随施肥配比的N、K比例升高,Shannon指数(H)和Gleason物种丰富度指数(D′)呈显著递增趋势,与对照处理相比表现出低比例时抑制和高比例时促进;Simpson指数(D)和Pielou均匀度指数(E)呈显著单峰趋势,各指数受不同施肥量影响的差异不显著。(2)2021年,指数H和D′的显著变化趋势消失;指数D和E保持显著单峰趋势,施肥配比为A2时达到峰值。(3)在时间动态上,施肥处理对林下植被多样性的影响表现出“先促进后抑制”的模式,2021年指数H、...     

低丘人工林林下植被物种多样性初步研究

选取江西省泰和县狗丝茅岭低丘荒山人工造林l0a的人工生态系统中8种人工林主要类型和1个对照区,通过比较这些类型林下植被的物种多样性(物种丰富度和Shannon-Wiener指数)和相关的环境因子,揭示林下植被物种多样性的差异及其与环境因子之间的关系。结果显示：人工林类型(造林树种)、林分组成(纯林或混交林)和林分密度对物种多样性的影响较为明显,其中林分密度的影响最为显著：各人工林类型林下植被的Shannon—Wiener指数与物种丰富度具有大体相似的规律,即在相近造林密度下,不同造林树种其林下植被物种多样性以针叶纯林稍占优势,针阔混交林次之,而阔叶纯林相对较低：针叶林林下植被物种多样性虽然最高,但针叶林土壤的持水力相对较差,有机质含量也较低,而阔叶纯林相对较好,针阔混交林则最佳。     

油松(Pinus tabulaeformis)人工林林下植被发育对油松生长节律的响应

林下植被作为森林生态系统的一个重要组成部分,对维持林分结构和土壤质量起着重要作用.不同年龄树种对林下植被发育的影响已有所涉及,但这些为数不多的研究往往割裂了林木种群的生长规律与其林下植被间的相互作用,以林龄为尺度探讨林下植被发育的差异必然掩盖了林分种群对林下植被作用的异质性.采用时序研究法,按照油松(Pinus tabulaeformis)高速生期、径速生期、材积慢生期和材积速生期等不同发育时期,探讨林下植被组成、多样性、生物量和元素积累量的差异性.结果表明,高速生期阶段油松与林下植被竞争最为激烈,林下植被物种丰富度、多样性、生物量、元素积累量均最低.因此,高速生期阶段应及时对油松采取较大强度的抚育间伐以缓和油松种群与林下植被剧烈竞争的关系.径速生阶段林下植被与油松竞争最为缓和,草本层Gleason、Shannon-Wiener、Pielow指数由高生长阶段的7.817、2.222和0.769剧增到19.978、3.470和0.907,灌木层、草本层地上部分生物量、元素积累量也均达到最大.径速生阶段对油松林分的管理可相对粗放一些.进入材积阶段,油松与林下植被的关系日趋紧张.材积慢生阶段灌木层、草本层生物量由径速生期的2 262.61、461.92 kg/hm2分别下降至1 549.85、 220.84 kg/hm2,而灌木层Gleason、Shannon-Wiener指数均达到峰值.相对于材积慢生期,材积速生期灌木层、草本层物种多样性指数、元素积累量进一步下降,而生物量略有上升,材积速生期阶段应对油松林分适度间伐或主伐.可见,林下植被可作为人工纯林乔木生长规律的指示剂,根据林下植被发育状况选择林分经营方式具有一定的参考价值.     

