Impact of off-road vehicles on soil and vegetation in a desert rangeland in Saudi Arabia

Off-road vehicle driving is considered as main contributor to land degradation in arid regions. This study examined the impact of off-road vehicles (ORV) on soil and vegetation in a natural recreational desert meadow of Raudhat Khuraim, Saudi Arabia. Vegetation canopy cover and plant height away from road tracks were assessed. Also, species density and canopy cover, bare ground cover and soil attributes were assessed in four microhabitats; tracks, inter-tracks, verges, and away from vehicle tracks (undisturbed natural areas). Results show that the cover of forbs and grasses was negatively associated with distance from road verges. It was observed that the height of woody species responded negatively to distance away from tracks. Cover of native species decreased under verge, inter-track and track microhabitats giving more opportunity for weeds to flourish. Bare ground was highest (60.7%) in tracks. ORV impact on soil bulk density was clear with an increase of 38% under tracks compared to soils of undisturbed natural vegetation and a similar decrease in porosity was observed. On the other hand, soil electrical conductivity was significantly higher (5.45 mS cm^?1) under disturbance compared to 1.32 mS cm^?1 in undisturbed natural vegetation. Organic matter and nitrogen were not affected significantly by ORV disturbance. The results emphasize that managing off-road vehicle driving is essential for conserving native vegetation.     

Using unmanned aerial vehicle‐based multispectral,RGB and thermal imagery for phenotyping of forest genetic trials: A case study in Pinus halepensis

The assessment of genetic differentiation in functional traits is fundamental towards understanding the adaptive characteristics of forest species. While traditional phenotyping techniques are costly and time‐consuming, remote sensing data derived from cameras mounted on unmanned aerial vehicles (UAVs) provide potentially valid high‐throughput information for assessing morphophysiological differences among tree populations. In this work, we test for genetic variation in vegetation indices (VIs) and canopy temperature among populations of Pinus halepensis as proxies for canopy architecture, leaf area, photosynthetic pigments, photosynthetic efficiency and water use. The interpopulation associations between vegetation properties and above‐ground growth (stem volume) were also assessed. Three flights (July 2016, November 2016 and May 2017) were performed in a genetic trial consisting of 56 populations covering a large part of the species range. Multispectral (visible and near infrared wavelengths), RGB (red, green, blue) and thermal images were used to estimate canopy temperature and vegetation cover (VC) and derive several VIs. Differences among populations emerged consistently across flights for VC and VIs related to leaf area, indicating genetic divergence in crown architecture. Population differences in indices related to photosynthetic pigments emerged only in May 2017 and were probably related to a contrasting phenology of needle development. Conversely, the low population differentiation for the same indices in July 2016 and November 2016 suggested weak interpopulation variation in the photosynthetic machinery of mature needles of P. halepensis. Population differences in canopy temperature found in July 2016 were indicative of variation in stomatal regulation under drought stress. Stem volume correlated with indices related to leaf area (positively) and with canopy temperature (negatively), indicating a strong influence of canopy properties and stomatal conductance on above‐ground growth at the population level. Specifically, a combination of VIs and canopy temperature accounted for about 60% of population variability in stem volume of adult trees. This is the first study to propose UAV remote sensing as an effective tool for screening genetic variation in morphophysiological traits of adult forest trees.     

Composition,biomass and structure of mangroves within the Zambezi River Delta

We used a stratified random sampling design to inventory the mangrove vegetation within the Zambezi River Delta, Mozambique, to provide a basis for estimating biomass pools. We used canopy height, derived from remote sensing data, to stratify the inventory area, and then applied a spatial decision support system to objectively allocate sample plots among five strata. Height and diameter were measured on overstory trees, saplings and standing dead trees in nested plots, and biomass was calculated using allometric equations. Each of the eight mangrove species occurring in Mozambique exist within the Delta. They are distributed in heterogeneous mixtures within each of the five canopy height classes, not reflecting obvious zonation. Overstory trees averaged approximately 2000 trees ha^?1, and average basal area ranged from 14 to 41 m² ha^?1 among height classes. The composition of the saplings tended to mirror the overstory, and the diameter frequency distributions suggest all-aged stands. Above-ground biomass ranged from 111 to 483 Mg ha^?1 with 95 % confidence interval generally within 15 % of the height class mean. Despite over 3000 trees ha^?1 in the small-tree component, 92 % of the vegetation biomass is in the overstory live trees. The objective inventory design proved effective in estimating forest biomass within the 30,267 ha mangrove forest.     

