Improved methods for measuring forest landscape structure: LiDAR complements field-based habitat assessment

Conservation and monitoring of forest biodiversity requires reliable information about forest structure and composition at multiple spatial scales. However, detailed data about forest habitat characteristics across large areas are often incomplete due to difficulties associated with field sampling methods. To overcome this limitation we employed a nationally available light detection and ranging (LiDAR) remote sensing dataset to develop variables describing forest landscape structure across a large environmental gradient in Switzerland. Using a model species indicative of structurally rich mountain forests (hazel grouse Bonasa bonasia), we tested the potential of such variables to predict species occurrence and evaluated the additional benefit of LiDAR data when used in combination with traditional, sample plot-based field variables. We calibrated boosted regression trees (BRT) models for both variable sets separately and in combination, and compared the models’ accuracies. While both field-based and LiDAR models performed well, combining the two data sources improved the accuracy of the species’ habitat model. The variables retained from the two datasets held different types of information: field variables mostly quantified food resources and cover in the field and shrub layer, LiDAR variables characterized heterogeneity of vegetation structure which correlated with field variables describing the understory and ground vegetation. When combined with data on forest vegetation composition from field surveys, LiDAR provides valuable complementary information for encompassing species niches more comprehensively. Thus, LiDAR bridges the gap between precise, locally restricted field-data and coarse digital land cover information by reliably identifying habitat structure and quality across large areas.     

Quantitatively defining the conservation status of Natura 2000 forest habitats and improving management options for enhancing biodiversity

The main goal of Natura 2000 network is to guarantee the favourable conservation status of habitats and species ensuring European biodiversity. As a result, certain forest areas have been included in this network listed as 9230-Quercus pyrenaica habitat and 9340-Quercus ilex subsp. rotundifolia forest habitat. These areas were previously used for firewood extraction or livestock grazing and browsing. Nowadays these habitats are coppice forests with asexual regeneration, which is far from the desired conservation status. Traditional timber harvesting plans do not take account of the new objectives required for these Natura sites, which attempt to ensure biodiversity and recreational uses instead of simply focusing on timber production. This paper proposes a flexible methodology (applied to the study area “Dehesa Boyal” in ávila, Spain) for managing Natura 2000 forest sites by stands for sustainable forest management and the new requirements. The methodology has two phases. The first, “Division of the forest area into stands”, defines homogeneous patches of vegetation distinct in species composition, physiognomic structure and future management. The second, “Conservation status assessment of stands”, quantifies the conservation status of each previously classified stand considering a series of factors such as: functional health, restoration, floral richness and structure. A total value integrating the conservation status of stands is then calculated for the habitat. Both phases use Geographic Information System tools for managing information and visualizing results. The proposed methodology provides forest managers with a good knowledge of the territory and subsequently enables them to take appropriate conservation measures to maintain biodiversity.     

Habitat type richness associations with environmental variables: a case study in the Greek Natura 2000 aquatic ecosystems

We investigated the potential associations of habitat type richness patterns with a series of environmental variables in 61 protected aquatic ecosystems of the Greek Natura 2000 network. Habitat type classification followed the Natura 2000 classification scheme. Habitat type richness was measured as the number of different habitat types in an area. To overcome a potential area effect in quantifying habitat type richness, we applied the “moving window” technique. The environmental variables were selected to account for some of the major threats to biodiversity, such as fragmentation, habitat loss and climate change. We run GLMs to associate habitat type richness with different combinations of climatic, spatial and topographic variables. Habitat type richness seemed to significantly associate with climatic variables, more than spatial or topographic ones. In particular, for the climatic ones, the importance of precipitation surpassed that of temperature and especially the precipitation of the wettest and driest month had a limiting contribution to richness unlike average climate estimators. Moreover, the landscape’s latitude and longitude and fragmentation were significantly associated to richness. Our findings are in accordance to those observed in recent literature at lower (i.e. species) levels of ecological organization, fact showing that large-scale phenomena (such as climate change) can also be observed at the habitat type level, at least in our case. Thus, following the context of the Habitats Directive (92/43/EEC), that habitat types and not solely species of community interest should be protected and restored, this study serves as a first step towards investigating habitat type richness patterns.     

