基于植被降水利用效率和NDVI的黄河上游地区生态退化研究

提出了一种植被降水利用效率和NDVI变化趋势分析相结合识别生态退化、生态恢复区域的方法。利用黄河上游地区1982—2006年的AVHRR NDVI数据及同期16个气象站的降水量数据为基础数据源,计算每个像元的降水利用效率及其变化趋势,结合NDVI变化辨识生态退化和生态恢复的区域范围。结果表明,研究区域80%处于生态恢复阶段,恢复现象较为明显的区域主要位于东南部;生态退化显著的区域主要集中在玛多县县城,扎陵湖、鄂陵湖附近和龙羊峡库区周边。该结果与黄河上游地区草地退化的现状基本吻合,表明该方法可靠性较强,可以作为评估区域生态退化或生态恢复的方法。植被降水利用效率与NDVI变化趋势相结合的方法可以避免仅使用降水利用效率可能产生的误判。研究可为黄河上游地区开展生态恢复工程,合理规划和调整生态建设布局提供科学依据。     

Monitoring ecological indicators of rangeland functional integrity and their relation to biodiversity at local to regional scales

Abstract Functional integrity is the intactness of soil and native vegetation patterns and the processes that maintain these patterns. In Australia's rangelands, the integrity of these patterns and processes have been modified by clearing, grazing and fire. Intuitively, biodiversity should be strongly related to functional integrity; that is, landscapes with high functional integrity should maintain biodiversity, and altered, less functional landscapes may lose some biodiversity, defined here as the variety and abundance of the plants, animals and microorganisms of concern. Simple indicators of biodiversity and functional integrity are needed that can be monitored at a range of scales, from fine to coarse. In the present paper, we use examples, primarily from published work on Australia's rangeland, to document that at finer patch and hillslope scales several indicators of landscape functional integrity have been identified. These indicators, based on the quantity and quality of vegetation patches and interpatch zones, are related to biodiversity. For example, a decrease in the cover and width (quantity) and condition (quality) of vegetation patches, and an increase in bare soil (quantity of interpatch) near cattle watering points in a paddock are significantly related to declines in plant and grasshopper diversity. These vegetation patch‐cover and bare‐soil indicators have been monitored traditionally by field‐based methods, but new high‐resolution, remote‐sensing imagery can be used in specific rangeland areas for this fine‐scale monitoring. At intermediate paddock and small watershed scales, indicators that can be derived from medium‐resolution remote‐sensing are also needed for efficient monitoring of rangeland condition (i.e. functional integrity) and biodiversity. For example, 30–100‐m‐pixel Landsat imagery has been used to assess the condition of rangelands along grazing gradients extending from watering‐points. The variety and abundance of key taxa have been related to these gradients (the Biograze project). At still larger region and catchment scales, indicators of rangeland functional integrity can also be monitored by coarse‐resolution remote‐sensing and related to biodiversity. For example, the extent and greenness (condition) of different regional landscapes have been monitored with 1‐km‐pixel satellite imagery. This regional information becomes more valuable when it indicates differences as a result of land management. Finally, we discuss potential future developments that could improve proposed indicators of landscape functional integrity and biodiversity, thereby improving our ability to monitor rangelands effectively.     

The missing wetlands: using local ecological knowledge to find cryptic ecosystems

Small, temporally dynamic, biologically diverse isolated wetlands are among the most imperiled ecosystems, yet their conservation is hindered by lack of protective legislation and mapping. As part of an effort to better understand isolated wetland ecology in an area undergoing dramatic land use change, we mapped isolated wetlands in South Carolina’s Piedmont and Blue Ridge regions using remote sensing and local ecological knowledge (LEK). Remote detection of isolated wetlands was limited by digital resource resolution, topography, and wetland size. LEK was the most useful tool for locating small isolated wetlands. We sampled 10% of the study area using LEK and discovered 44 wetlands with “isolated” characteristics, none of which had been identified by remote sensing. Only 8 of 44 wetlands found through LEK could be identified using remote sensing after their discovery. LEK fills a gap in cryptic ecosystem detection when adequate remotely sensed data are not available. Though effective, using LEK is neither as rapid nor as repeatable as remote sensing. We suggest a two-pronged approach for finding cryptic ecosystems: remote sensing coupled with LEK where data resolution is inadequate. For remote detection of isolated wetlands, we suggest a minimum resolution of 0.33 m for Color Infrared, leaf-off, high-water photography. Despite great advances in remote sensing, data are not uniformly available worldwide and LEK may serve as an effective tool for locating cryptic resources for biodiversity conservation. Mapping cryptic resources will allow for more accurate resource and biodiversity conservation planning under current and future climate scenarios.     

