GIS technologies for aquatic macrophyte studies: I. Database development and changes in the aquatic environment

Geographic information system (GIS) and digital database technologies provide a link between landscape-scale ecological studies and resource management applications. A case study involves the development of an extensive GIS database for upper Lake Marion, South Carolina that includes macrophyte distributions for 1972–1988, bathymetry, sedimentation and water chemistry. This database was utilized to assess changes in the aquatic environment related to management practices such as herbicide applications for aquatic plant control. Although the herbicides were found to be very effective, spraying must be repeated annually to maintain open water areas clear of aquatic vegetation. Without herbicides macrophytes quickly reinvade and proceed in normal successional patterns to establish submergent and emergent aquatic plant beds. The PC-based procedures developed in this study can be utilized by local resource managers to assess the impact of management practices on the aquatic environment.     

The use of a geographic information system to analyze long-term landscape alteration by beaver

A Geographic Information System (GIS) was used to analyze how beaver (Castor canadensis) have altered the hydrology and vegetation of Voyageurs National Park, Minnesota over a 46-year period. Maps of beaver ponds prepared from 1940, 1948, 1961, 1972, 1981, and 1986 aerial photographs were analyzed with a rasterbased based GIS to determine impoundment hydrology and vegetation distributions for each map date. Overlay and classification techniques were used to quantify hydrologic and vegetation changes between map dates. The GIS was superior to manual methods for some analyses (e.g., area measurement), and indispensible for others (e.g., transition analysis). Total area impounded increased from 1% to 13% of the landscape between 1940 and 1986, as the beaver population increased from near extirpation to a density of 1 colony/km². Most of the impoundment area increase occurred during the first two decades, when 77% of cumulative impoundment area was flooded. Once impounded ≥60% of the area maintained the same water depth or vegetation during any decade. GIS procedures were combined with field data to show that available nitrogen stocks nearly tripled between 1940 and 1986 as a result of beaver impoundment.     

微纳米气泡发生技术及其在水培增氧上的应用

为了验证微纳米气泡技术在无土栽培中的应用效果,以紫叶生菜为试验材料,采用微纳米气泡快速发生装置(HP-50),测定了产生气泡的粒径,分别以空气和氧气为气源测定了溶氧值。结果显示:微纳米气泡快速发生装置能够产生纳米级别的气泡,并快速增加水体溶氧值,以空气为气源时溶氧值可达到饱和状态,以氧气为气源时溶氧值可达到超饱和状态,并且具有优异的溶氧保持能力。将微纳米气泡快速发生装置与水培设施结合来种植紫叶生菜的试验结果表明,以氧气和空气为气源的曝气处理能够提高水培生菜的产量,并促进根系的生长。     

Anthropogenic influences on potential fire spread in a pyrogenic ecosystem of Florida, USA

Fire has historically been an important ecological factor maintaining southeastern U.S. vegetation. Humans have altered natural fire regimes by fragmenting fuels, introducing exotic species, and suppressing fires. Little is known about how these alterations specifically affect spatial fire extent and pattern. We applied historic (1920 and 1943) and current (1990) GIS fuels maps and the FARSITE fire spread model to quantify the differences between historic and current fire spread distributions. We held all fire modeling variables (wind speed and direction, cloud cover, precipitation, humidity, air temperature, fuel moistures, ignition source and location) constant with exception of the fuel models representing different time periods. Model simulations suggest that fires during the early 1900's burned freely across the landscape, while current fires are much smaller, restricted by anthropogenic influences. Fire extent declined linearly with patch density, and there was a quadratic relationship between fire extent and percent landscape covered by anthropogenic features. We found that as little as 10 percent anthropogenic landcover caused a 50 percent decline in fire extent. Most landscapes (conservation or non-conservation areas) are now influenced by anthropogenic features which disrupt spatial fire behavior disproportionately to their actual size. These results suggest that land managers using fire to restore or maintain natural ecosystem function in pyrogenic systems will have to compensate for anthropogenic influences in their burn planning. This revised version was published online in May 2005 with corrections to the Cover Date. This revised version was published online in July 2006 with corrections to the Cover Date.     