杨树人工林幼林阶段林下植被管理对土壤微生物生物量碳、氮酶活性的影响

为了探讨林下植物物种多样性对杨树（Populus spp.）人工幼林阶段土壤微生物区系的影响,在林下设计了林下植被物种数量递增的3种处理,即清除林下植被（无林下植物）、保留单一林下植物（一种林下植物）和保留物种多样的自然林下植被（多种林下植物）,于处理1年后采样分析土壤微生物生物量碳（MBC）和氮（MBN）含量、基于Biolog-ECO微平板的土壤微生物群落代谢特征以及与土壤碳、氮转化相关的胞外酶活性的差异,以期从土壤养分转化和供应的角度为科学管理人工林林下植被提供依据。结果表明,林下植被处理对8月份0-5 cm土层的土壤MBC、MBN含量以及酶活性有较大影响。与清除林下植被处理相比,保留单一林下植物处理8月份0-5 cm土层的土壤MBC、MBN含量以及β-葡萄糖苷酶、多酚氧化酶和芳基酰胺酶活性显著增加,增幅分别为27.91%、54.48%、14.74%、32.53%和6.20%,而保留物种丰富度高的自然林下植被处理林地土壤的上述指标进一步分别增加了4.88%、14.93%、9.22%、13.63%和12.86%。此外,林下植被处理还改变了土壤微生物群落代谢特征,8月份0-5 cm土层的土壤微生物Shannon指数随着林下植被物种数量的增加而显著增大。清除林下植被处理的土壤微生物主要利用的碳源包括部分糖类、氨基酸类和酯类,与清除林下植被处理相比,保留单一林下植物处理的土壤微生物提高了对上述几种碳源的利用能力,同时对糖类、氨基酸类、酯类和有机酸类碳源的利用种类范围明显扩大,而保留物种多样的自然林下植被的土壤微生物对31种碳源基本上可以全面有效利用。因此,保留林下植被,特别是提高林下植被的物种丰富度,有利于增加土壤微生物生物量,提高土壤微生物的代谢功能和分解活性,可以在一定程度上加快土壤的物质转化和养分循环功能。     

生态养殖河田鸡对林下植被多样性及土壤的影响

通过林下人工种草养殖河田鸡,调查林下生态养殖区与对照区的林木蓄积量、林地植被多样性指标、土壤理化性状、土壤侵蚀性。结果显示,林下生态养殖区内林木蓄积量显著高于对照区(P0.05);植被多样性与对照相比差异不显著(P0.05);土壤含水量、土壤pH值、硝态氮和铵态氮与对照相比均有所提高;林下生态养殖区下坡位的土壤侵蚀模数为120 t·km~(-2),与对照区相比总体土壤侵蚀量下降770 t·km~(-2),降幅达95.1%。     

北京地区油松人工林不同演替类型空间结构对林下植被及土壤的影响

以北京地区油松(Pinus tabuliformis)人工林不同演替类型林分为研究对象,研究油松纯林、油松-栓皮栎(Quercus variabilis)混交林和栓皮栎纯林三种不同演替类型林分的空间结构、林下植被和土壤水分的变化规律及其相互作用关系。结果表明：(1)林分水平及垂直空间结构、草本层物种多样性、更新幼树生长、土壤持水和透气性能等指标在三种不同演替类型林分间差异显著(P<0.05),林分空间结构参数中的角尺度、林层指数和开敞度显著影响了各类型林分的灌草多样性,混交度、林层指数和大小比数显著影响了更新幼树的生长,混交度和林层指数显著影响了土壤水分的变化(P<0.05)。(2)松栎混交林灌草生物量、天然更新幼树的生长以及土壤水分物理状况均好于纯林,并主要受林分混交度和林层指数的共同作用。(3)各演替类型林分内均存在栓皮栎更新幼树,混交林栓皮栎更新幼树数量最多、长势最好,对林地资源的竞争最为激烈。因此,可以通过调整林分空间结构实现种间关系及林地资源的调控,以充分发挥森林生态系统的各项功能与价值。     

不同密度格木幼林的土壤理化与林下植被特征

为探索适合格木(Erythrophleum fordii)人工林在幼龄阶段的种植密度,在不同林分密度(2 m×1 m、2 m×2 m、2 m×3 m、3 m×3 m)的6 a生格木人工林下设置标准样地,采用土壤质量评价和灰色关联度等方法,探究不同密度下格木幼林的土壤理化与林下植被特征。结果表明,密度2 m×3 m下的林木胸径、树高最优,较最低水平高16.7%、27.9%;土壤总孔隙度最大,全N、硝态N、铵态N含量最高,灌木草本多样性最高。相关性分析表明土壤化学性质对灌木草本的多样性影响最大。不同林分密度下格木幼林土壤理化性质及林下植物多样性有显著差异,因此,选择合适的林分密度对人工林土壤肥力的可持续利用及林分的经营培育至关重要。     