Predicting Extreme Droughts in Savannah Africa: A Comparison of Proxy and Direct Measures in Detecting Biomass Fluctuations,Trends and Their Causes

We monitored pasture biomass on 20 permanent plots over 35 years to gauge the reliability of rainfall and NDVI as proxy measures of forage shortfalls in a savannah ecosystem. Both proxies are reliable indicators of pasture biomass at the onset of dry periods but fail to predict shortfalls in prolonged dry spells. In contrast, grazing pressure predicts pasture deficits with a high degree of accuracy. Large herbivores play a primary role in determining the severity of pasture deficits and variation across habitats. Grazing pressure also explains oscillations in plant biomass unrelated to rainfall. Plant biomass has declined steadily and biomass per unit of rainfall has fallen by a third, corresponding to a doubling in grazing intensity over the study period. The rising probability of forage deficits fits local pastoral perceptions of an increasing frequency of extreme shortfalls. The decline in forage is linked to sedentarization, range loss and herbivore compression into drought refuges, rather than climate change. The results show that the decline in rangeland productivity and increasing frequency of pasture shortfalls can be ameliorated by better husbandry practices and reinforces the need for ground monitoring to complement remote sensing in forecasting pasture shortfalls.     

藏北高原牧区人工草地建设布局的适宜性分析

人工草地是缓解天然草地退化和提升草地生产力的一种有效途径,但人工草地建设发展需注重区域布局、种植区划、经营管理等战略问题,尤其是在高寒牧区建立人工草地,目前还存在诸多值得探讨的科学问题。为此,选取藏北高原高寒牧区为研究区,基于遥感数据,土壤数据,气象数据,地形和土地利用数据,结合野外实地调查,从可利用土地资源角度考虑,通过分析藏北现有人工草地建设的立地条件,识别出区域适宜人工草地建设的潜在分布区,并与现有人工草地分布位置及其面积进行对比分析和验证,以期为区域未来人工草地建设布局提供科学指导。研究结果表明:在各种约束因子的限制下,藏北满足人工草地建设条件的适宜区域极其有限,难以发展大面积的人工草地建设工程。水热条件和海拔是限制区域人工草地建设的主要地理因素,尤其是那曲地区,绝大部分区域无法满足人工牧草生长活动的积温需求。因此,区域牧草种植规划中需重点考虑牧草品种的生物学特性。另一方面,在藏北高寒牧区建立人工草地必须慎重,今后人工草地种植规划还需要加强牧草的抗寒性和抗旱性研究,在人工草地的管理方面要特别关注已建人工草地的可持续性和稳定性,防止出现草地退化和沙化等问题。     

Detecting early warning signals of tree mortality in boreal North America using multiscale satellite data

Increasing tree mortality from global change drivers such as drought and biotic infestations is a widespread phenomenon, including in the boreal zone where climate changes and feedbacks to the Earth system are relatively large. Despite the importance for science and management communities, our ability to forecast tree mortality at landscape to continental scales is limited. However, two independent information streams have the potential to inform and improve mortality forecasts: repeat forest inventories and satellite remote sensing. Time series of tree‐level growth patterns indicate that productivity declines and related temporal dynamics often precede mortality years to decades before death. Plot‐level productivity, in turn, has been related to satellite‐based indices such as the Normalized difference vegetation index (NDVI). Here we link these two data sources to show that early warning signals of mortality are evident in several NDVI‐based metrics up to 24 years before death. We focus on two repeat forest inventories and three NDVI products across western boreal North America where productivity and mortality dynamics are influenced by periodic drought. These data sources capture a range of forest conditions and spatial resolution to highlight the sensitivity and limitations of our approach. Overall, results indicate potential to use satellite NDVI for early warning signals of mortality. Relationships are broadly consistent across inventories, species, and spatial resolutions, although the utility of coarse‐scale imagery in the heterogeneous aspen parkland was limited. Longer‐term NDVI data and annually remeasured sites with high mortality levels generate the strongest signals, although we still found robust relationships at sites remeasured at a typical 5 year frequency. The approach and relationships developed here can be used as a basis for improving forest mortality models and monitoring systems.     