A general grass growth model for urban green spaces management in tropical regions: A case study with bahiagrass in southeastern Brazil

Urban green spaces (UGS) positively impact the population, providing essential ecosystem services and improving public health. Urban vegetation management needs to optimize mowing process costs and reducing impacts on the natural ecosystem. Thus, we implemented a general grass growth model suitable for UGS management in tropical areas, focused on lawns, public parks and squares, roadsides, and around waterways. The model incorporates local edaphoclimatic conditions to simulates the daily dynamics of leaf area index (LAI), biomass, evapotranspiration, and soil water content, going under mowing processes or not, with spatialization capability which might be integrated within geographic information system (GIS) environments. A case study assessing bahiagrass (Paspalum notatum Flüggé) vegetation species in São Carlos, southeastern Brazil, is presented, considering two scenarios to demonstrate the spatial capabilities of the model: (i) UGS as a single area, and (ii) several areas independently. For model validation, vegetation indices calculated based on data from an unmanned aerial vehicle (UAV) and CubeSat imagery (PlanetScope) were used to retrieve LAI time series, calibrated with spectral signatures from leaf ground sampling. For performance analysis, LAI time series from the model and LAI retrieved from both sensors were compared via determination coefficient (R²⁾ and root mean square error (RMSE). Our findings suggest that the proposed model is accurate, and due to its spatialization capability and integration with a GIS, its application may help government administrations to optimize UGS mowing processes.     

Error assessment in decision-tree models applied to vegetation analysis

Methods were developed to evaluate the performance of a decision-tree model used to predict landscape-level patterns of potential forest vegetation in central New York State. The model integrated environmental databases and knowledge on distribution of vegetation. Soil and terrain decision-tree variables were derived by processing state-wide soil geographic databases and digital terrain data. Variables used as model inputs were soil parent material, soil drainage, soil acidity, slope position, slope gradient, and slope azimuth. Landscapescale maps of potential vegetation were derived through sequential map overlay operations using a geographic information system (GIS). A verification sample of 276 field plots was analyzed to determine: (1) agreement between GIS-derived estimates of decision-tree variables and direct field measurements, (2) agreement between vegetation distributions predicted using GIS-derived estimates and using field observations, (3) effect of misclassification costs on prediction agreement, (4) influence of particular environmental variables on model predictions, and (5) misclassification rates of the decision-tree model. Results indicate that the prediction model was most sensitive to drainage and slope gradient, and that the imprecision of the input data led to a high frequency of incorrect predictions of vegetation. However, in many cases of misclassification the predicted vegetation was similar to that of the field plots so that the cost of errors was less than expected from the misclassification rate alone. Moreover, since common vegetation types were more accurately predicted than rare types, the model appears to be reasonably good at predicting vegetation for a randomly selected plot in the landscape. The error assessment methodology developed for this study provides a useful approach for determining the accuracy and sensitivity of landscape-scale environmental models, and indicates the need to develop appropriate field sampling procedures for verifying the predictions of such models.     

Simulating Spatial Nitrogen Dynamics in a Forested Reference Watershed, Hubbard Brook Watershed 6, New Hampshire, USA

We demonstrate that available information on spatial heterogeneity in biotic, topographic, and climatic variables within a forested watershed, Hubbard Brook Experimental Forest (HBEF) Watershed 6, New Hampshire, USA, was sufficient to reproduce the observed elevational pattern in stream NO₃ concentration during the 1982–1992 period. Five gridded maps (N mineralization factor, N uptake factor, precipitation, elevation, and soil depth factor) were created from spatial datasets and successively added to the spatially explicit model SINIC-S as spatially varying input parameters. Adding more spatial information generally improved model predictions, with the exception of the soil depth factor. Ninety percent of the variation in the observed stream NO₃ concentration was explained by the combination of the spatial variation of the N mineralization and N uptake factors. Simulated streamflow NO₃ flux at the outlet point was improved slightly by introducing spatial variability in the model parameters. The model exhibited substantial cell-to-cell variation in soil N dynamics and NO₃ loss within the watershed during the simulation period. The simulation results suggest that the spatial distributions of forest floor organic matter and standing biomass are most responsible for creating the elevational pattern in stream NO₃ concentration within this watershed.     