Optical trait indicators for remote sensing of plant species composition: Predictive power and seasonal variability

Most plant species feature similar biochemical compositions and thus similar spectral signals. Still, empirical evidence suggests that the spectral discrimination of species and plant assemblages is possible. Success depends on the presence or absence of faint but detectable differences in biochemical (e.g., pigments, leaf water and dry matter content) and structural properties (e.g., leaf area, angle, and leaf structure), i.e., optical traits. A systematic analysis of the contributions and spatio-temporal variability of optical traits for the remote sensing of organismic vegetation patterns has not yet been conducted. We thus use time series of optical trait values retrieved from the reflectance signal using physical models (optical trait indicators, OTIs) to answer the following questions: How are optical traits related among patterns of floristic composition and reflectance? How variable are these relations in space and time? Are OTIs suitable predictors of plant species composition?We conducted a case study of three temperate open study sites with semi-natural vegetation. The canopy reflectance of permanent vegetation plots was measured on multiple dates over the vegetation period using a field spectrometer. We recorded the cover fractions of all plant species found in the vegetation plots and extracted gradients of species composition from these data. The physical PROSAIL leaf and canopy optical properties model was inverted with random forest regression models to retrieve time series of OTIs for each plot from the reflectance spectra. We analyzed these data sets using correlation analyses. This approach allowed us to assess the distribution of optical traits across gradients of species composition. The predictive performance of OTIs was tested in relation to canopy reflectance using random forest models.OTIs showed pronounced relationships with floristic patterns in all three study sites. These relationships were subject to considerable temporal variability. Such variability was driven by short-term vegetation dynamics introduced by local resource stress. In 72% of all cases OTIs out-performed the original canopy reflectance spectra as indicators of plant species composition. OTIs are also easier to interpret in an ecological sense than spectral bands or features. We thus conclude that optical traits retrieved from reflectance data have a high indicative value for ecological research and applications.     

Response of riparian plant communities to distance from surface water in the Okavango Delta,Botswana

The objective of this study was to determine the influence of distance from surface water on riparian woodland communities in the Okavango Delta. Vegetation sampling was conducted in seven sites within the Okavango Delta in 20 m × 10 m belted plots placed perpendicular to the river bank. The plots were placed at 0–10 m, 10–20 m, 20–30 m, 30–40 m and 40–50 m distance classes increasing away from the river bank. Tree height, basal area, species richness, canopy cover and diversity were determined for each distance class. Indicator species analysis was used to determine the characteristic species at each distance class. Single‐factor ANOVA and Tukey post hoc analysis were used to compare species diversity, mean tree height, cover and basal area between distance classes. Correlation between distance from surface water and vegetation parameters was sought using Spearman regression analysis. All parameters except for species richness varied significantly (P < 0.05) along distance from surface water. Distance from surface water was positively correlated all vegetation parameters except for mean species richness/plot. These results show that distance from surface water influences riparian plant community composition and distribution in the Okavango Delta. This implies that riparian plant species can be indicators of long‐term hydrologic conditions in the Delta.     

Biophysical parameters retrieval of mangrove ecosystem using 3D point cloud descriptions from UAV photographs

The deriving of mangrove biophysical parameters in a cost-effective manner, at a fine spatial scale and over relatively large areas remains a significant challenge. This study aims to provide a comprehensive integrated technical method to map mangrove landscape biophysical characteristic parameters (height, canopy area, canopy perimeter and volume) of two typical mangrove areas in China based on unmanned aerial vehicle (UAV) techniques. In this study, initially, response surface methodology (RSM) was applied to seek the optimal flight parameters for obtaining good-quality synthesized the orthophoto digital composite images. Afterward, a digital surface model (DSM) and a dense photogrammetric point cloud technical method were utilized to derive the mangrove parameters, and artificial visual interpretation was applied to carry out species discrimination and mangrove community canopy coverage. The results showed that the most efficient combination of flight parameters for mangrove extraction is UAV vertical shooting at 30 m altitude and a 75% overlap ratio, which could cover a maximum mangrove investigation area of 0.51 ha during low tide within a day. (2) The integrated technical methods demonstrated good performance in retrieving high-precision mangrove landscape parameters by taking the Dongwei and Daguansha mangrove areas as examples. (3) Transact analysis showed an inverted U-curve of height, canopy area, and volume from the seaward mangrove edge to the landward mangrove edge. Overall, the UAV system with high-resolution (8 cm pixel) images has the potential to enable satisfactory extraction of mangrove landscape parameters by using multisoftware processing. The study will be helpful to the policy-makers, ecologists and environmentalists to formulate and implement various sustainable development programs in mangrove ecosystems.     