Vegetation Colonization in a Restoring Tidal Marsh: A Remote Sensing Approach

Although remote sensing offers the ability to monitor wetland restoration, few have tested automated methods for quantifying vegetation change. We implemented a semiautomated technique using color infrared aerial photography and a common vegetation index, Normalized Difference Vegetation Index (NDVI), to document vegetation colonization in a restoring salt marsh. Change in vegetation over a period of 10 years was analyzed using a postclassification comparison technique where each image year was classified individually into vegetated and nonvegetated areas using NDVI thresholds and then differenced between years to identify areas of vegetation change. Vegetated and nonvegetated areas were identified using this technique, as were areas and time periods of vegetation change. By comparing classified NDVI imagery, we calculated that 90% of our study site was vegetated 10 years after restoration. This study demonstrated that high-resolution remotely sensed data can be analyzed with common geospatial software to monitor change in a rapidly vegetating wetland and that long time frames with yearly image acquisition are needed to quantify plant colonization rates. This method was effective at detecting change in vegetation over time in a variable tidal marsh environment using imagery that had inconsistent specifications and quality across years. Inconsistencies included interannual climate variation, phenology, and presence of algae, as well as differences in pixel size and image brightness. Our findings indicate that remote sensing is useful for postrestoration monitoring of tidal marsh ecosystems.     

Monitoring succession from space: A case study from the North Carolina Piedmont

Question: Is the successional transition from pine to hardwood, which has been inferred from chronosequence plots in previous studies, validated through a time line of satellite imagery? Location: Durham, North Carolina, USA. Methods: We examined successional trends in a time‐series of winter‐summer pairs of Thematic Mapper imagery from 1986 to 2000. We calculated the normalized difference of vegetation index (NDVI) for winter and summer, as well as the difference between summer and winter NDVI (i.e., summer increment NDVI). A set of approximately 50 forest stands of known age and phenology were used to interpret patterns in winter and summer increment NDVI over successional time, and a continuum was found to exist between pine‐dominance and hardwood‐dominance. We fitted a series of linear regressions that modeled the change in winter and summer increment NDVI as a function of initial winter and summer increment NDVI, and additional explanatory variables. Results: All regressions were highly significant (P < 0.0001, R²= ca. 0.3). Predicted dynamics are in accord with successional theory, with pixels moving from evergreen dominance to deciduous dominance along a line of fairly constant summer NDVI. A large disturbance event that occurred over the course of this study, Hurricane Fran, appeared to slow rates of succession in the short term (1–3 years), but increase the rate of conversion to hardwoods over longer time spans. Conclusions: We conclude that temporal sequences of remote sensing images provide an excellent opportunity for broad‐scale monitoring of successional processes, and that continuous metrics of that change are essential to accurate monitoring.     

Differentiating aquatic plant communities in a eutrophic river using hyperspectral and multispectral remote sensing

