What multiscale environmental drivers can best be discriminated from a habitat index derived from a remotely sensed vegetation time series?

Understanding which environmental conditions are critical for species survival is a critical, ongoing question in ecology. These conditions can range from climate, at the broadest scale, through to elevation and other local landscape conditions, to fine scale landscape patterns of land cover and use. Remote sensing is an ideal technology to monitor and assess changes in these environmental conditions at a variety of spatial and temporal scales, with many studies focusing on the physiological state of vegetation derived from time series of satellite measurements. As vegetation occurs within specific climatic zones, over certain soil, terrain, and land cover types, it can be difficult to decipher the influence of the underlying role of climate, topography, soil, and land cover on the observed vegetation signal. In this article, we specifically addressed this problem by asking the question: what is the relative impact and importance of these different scales of environmental drivers on the temporal and spatial patterns observed on a habitat index derived from remotely sensed data? To find the solution, we utilized a SPOT VEGETATION-normalized difference vegetation index time series of Europe to create a remote-sensing-derived habitat index, which incorporates aspects of productivity, seasonality, and cover. We then compared the observed temporal and spatial variations in the index to a pan-Europe terrestrial classification system, which explicitly incorporates variations in climate, terrain, soil parent material, land cover, and use. Results indicated that the most accurate level of discrimination from the habitat index was at the broadest level of the hierarchy, climate, while the poorest degree of discrimination was associated with elevation. In terms of similarity on the index across time and space, we found that arable and forest cover classes were more similar across elevation and parent materials than across other land cover types within them. Analyzing the remote-sensing index, at multiple scales, provides significant insights into the drivers of satellite-derived greenness indices, as well as highlights the benefit and cautions associated with linking satellite-derived indirect indicators to species distribution modeling and biodiversity.     

阜平县北流河流域林地多功能评价及分区研究

由于人类对土地功能的认识单一,造成乡村地区土地利用不充分,导致土地资源的闲置与浪费。而土地单一功能利用模式转变的关键是探究土地多功能的利用。以北流河流域林地为研究区对象,从气候、土壤、地质、地形、植被要素进行综合分析,对林地土地的生产功能、生态功能、景观功能和材料功能进行空间定量化,运用热点分析和地理探测器评价北流河流域林地多功能性及影响因素;并通过K均值聚类分析划分林地土地多功能利用类型区。结果表明：(1)流域内林地多功能热点区域呈集聚分布,冷点区域呈带状分布在北流河流域的山麓。(2)北流河流域林地多功能空间分异的驱动力主要以植被因素为主,其中郁闭度、蓄积量、碳汇为主导因子,植被盖度对林地土地多功能空间分异的影响较小,应加强北流河流域内的植被保护和严禁过度开发林地;交互作用明显,交互作用均为双因子增强或非线性增强,气候、土壤、植被、地形、地质条件共同制约着北流河流域林地多功能水平。(3)通过伪F统计将北流河流域林地划分为3个主导区和1个提升区,分别为生产功能主导区、生态功能主导区、景观功能主导区以及综合功能提升区,其中生态功能主导区面积最大;并针对主导功能提出相应的利用方向。     

Riparian plant composition in an urbanizing landscape in southern California,U.S.A.

In coastal southern California, natural riparian corridors occur in a landscape mosaic comprised of human land uses (mainly urban and suburban development) interspersed among undeveloped areas, primarily native shrublands. We asked, does the composition of the landscape surrounding a riparian survey point influence plant species distribution, community composition, or habitat structure? We expected, for example, that invasive non-native species might be more abundant as the amount of surrounding urbanization increased. We surveyed 137 points in riparian vegetation in Orange County, California, along an urbanization gradient. Using logistic regression we analyzed 79 individual plant species’ distributions, finding 20 negatively associated and 12 positively associated with the amount of development within a 1-km radius around the survey points, even after accounting for the effects of elevation. However, after summarizing plant community composition with Detrended Correspondence Analysis we observed that, overall, community composition was not statistically correlated with the amount of development surrounding a survey point once the association between development and elevation was taken into account. Non-native species were not particularly associated with increasing development, but instead were distributed throughout vegetation and urbanization gradients. However, the extent of the tree and herb layers (structural attributes) was associated with development, with the tree layer increasing and the herb layer decreasing as urbanization increased. Thus, although the degree of surrounding urbanization appears to influence the distribution of a number of individual plant species, overall composition of the community in our study system seemed relatively unaffected. Instead, we suggest that community composition reflected larger-scale environmental conditions, such as stream order and other variables associated with elevation, and/or regional-scale disturbances, such as historic grazing or enhanced atmospheric deposition of nitrogen.     