Untangling the positive and negative effects of shrubs on herbaceous vegetation in drylands

Woody vegetation, as an ecosystem engineer, can modulate the landscape such that the levels of resources in its vicinity undergo positive and negative changes as far as the herbaceous vegetation is concerned. To better understand how these processes play out in a semi-arid ecosystem, we examined resource modulation by woody vegetation, and the response of herbaceous vegetation to that modulation, at a fine spatial scale. Experimental manipulations were employed to separate the positive and negative effects of water, light and seed dispersal in determining herbaceous species density and biomass in three patch types within and adjacent to the shrub (core, periphery and open). We synthesized our results into a multilayered landscape diversity (MLLD) model. Woody vegetation creates distinct multilayered resource patches at its core and periphery which do not correspond to the dichotomous structural pattern of shrub canopy versus intershrub background. The combined effect of these multilayered resource patches had higher herbaceous species density (8.2 vs. 4.0 species 400?cm^?2) and herbaceous biomass (5.4 vs. 1.0?g 400?cm^?2) in the periphery than in the core (3-yr averages). The periphery??s net positive effects are due to enhancement of soil properties (water infiltration depth of 11.1?cm at periphery vs. 8.1?cm at core), while the core??s net negative effects are due to modulation of seed (seed abundance per seed trap of 44.2 at periphery vs. 3.0 at core) and light availability (PAR transmittance of 41.9?% at periphery vs. 16.5?% at core) by the shrub canopy. Thus, when examined at this fine spatial resolution, woody vegetation has both net positive and net negative effects on herbaceous vegetation. Analysis of our results by means of the MLLD model emphasizes the importance of examining the landscape at the spatial scale of the modulated resources and of recognizing different patch types and their differing effects on herbaceous vegetation.     

Modeling dissolved organic carbon in subalpine and alpine lakes with GIS and remote sensing

Current global trends in lake dissolved organic carbon (DOC) concentrations suggest a need for tools to more broadly measure and predict variation in DOC at regional landscape scales. This is particularly true for more remote subalpine and alpine regions where access is difficult and the minimal levels of anthropogenic watershed disturbance allow these systems to serve as valuable reference sites for long-term climate change. Here geographic information system (GIS) and remote sensing tools are used to develop simple predictive models that define relationships between watershed variables known to influence lake DOC concentrations and lake water color in the Absaroka-Beartooth Wilderness in Montana and Wyoming, USA. Variables examined include watershed area, topography, and vegetation cover. The resulting GIS model predicts DOC concentrations at the lake watershed scale with a high degree of accuracy (R ² = 0.92; P ≤ 0.001) by including two variables: vegetation coverage (representing sites of organic carbon fixation) and areas of low slope (0–5%) within the watershed (wetland sites of DOC production). Importantly, this latter variable includes not only surficially visible wetlands, but “cryptic” subsurface wetlands. Modeling with Advanced Land Imager satellite remote sensing data provided a weaker relationship with water color and DOC concentrations (R ² = 0.725; P ≤ 0.001). Model extrapolation is limited by small sample sizes but these models show promise in predicting lake DOC in subalpine and alpine regions.     

The development of forage production and utilization gradients around livestock watering points

Large herbivores can impose spatial patterns on otherwise homogeneous vegetation, but how these patterns change through time is poorly understood. Domestic livestock pastures are model systems for studying how foraging behavior influences the development of coupled grazing and vegetation patterns. We sampled forage production and utilization by cattle along distance-from-water gradients to provide a snapshot of grazing and vegetation patterns, and then evaluated the ability of simulation models to qualitatively reproduce these patterns. In the field, forage production increased with distance from water, as expected, but utilization peaked at intermediate distances from water in two of three study areas. Likewise, simulations based on a variety of foraging strategies produced gradients in forage production and, after forage availability near water declined sufficiently, peaks in utilization at intermediate distances. Distance-from-water gradients thus represent cumulative but not necessarily present day gradients in grazing intensity. The model with a foraging strategy based on time minimization produced slightly more realistic patterns in forage abundance than a model based on energy maximization, although results were sensitive to the value of the threshold for rejecting sites of low forage biomass. However, all models produced implausible thresholds in grazing and forage distribution, suggesting that factors besides resource distribution influence herbivore distributions. Moreover, different foraging rules produced similar vegetation gradients, especially on point water source landscapes, illustrating the difficulty of inferring foraging processes from vegetation patterns.     