1. This study evaluates the efficacy of remote sensing technology to monitor species composition, areal extent and density of aquatic plants (macrophytes and filamentous algae) in impoundments where their presence may violate water‐quality standards. 2. Multispectral satellite (IKONOS) images and more than 500 in situ hyperspectral samples were acquired to map aquatic plant distributions. By analyzing field measurements, we created a library of hyperspectral signatures for a variety of aquatic plant species, associations and densities. We also used three vegetation indices. Normalized Difference Vegetation Index (NDVI), near‐infrared (NIR)‐Green Angle Index (NGAI) and normalized water absorption depth (D_H)_, at wavelengths 554, 680, 820 and 977 nm to differentiate among aquatic plant species composition, areal density and thickness in cases where hyperspectral analysis yielded potentially ambiguous interpretations. 3. We compared the NDVI derived from IKONOS imagery with the in situ, hyperspectral‐derived NDVI. The IKONOS‐based images were also compared to data obtained through routine visual observations. Our results confirmed that aquatic species composition alters spectral signatures and affects the accuracy of remote sensing of aquatic plant density. The results also demonstrated that the NGAI has apparent advantages in estimating density over the NDVI and the D_H. 4. In the feature space of the three indices, 3D scatter plot analysis revealed that hyperspectral data can differentiate several aquatic plant associations. High‐resolution multispectral imagery provided useful information to distinguish among biophysical aquatic plant characteristics. Classification analysis indicated that using satellite imagery to assess Lemna coverage yielded an overall agreement of 79% with visual observations and >90% agreement for the densest aquatic plant coverages. 5. Interpretation of biophysical parameters derived from high‐resolution satellite or airborne imagery should prove to be a valuable approach for assessing the effectiveness of management practices for controlling aquatic plant growth in inland waters, as well as for routine monitoring of aquatic plants in lakes and suitable lentic environments.     

施氮时期对高产夏玉米氮代谢关键酶活性及抗氧化特性的影响

选用玉米品种登海661和郑单958为材料,研究了高产条件下施氮时期对夏玉米产量、氮素利用率、氮代谢相关酶及抗氧化酶活性的影响.结果表明： 拔节期一次性施氮不利于夏玉米产量提高和氮素积累,分次施氮且增施花粒肥显著提高了植株和籽粒的吸氮量,并提高了籽粒产量.拔节期、10叶期、花后10 d按2∶4∶4施氮,登海661产量最高可达14123.0 kg·hm^-2;基肥、拔节期、10叶期、花后10 d按1∶2∶5∶2施氮,郑单958产量最高可达14517.1 kg·hm^-2,这2种施氮方式较拔节期一次性施氮分别增产14.5%和17.5%.花前分次施氮可以显著提高开花期硝酸还原酶活性;登海661和郑单958在花后0~42 d中,施氮处理的谷氨酰胺合成酶、谷氨酸合成酶、谷氨酸脱氢酶活性分别平均提高了32.6%、47.1%、50.4%和145%、61.8%、25.6%,减缓了其下降趋势;超氧化物歧化酶、过氧化氢酶活性提高了22.0%、36.6%和13.4%、62.0%,丙二醛含量显著降低.在高产条件下,分次施氮且适当增加花粒肥施入比例可以提高氮代谢相关酶活性,延缓植株衰老,促进氮素吸收利用,进而提高籽粒产量.     

基于遥感的草原退化人为因素影响趋势分析

干旱、半干旱地区草原退化是我国重要的生态和经济问题,其通常是自然与人为因素综合影响的结果。而区分这两者的影响,无疑对草原退化的恢复重建工作具有重要的意义。该文在基于前人的工作基础上,发展了一种分时段的回归分析和残差分析相结合的方法来评价人为因素在草地退化区域中的影响趋势。具体而言,以内蒙古自治区锡林郭勒草原为例,利用1983~1999年8 km空间分辨率的逐旬NOAA/AVHRR NDVI数据及同期气象数据为基础数据源,对每个像元建立1983~1988年的气候因子(考虑温度、降水,及其时滞效应)与NDVI的回归关系模型,并逐年分析1989~1999年回归关系模型的预测NDVI值与实际NDVI的残差及变化趋势,从而判断以1983~1988年为基准各像元受人为因素影响的趋势。结果表明,除东乌珠穆沁旗以外,锡林郭勒草原的各旗(市)20世纪90年代都出现了较为严重的人类活动影响加剧的草原退化,但退化的严重程度不一,呈现出东部和中部较轻、西部较重的空间格局,整个研究区域已达到中等退化程度。该结果与锡林郭勒草原退化的现状基本相吻合。     

Biological-based and remote sensing techniques to link vegetative and reproductive development and assess pollen emission in Mediterranean grasses