林下植被抚育对樟人工林生态系统碳储量的影响

以亚热带东部地区48年生樟(Cinnamomum camphora)人工林为研究对象, 探讨不同林下植被处理方式对植被和土壤碳储量的影响。研究结果表明: 1)林下植被抚育增加了植被的碳储量, 增幅为48.87%, 平均每年比未抚育林分增加了0.62 t·hm^-2; 2)林下植被抚育降低了土壤有机碳含量, 降低幅度介于4.79%-34.13%之间, 其中0-10 cm、10-20 cm土层比未抚育林分分别降低了10.16 g·kg^-1和8.58 g·kg^-1, 差异达到显著水平(p < 0.05); 3)林下植被抚育降低了森林土壤碳储量, 降低幅度介于1.98%-43.45%之间, 其中0-10 cm和10-20 cm土层分别降低了15.39 t·hm^-2和11.58 t·hm^-2, 差异达到极显著水平(p < 0.01)和显著水平(p < 0.05); 4)林下植被抚育降低了森林生态系统总碳储量, 降低幅度为4.27%, 但差异不显著。因此, 林下植被抚育虽有利于植被碳储量的积累, 但降低了土壤有机碳含量和储量。     

短期增温对亚热带常绿阔叶林林下植被物种多样性的影响

为了解气候变暖对亚热带常绿阔叶林林下植被物种多样性的影响,采用土壤增温方式,研究短期4年增温(4℃)对亚热带常绿阔叶天然林林下植被物种多样性的影响。结果表明,短期增温对林下植被物种组成影响不显著(P>0.05),增温和对照样地林下植被共有植物38科59属77种,其中增温样地37科53属65种,对照样地36科52属63种。短期增温使乔木盖度增加了22.61%,草本和灌木盖度分别降低4.97%和21.75%;增温使草本、灌木和乔木的高度分别降低21.64%、3.37%和5.59%。草本植物中的蕨类重要值排名在增温后呈下降趋势,乔木重要值呈上升趋势(P>0.05)。虽然植物物种多样性指数在增温后差异不显著(P>0.05),但随温度增加均呈递减的趋势。因此,林下植被物种组成对短期增温响应不敏感,增温使草本植物中的蕨类重要值下降,对植物多样性指数产生一定负面影响,但这种响应并不敏感,预计长期增温将可能导致整个群落从草本向灌木和乔木方向演替。     

Community Comparison and Determinant Analysis of Understory Vegetation in Six Plantations in South China

Plantations cover large areas in many countries, and the enhancement of plantation biodiversity is an increasingly important ecological concern. Many studies have demonstrated that overstory composition is important because it influences understory regeneration. To compare the understory vegetation and analyze its determinant factors, six typical plantations in South China were investigated: Acacia mangium plantation, Schima superba plantation, Eucalyptus citriodora plantation, E. exserta plantation, mixed‐coniferous plantation, and mixed native species plantation. The results show that native species plantations shaded out more grasses and herbs than exotic species plantations, mixed‐species plantations recruited more understory species than monoculture plantations, the leguminous species plantation had higher soil nitrogen than nonleguminous species plantations, and understory vegetation in the mixed‐coniferous plantation was similar to that of mixed, native broadleaf species plantation. Although light is the crucial environmental factor affecting the understory community and diversity among the 14 measured factors, other environmental variables such as soil nutrients and soil moisture are also important.     