网箱养鳝水体适宜水生植物的筛选

从经济价值、对水深的适应性及植株扩展度3个方面对长江流域适宜种植的23种水生植物进行了筛选．认为菜用睡莲（咖n加aeaspp．）、蕹菜（昂0埘0eaaquatiea）、菱角（Trapaspp．）及芡实（Euryaleferox）4种水生经济植物比较适合于网箱养蟮水体种植,并提出了相应的栽培技术要点。     

Response of high mountain landscape to topographic variables: Central pyrenees

An objective method for inductively modelling the distribution of mountain land units using GIS managed topographic variables is presented. The landscape of a small high mountain catchment in the Spanish Pyrenees, covered with grassland, was classified in ten land units by hierarchical agglomerative clustering, using a sample of 194 random plots, in which classes of vegetation, soils and landforms were defined. Additionally, seven layers of topographic variables (altitude, slope angle, aspect, solar radiation, topographic wetness index, specific catchment area, and regolith thickness) were created from a Digital Elevation Model. The affinity of each land unit to the topographic variables was calculated using Binary Discriminant Analysis (BDA), after dichotomising the latter around their mean values. Then, the distribution of each land unit was predicted by boolean operations combining step by step distributions for the seven topographic variables ordered, for each unit, after the absolute values of the Haberman’s residuals in BDA. The predicted distributions were tested (χ²) against that of the observed sampling plots. From the original ten land units, the distributions of eight of them were successfully predicted (four are related to the slope sequence, two reflect the water accumulation in the soil, and two respond to geomorphic processes) while the remaining two had to be rejected. Part of the catchment (39%) was not assigned to any land unit, probably because more distributed variables accounting for snow distribution are necessary.     

Erosion regulation as a function of human disturbances to vegetation cover: a conceptual model

Human-induced land cover changes are causing important effects on the ecological services rendered by mountain ecosystems, and the number of case-studies of the impact of humans on soil erosion and sediment yield has mounted rapidly. In this paper, we present a conceptual model that allows evaluating overall changes in erosion regulation after human disturbances. The basic idea behind this model is that soil erosion mechanisms are independent of human impact, but that the frequency–magnitude distributions of erosion rates change as a response to human disturbances. Pre-disturbance (or natural) erosion rates are derived from in situ produced ¹⁰Be concentrations in river sediment, while post-disturbance (or modern) erosion rates are derived from sedimentation rates in small catchments. In its simplicity, the model uses vegetation cover change as a proxy of human disturbance. The erosion regulation model is here applied in two mountainous regions with different vegetation dynamics, climatic and geological settings: the Austro Ecuatoriano, and the Spanish Betic Cordillera. Natural erosion benchmarks are necessary to assess human-induced changes in erosion rates. While the Spanish Betic Cordillera is commonly characterized as a degraded landscape, there is no significant difference between modern catchment-wide erosion and long-term denudation rates. The opposite is true for the Austro Ecuatoriano where the share of natural erosion in the total modern erosion rate is minimal for most disturbed sites. When pooling pre- and post-disturbance erosion data from both regions, the data suggest that the human acceleration of erosion is related to vegetation disturbances. The empirical regression model predicts human acceleration of erosion, here defined as the ratio of post-disturbance to pre-disturbance (or natural benchmark) erosion rate, as an exponential function of vegetation disturbance. This suggests that the sensitivity to human-accelerated erosion would be ecosystem dependent, and related to the potential vegetation cover disturbances as a result of human impact. It may therefore be expected that the potential for erosion regulation is larger in well-vegetated ecosystem where strong differences may exist in vegetation cover between human disturbed and undisturbed or restored sites.     