城郊观光型葡萄园营建及效益估算

针对城郊型观光葡萄园的特点,从品种选择、果园模式、架式和效益估算几方面,对城郊观光型葡萄园进行研究分析.指出了葡萄早实、丰产、高效及其树种优势和产业特点,非常适于城郊观光园型果树种植,城郊观光型葡萄园建设也为城郊农业生产结构调整提供一个新思路.     

Topography-mediated controls on local vegetation phenology estimated from MODIS vegetation index

Forest canopy phenology is an important constraint on annual water and carbon budgets, and responds to regional interannual climate variation. In steep terrain, there are complex spatial variations in phenology due to topographic influences on microclimate, community composition, and available soil moisture. In this study, we investigate spatial patterns of phenology in humid temperate forest as a function of topography. Moderate-resolution imaging spectro-radiometer (MODIS) vegetation indices are used to derive local patterns of topography-mediated vegetation phenology using a simple post-processing analysis and a non-linear model fitting. Elevation has the most explanatory power for all phenological variables with a strong linear relationship with mid-day of greenup period, following temperatures lapse rates. However, all other phenological variables show quadratic associations with elevation, reflecting an interaction between topoclimatic patterns of temperature and water availability. Radiation proxies also have significant explanatory power for all phenological variables. Though hillslope position cannot be adequately resolved at the MODIS spatial resolution (250 m) to discern impacts of local drainage conditions, extended periods of greenup/senescence are found to occur in wet years. These findings are strongly supported by previous field measurements at different topographic positions within the study area. The capability of detecting topography-mediated local phenology offers the potential to detect vegetation responses to climate change in mountainous terrain. In addition, the large, local variability of meteorological and edaphic conditions in steep terrain provides a unique opportunity to develop an understanding of canopy response to the interaction of climate and landscape conditions.     

Predicting Southern Appalachian overstory vegetation with digital terrain data

Vegetation in mountainous regions responds to small-scale variation in terrain, largely due to effects on both temperature and soil moisture. However there are few studies of quantitative, terrain-based methods for predicting vegetation composition. This study investigated relationships between forest composition, elevation, and a derived index of terrain shape, and evaluates methods for predicting forest composition. Trees were measured on 406 permanent plots within the boundaries of the Coweeta Hydrologic Lab, located in the Southern Appalachian Mountains of western North Carolina, USA. All plots were in control watersheds, without human or major natural disturbance since 1923. Plots were 0.08 ha and arrayed on transects, with approximately 380 meters between parallel transects. Breast-height diameters were measured on all trees. Elevation and terrain shape (cove, ridge, sideslope) were estimated for each plot. Density (trees/ha) and basal area were summarized by species and by forest type (cove, xeric oak-pine, northern hardwoods, and mixed deciduous). Plot data were combined with a digital elevation data (DEM), and a derived index of terrain shape at two sampling resolutions: 30 m (US Geological Survey), and 80 m (Defense Mapping Agency) sources. Vegetation maps were produced using each of four different methods: 1) linear regression with and without log transformations against elevation and terrain variables combined with cartographic overlay, 2) kriging, 3) co-kriging, and 4) a mosaic diagram. Predicted vegetation was compared to known vegetation at each of 77 independent, withheld data points, and an error matrix was determined for each mapping method.We observed strong relationships between some species and elevation and/or terrain shape. Cove and xeric oak/pine species basal areas were positively and negatively related to concave landscape locations, respectively, while species typically found in the mixed deciduous and northern hardwood types were not. Most northern hardwood species occurred more frequently and at higher basal areas as elevation increased, while most other species did not respond to elevation. The regression and mosaic diagram mapping approaches had significantly higher mapping accuracies than kriging and co-kriging. There were significant effects of DEM resolution on map accuracy, with maps based on 30 m DEM data significantly more accurate than those based on 80 m data. Taken together, these results indicate that both the mapping method and terrain data resolution significantly affect the resultant vegetation maps, even when using relatively high resolution data. Landscape or regional models based on 100 m or lower resolution terrain data may significantly under-represent terrain-related variation in vegetation composition.     