Connecting the signals of the vegetative and reproductive cycles of plants using large-scale phenological techniques is not always an easy task, and this complexity increases considerably when analysing the plant life cycle in grasses, due to the ubiquity and diversity of this taxonomic family. This work integrates remote sensing techniques (NDVI from satellite remote sensing data and greenness from near-surface imagery) and biological-based techniques (airborne pollen monitoring and field observations and sampling) to analyse phenological patterns and productivity in grass-dominated vegetation types. We aim to answer two main applied and unanswered questions; i) how are the specific phases of vegetative and reproductive cycles in grasses linked at the species and plant community level? and ii) which grass-dominant habitats are the major contributors of grass pollen emission to the atmosphere at the plant community level? The multi-scale integration and validation of large-scale methods such as satellite remote sensing data and aerobiological monitoring using high-resolution or field phenological techniques is recommended. The results clearly support the hypothesis that the highest rates of grass pollen emission are successively produced when the major grass-dominated vegetation types go through the final phases of vegetative development during their biological senescence or equivalent phases. At the plant community level, natural and semi-natural grass-dominated vegetation types, rather than grass cropland habitats, constitute the major sources of pollen emission. The major contributors to the grass pollen emission at the species level are also identified. Finally, a positive relationship between year-to-year primary productivity (measured as annual sum or maximum NDVI) and pollen production (measured as airborne pollen intensity) was observed at the community level. This is a very timely study, as the availability of remote sensing data is increasing interest in generating enhanced forecasting model of allergenic airborne pollen.     

Applying remote sensing techniques to monitor shifting wetland vegetation: A case study of Danshui River estuary mangrove communities,Taiwan

The purpose of this study is to apply different remote sensing techniques to monitor shifting mangrove vegetation in the Danshui River estuary in Taipei, Taiwan, in order to evaluate a long-term wetland conservation strategy compromising between comprehensive wetland ecosystem management and urban development. In the Danshui estuary, mangrove dominated by Kandelia candel is the major vegetation, and a large area of marsh with freshwater grasses has been protected in three reserves along the river shore. This study applied satellite imagery from different remote sensors of various resolutions for spectral analysis in order to compare shifting wetland vegetation communities at different times. A two-stage analytical process was used for extracting vegetation area and types. In the first-stage, a normalized difference vegetation index (NDVI) was adopted to analyze SPOT, Landsat, and QuickBird imagery to obtain the spatial distribution of vegetation covers. In the second stage, a maximum likelihood classification (MLC) program was used to classify mangrove and non-mangrove areas. The results indicated that the spatial distribution of mangroves expanded 15.18 and 40 ha in two monitoring sites in 10 years, demonstrating the success of establishing reserves for protecting mangrove habitats. The analytical results also indicated that satellite imagery can easily discern the difference in characteristics between imagery of mangrove and other vegetation types, and that the logistical disadvantages of monitoring long-term vegetation community changes as well as evaluating an inaccessible area may be overcome by applying remote sensing techniques.     

基于植被遥感的西南喀斯特退耕还林工程效果评价——以贵州省毕节地区为例

中国西南喀斯特地区生态环境脆弱,人口压力和不合理的土地利用方式使得土地退化问题严峻。2000年以来,国家开始在该地区推行退耕还林等一系列生态工程。需要评估这些工程的效果,以期为进一步的生态建设工程决策提供科学依据。本文以贵州省毕节地区为例,利用SPOT-VGT NDVI遥感数据,以大规模开展退耕还林工程前的1998—2001年为基准,建立NDVI-气候响应模型,在此基础上结合残差法来分析2002—2008年以退耕工程为主的人为因素在当地生态恢复中的作用。结果表明,近年来开展的生态工程使得整个毕节地区植被条件得到了明显的改善,但在东部大方、黔西一些区域土地退化的趋势仍未扭转,需要今后进一步的政策引导和开展后续生态工程。     

Traditional shifting agriculture: tracking forest carbon stock and biodiversity through time in western Panama