青海大通典型林分冠层结构与林下植被物种多样性关系研究

为探究青海高寒山区典型林分冠层结构与林内光环境中维持林下植被物种多样性稳定的关键因素,该研究以青海大通县青海云杉林(Ⅰ)、青杨林(Ⅱ)、华北落叶松-青海云杉混交林(Ⅲ)、青杨-白桦混交林(Ⅳ)和白桦-青海云杉混交林(Ⅴ)5种典型人工林分为研究对象,运用冠层分析仪采集数据,并结合实地调查,研究冠层结构与林内光环境特征及其对林下植被的影响。结果表明:(1)林分Ⅰ、Ⅲ的林冠开度显著低于林分Ⅱ、Ⅳ、Ⅴ(P0.05),各林分叶面积指数大小顺序为ⅢⅠⅡⅤⅣ,总体表现为阔叶林的林冠开度大于针叶林,但其叶面积指数小于针叶林;林分Ⅱ、Ⅳ的直射辐射、散射辐射及总辐射均显著高于林分Ⅰ、Ⅲ、Ⅴ(P0.05),其中林下总辐射与散射辐射表现为ⅡⅣⅤⅠⅢ,直射辐射为ⅡⅣⅠⅢⅤ;林分Ⅱ、Ⅳ、Ⅴ的消光系数均显著高于Ⅰ、Ⅲ,总体上均表现为阔叶林针叶林。(2)相关分析结果表明,林冠开度与林下光照指标呈极显著正相关关系(P0.01),叶面积指数与林下光照指标呈极显著负相关关系(P0.01),且其对林下散射辐射的控制能力最强;典型相关分析表明,纯林的林冠开度对冠层结构的贡献和解释能力较叶面积指数和平均叶倾角大,混交林的叶面积指数对林下光照的影响大于纯林。(3)混交林的林下物种多样性指数(H)及丰富度指数(P)均高于纯林;林下草本层物种多样性指数(H)及丰富度指数(P)与林冠开度及林下光辐射呈显著正相关关系,与叶面积指数呈显著负相关关系(P0.05);物种均匀度(J_(sw))与平均叶倾角呈极显著负相关关系(P0.01),与林下散射辐射呈显著正相关关系(P0.05)。研究认为,在人工纯林改造和结构调整中,对乔木层适当补植伴生树种,并逐步调整为多树种混交林,增加冠层结构和林下光照异质性,将更有利于林下植被物种多样性的维持。     

云顶山不同人工林林下植物多样性及其与土壤理化性质的关系

以成都云顶山5种人工林（Ⅰ：柏木枫杨林;Ⅱ：银杏楠木林;Ⅲ：光皮梾木香樟林;Ⅳ：枫杨桤木林;Ⅴ：柏木林）为研究对象,重点研究不同人工林林下植物多样性与土壤理化性质差异以及二者间的关系。结果表明：不同人工林灌草层重要值最高的物种不同,光皮梾木香樟林林下植物组成最丰富,而银杏楠木林最贫乏。各人工林灌木层多样性指数H、优势度指数H''、丰富度指数D均以光皮梾木香樟林最大,而均匀度指数J_sw无显著差异;草本层H、D、J_sw均以柏木林最大,银杏楠木林最小,而H''差异不显著。不同人工林土壤pH值、有机质、全氮、全磷、速效钾、速效磷含量差异显著,pH值、全磷含量柏木枫杨林最高,有机质、全氮、速效钾、速效磷含量银杏楠木林最高。显著影响灌木层物种多样性的土壤因子为有机质、速效磷,草本层为pH、全磷、速效磷。结论：光皮梾木香樟林林下整体植物多样性水平最高,经营此种林分有利于林下植物多样性维持及发展,pH、有机质、全磷、速效磷是影响研究区林下植物多样性的主要土壤因子。     

陕北刺槐林木生长及林下植被与土壤水分对种植密度的响应特征

以陕西省安塞县2000年左右退耕栽植的5种不同密度(830~3 330株/hm~2)刺槐林地为研究对象,分析不同栽植密度对刺槐林木生长、林下植被及土壤水分的影响,为黄土高原丘陵沟壑区刺槐人工林合理栽植密度的确定以及可持续经营提供理论依据。结果表明:(1)阳坡中不同密度间刺槐林木的胸径、树高、冠幅均差异显著;阴坡中2 500株/hm~2的刺槐林木平均胸径、树高与两个低密度林的差异显著,且平均冠幅与1 670株/hm~2差异显著,与2 000株/hm~2差异不显著。(2)当栽植密度为1 670株/hm~2时,刺槐林地水分含量相对较高,林下植被平均盖度及物种多样性也较高。(3)各栽植密度刺槐林地0~500cm土壤含水量均低于该地区土壤稳定湿度(12%)。(4)阳坡中3 330株/hm~2的林地0~500cm土层含水量仅为4.5%,土壤干旱化严重,而830株/hm~2的刺槐林地土壤水分为7.8%;阴坡中栽植密度为1 670~2 000株/hm~2的刺槐林地土壤含水量较高,为7.5%~8.2%。研究表明,在陕北黄土高原丘陵沟壑区,刺槐初始造林密度不宜超过1 670株/hm~2(株行距2m×3m),在进入刺槐生长高峰期后,应采取间伐管理以调整林分密度,使其维持刺槐人工林林地的稳定性与可持续性。     