Assessing seasonal and long-term mangrove canopy variations in Sinaloa,northwest Mexico,based on time series of enhanced vegetation index (EVI) data

The use of remote sensing tools for mangrove monitoring is currently a strategy used to preserve this important coastal vegetation type. However, the temporal resolution of most satellite imagery limits the analysis of seasonal changes. Here, seasonal trend analysis (STA) was performed using an enhanced vegetation index (EVI) monthly time series (2005–2016) edited from MOD13Q1 products (MODIS Terra), to detect changes in mangrove cover in Sinaloa State in northwestern Mexico. The results were compared with a baseline map derived from a post-classification comparison of two mangrove distribution maps of 2005 and 2015. The STA procedure enabled the identification of mangrove canopy seasonal cycles, with open canopies between May and July and closed canopies from August to October. It was also possible to detect annual and long-term changes in canopy, with positive trends observed in most of Sinaloa’s mangrove ecosystems, which partially agree with the post-classification comparison results. Despite their coarse resolution, using the MODIS EVI products proved to be useful to confidently detect short- and long-term changes in mangrove cover, particularly in large ecosystems. Consequently, land use change analyses using these inputs could help to take actions related to mangrove cover management, considering the trends of change in this vegetation type.

     

Influence and value of different water regimes on avian species richness in arid inland Australia

Riparian habitats in arid landscapes are recognised for their structurally diverse vegetation and diverse bird species assemblages. In the extensive semi-arid and arid centre of Australia, riparian woodland habitats are impacted by pastoral land-use which may negatively influence vegetation structure and avian species composition. However, pastoralism has promoted the establishment of artificial water bodies, so that additional riparian vegetation may occur in the landscape. In this study, we surveyed the importance of different water regimes (i.e. artificial lakes, natural waterholes, desert sites) together with their associated vegetation on avian species richness in north-western New South Wales, Australia. Our results show that bird species richness was highest at water locations, in particular at artificial lakes. Avian species richness was negatively associated with distance to water bodies, both in desert vegetation types and in the riparian vegetation type along dry creeks. Moreover, riparian habitats supported larger avian assemblages and especially those of sedentary bird species compared to the surrounding shrub-steppe landscape. This indicates that artificial water bodies may be of significance for arid zone bird species and might gain in importance with changing water availabilities due to climatic changes.     

Salinity-induced limits to mangrove canopy height

Aim

Mangrove canopy height is a key metric to assess tidal forests' resilience in the face of climate change. In terrestrial forests, tree height is primarily determined by water availability, plant hydraulic design, and disturbance regime. However, the role of water stress remains elusive in tidal environments, where saturated soils are prevalent, and salinity can substantially affect the soil water potential.

Location

Global.

Time Period

The canopy height dataset provides a global snapshot of the maximum mangrove height geographical distribution for the year 2000. Climate and environmental variables extend over the period 1970–2018.

Major Taxa Studied

Mangroves.

Methods

We use global observations of maximum canopy height, species richness, air temperature, and seawater salinity—a proxy of soil water salt concentration—to explore the causal link between salinity and mangrove stature.

Results

Our findings suggest that salt stress limits mangrove height. High salinity favours more salt-tolerant species, narrowing the spectrum of viable traits. Highly salt-tolerant mangroves have evolved to cope with high salt concentrations in the soil, but this adaptation comes at a cost. They typically have lower rates of photosynthesis and growth, resulting in reduced productivity and smaller stature compared to more salt-sensitive mangrove species. This suggests a causal link between salinity, biodiversity, and tree height, where high salinity selects for more salt-tolerant species that tend to be less productive and shorter.

Conclusions

We hypothesize that the salinity-induced limit to mangrove canopy height is the direct result of a reduction of primary productivity, an increment in the risk of xylem cavitation, and an indirect consequence of the decrease in biodiversity. As sea-level rise enhances coastal salinisation, failure to account for these effects can lead to incorrect estimates of future carbon stocks in Tropical coastal ecosystems and endanger preservation efforts.     