Environmental diagnosis: Integrating biodiversity conservation in management of Natura 2000 forest spaces

The conservation of biodiversity in Europe is defined by Directive 92/43/EEC – commonly known as the Habitats Directive – relating to the conservation of natural habitats and of wild flora and fauna. This Directive established the creation of an ecological network of European protected areas – the Natura 2000 network – , and also recognised the need to manage these areas to maintain their “favourable conservation status”.This paper proposes a methodology which enables the conservation of biodiversity to be integrated into the management of Natura 2000 forest spaces. The methodology comprises an “environmental diagnosis” in three phases. The first phase evaluates the current conservation status of habitats using the following criteria: vital functions; floristic richness; forest structure; area occupied by the habitat; and recovery capacity. The second phase assesses the fragility of the space to determine the degree of vulnerability of habitats. This involves evaluating the fire hazard, erosion hazard, and the fragility of the vegetation. The last phase combines the two previous ones to generate management areas (optimum, intermediate or unfavourable) and to prioritise management actions.This methodology was applied in a protected forest area in the Natura 2000 network, located in Avila (Spain). Different management areas were generated for biodiversity conservation, and each habitat was associated to one of them. Finally, actions were prioritised and designed to raise the habitats to a “favourable conservation status”.     

Characterization of diverse plant communities in Aspen Parkland rangeland using LiDAR data

Question: How effective is high-resolution airborne LiDAR technology for quantifying biophysical characteristics of multiple community types within diverse rangeland environments? Location: Native Aspen Parkland vegetation in central Alberta, Canada. Methods: Vegetation within 117 reference plots stratified across eight types, including forest, shrubland, upland grassland and lowland meadow communities, were assessed in 2001 for the height, cover and density of vegetation within various strata (herb, shrub and tree layers). Actual ground data were subsequently compared against modelled values for each community type and strata derived from the analysis of airborne LiDAR data obtained in 2000. Results: LiDAR data were effective for quantifying vegetation height, cover and density of the overstory within closed- and open Populus forest communities. However, LiDAR measurements typically underestimated the height and cover of shrublands, as well as most of the herbaceous communities. Analysis of LiDAR intensity data indicated reflectance generally decreased as LiDAR sampling points moved upwards from the ground to the vegetation canopy. Conclusions: While LiDAR technology is useful for characterizing deciduous forest properties, the quantification of understory vegetation characteristics, as well as those of individual shrublands and grasslands, was more limiting. Further refinements in analysis methods are necessary to increase the reliability of characterizing these communities.     

Effectiveness of a large reserve network in protecting freshwater biodiversity: a test for the Iberian Peninsula

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Modelling relationships between birds and vegetation structure using airborne LiDAR data: a review with case studies from agricultural and woodland environments

Airborne LiDAR (Light Detection and Ranging) is a remote sensing technology that offers the ability to collect high horizontal sampling densities of high vertical resolution vegetation height data, over larger spatial extents than could be obtained by field survey. The influence of vegetation structure on the bird is a key mechanism underlying bird–habitat models. However, manual survey of vegetation structure becomes prohibitive in terms of time and cost if sampling needs to be of sufficient density to incorporate fine-grained heterogeneity at a landscape extent. We show that LiDAR data can help bridge the gap between grain and extent in organism–habitat models. Two examples are provided of bird–habitat models that use structural habitat information derived from airborne LiDAR data. First, it is shown that data on crop and field boundary height can be derived from LiDAR data, and so have the potential to predict the distribution of breeding Sky Larks in a farmed landscape. Secondly, LiDAR-retrieved canopy height and structural data are used to predict the breeding success of Great Tits and Blue Tits in broad-leaved woodland. LiDAR thus offers great potential for parameterizing predictive bird–habitat association models. This could be enhanced by the combination of LiDAR data with multispectral remote sensing data, which enables a wider range of habitat information to be derived, including both structural and compositional characteristics.     