基于SOFM模型的山区土地类型划分研究——以阜平县为例

山区土地与平原土地在地形地貌等自然要素上存在明显差异,从而导致山区土地类型的划分有很大的特殊性。为了充分体现山区县域尺度自然要素差异,为山区县域尺度土地类型划分提供新方法、新思路,选取太行山典型地区阜平县作为研究区,选取气候、地形、土壤、植被因素,通过SOFM模型及传统土地类型划分方法,对山区县域尺度土地类型进行划分。结果表明：(1)将SOFM模型(自组织特征映射)与传统的土地类型划分方法相结合,对阜平县土地类型进行了三级划分,其中一级类7个,二级类47个,三级类81个;(2)通过对比验证,该方法与传统分类方法存在一致性。基于SOFM模型的土地类型划分方法对山区县域尺度进行土地类型划分,可充分反映山区县域尺度土地分异规律,比传统方法相更加精确。     

Acreage and production estimation of mango orchards using Indian Remote Sensing (IRS) satellite data

In order to exploit the potential of remote sensing in the field of horticulture, a study was initiated to estimate acreage and production of mango orchards using Indian Remote Sensing (IRS) satellite data. The data from linear imaging self scanning (LISS) II of IRS 1B and IRS 1C LISS III data covering the study area have been used. The boundary mask as well as sample segment approaches were tried for acreage estimation. Available yield data and meteorological and growth parameter data were collected to develop an agro-meteorological model. The study has clearly demonstrated the usefulness of LISS II and LISS III data for identifying and estimating mango orchard acreage. It was observed that use of LISS III is better compared to LISS II as the spatial resolution has improved the classification using maximum likelihood algorithm. The study also indicated that the condition of orchards could also be assessed to some extent. Total enumeration technique using summer season data gave very accurate acreage estimates of mango. The sampling approach is also good for mango orchard acreage estimation which provided almost the same accuracy as total enumeration technique but by saving about 6–8 times the analysis time and cost. Due to non-availability of reliable data at different levels, it was difficult to develop any regional level single yield model. However, it was observed that an agro-meteorological data-based model could be developed by collecting such data for 3–4 years in selected orchards.     

Identifying structural self-similarity in mountainous landscapes

Digital elevation model data were used to partition a mountainous landscape (northwestern Montana, USA) into watershed/hillslope terrain units at several different spatial scales. Fractal analysis of the perimeter to area relationships of the resulting partition polygons identified statistical self-similarity across a range of spatial scales (approximately four orders of magnitude in partition area). The fractal dimension was higher for a relatively complex fluvially-dominated terrain than for a structurally simpler glacially-dominated terrain (1.23 vs. 1.02, respectively). The structural self-similarity exhibited by this landscape has direct implications in scaling up ecosystem process models for landscape to regional simulations.     

Analyzing a forest conversion history database to explore the spatial and temporal characteristics of land cover change in Guatemala's Maya Biosphere Reserve

We analyzed forest clearing and regrowth over a 23-year time period for 21 forest concession and management units within the Maya Biosphere Reserve(MBR), Guatemala. The study area as a whole experienced a clearing rate of0.16%/year from 1974 through 1997. The overall clearing rate appears rather low when averaged over the entire study area over 23 years because most of the reserve was inaccessible. However, despite the granting of legal protection to the MBR in 1990, clearing rates continued to rise, with the highest rates occurring in the most recent time period in the analysis, 1995 to1997. Higher rates of clearing relative to regrowth occurred in newly established communities and in the Reserve's buffer zone, where the clearing of high forest was preferred for pasture development. Exploratory models were built and analyzed to examine the effects of various landscape variables on forest clearing. The different units in the analysis showed different relationships of forest clearing with variables such as forest cover type and distance to access(roads and river corridors). Where available, socio-economic household survey data helped to explain patterns and trends observed in the time series Landsat imagery. A strong relationship between forest clearing and distance to access was demonstrated. More clearing occurred further from roads during later time periods as farmers moved deeper into the forest to find land to clear. Communities inside the MBR that were less dependent on farming had forest clearing to regrowth ratios of one:one or less. These communities used fallow fields in greater proportions than communities in the Reserve's buffer zone. General trends in clearing by forest cover type suggest a preference for clearing high forest (bosque alto) types found on the higher elevation, better-drained soils, and fallow fields,and an avoidance of low-lying, seasonally flooded terrain(bajos). Satellite remote sensing observations of forest clearing and regrowth patterns can provide an objective source of information to complement socio-economic studies of the human driving forces in land cover and land use change. This revised version was published online in July 2006 with corrections to the Cover Date.     