A cost-effective monitoring method using digital time-lapse cameras for detecting temporal and spatial variations of snowmelt and vegetation phenology in alpine ecosystems

Alpine ecosystems are particularly vulnerable to the effects of climate change. Although long-term and detailed monitoring is required to conserve alpine ecosystems, field surveillance and satellite remote sensing have difficulties in providing wide coverage or frequent observation in mountain areas. In this study, a new method for monitoring alpine ecosystems by digital cameras was developed in order to detect both snow-cover areas and vegetation phenology at the plant community or species level. We used images from cameras that have been installed at mountain lodges in the northern Japanese Alps (at elevations around 2350–3100 m). Red, green, and blue (RGB) digital numbers were derived from each pixel within the images. The snow-cover and snow-free pixels were statistically classified by analysis of variance of gray-level histograms. A flexible threshold was determined for each image to maximize the between-class variance. The temporal variations of the snowmelt rate showed site-specific characteristics and yearly variations. The snowmelt times reflected the local microtopography and differed among the habitats of various functional types of vegetation (i.e., evergreen dwarf pine, deciduous shrubs, evergreen Sasa, tall forbs, and snowbed plants). In addition, the vegetation phenology was quantified by using a vegetation index (green ratio) calculated from RGB digital numbers. An increase in the green ratio indicated the start of the growing period following snowmelt and a decrease indicated leaf senescence. By using pixel-based analysis of the temporal variations of the green ratio, local distributions of the start and end dates and length of the growing period were illustrated at the plant species level for the first time. The distribution of the start of the growing period strongly corresponded to the snowmelt gradient, whereas the end of the growing period was related to the vegetation type. Our results suggest that the length of the growing period mainly corresponded to the snowmelt gradient in relation to the local microtopography. Thus, commercially available digital time-lapse cameras enabled us to clarify the snow–vegetation relationships and the growing period at high temporal and spatial resolutions. This monitoring method should greatly improve our understanding of alpine ecosystems and help to assess the influence of future climate change.     

The potential of modeling Prosopis Juliflora invasion using Sentinel-2 satellite data and environmental variables in the dryland ecosystem of Ethiopia

Earth observation data play a vital role for efficient modeling of invasive species. Particularly, optical Sentinel-2 (S2) data with its capability of providing high spatial, spectral and temporal resolutions creates ample opportunities. However, few studies so far evaluated the combined use of S2 derived variables and environmental variables for modeling the distribution of invasive species. This study aims to compare the performance of models using S2 derived variables with environmental variables and their integration for modeling invasive Prosopis juliflora in the lower Awash River basin of Ethiopia. A total of 680 field data were used to train and validate the Random Forest (RF) approach. Model performances were evaluated using True Skill Statistics (TSS), kappa index, correlation, area under the curve (ROC), sensitivity and specificity. Our results demonstrated that modeling using S2 vegetation indices and S2 spectral bands showed higher performance compared to topo-climatic based variables with TSS of 0.91, 0.89, and 0.74, respectively. The ROC also confirmed the higher accuracy of S2 vegetation indices, S2 spectral bands and combined models compared to a topo-climatic based modeling. Interestingly, models using the integration of S2 derived variables with topo-climatic variables showed even better performance than the individual models. Our study highlighted that S2 derived variables and their integration with topo-climatic variables are highly recommended for efficient monitoring of invasive species distribution.     

Testing the Wiegand–Milton model: A long‐term experiment to understand mechanisms driving vegetation dynamics in arid shrublands

The Wiegand and Milton (1996) simulation model predicts that vegetation dynamics in arid shrublands are characterized by event‐driven stochasticity (weather events), and demographic inertia (persistence of a species in a community) that lead to a lagged response in vegetation compositional change. Slow plant growth is one of the mechanisms driving slow vegetation change. We test this model at the same location (Tierberg Long‐term Ecological Research site) on which the model was based. Three dwarf shrub species, differing in palatability, were tracked over 25 years (1988–2014) at two levels of the past herbivory (pre‐1960) and three levels of the present herbivory (post‐1988). In the period between 1960 and 1988, all sites were grazed at the recommended agricultural stocking rate. For each species, plant density and a number of size attributes (basal diameter, height, canopy area) were surveyed. Analyses using a two‐way Analysis of Covariance (ANCOVA) took initial starting size into consideration. As the model predicted, event‐driven stochasticity (rainfall) resulted in an increase in density of the smaller size classes following a single large recruitment event across all grazing regimes for the palatable and unpalatable species. Size‐class distribution curve types remained unchanged illustrating that population demography remains unaffected for long periods and responses are slow (lagged response). Slow plant growth was evident in that there were no changes in height, canopy area, or density under present grazing regimes over the 25‐year period. Palatable species had a reduced canopy area and density compared to unpalatable species. Our findings provide empirical evidence supporting the predictions of the Wiegand and Milton (1996) model, notably event‐driven stochasticity, demographic inertia, and a lagged response in vegetation change in arid shrublands. In addition, our results support the model assumption of the significance of slow growth in long‐lived plant species and the influence of grazing regime.     