Climate change threatens European conservation areas

Europe has the world's most extensive network of conservation areas. Conservation areas are selected without taking into account the effects of climate change. How effectively would such areas conserve biodiversity under climate change? We assess the effectiveness of protected areas and the Natura 2000 network in conserving a large proportion of European plant and terrestrial vertebrate species under climate change. We found that by 2080, 58?±?2.6% of the species would lose suitable climate in protected areas, whereas losses affected 63?±?2.1% of the species of European concern occurring in Natura 2000 areas. Protected areas are expected to retain climatic suitability for species better than unprotected areas (P?相似文献   

Selection and application of spatial indicators for nature conservation at different institutional levels

As European integration increasingly affects pan-European nature conservation, indicators for the assessment of habitats are urgently needed to support ecosystem integrity monitoring as well as the target of halting biodiversity loss by 2010. The Natura 2000 network of protected sites with a strong focus on the protection of habitat types and strict monitoring obligations is now legally binding for all Member States. From a set of indicators that have been proposed for habitat monitoring by the SPIN project (Spatial Indicators for European Nature Conservation) we describe measures of landscape structure and soil function and their potential for the monitoring and management of protected areas and the surrounding landscape. In a case study from Austria, we show that structure-related indicators hold potential for the documentation of local-scale changes on a degraded raised bog Natura 2000 site. In a regional scale case study in northern Germany, we show how landscape metrics relate agricultural statistics, e.g. farm size and livestock density to landscape structure. In a third case study from Slovenia, we show how coarse-scale soil data can be disaggregated to finer scale by integrating topographic information and additional parameters for modelling, and production of soil-related habitat suitability maps. From these case studies we provide an overview of some of the critical issues affecting the selection and application of spatial indicators for nature conservation monitoring tasks. End users of spatial indicators work at different scales and in different biogeographical regions. The indicator selection and application demonstrated in our three case studies reveals the capability to contribute to a more quantitative evidence base for monitoring and management of biodiversity in Europe.     

西辽河流域植被NPP时空分布特征及其影响因素研究

为研究西辽河流域植被生长特征及受气候变化的影响,该文以2000年—2015年MOD17A3的年均植被净初级生产力(NPP)数据、植被类型数据、土壤类型数据以及气温、降水资料为基础,利用GIS和RS技术,分析了西辽河流域植被净初级生产力时空格局、演变特征及驱动因子。结果表明:(1)西辽河流域近16年来植被NPP总量呈波动增加的趋势,变化范围为156.89～260.90 g C·m^-2·a^-1,平均值为219.76 g C·m^-2·a^-1,空间分布呈“边缘高、中间低”的特征; 植被NPP变化斜率为-16.53～16.65,95.74%的区域NPP呈增加趋势。(2)不同植被类型的NPP总量大小排序为草原>栽培植被>阔叶林>灌丛>草甸>针叶林; 西辽河流域固碳的植被类型主要是草原、栽培植被以及阔叶林,固碳能力较强的为针叶林。(3)生长在棕壤、褐土和潮土的植被年均NPP较高,生长在栗钙土和风沙土的植被年均NPP较低。(4)16年间植被NPP增长主要受降雨影响。气候暖-湿化及生态建设工程的实施,促进了西辽河流域植被的生长。以上研究结果为后期流域生态环境治理提供了科学依据及数据支持。     

Elevational gradient and vegetation‐environmental relationships in the central Hyrcanian forests of northern Iran

Tertiary‐relict Hyrcanian (Caspian) forest along the shores of the southern Caspian Sea is a center of biodiversity. Still, there is little information on plant diversity patterns in this area. This study evaluated plant diversity, variation in life forms, and geographical distribution of the zonal vegetation types and their relationships with environmental variables, in the educational and experimental forest of Kheyrudkenar, an important protected area in the central Hyrcanian forest of northern Iran. For this purpose, 226 vegetation plots of 400 m² were laid out along two altitudinal transects from the lowlands (100 m a.s.l.) to the timberline (2000 m a.s.l.). Four vegetation types were identified using modified TWINSPAN, indirect and direct gradient analyses. Species‐related (species diversity indices, life form and phytogeographical elements) and environmental variables (climate, topographic and soil variables) were calculated and subjected to one‐way ANOVA among the vegetation types. Both constrained (CCA) and unconstrained (DCA) ordination analyses showed an almost identical variation of the floristic composition along their axes and demonstrated that there are two main gradients in the Hyrcanian forest. Elevation together with annual precipitation and mean annual temperature were the most important factors controlling the floristic composition in the area. Topographic features such as slope inclination and heat index were found to be important within an elevation zone/vegetation type. Soil physical and chemical properties were of secondary importance for the separation of the vegetation types. This knowledge will be useful for forest management and conservation practices in the Hyrcanian area with its distinct and unique flora and vegetation.     