烟台地区果园面积变化及其相关因素分析

利用近20年烟台地区果园面积、农业生产总值和耕地面积的统计数据,分析研究了烟台地区果园面积变化的过程及引起变化的相关因素。结果表明:近20年来,烟台地区果园面积总体呈增长趋势;1986~2009年,烟台水果的产量和质量大幅提高;烟台地区果园面积变化的相关因素是:农业生产总值、比较效益、相关政策。     

Agricultural expansion: land use shell game in the U.S. Northern Plains

Land area planted to row crops has expanded globally with increased demand for food and biofuels. Agricultural expansion in the Dakota Prairie Pothole Region (DPPR), USA affects a variety of agricultural and non-agricultural land-use types, including grasslands and wetlands that provide critical wildlife habitat and other ecosystem services. The purpose of this study was to quantify recent changes in rural land cover/land use, analyze trends, and interpret results in relation to climate, agronomic practice, and ethanol production. The primary data sources were 1980–2012 statewide cropland data from the U.S. Department of Agriculture (USDA) National Agricultural Statistics Service, and the USDA Cropland Data Layer, produced annually for the DPPR from 2006 through 2012. Area planted to corn or soybean row crops increased, and small grain (e.g., wheat, barley) area decreased significantly over the analysis period. Corn and soybean expanded by 27 % in the DPPR between 2010 and 2012 alone, an areal increase (+15,400 km²) larger than the U.S. state of Connecticut. This expansion displaced primarily small grains and grassland (e.g., pastures, haylands, remnant prairies). Grassland regularly exchanged land with corn and soybean, small grains, and wetlands and water. Corn and soybean had high inter-annual self-replacement values (68–80 %), and continuous corn/soy row cropping was the second most common combination over a three-year period, ranking after continuous grassland. Small grain self-replacement values were only 22–35 %, indicating frequent relocation in the landscape. Temporary gains in wetland and grassland area were attributed to unusually wet climatic conditions and late snowfalls that prevented crop planting. Nearly all of the region’s ethanol refineries were located where corn and soybean crops constituted 50 % or more of the land area. Quantification of grassland losses in the U.S. Northern Plains requires evaluation of all land uses that interact with grasslands, and a longer term perspective that incorporates grassland as part of a normal land-use rotation.     

Assessing the utility of topographic variables in predicting structural complexity of tree stands in a reforested urban landscape

The transformation of natural landscapes into impervious built-up surfaces through urbanization is known to significantly interfere with the ecological integrity of urban landscapes and accelerate climate change and associated impacts. Although urban reforestation is widely recognised as an ideal mitigation practice against these impacts, it often has to compete with other lucrative land uses within an urban area. The often limited urban space provided for reforestation therefore necessitates the optimization of the ecological benefits, which demands spatially explicit information. The recent proliferation of tree stands structural complexity (SSC) and topographic data offer great potential for determining the ecological performance of reforested areas across an urban landscape. This study explores the potential of using topographic datasets to predict SSC in a reforested urban landscape and ranks the value of these topographic variables in determining SSC. Tree structural data from a reforested urban area was collected and fed into a tree stand structural complexity index, which was used to indicate ecological performance. Topographic variables (Topographic Wetness Index, slope, Area Solar Radiation and elevation)- were derived from a Digital Elevation Model (DEM) and used to predict SSC using the Partial Least Squares (PLS) regression technique. Results show that SSC varied significantly between the topographic variables. Results also show that the topographic variables could be used to reliably predict SSC. As expected, the Topographic Wetness Index and slope were the most important topographic determinants of SSC while elevation was the least valuable. These results provide valuable spatially explicit information about the ecological performance of the reforested areas within an urban landscape. Specifically, the study demonstrates the value of topographic data as aids to urban reforestation planning.     