Vegetation classification of East China with multi-temporal NOAA-AVHRR data

East China lies in the subtropical monsoon climatic zone and is dominated by subtropical evergreen broad-leaved forests, a unique vegetation type mainly distributed in East Asia with the largest distribution in China. It is important to be able to monitor and estimate forest biomass and production, regional carbon storage, and global climate change impacts on these important vegetation types. In this paper, we used coarse resolution remote sensing data to identify the vegetation types in East China and developed a map of the spatial distribution of vegetation types in this region. Nineteen maximum normalized difference vegetation index (NDVI) composite images (acquisition time span of 7 months from February to August), which were derived from 10 days National Oceanographic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) channel 1 and channel 2 observations, an unsupervised classification method, and the ISODATA algorithm were employed to identify the vegetation types. To reduce the dimensions of the dataset resulted in a total of 28 spectral clusters of land-cover of which two clusters were urban/bare soil and water, the images were processed using principal component analysis (PCA). The 26 remaining spectral clusters were merged into six vegetation types using the Chinese vegetation taxonomy system: evergreen broad-leaved forest, coniferous forest, bamboo forest, shrub-grass, aquatic vegetation, and agricultural vegetation. The spatial distribution and areal extent for the coniferous forests, shrub-grass, evergreen broad-leaved forests, and agricultural vegetation were calculated and compared with the Vegetation Atlas of China at a 1:1,000,000 scale. The spatial accuracy and the area accuracy for coniferous forests, shrub-grass, evergreen broad-leaved forests, and agricultural vegetation were 79.2%, 91.3%, 68.2% and 95.9% and 92.1%, 95.9%, 63.8% and 90.5%, respectively. The spatial accuracy and area accuracy of the bamboo forest were 28.7% and 96.5%, respectively; the spatial accuracy of aquatic vegetation was 69.6%, but there was a significant difference in its area accuracy because image acquisition did not cover the full year. Our study demonstrated the feasibility of using NOAA-AVHRR to identify the different vegetation types in the subtropical evergreen broad-leaved forest zone in East China. The spatial location of the six identified vegetation types agreed with the actual geographical distribution of the vegetation types in East China. __________ Translated from Acta Phytoecologica Sinica, 2005, 29(3): 436–443 [译自: 植物生态学报, 2005, 29(3): 436–443]     

Vegetation classification of East China with multi-temporal NOAA-AVHRR data

East China lies in the subtropical monsoon climatic zone and is dominated by subtropical evergreen broad-leaved forests,a unique vegetation type mainly distributed in East Asia with the largest distnbution in China.It is important to be able to monitor and estimate forest biomass and production,regional carbon storage,and global climate change impacts on these important vegetation types.In this paper,we used coarse resolution remote sensing data to identify the vegetation types in East China and developed a map of the spatial distribution of vegetation types in this region.Nineteen maximum normalized difference vegetation index(NDVI)composite images(acquisition time span of 7 months from February to August),which were derived from 10 days National Oceanographic and Atmospheric Administration(NOAA)Advanced Very High Resolution Radiometer(AVHRR)channel 1 and channel 2 observations,an unsupervised classification method,and the ISODATA algorithm were employed to identify the vegetation types.To reduce the dimensions of the dataset resulted in a total of 28 spectral clusters of land-cover of which two clusters were urban/bare soil and water,the images were processed using principal component analysis(PCA).The 26 remaining spectral clusters were merged into six vegetation types using the Chinese vegetation taxonomy system:evergreen broad-leaved forest,coniferous forest,bamboo forest,shrub-grass,aquatic vegetation,and agricultural vegetation.The spatial distribution and areal extent for the coniferous forests,shrub-grass,evergreen broad-leaved forests,and agricultural vegetation were calculated and comscale.The spatial accuracy and the area accuracy for coniferous forests,shrub-grass,evergreen broad-leaved forests,and agricultural vegetation were 79.2%,91.3%,68.2% and 95.9% and 92.1%,95.9%,63.8% and 90.5%,respectively.The spatial accuracy and area accuracy of the bamboo forest were 28.7% and 96.5%,respectively;the spatial accuracy of aquatic vegetation was 69.6%,but there was a significant difference in its area accuracy because image acquisition did not cover the full year.Our study demonstrated the fea sibility of using NOAA-AVHRR to identify the different vegetation types in the subtropical evergreen broad-leaved forest zone in East China.The spatial location of the six identified vegetation types agreed with the actual geo graphical distribution of the vegetation types in East China.