甘肃子午岭天然次生林区三种植被类型中土壤蜘蛛群落的组成及多样性

2004年4—10月,在甘肃子午岭天然次生林区采用巴氏诱罐法采集土壤蜘蛛2164头,隶属于19科43种。研究表明辽东栎林(Quercusliaotungensis)、油松林(Pinustabulaeformis)和杨树林(Populusdavidiana)3种森林植被类型中土壤蜘蛛群落组成有明显的差异;不同生境蜘蛛群落的组成成分和多样性指数各异;从各生境中捕获的蜘蛛个体数量分析,皿蛛科、平腹蛛科和科狼蛛科的数量最多,优势类群的组成相似;各生境类型中蜘蛛功能集团的组成及多样性也有明显差异。同时,分析了影响蜘蛛群落组成和多样性的主要因子是生境的植被类型和生境异质性。     

Climate change,woodpeckers, and forests: Current trends and future modeling needs

The structure and composition of forest ecosystems are expected to shift with climate‐induced changes in precipitation, temperature, fire, carbon mitigation strategies, and biological disturbance. These factors are likely to have biodiversity implications. However, climate‐driven forest ecosystem models used to predict changes to forest structure and composition are not coupled to models used to predict changes to biodiversity. We proposed integrating woodpecker response (biodiversity indicator) with forest ecosystem models. Woodpeckers are a good indicator species of forest ecosystem dynamics, because they are ecologically constrained by landscape‐scale forest components, such as composition, structure, disturbance regimes, and management activities. In addition, they are correlated with forest avifauna community diversity. In this study, we explore integrating woodpecker and forest ecosystem climate models. We review climate–woodpecker models and compare the predicted responses to observed climate‐induced changes. We identify inconsistencies between observed and predicted responses, explore the modeling causes, and identify the models pertinent to integration that address the inconsistencies. We found that predictions in the short term are not in agreement with observed trends for 7 of 15 evaluated species. Because niche constraints associated with woodpeckers are a result of complex interactions between climate, vegetation, and disturbance, we hypothesize that the lack of adequate representation of these processes in the current broad‐scale climate–woodpecker models results in model–data mismatch. As a first step toward improvement, we suggest a conceptual model of climate–woodpecker–forest modeling for integration. The integration model provides climate‐driven forest ecosystem modeling with a measure of biodiversity while retaining the feedback between climate and vegetation in woodpecker climate change modeling.     

Effects of decadal experimental drought and climate extremes on vegetation growth in Mediterranean forests and shrublands

Increased drought combined with extreme episodes of heatwaves is triggering severe impacts on vegetation growth, particularly for plant communities in arid and semiarid ecosystems. Although there is an abundance of short‐term field drought experiments in natural ecosystems, remaining knowledge gaps limit the understanding and prediction of vegetation growth to ongoing and future climate scenarios. Here, we assessed the impacts of long‐term (1999–2016) experimental drought (ca. ?30% rainfall) on the vegetation growth of a Mediterranean high (H) and low (L)‐canopy forests and an early‐successional shrubland, as indicated by above‐ground biomass increment (ABI) and standing density, respectively. We found habitat context (impact of historical climate change, soil depth and successional status) of the study sites significantly affected the magnitude of climate impacts; there were synergistic effects of experimental drought and meteorological drought (Standardised Precipitation–Evapotranspiration Index, SPEI) as well as extreme dry years on vegetation growth. Long‐term experimental drought decreased the ABI for the two forest canopy types and the standing density for the shrubland. Water availabilities in winter–spring (SPEIs) were positively correlated with the ABI and standing density. Moreover, experimental drought decreased the vegetation growth in extreme dry years for the shrubland. We propose that future work not only study the vegetation dynamics with physiological, phenological and demographical changes in long‐term processes and across climate gradients, but also should explore the changes of multiple functions simultaneously (e.g. multifunctionality) under long‐term processes and extremes. This type of analysis of long‐term data is essential to understand and predict biodiversity loss, composition shifts, declines in ecosystem function and carbon budgets at temporal and spatial scales, to enable policy makers to design and implement strategies for the maintenance of sustainable ecosystem function under future climate change scenarios.     