Spatial impacts of multimodal accessibility to green spaces on housing price in Cook County,Illinois

This study explores the impacts of multimodal accessibility to green space on housing price. Quantifying the benefits of green space accessibility is important for supporting green infrastructure planning and guiding land use development. In this study, we calculate multimodal travel times (walking and driving) from each residential property in Cook County (Chicago metro), Illinois to each articulated (public or significant private) green space. A gravity-model based method is used to compute accessibility (by travel mode), which considers the access to multiple green spaces and weights prioritization. Green spaces are divided into seven categories depending on their type and size to differentiate their potential benefits. Hedonic models using housing structural features, locational attributes, socio-economic factors and green space accessibility as explanatory variables, are used to evaluate housing price (using housing transactions records from 2010 sales in the county). The spatial effects of green space accessibilities on housing prices are explored by an Ordinary Least Squares (OLS) regression, with and without fixed locational effects, and a Geographically Weighted Regression (GWR). Results show walking and driving accessibility to all sizes of recreational, medium conversational and private green spaces present positive impacts on housing price, with some negative impacts to larger (and smaller) conservation areas. The relationship also exhibits different heterogeneous spatial pattern over the study area between walking and driving accessibility to green space, possibly related to economic variation.     

Assessing the potential impacts of climate change on the alpine habitat suitability of Japanese stone pine (Pinus pumila)

To assess the potential distribution of Pinus pumila, a dominant species of the Japanese alpine zone, and areas of its habitats vulnerable to global warming, we predicted potential habitats under the current climate and two climate change scenarios (RCM20 and MIROC) for 2081–2100 using the classification tree (CT) model. The presence/absence records of P. pumila were extracted from the Phytosociological Relevé Database as response variables, and five climatic variables (warmth index, WI; minimum temperature for the coldest month, TMC; summer precipitation, PRS; maximum snow water equivalent, MSW; winter rainfall, WR) were used as predictor variables. Prediction accuracy of the CT evaluated by ROC analysis showed an AUC value of 0.97, being categorized as “excellent”. We designated Third Mesh cells with an occurrence probability of 0.01 or greater as potential habitats and further divided them into suitable and marginal habitats based on the optimum threshold probability value (0.06) in ROC analysis. Deviance weighted scores revealed that WI was the largest contributing factor followed by MSW. Changes in habitat types from the current climate to the two scenarios were depicted within an observed distribution (Hayashi’s distribution data). The area of suitable habitats under the current climate decreased to 25.0% and to 14.7% under the RCM20 and MIROC scenarios, respectively. Suitable habitats were predicted to remain on high mountains of two unconnected regions, central Honshu and Hokkaido, while they were predicted to vanish in Tohoku and southwestern Hokkaido. Thus P. pumila populations in these regions are vulnerable to climate change.     

Plant and animal diversity in a region of the Southern Alps: the role of environmental and spatial processes

Different organisms respond to landscape configuration and spatial structure in different terms and across different spatial scales. Here, regression models with variation partitioning were applied to determine relative influence of the three groups of variables (climate, land use and environmental heterogeneity) and spatial structure variables on plant, bird, orthopteran and butterfly species richness in a region of the Southern Alps, ranging in elevation from the sea level to 2,780 m. Grassland and forest cover were positively correlated with species richness in both taxonomic groups, whilst species richness decreased with increasing urban elements and arable land. The variation was mainly explained by the shared component between the three groups in plants and between landscape and environmental heterogeneity in birds. The variation was related to independent land use effect in insects. The distribution in species richness was spatially structured for plants, birds and orthopterans, whilst in butterflies, no spatial structure was detected. Plant richness was associated with linear trend variation and broad-scale spatial structure in the northern part of the region, whilst bird richness with broad-scale variation which occurs on the external Alpine ridge. Orthopteran diversity was strongly related to fine-scale spatial structure, generated by dynamic processes or by unmeasured spatially structured abiotic factors. Although the study was carried out in relatively small area, the four taxonomic groups seem to respond to biodiversity drivers in a surprisingly different way. This has considerable implications for conservation planning as it restricts the usefulness of simple indicators in prioritizing areas for conservation purposes.     