Can green roofs help with stormwater floods? A geospatial planning approach

Increasing urbanization, impervious space, and the impact of climate change are threatening the future of cities. Nature-based solutions, specifically urban green infrastructures, are seen as a sustainable strategy to increase resilience against extreme weather events, including the escalating occurrence of stormwater runoff flooding. Consequently, urban planners and decision-makers have pushed their efforts toward implementing green infrastructure solutions to reduce the impact of stormwater floods. Among others, green roofs help store water and decrease stormwater runoff impacts on a local scale. This research aims to investigate the effect of surface permeability and green roof implementation on reducing stormwater flooding and subsequently provide urban planners with evidence-based geospatial planning recommendations to improve urban resilience in Helsinki. First, we modeled the current impact of stormwater flooding using the Arc-Malstrom model in Helsinki. The model was used to identify districts under high stormwater flood risk. Then, we zoomed in to a focus area and tested a combination of scenarios representing four levels of green roof implementation, two levels of green roof infiltration rates under 40-, 60-, 80-, 100 mm precipitation events on the available rooftops. We utilized open geographic data and geospatial data science principles implemented in the GIS environment to conduct this study. Our results showed that low-level implementation of green roofs with low retention rates reduces the average flood depth by only 1 %. In contrast, the maximum green roof scenario decreased most of the average flood depth (13 %) and reduced the number of vulnerable sites. The proposed methodology can be used for other cities to develop evidence-based plans for green roof implementations.     

Simulated productivity of heterogeneous patches in Southern African savanna landscapes using a canopy productivity model

A daily model of terrestrial productivity is used to simulate the annual productivity of heterogeneous vegetation structure at three savanna/woodland sites along a large moisture gradient in southern Africa. The horizontal distributions of vegetation structural parameters are derived from the three-dimensional canopy structure generated from detailed field observations of the vegetation at each site. Rainfall and daily climatic data are used to drive the model, resulting in a spatially explicit estimate of vegetation productivity in 100 m² patches over an area 810,000 m² (8,100 patches per site). Production is resolved into tree and grass components for each subplot. The model simulates the relative contribution of trees and grasses to net primary productivity (NPP) along the rainfall gradient. These simulated production estimates agree with previously published estimates of productivity in southern African savannas. Water-use efficiency of each site is directly related to the structural composition of the site and the differing water-use efficiencies for tree and grass functional types. To assess the role of spatial scale in governing estimates of vegetation productivity in heterogeneous landscapes, spatial aggregation is performed on the canopy mosaic at the northern-most (wettest) site for 625 m², 2500 m² and 5625 m² resolutions. These simulations result in similar overall patterns of average NPP for both trees and grasses, but drastically reduced distributions of productivity due to reduced structural heterogeneity. In particular, the aggregation of the detailed spatial mosaic to coarser resolutions is seen to eliminate information regarding demographic processes such as regeneration and mortality, and the dependence of grass productivity on over-story density. These results indicate that models of system productivity in savanna/woodland ecosystems must retain high spatial resolution to adequately characterize multi-year structural responses and to accurately represent the contribution of grass biomass to overall ecosystem production.This revised version was published online in May 2005 with corrections to the Cover Date.     

单核苷酸多态性标记技术及其在水生蔬菜中的应用

水生蔬菜是我国乃至世界蔬菜的特色种类,在国际市场中占有重要地位,需求量逐年增长。单核苷酸多态性（SNP）技术在作物基因组中分布密度高、遗传稳定,易实现自动化,是新一代分子标记技术。以此新技术加速我国水生蔬菜的基础和应用研究对培育高产、优质品种,增强出口创汇和提升科研水平与国际地位有着重要意义。由于该技术在水生蔬菜上尚未见报道．因此本文综述能给国内外同行提供些许参考。     

