The impact of farm management on species-specific leaf area index (LAI): Farm-scale data and predictive models
The impact of farm management on species-specific leaf area index (LAI): Farm-scale data and predictive models
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农场管理对物种特定叶面积指数 (LAI) 的影响：农场规模数据和预测模型
DOI：
10.1016/j.agee.2009.10.006
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发表时间：
2010
期刊：
影响因子：
--
通讯作者：
Pocock M
中科院分区：
文献类型：
--
作者：
Pocock M
叶面积指数（LAI，单位面积单面叶面积）是陆地生态系统中植物立地作物的度量，是气象、气候和水文模型中的关键参数。虽然可以通过破坏性采伐测量单个物种的LAI，也可以通过遥感估算整个景观的LAI，但在景观尺度上缺乏物种特异性LAI的估算。在2007年和2008年的夏天，我们在英国萨默塞特郡一个125公顷的农场工作，开发了一种方法来确定总叶面积随时间、栖息地和物种之间的变化来源。我们测量了农场所有植被类型的LAI，即：作物、未管理的非木本植被、树篱和树木。利用已有的方法估算LAI，主要是利用LI-COR LAI-2000植物冠层分析仪进行间隙分数分析，并根据野外调查数据将LAI划分为组成种。我们发现该农场的总LAI为4.1，尽管这在不同的栖息地之间有很大的差异，从稻田的3.3到森林的8.0。每个月我们测量LAI发现，根据月份的不同，61-81%的叶面积由作物物种组成（包括牧草和短期leyley中的草和三叶草），7-10%为木本植被，其余为非木本半自然植被。基于对每个生境LAI的测量，我们建立了LAI的预测模型，发现对于非木本植被，LAI的变化是植被类型和植被高度的函数，而对于树篱，LAI是树篱高度和宽度的函数。根据我们的数据和预测模型，我们预测了五种可能的农场管理情景导致的LAI变化。预计对视觉景观产生巨大影响的变化（森林损失、树篱大小减少）对农场尺度LAI的影响要小于视觉上更微妙的变化（草地植被长度的变化）。这种类型的建模可以与区域土地利用数据相结合，以预测区域农业变化（土地利用或土地管理强度的变化）对LAI的影响，从而对生态系统、生物地球化学循环、碳封存和水文的影响。
Leaf area index (LAI; the single-sided leaf area per unit area of ground) is a measure of plant standing crop in terrestrial ecosystems and is a key parameter in meteorological, climate and hydrological models. While the LAI of individual species can be measured by destructive harvesting and LAI of whole landscapes can be estimated by remote sensing, estimates of species-specific LAI at the landscape-scale are lacking. Working on a 125ha farm in Somerset, UK during the summers of 2007 and 2008, we developed a method to identify sources of variation in total leaf area over time, between habitats and between species. We measured LAI for all vegetation types on the farm, namely: crops, unmanaged non-woody vegetation, hedgerows and trees. We used established methods to estimate LAI, mostly by gap fraction analysis with a LI-COR LAI-2000 Plant Canopy Analyzer and we divided LAI into its constituent species based on the data from field surveys. We found that the total LAI of the farm was 4.1, although this varied substantially between habitats from 3.3 for cereal fields to 8.0 for woods. Each month we measured LAI and found that, depending on the month, 61–81% of the leaf area was comprised of crop species (including grass and clover in pastures and short-term leys), 7–10% was woody vegetation and the remainder was non-woody semi-natural vegetation. We developed predictive models of LAI, based on our measurements of LAI in each habitat, and found that, for non-woody vegetation, variation in LAI was a function of vegetation type and vegetation height, while for hedgerows LAI was a function of hedge height and width. From our data and our predictive models we predicted changes in LAI due to five likely farm management scenarios. Changes that would have a huge impact on the visual landscape (loss of woods, reduction in hedge size) were predicted to have a smaller effect on farm-scale LAI than changes that would be visually more subtle (changes in vegetation length of grass fields). This type of modelling could be combined with regional land use data to predict the effect of regional agricultural changes (changes in land use or the intensity of land management) on LAI, and hence on ecosystems, biogeochemical cycling, carbon sequestration and hydrology.
影响因子：
6.2
作者：
K. Nasahara;H. Muraoka;S. Nagai;Hiroaki Mikami
通讯作者：
K. Nasahara;H. Muraoka;S. Nagai;Hiroaki Mikami
在转基因耐除草剂作物的农场规模评估中，与作物相邻的无脊椎动物和植被受到对比除草剂制度的影响。
DOI：
--
发表时间：
2003
期刊：
Philosophical transactions of the Royal Society of London. Series B, Biological sciences
影响因子：
--
作者：
D. Roy;David A. Bohan;A. Haughton;M. Hill;J. Osborne;S. Clark;J. Perry;P. Rothery;R. Scott;D. Brooks;G. Champion;C. Hawes;M. Heard;L. Firbank
通讯作者：
L. Firbank