Habitat structure and neighbor linear features influence more carabid functional diversity in olive groves than the farming system

The effects of land-use management and environmental features at different scales on carabid beetle diversity and trait structure were assessed across olive groves in northeastern Portugal. We selected organic and integrated olive groves that were distinct in terms of specific management practices, local linear features and landscape configurations. Besides the management intensification levels, differences in carabid diversity and community traits were mainly due to local habitat and ecological linear structures at a finer spatial scale. Carabid community traits related to disturbance, namely traits of body size and species dispersal ability, responded to land-use intensity and particular olive grove features were influencing diversity patterns. Within the olive grove patches, larger and brachypterous species were associated to plots with more dense vegetation cover while macropterous and small-sized species were more associated to open areas. Also, larger carabid species benefitted from higher patch size heterogeneity within the landscape mosaics. Our findings indicate that the effects of farming system is contingent on the specific management practices, local and linear features present in agroecosystems such as olive groves. Particularly, the influence of local features on carabid diversity patterns and community traits linked to dispersal and movement may be crucial in maintaining pest control at a landscape scale.     

Exploring the effect of soil management intensity on taxonomic and functional diversity of ants in Mediterranean olive groves

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Implementation of a hierarchical global vegetation classification in ecosystem function models

Abstract. We propose an alternative approach for the currently used biogeographic global vegetation classifications. A hierarchical vegetation classification system is proposed for consistent and routine monitoring of global vegetation. Global vegetation is first defined into six classes based on plant canopy structure and dynamics observable by remote sensing from satellites. Additional biome variability is then represented through a remote sensing derived leaf area index map, and direct climate data sets driving an ecosystem model to compute and map net primary production and evapotranspiration. Simulation results from an ecosystem function model suggest that the six canopy structure-based classes are sufficient to represent global variability in these parameters, provided the spatio-temporal variations in Leaf Area Index and climate are characterized accurately. If a bioclimatically based classification is needed for other purposes, our six class approach can be expanded to a possible 21 classes using archived climatic zones. For example, tropical, subtropical, temperate and boreal labels are defined by absolute minimum temperature. Further separation in each class is possible through changes in water availability defined by precipitation and/or soils. The resulting vegetation classes correspond to many of the existing, conventional global vegetation schemes, yet retain the measure of actual vegetation possible because remote sensing first defines the six biome classes in our classification. Vegetation classifications are no longer an end product but a source of initializing data for global ecosystem function models. Remote sensing with biosphere models directly calculates the ecological functions previously inferred from vegetation classifications, but with higher spatial and temporal accuracy.     

Time course study of Bactrocera oleae (Diptera: Tephritidae) pupae predation in soil: the effect of landscape structure and soil condition

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USLE/RUSLE模型中植被覆盖管理因子的遥感定量估算研究进展

通用土壤流失方程（USLE）及其后续修正方程（RUSLE）是区域土壤侵蚀风险评估和水土保持规划的有效工具.植被覆盖管理因子作为USLE和RUSLE的重要参数之一,其合理估算对土壤侵蚀的准确预测尤为重要.基于野外实地调查和测量的传统估算法费时、费力且费用高,无法满足宏观尺度上植被覆盖管理因子的快速提取.近年来,遥感技术的发展为大尺度植被覆盖管理因子获取提供了丰富的数据和方法.本文基于国内外相关研究成果,综述了植被覆盖管理因子遥感定量估算方法的研究进展,评述了各类方法的优劣,以期为进一步开展大尺度植被覆盖管理因子的定量估算及拓展现有研究思路提供借鉴.     

Ecosystem functional units characterized by satellite observed phenology and productivity gradients: A case study for Europe

The present study demonstrates remote sensing derived phenological and productivity indicators of ecosystem functional dynamism. The indices were derived from SPOT VEGETATION NDVI data on 1 km spatial resolution across the pan-European continent using the Phenolo approach. The phenological and productivity indices explained 78% of the variance in the European ecosystem gradient measured by bio-climatic zones. Along this gradient climatic predictors could only explain 57% of the variance in the satellite metrics. Reclassification of the bio-climatic zones into phenology and productivity related ecosystem functional units (EFUs) selected five metrics related to the cyclic and permanent fraction of productivity, to the background, to the growing season start and the timing of the maximum NDVI value. Along the EFU gradient the climatic predictors explained over 90% of the variance of the remote sensing variables, 30% more than along the bio-climatic gradient. The EFUs showed strong correspondence to 14 land-cover types in Europe and the selected remote sensing metrics explained 86% of the variation in the land-cover classes. These results show that remote sensing derived parameters have tremendous potential for the quantification of ecosystem functional dynamism. Phenological and productivity metrics offer an indicator system for ecosystems that climatic indicators alone cannot manifest. Their potential to monitor the spatial pattern, status and inter-annual variability of ecosystems and vegetation cover can deliver reference status information for future assessments of the impacts of human or climate change induced ecosystem changes.     