Reducing emissions from deforestation and forest degradation (REDD+) requires developing countries to quantify greenhouse gas emissions and removals from forests in a manner that is robust, transparent, and as accurate as possible. Although shifting cultivation is a dominant practice in several developing countries, there is still very limited information available on how to monitor this land‐use practice for REDD+ as little is known about the areas of shifting cultivation or the net carbon balance. In this study, we propose and test a methodology to monitor the effect of the shifting cultivation on above‐ground carbon stocks. We combine multiyear remote sensing information, taken from a 12‐year period, with an in‐depth community forest carbon stock inventory in Palo Seco Forest Reserve, western Panama. Using remote sensing, we were able to separate four forest classes expressing different forest‐use intensity and time‐since‐intervention, which demonstrate expected trends in above‐ground carbon stocks. The addition of different interventions observed over time is shown to be a good predictor, with remote sensing variables explaining 64.2% of the variation in forest carbon stocks in cultivated landscapes. Multitemporal and multispectral medium‐resolution satellite imagery is shown to be adequate for tracking land‐use dynamics of the agriculture‐fallow cycle. The results also indicate that, over time, shifting cultivation has a transitory effect on forest carbon stocks in the study area. This is due to the rapid recovery of forest carbon stocks, which results in limited net emissions. Finally, community participation yielded important additional benefits to measuring carbon stocks, including transparency and the valorization of local knowledge for biodiversity monitoring. Our study provides important inputs regarding shifting cultivation, which should be taken into consideration when national forest monitoring systems are created, given the context of REDD+ safeguards.     

Comparing and Combining Landsat Satellite Imagery and Participatory Data to Assess Land-Use and Land-Cover Changes in a Coastal Village in Papua New Guinea

In regions lacking socio-economic data, pairing satellite imagery with participatory information is essential for accurate land-use/cover (LULC) change assessments. At the village scale in Papua New Guinea we compare swidden LULC classifications using remote sensing analyses alone and analyses that combine participatory information and remotely sensed data. These participatory remote sensing (PRS) methods include participatory land-use mapping, household surveys, and validation of image analysis in combination with remotely sensed data. The classifications of the swidden area made using only remote sensing analysis show swidden areas are, on average, two and a half times larger than land managers reported for 1999 and 2011. Classifications made using only remote sensing analysis are homogeneous and lack discrimination among swidden plots, fallow land, and non-swidden vegetation. The information derived from PRS methods allows us to amend the remote sensing analysis and as a result swidden areas are more similar to actual swidden area found when ground-truthing. We conclude that PRS methods are needed to understand swidden system LULC complexities.     

Linking vegetation heterogeneity and functional attributes of temperate grasslands through remote sensing

Question: How are plant communities of the Flooding Pampa grasslands spatially distributed? How do canopy dynamics of the different communities vary among seasons and years? Location: Buenos Aires province, Argentina. Methods: We characterized the distribution of communities through a supervised classification based on four Landsat 5TM images. We sampled species composition of 200 sites, with 130 of them corresponding to natural communities. Of the sampling areas 60% were used to classify, and the remaining areas to assess classification accuracy. We characterized the seasonal and interannual variability of canopy dynamics using NDVI (Normalized Difference Vegetation Index) data provided by MODIS /Terra images. Results: Overall accuracy of the classification was satisfactory. The resulting maps showed a landscape formed by a matrix of extended lowlands with small patches of mesophytic and humid mesophytic meadows. The October scene (near the peak of productivity) was particularly important in discriminating among communities. The seasonal pattern of NDVI differed among communities and years. Mesophytic meadows had the highest NDVI mean and the lowest interannual coefficient of variation, halophytic steppes had the lowest mean, and vegetated ponds were the most variable. Conclusions: These grasslands have a fine‐grained heterogeneity at the landscape scale. Each plant community has distinct seasonal and interannual canopy dynamics. These two features of grassland structure and functioning represent key information for rangeland management that may be obtained through a combination of minor field sampling and remote sensing.     

无人机遥感在生态学中的应用进展

无人机与遥感技术的结合,即无人机遥感。与传统的以卫星和有人机遥感相比,无人机遥感具有高时效、高时空分辨率、云下低空飞行、高机动性等优势,是传统卫星和有人机遥感手段所无法比拟的。这些优点使得无人机在生态学和保护生物学等领域获得迅速发展。首先对无人机遥感技术的发展历程、系统组成、分类与选型、应用优势等进行了介绍。在此基础上,对无人机在生态学中的应用案例进行了总结,内容涉及生境监测、植物物候调查、动物监测等方面。最后通过比较国内外相关领域的研究进展对无人机生态学存在的问题(技术门槛较高和法律法规不完善等)和潜在应用前景进行了探讨。