Effects of the physical structure of mangrove vegetation on a benthic faunal community

Clarification of the role of the physical structure of mangrove for benthic faunal communities was sought by investigating the impacts of canopy shade and root structure on (1) the physical environment, including temperature, moisture and grain size of the substrate sediment, (2) benthic faunal distribution, and (3) food resource availability, using a field manipulated experiment at an intertidal mangrove forest around Sikao Creek, Trang Province, Thailand. Five treatments were established, including artificial shade cover, root simulated structure, mix (shade and structure) and control of the canopy gap (which had no mangrove vegetation), in addition to forest control under the mangrove canopy. Following 18 months of observation, species' richness and abundance of epifauna were found to have increased in shaded treatments, which had low temperature and high moisture substrate. Food resource conditions had also altered from abundant microphytobenthos (relatively high nutritional values) to enriched mangrove detritus due to shading. These results indicated that the physical structure of mangrove vegetation facilitates the habitation of intertidal epifauna, canopy shade having an important function in providing cooler wetter surface substrate, despite also inducing a reduction of favorable food resources (i.e. microphytobenthos).     

Microenvironmental and vegetational heterogeneity induced by phytogenic nebkhas in an arid coastal ecosystem

The nebkhas of woody plants represent distinct habitats in arid and semiarid ecosystems. Nebkhas are mounds composed of wind-borne sediment within or around shrub canopies. We studied the effects of widely spaced nebkhas of Retama raetam shrub on their microenvironment and associated herbaceous vegetation in the Mediterranean coast of Sinai Peninsula. Our measurements included nebkha size (height and width) and shrub size (canopy height and diameter). We identified four distinct microsites at each nebkha: crest, mid-slope, edge, and internebkha space. We measured soil temperature and moisture, photosynthetically active radiation (PAR), and soil properties. The plant species grown at each microsite were identified and their densities were measured. Average soil temperature and PAR were highest at internebkha space and lowest at nebkha crest. The maximum diurnal temperature and PAR of internebkhas exceeded that of nebkhas. Soil moisture and nutrient concentrations showed a gradient of spatial heterogeneity and were highest at the nebkha edge. Regression analysis indicated that total herbaceous plant density was significantly related to nebkha size, and to shrub canopy diameter and area. Detrended correspondence analysis indicated that patterns of species composition were correlated with the spatial variability in soil moisture and nutrient content along the gradient of increasing distance from the nebkha crest. It is assumed that shrub canopy and its nebkha interact in governing ecosystem functioning in this environment.     

生物土壤结皮对照相法测量植被覆盖度结果的影响

植被覆盖度测度的准确性很大程度上影响着研究结论是否科学合理。在干旱半干旱退化草原区,尤其是受采矿剧烈扰动的矿区,发育的生物土壤结皮(Biological soil crust,BSC)由于其颜色和光谱同绿色植被具有相似性,导致对植被覆盖度的测量存在一定的影响。以伊敏露天矿区为研究区,在西排土场和内排土场采集了含苔藓结皮、地衣结皮和藻结皮的样方相片各四组(每组中包含样方喷水前和喷水后的相片各一张),并采集了一组不含结皮的样方相片作为对照组,运用数码照相法提取植被覆盖度,通过不同的数据处理方法(最大似然分类法及RGB阈值法)进行植被覆盖度提取,设立对比试验,分析BSC对于植被覆盖度测度是否有影响,其影响大小如何,影响程度是否受BSC含水量大小的影响,并对比各常规处理方法的优劣,研究能否通过结合纹理特征与色彩信息剔除BSC对植被覆盖度提取值的影响。研究结论:1)基于照相法的常规数据处理方法提取植被覆盖度时,BSC的存在导致测得的植被覆盖度值偏高,且苔藓结皮、地衣结皮吸水后比吸水前影响更显著,藻结皮相反;2)3个演替阶段的BSC中,尤以含苔藓结皮的样方植被覆盖度高估最为明显,其次为地衣,而含藻结皮样方规律不明显;3)样方内BSC覆盖度越高,植被覆盖度越低,其植被覆盖度测度越不准确,因此在研究草原矿区这类草本植物覆盖度较低、结皮发育的区域时,应当注意BSC的影响;4)试通过应用纹理信息提出改进的提取方法,发现单纯的纹理分类精度极低,而结合了纹理信息与RGB色彩信息的分类精度较高;5)对两种常规分类方法的精度进行比较,RGB阈值法较最大似然分类法更为不准确,对植被覆盖度的高估接近最大似然分类法的2倍。对两种改进的提取方法的精度进行比较,二者都可以有效提高测量精度,基于波段合成的纹理分类方法最佳。四种方法精度由高到低的顺序为:纹理结合RGB法考虑生物土壤结皮的最大似然分类法普通最大似然分类法RGB阈值法。     