Vegetation maps based on remote sensing are informative predictors of habitat selection of grassland birds across a wetness gradient

Vegetation is a major environmental factor influencing habitat selection in bird species. High resolution mapping of vegetation cover is essential to model the distribution of populations and improve the management of breeding habitats. However, the task is challenging for grassland birds because microhabitat variations relevant at the territory scale cannot be measured continuously over large areas to delineate areas of higher suitability. Remote sensing may help to circumvent this problem. We addressed this issue by using SPOT 5 imagery and phytosociological data. We mapped grassland vegetation in a floodplain using two methods. We (i) mapped the continuous Ellenberg index of moisture and (ii) identified 5 vegetation classes distributed across the wetness gradient. These two methods produced consistent output maps, but they also provided complementary results. Ellenberg index is a valuable proxy for soil moisture while the class approach provided more information about vegetation structure, and possibly trophic resources. In spite of the apparent uniformity of meadows, our data show that birds do not settle randomly along the moisture and vegetation gradients. Overall birds tend to avoid the driest vegetation classes, i.e. the highest grounds. Thus, vegetation maps based on remote sensing could be valuable tools to study habitat selection and niche partition in grassland bird communities. It is also a valuable tool for conservation and habitat management.     

Land use and biodiversity patterns of the herpetofauna: The role of olive groves

The intensification of agriculture has significant environmental consequences. This intensification entails the simplification and homogenisation of the landscape, which leads to strong negative impacts at ecosystem level, including declines in animal biodiversity. The purpose of this study was to assess the effect of different land uses on reptilian and amphibian biodiversity patterns at a regional scale by analysing a large database on the presence of amphibians and reptiles in Andalusia (southern Spain). GIS techniques and the Ecological-Niche Factor Analysis (ENFA) were applied in order to assess whether the habitat was suitable for each reptilian and amphibian species, when the land use variables were excluded. The incongruence between the potential and the observed species richness was then correlated with the main types of land use in Andalusia. Our results showed that irrigated and unirrigated olive groves were associated with a biodiversity deficit of amphibians and reptiles respectively, whereas natural forests and pastures, along with more heterogeneous crops areas, were more suitable. A clustering analysis showed that generalist species were related to olive groves whereas rare and specialist species were related to land uses related to natural vegetation. In summary, our results indicate that large areas covered by olives groves harbour less amphibian and reptilian diversity, thus suggesting that agro-environmental schemes should be carried to promote the species richness in these crops.     

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.     

基于不同光谱指数的植被物候期遥感监测差异

植被物候是陆地生态系统响应气候和环境变化的一项综合性指标.遥感光谱已经被广泛用于提取植被物候期,但遥感提取的物候期与站点观测差别很大,其物理意义尚不明确.本文选取中国东北部的一景MODIS数据(2000—2014年),分析了基于红波段和近红外波段的归一化差值植被指数(NDVI)和简单比植被指数(SR)提取的植被生长季起始期(SOS)和结束期(EOS)的差异.结果表明:两者的物候期存在显著差别,基于NDVI提取的SOS比SR提取的SOS平均早18.9 d,基于NDVI提取的EOS比SR提取的EOS平均晚19.0 d,NDVI得到的生长季长度更长.基于NDVI和SR提取的物候期的年际变化也存在显著差别,超过20%的像元SOS和EOS甚至表现出相反的年际变化趋势.上述差异与两种植被指数自身的季节曲线特征和抗噪性差异有关.NDVI与SR观测数据来源完全一致,仅数学表达形式不同,提取的物候期结果却存在显著差异.说明遥感监测的植被物候期高度依赖于植被指数的数学表达形式,如何建立可靠的植被物候期遥感提取方法仍需进一步研究.     