The influence of landscape on insect pest dynamics: a case study in southeastern France

Managing the spatial distribution of crop and non-crop habitats over landscapes could be used as a means to reduce insect pest densities. In this study, we investigated whether or not landscape characteristics affected the number of codling moths in commercial orchards. To do this, we collected overwintering larvae in 2006 and 2007 in 76 orchards over a 70 km2 area in southeastern France. We analysed variations in the number of larvae using correlation tests and linear models. As independent variables, we took both characteristics of focus orchards (pear vs. apple, organic vs. conventional orchards) and of their surrounding landscape (orchard density and hedgerow network attributes) into account in buffers with widths varying from 50 to 500 m. Although the codling moth is specialised on orchards, the number of codling moths was lower in orchards within a high orchard density area. There was some indication that this effect was mostly due to the density of conventional orchards and thus to the intensity of insecticide treatments. Conversely, we found no particular effect of abandoned or organic orchards. In 2006, the number of codling moths was also significantly lower in a focus orchard when the hedgerow network acted as a protection against the prevailing wind. Finally, major effects of landscape variables on the number of codling moths were observed for distances of less than 150 m from the focus orchards, suggesting that codling moth management should be organised over areas of about 16 ha. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Coupling ecosystem and landscape models to study the effects of plot number and location on prediction of forest landscape change

A fundamental but unsolved dilemma is that observation and prediction scales are often mismatched. Reconciling this mismatch largely depends on how to design samples on a heterogeneous landscape. In this study, we used a coupled modeling approach to investigate the effects of plot number and location on predicting tree species distribution at the landscape scale. We used an ecosystem process model (LINKAGES) to generate tree species response to the environment (a land type) at the plot scale. To explore realistic parameterization scenarios we used results from LINKAGES simulations on species establishment probabilities under the current and warming climate. This allowed us to design a series of plot number and location scenarios at the landscape scale. Species establishment probabilities for different land types were then used as input for the forest landscape model (LANDIS) that simulated tree species distribution at the landscape scale. To investigate the effects of plot number and location on forest landscape predictions, LANDIS considered effects of climate warming only for the land types in which experimental plots were placed; otherwise inputs for the current climate were used. We then statistically examined the relationships of response variables (species percent area) among these scenarios and the reference scenario in which plots were placed on all land types of the study area. Our results showed that for species highly or moderately sensitive to environmental heterogeneity, increasing plot numbers to cover as many land types as possible is the strategy to accurately predict species distribution at the landscape scale. In contrast, for species insensitive to environmental heterogeneity, plot location was more important than plot number. In this case, placing plots in land types with large area of species distribution is warranted. For some moderately sensitive species that experienced intense disturbance, results were different in different simulation periods. Results from this study may provide insights into sample design for forest landscape predictions.     

Predator activity and predation on songbird nests on forest-field edges in east-central Illinois

We measured the activity of mammalian predators, numbers of singing male songbirds, and predation rates on nests of songbirds (152 natural, open-cup nests and 380 artificial nests) on 38 250 m transects located along various types of forest-field edges in a wildlife management area in east-central Illinois. We then related these variables to each other and to measures of the vegetative structure of our transects that we anticipated might influence predator activity or predation rates on nests of birds characteristic of edge and shrubland habitats. Mammalian predators, particularly raccoons (Procyon lotor), were abundant in the wildlife area and present on all transects surveyed. We did not find significant relationships among the variables we measured. Rather, rates of nest predation were consistently high (>70%) and generally evenly distributed around our study site. Medium-sized, generalist mammalian predators in the midwestern United States reach their highest population densities in fragmented landscapes with abundant edge habitat, particularly agricultural edges. Areas of natural habitat in these landscapes dominated by agriculture may concentrate predators and act as ecological traps for nesting birds because they attract high densities of breeding birds that are subjected to high rates of nest predation.     

不同保果方式和气象因子对鲍威尔脐橙冬季落果的影响

调查了鲍威尔脐橙在重庆市奉节铁佛果园和巫山县福田果园两个点的冬季落果情况。结果表明,自然情况下,奉节铁佛果园的鲍威尔脐橙落果率明显低于巫山福田果园的落果率,至翌年2月底,后者的落果率是前者的5倍左右;和对照相比,11月和12月上旬喷两次保果剂处理能够明显降低脐橙的落果率。结合两个点的不同生态气候条件,对落果的原因进行了分析,认为低温特别是-2℃温度持续时间的长短是影响落果的主要原因。