Assessing long-term spatial changes of natural habitats using old maps and archival sources: a case study from Central Europe

Landscapes intensively farmed over a long time period represent a threat for natural habitats and high levels of biodiversity. Information on the historical land use and spatial changes of natural habitats can help to explain the causes of a number of contemporary phenomena, which are important for the development of effective conservation and ecosystem management. This case study from the Czech Republic shows that archival written sources describing landscape quality, including vegetation cover, allow the reclassification of old maps to the level of natural habitat categories (sensu Natura 2000), with the aim of analyzing historic changes in land cover. Significant natural habitat decreases began by the middle of the 19th century. Over the course of 250 years, this area of formerly widespread natural wet meadows has declined by 99 %. An area of water vegetation was reduced by 95 %, willow carrs by 98 %, and a mosaic of willow carrs, wet Cirsium meadow, and alder carrs has decreased by 100 %. These decreases were caused by the conversion of meadows, pastures, and ponds into arable lands. Areas of oak-hornbeam forest, acidophilous oak forest, and thermophilous oak forest were primarily converted into monocultures of coniferous trees. Similarly, the areas with alluvial forests decreased. We conclude that old maps and other archive materials, despite their coarse accuracy, can serve as useful tools for disclosing natural habitat changes and their causes, providing a foundation for formulating biodiversity conservation strategies.     

太行山南麓山区不同植被恢复类型土壤理化和细根结构特征

在干旱半干旱地区,由于水分匮乏、土壤贫瘠等因素,将形成一定的裸地斑块,而这些斑块极易造成水土流失、滑坡等灾害,而具有不同植被覆盖的林地则能有效的保持水土。为完善干旱半干旱地区不同植被恢复类型下土壤理化和细根特征,选择太行山南麓山区具有代表性的裸露地、草地、荆条地、侧柏地、栓皮地和刺槐地等植被恢复类型,比较了各植被恢复类型下的土壤养分、粒径及细根状况等差异。研究表明:1)相对于裸露地,有植被覆盖的植被恢复类型拥有良好的土壤及细根状况。2)在不同植被类型中,刺槐林的有效氮转化速率较高;侧柏林有较高的细根参数;草地能够提高土壤中可吸收的磷组分。3)林地类型和土层均对土壤中含水率、黏粒、细根生物量和比根长产生极显著影响(P0.001)。4)各植被类型的对于土壤斑块的利用能力不同;不同植被类型中土壤及细根状况变化量具有一定的相似性,研究为生态恢复中植被类型的合理布局提供了新思路。     

Range reshuffling: Climate change,invasive species,and the case of Nothofagus forests in Aotearoa New Zealand

Aim

The impact of climate change on forest biodiversity and ecosystem services will be partly determined by the relative fortunes of invasive and native forest trees under future conditions. Aotearoa New Zealand has high conservation value native forests and one of the world's worst invasive tree problems. We assess the relative effects of habitat redistribution on native Nothofagus and invasive conifer (Pinaceae) species in New Zealand as a case study on the compounding impacts of climate change and tree invasions.

Location

Aotearoa New Zealand.

Methods

We use species distribution models (SDMs) to predict the current and future distribution of habitat for five native Nothofagus species and 13 invasive conifer species under two 2070 climate scenarios. We calculate habitat loss/gain for all species and examine overlap between the invasive and native species now and in future.

Results

Most species will lose habitat overall. The native species saw large changes in the distribution of habitat with extensive losses in North Island and gains mostly in South Island. Concerningly, we found that most new habitat for Nothofagus was also suitable for at least one invasive species. However, there were refugia for the native species in the wetter parts of the climate space.

Main Conclusion

If the predicted changes in habitat distribution translate to shifts in forest distribution, it would cause widespread ecological disruption. We discuss how acclimation, adaptation and biotic interactions may prevent/delay some changes. But we also highlight that the poor establishment capacity of Nothofagus, and the contrasting ability of the conifers to invade, will present persistent conservation challenges in areas of both new habitat and forest retreat. Pinaceae are problematic invaders globally, and our results highlight that control of invasions and active native forest restoration will likely be key to managing forest biodiversity under future climates.     