基于多源遥感数据的荒漠植被覆盖度估测

以塔里木河下游为靶区,根据地面调查和不同分辨率的多源遥感数据,逐级建立荒漠植被覆盖度遥感估测模型,并对不同模型、不同估测方法的估测精度进行比较.结果表明: 随着遥感数据空间分辨率的提高,植被覆盖度遥感估测模型精度增加;基于高分辨率、中高分辨率及中低分辨率遥感数据建立的植被覆盖度模型的估测精度分别为89.5%、87.0%和84.6%;遥感模型法的估测精度高于植被指数法.不同分辨率遥感数据估测荒漠植被覆盖度的精度变化规律,实现了荒漠植被覆盖度估测的高、中、低分辨率遥感数据参数及尺度的定量转换,可为研究区生态恢复遥感综合监测方案的制定和实施提供直接依据.     

利用遥感光谱法进行农田土壤水分遥感动态监测

自 1 997年 4月至 1 998年 1 0月 ,在甘肃省定西县进行了大面积 0～ 5 0 cm土层农田土壤水分按每 1 5 d本底资料实际观测 ,对此间收到的 5幅 TM与 7幅 NOAA卫片数据资料进行了加工处理 ,并对地面光谱资料也进行了观测。在光谱反演与光谱和土壤水分相关性分析基础上 ,利用遥感技术和地理信息系统 ,初步建立了典型试验区 ( 3× 3km2 )遥感信息与土壤含水量之间的遥感光谱相关监测模型 ,做出了观测区土壤水分含量分布图和得到了大面积农田土壤水分宏观动态监测结果 ,并同地面实测土壤水分进行了精度校正。研究结果表明 ,文中提出的“光学植被盖度”概念 ,对土壤水分遥感监测研究是有益的 ,利用遥感光谱法和数学统计方法求出了有关物理参数 ,初步建立了 TM与 NOAA光谱水分监测模型 ,其模型监测 0～2 0 cm土层含水量的精度达到 90 %以上 ,实际监测土壤水分精度达到 72 .3% ;在遥感监测 2 0～ 5 0 cm土层土壤含水量中 ,利用遥感模型监测土壤水分精度达到 80 %以上 ,实际遥感监测精度达到 60 %左右 ,其结果可有效指导干旱半干旱雨养农业区春耕时间和动态监测大面积土壤墒情 ,可为农业生产提供科学依据。另外 ,经地面大量观测表明 ,一般来说 ,当土壤含水量为田间最大持水量的 5 5 %～ 85 %时 ,从生长状况和经济     

中国陆地植被净初级生产力遥感估算

该文在综合分析已有光能利用率模型的基础上,构建了一个净初级生产力(NPP)遥感估算模型,该模型体现了3方面的特色:1)将植被覆盖分类引入模型,并考虑植被覆盖分类精度对NPP估算的影响,由它们共同决定不同植被覆盖类型的归一化植被指数(NDVI)最大值;2)根据误差最小的原则,利用中国的NPP实测数据,模拟出各植被类型的最大光能利用率,使之更符合中国的实际情况;3)根据区域蒸散模型来模拟水分胁迫因子,与土壤水分子模型相比,这在一定程度上对有关参数实行了简化,使其实际的可操作性得到加强。模拟结果表明,1989~1993年中国陆地植被NPP平均值为3.12 Pg C (1 Pg=10¹⁵ g),NPP模拟值与观测值比较接近,690个实测点的平均相对误差为4.5%;进一步与其它模型模拟结果以及前人研究结果的比较表明,该文所构建的NPP遥感估算模型具有一定的可靠性,说明在区域及全球尺度上,利用地理信息系统技术将遥感数据和各种观测数据集成在一起,并对NPP模型进行参数校正,基本上可以实现全球范围不同生态系统NPP的动态监测。     

Native Mediterranean plants as potential food sources for natural enemies of insect pests in olive groves