不同固沙植被下沙丘土壤水分动态比较

以毛乌素沙地覆盖度>90%的油蒿、50%～60%的沙柳、35%～40%的樟子松固定沙丘为研究对象,流动沙丘为对照,采用自动监测系统实时监测降雨、0～200 cm土壤含水量及200 cm以下渗漏量,分析5—11月不同固沙植被下沙丘土壤水分动态差异,以期为固沙植被稳定性评价提供参考。结果表明:较低覆盖度樟子松与高盖度油蒿、沙柳相比更具固沙优势。3种固沙植被表层0～30 cm土壤水分受降雨影响大,对>20 mm降雨均产生响应;60～200 cm土壤水分时间变化特征存在差异,樟子松与对照变化趋势一致,油蒿和沙柳仅对40 mm降雨产生响应;0～200 cm土壤水分垂直变化没有相同规律,变异性较大,樟子松变幅最大,为(5.03±3.09)%;深层渗漏特征基本一致,均有极少量水分渗漏到200 cm以下。     

Processes of environmental degradation and opportunities for rehabilitation in Adwa,Northern Ethiopia

There are only a few studies of land cover-land use changes which provide an integrated assessment of the biophysical and societal causes and consequences of environmental degradation in Ethiopia. Our objectives were to determine the status of the environmental degradation, analyse and evaluate the relationships among vegetation, geomorphological and socio-economic factors contributing to environmental degradation, and propose opportunities for rehabilitation of these natural resources. Field and other environmental data in northern Ethiopia and those acquired by remote sensing techniques were used to accomplish these objectives. These were integrated with socio-economic data obtained from official sources using a Geographic Information System (GIS).Spatial information such as the percent of land cover-land use types and geomorphological categories, and the percent of each land cover-land use type in the geomorphological categories were calculated using Geographic Information System (GIS). The three most dominant features of the geomorphological categories (93.0%) are scarps and denuded rock slopes, erosion surfaces and badlands, while the three most dominant features in the land cover-land use types (71.3%) are croplands, open woodlands and bushlands. Badlands account for 38.7% of the geomorphological units and 41.8% of the croplands currently occur on badlands. Simple and partial correlation analyses were applied to explore the extent of the interaction between the anthropogenic and the natural system. The anthropogenic system is influenced by elevation, which is positively correlated with human population and livestock densities and area of croplands. The natural system finds its place only on steep slopes as shown by the positive correlation between woodland,slope, high potential erosion, scarps and denudational rock slopes. The study indicates that agriculture in the study area is in a critical environmental situation. A change of paradigm in land-use and development is needed to encourage participation of the landowners and users in the efforts to conserve the vegetation and the soil. This study provides sound options that could be used to rehabilitate the vegetation directly and to alleviate the current pressure on the land and improve human welfare indirectly. Matching the human and livestock densities with the carrying capacity of the land through recruitment of the surplus labour force for a modern economy, resettlement,off-farm employment and intensification of agriculture are t he long and short-term actions that may contribute to the rehabilitation of the degraded areas. This revised version was published online in July 2006 with corrections to the Cover Date.     

Multiscale control of vegetation patterns: the case of Doñana (SW Spain)

The early studies about the plant ecology of Doñana carried out at a small scale showed that the main process controlling vegetation composition of the stabilized dunes was soil water availability. However, the extrapolation of this model to larger spatial scales failed to explain observed vegetation patterns. In this work, the vegetation patterns and the processes causing them are studied at a larger scale. Data of topography, soil pH, electrical conductivity, and available iron allowed to distinguish three large geomorphologic zones on the stabilized dunes of the Doñana Biological Reserve which correspond to different dune building episodes. Different dune episodes showed differences in both water table depth and dynamics, which are due to groundwater flow systems of different scale. It is further manifested by differences in shrub composition. The results show that geomorphology controls the vegetation pattern at different scales mediated through water availability. Differences in water availability are due to the connection to groundwater flow systems of contrasted scale. On a small scale (10−10² m), along dune slopes, there is a gradient from dune ridges to slacks, from xerophyte to hygrophyte vegetation types. On a mesoscale (10²−10³ m), there are several dune episodes with variable topographic altitude, dominated by different types of xerophytes. On a regional scale (>10³ m), the discharges of the regional aquifer produce strong environmental and biotic stresses resulting in a mixed community.