High-elevation rock outcrop vegetation of the Southern Appalachian Mountains

Abstract. Species composition patterns and vegetation-environment relationships were quantified for high-elevation rock outcrops of the Southern Appalachian Mountains, an infrequent and insular habitat in a forested landscape. Outcrops occur over a wide geographic range encompassing extensive variation in both geology and climate. Geographic-scale factors interact with site-scale factors to produce variation in vegetation among outcrops. Similarly, site-scale factors interact with micro-scale factors to produce variation in vegetation within outcrops. To provide a quantitatively-based classification of outcrop vegetation we used a TWINSPAN analysis of 154 100-m² plots. We recognized nine communities that primarily correspond to different combinations of elevation, bedrock type, geography, and moisture. Within outcrops of a single bedrock type, vegetation composition of 100-m² plots was consistently correlated with elevation and solar radiation, but relationships to soil nutrients varied with bedrock type. Both site-scale (100 m²) factors (e.g. elevation, slope, aspect, and bedrock type) and plot-scale (1-m²) microsite factors (e.g. soil depth, vegetation height, soil nutrients) were strongly correlated with species composition at the 1-m² level. Environment can be used to predict composition more effectively for 100-m² plots on a single bedrock type than either across bedrock types or at a 1-m² scale. Composition-environment relationships resemble those described for outcrop systems from other regions with pronounced topographic relief more than they do those described for the nearby but flatter and lower-elevation outcrops of the Southeastern Piedmont. There is strong spatial autocorrelation in this community, perhaps owing to dispersal limitation. Consequently, a comprehensive conservation strategy must include reservation of both a range of geologic types and a range of geographic locations.     

Empirical realised niche models for British higher and lower plants – development and preliminary testing

Question: Can useful realised niche models be constructed for British plant species using climate, canopy height and mean Ellenberg indices as explanatory variables? Location: Great Britain. Methods: Generalised linear models were constructed using occurrence data covering all major natural and semi‐natural vegetation types (n=40 683 quadrat samples). Paired species and soil records were only available for 4% of the training data (n=1033) so modelling was carried out in two stages. First, multiple regression was used to express mean Ellenberg values for moisture, pH and fertility, in terms of direct soil measurements. Next, species presence/absence was modelled using mean indicator scores, cover‐weighted canopy height, three climate variables and interactions between these factors, but correcting for the presence of each target species in training plots to avoid circularity. Results: Eight hundred and three higher plants and 327 bryophytes were modelled. Thirteen per cent of the niche models for higher plants were tested against an independent survey dataset not used to build the models. Models performed better when predictions were based only on indices derived from the species composition of each plot rather than measured soil variables. This reflects the high variation in vegetation indices that was not explained by the measured soil variables. Conclusions: The models should be used to estimate expected habitat suitability rather than to predict species presence. Least uncertainty also attaches to their use as risk assessment and monitoring tools on nature reserves because they can be solved using mean environmental indicators calculated from the existing species composition, with or without climate data.     

激光雷达技术在动物生态学领域的研究进展

激光雷达(light detection and ranging, LiDAR)作为一门新兴的主动遥感技术, 近年来由于在提取和反演森林参数水平上不断提高, 被越来越多地应用于动物生态学研究中。本文通过整理和搜集国内外文献, 对激光雷达的技术特点及其在森林参数提取和动物生境上的研究进展进行综述, 指出当前基于LiDAR的森林参数反演算法主要服务于森林资源调查或林学研究, 缺少对动物生态或生理意义相关的参数量化信息。目前该技术在国内的动物生态学方面的应用较少, 尚未见文章发表。通过总结国外学者的研究, 分别从动物生境选择与三维森林结构的关系、栖息地立体生境制图、生物多样性评估和物种分布模型预测三个方面综述了LiDAR在动物生态学研究中的应用现状。相比传统方法, LiDAR技术提供的高精度三维结构信息, 能够显著提高动物生境质量的评估、生物多样性的监测水平和物种分布模型的评价精度, 有利于从机理上加深对物种生境选择和集群过程的理解。但目前LiDAR技术的应用主要集中在对已知的生态关系研究, 尤其是冠层结构与动物分布的关系, 缺少对林下层生活的动物生境质量和生物多样性的监测和评估, 同时很多有关动物生存和繁衍与立体生境的关系研究有待从LiDAR数据中进一步挖掘分析。未来应加强对森林林下层三维信息的提取, 提高林下层动物生境质量和生物多样性的监测水平, 同时建立适用于动物生态和生理意义相关的参数, 为动物生境质量和生物多样性的评估提供标准的量化指标。