The diversity of native non-crop (weed) vegetation in agricultural landscapes can provide arthropod natural enemies with food sources and shelter, thus improving natural pest control and reducing dependence on chemical pesticides. Moreover, native plants to a region are uniquely positioned to provide cultural ecosystem services such as wild food and wild medicinal plants, as well as aesthetics values. The Mediterranean Basin is one of the world’s richest places in terms of plant diversity. Olive cultivation is the basic tree cultivation in the Mediterranean and dominates its rural landscape. The olive grove ecosystem, whose flora presents a notable resemblance to the flora of Mediterranean type ecosystems, is home to a myriad of species of insects, spiders and other arthropods. This includes over one hundred phytophagous species, plus an uncounted number of entomophagous that help to reduce phytophagous populations. Here we present data on flowering plant species from the ground cover of olive groves, store information on characteristics of plant species namely physiognomic type and flowering period, geographic information and some statistical values on olive groves study area and records in the flora of visitor arthropods and cultural ecosystem services. The data include information on 36 olive groves, 100 flora species (taxa), of which 86 native in Portugal, 5 endemic to Iberian Peninsula and 4 endemic to Portugal Continental, and present also a summary of the records of visitor arthropods in these flora (i.e. 2 classes, 6 orders and 12 families).     

复杂地形草地植被碳储量遥感估算研究进展

草地生态系统是我国最大的陆地生态系统,其植被碳储量的准确评估对维护国家生态安全和指导畜牧发展有重要作用。植被生物量和草地面积是草地植被碳储量估算的关键,随着遥感技术的发展,两者估算精度和效率显著提高,先后发展出多种草地生物量遥感估算模型和土地覆被产品,并已在平坦地区取的较好估算结果。然而,复杂地形区迥异于平地的几何形态和水热分布所产生的不均一的生态系统结构和功能,给草地生物量和草地面积的遥感估算带来诸多困难,影响对草地植被碳储量的准确判定。本文在回顾国内外草地植被碳储量遥感估算方法与所需关键参数的基础上,对遥感估算复杂地形草地植被碳储量过程中所面临“遥感影像地形效应的去除和尺度选择”、“植被指数与地形指标的选取”、“过程模型植被生长参数的率定”、“草地面积估算”以及“气象数据与复杂地形上微气候的匹配”等问题进行了总结并提出相应的解决思路,以期为草地植被碳储量遥感估算模型的合理构建以及估算精度的提高提供参考。     

An integrated use of aerobiological and phenological data to analyse flowering in olive groves

Aerobiological and phenological investigation has been linked to analyse the flowering phenomena of olive (Olea europaea L.), a tree of economic importance, in Umbria, central Italy.

Olive tree flowering was analysed by phenological observations in olive groves. Aerobiological monitoring was carried out with pollen traps that captured the pollen grains in the atmosphere by remote distances. This combined study of flowering was useful in overcoming the principal limit of phenological observations caused by their geographical narrowness.

Eleven phenological stations in Perugia province were used and periodic observations were carried out during the flowering season. Two aerobiological stations located near the cities of Perugia and Spoleto were utilized to trap olive pollen grains in the atmosphere.

Graphic and statistical analyses were used in order to study flowering dynamics, and to compare the methodological approaches.

The phenological areas, according to their characteristics, were divided in two clusters each one related to a different pollen monitoring station. Statistical analyses showed the presence of a three ‐ four‐day period during which pollen released in the groves is persistent in the narrowness and resulted in a high correlation with the pollen monitored by the pollen traps. On the other hand, the phenological data considered along with the daily pollen concentrations permit the pollen peaks to be attributed to particular olive areas or olive cultivars. This demonstrates that both methodologies can be used effectively as integrated research tools in this kind of study.     

Weed control and persistence of two oxyfluorfen formulations in olive groves under non tillage conditions

To obtain profitable yields in olive groves, residual preemergence herbicides are applied in October or November before the winter rains, and before the winter annual weeds germinate. Simazine, one of the herbicides most used for weed control in olive groves, has recently been banned. Oxyfluorfen is presented as a good alternative to simazine in olive fields. Experiments were carried out in 2002 and 2003 to evaluate the behaviour of two oxyfluorfen formulations, 2XL and G4F, at 480 g a.i. ha(-1) for three different soil management systems with three replications (1. bare soil; 2. bare soil and grassed buffer strips, chemically controlled and 3. bare soil and grassed buffer strips with controlled mowing; under non tillage conditions in all three cases). The most important species that survived 2XL and G4F treatments was Sagina apetala ARD. Oxyfluorfen residues were evaluated throughout 158 days after the applications. Three soil samples from each plot were collected, mixed and air dried. The herbicide extractions were made with methanol and the residues were analyzed by HPLC. We found no differences between the two formulations, but results showed that recoveries of oxyfluorfen were higher in plots with chemically controlled buffer grassed strips than in the other soil management types.