Forest floor temperature and greenness link significantly to canopy attributes in South Africa’s fragmented coastal forests
Forest floor temperature and greenness link significantly to canopy attributes in South Africa’s fragmented coastal forests
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森林地面温度和绿度与南非分散的沿海森林的树冠属性显着相关
DOI：
10.7717/peerj.6190
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发表时间：
2018
期刊：
影响因子：
2.7
通讯作者：
Pieter I. Olivier
中科院分区：
文献类型：
--
作者：
M. Pfeifer;M. J. Boyle;S. Dunning;Pieter I. Olivier
由于土地使用和土地管理的变化，热带景观正在迅速变化。为了能够预测和监测土地利用变化对物种的保护或粮食安全的影响，需要使用生境质量指标，这些指标是一致的，可以使用地面传感器数据绘制地图，并与物种的表现有关。在这里，我们专注于地表温度（Thermalground）和地面植被绿度（NDVIdown）的栖息地质量的潜在合适的指标。两者都与文献中的物种人口统计学和群落结构有关。我们测试它们是否可以从地面测量一致，以及它们是否可以间接使用冠层结构图（叶面积指数，LAI，植被覆盖分数，FCover）开发的Landsat遥感数据。我们测量了南非夸祖鲁纳塔尔的人类改造的沿海森林景观中不同树木覆盖（天然草地到森林边缘到森林和树木种植园）的栖息地的Thermalground和NDVIdown。我们发现，这两个指标下降显着增加冠层郁闭度和叶面积，这意味着一个潜在的途径升级这两个指标使用冠层结构图来自地球观测。具体来说，我们的研究结果表明，开放森林冠层20%或减少森林冠层LAI一个单位将导致热地面增加1.2 °C在整个观测范围内研究。NDVI下降似乎下降0.1响应冠层叶面积指数增加1个单位，并与冠层关闭非线性下降。考虑到温度和资源的微尺度变化被认为是改善生物多样性影响预测的关键。我们的研究表明，映射地表温度和地面植被绿度利用遥感冠层覆盖图可以提供一个有用的工具，映射栖息地质量指标，物种的问题。然而，这种方法将受到用于绘制实地森林冠层属性的模型的预测能力的限制。此外，采样工作需要捕捉Thermalground的空间和时间变化内，并跨天和季节，以验证我们的研究结果的可转移性。最后，虽然我们的方法表明，地表温度和地面植被绿度可能是合适的栖息地质量指标用于生物多样性监测，下一步需要我们映射的人口特征的物种不同的威胁状态到地图上的这些指标的景观不同的干扰和管理的历史。由此得出的认识，然后可以利用有针对性的景观恢复，有利于生物多样性的保护在景观尺度。
Tropical landscapes are changing rapidly due to changes in land use and land management. Being able to predict and monitor land use change impacts on species for conservation or food security concerns requires the use of habitat quality metrics, that are consistent, can be mapped using above-ground sensor data and are relevant for species performance. Here, we focus on ground surface temperature (Thermalground) and ground vegetation greenness (NDVIdown) as potentially suitable metrics of habitat quality. Both have been linked to species demography and community structure in the literature. We test whether they can be measured consistently from the ground and whether they can be up-scaled indirectly using canopy structure maps (Leaf Area Index, LAI, and Fractional vegetation cover, FCover) developed from Landsat remote sensing data. We measured Thermalground and NDVIdown across habitats differing in tree cover (natural grassland to forest edges to forests and tree plantations) in the human-modified coastal forested landscapes of Kwa-Zulua Natal, South Africa. We show that both metrics decline significantly with increasing canopy closure and leaf area, implying a potential pathway for upscaling both metrics using canopy structure maps derived using earth observation. Specifically, our findings suggest that opening forest canopies by 20% or decreasing forest canopy LAI by one unit would result in increases of Thermalground by 1.2 °C across the range of observations studied. NDVIdown appears to decline by 0.1 in response to an increase in canopy LAI by 1 unit and declines nonlinearly with canopy closure. Accounting for micro-scale variation in temperature and resources is seen as essential to improve biodiversity impact predictions. Our study suggests that mapping ground surface temperature and ground vegetation greenness utilising remotely sensed canopy cover maps could provide a useful tool for mapping habitat quality metrics that matter to species. However, this approach will be constrained by the predictive capacity of models used to map field-derived forest canopy attributes. Furthermore, sampling efforts are needed to capture spatial and temporal variation in Thermalground within and across days and seasons to validate the transferability of our findings. Finally, whilst our approach shows that surface temperature and ground vegetation greenness might be suitable habitat quality metric used in biodiversity monitoring, the next step requires that we map demographic traits of species of different threat status onto maps of these metrics in landscapes differing in disturbance and management histories. The derived understanding could then be exploited for targeted landscape restoration that benefits biodiversity conservation at the landscape scale.