唐家河国家级自然保护区川金丝猴冬季栖息地选择

2009年12月至2010年2月,对唐家河自然保护区内的一群(约60只)川金丝猴群采用直接跟踪观察,并结合植物样方调查对该猴群冬季栖息地选择进行了初步研究。根据猴群的活动位点,设置了75个20m×20m的植物样方,测定了12个生态因子(植被类型、乔木的胸径、郁闭度、乔木的高度、海拔、坡度、坡向、坡位、坡形、距水源距离、乔木密度、灌木盖度)。研究发现,冬季猴群主要在海拔2000～2500m、乔木平均胸径11～30cm、乔木平均树高为10～29m、乔木密度为20～40棵/20m×20m之间的落叶阔叶林和针阔混交林的阳坡中活动,还偏好在郁闭度为25%～49%、坡度为6°～20°、坡形为凸坡和复合坡、坡位为脊中部和下部、距水源距离0～300m的生境中活动。研究表明,冬季的食物资源、气候条件是影响川金丝猴群栖息地选择的主要生态因子。     

Structure of the woody vegetation in disturbed and undisturbed arid savanna,Botswana

The structure of woody vegetation was studied in little disturbed arid savanna and in adjacent over-grazed vegetation. In the over-grazed areas density and cover of woody plants were higher than in the less disturbed vegetation. The difference was accounted for by one species, Acacia mellifera, which was strongly dominant in the overgrazed vegetation. In the open savanna, the woody species varied in height from small shrubs to trees, while the dense shrub vegetation was of uniformly low stature.It is suggested that, while the differences in total abundance of woody species depend on differences in the amount of soil water available for woody growth, differences in species composition and height distribution are governed by the spatial and temporal distribution of water in the soil profile.     

红树林恢复初期莱氏锥滨螺分布动态

树栖腹足类动物是红树林底栖动物的重要组成部分,其组成和分布受到红树植被的影响。因此,在红树林生态修复中,腹足类动物的恢复依赖于植被的发育。滨螺科(Littorinidae)锥滨螺属(Mainwaringia)动物是亚洲红树林的广布种,但针对其在红树林中的分布及种群特征的研究较少,对红树林植被恢复过程中锥滨螺属动物的恢复动态更是鲜有研究。调查了厦门下潭尾湿地秋茄(Kandelia obovata)红树林恢复初期,新记录种莱氏锥滨螺(Mainwaringia leithii)种群恢复的时间动态,并分析其与植被参数的关系。研究发现,红树林恢复初期,秋茄植被生长迅速,株高、冠幅、基径和覆盖度分别由0.5年生幼林的41.3 cm、25.0 cm、1.04 cm和25%增长为8年生样地的179.2 cm、76.7 cm、5.96 cm和95%。在秋茄胚轴种植6个月左右开始记录到莱氏锥滨螺的个体,其密度和生物量在1.5 a后达到最大(分别为136个/m²和1.86 g/m²),而后逐渐降低,种植3 a后秋茄林内莱氏锥滨螺仅零星分布。除8年生的样地,莱氏锥滨...     

不同水氮条件下水稻冠层反射光谱与植株含水率的定量关系

研究了不同土壤水氮条件下水稻 (Oryzasativa) 冠层光谱反射特征和植株水分状况的量化关系。结果表明, 水稻冠层近红外光谱反射率随土壤含水量的降低而降低, 短波红外光谱反射率随土壤含水量的降低而升高。相同土壤水分条件下, 高氮水稻的冠层含水率高于低氮水稻的冠层含水率 ;同一水分条件下, 高氮处理的可见光区和短波红外波段光谱反射率低于低氮处理, 近红外波段光谱反射率高于低氮处理。发现拔节后比值植被指数 (R810 /R460 ) 与水稻叶片含水率和植株含水率呈极显著的线性相关, 模型的检验误差 (RootmeansquareError, RMSE) 分别为 0.93和 1.5 0。表明比值植被指数R810 /R460 可以较好地监测不同生育期水稻叶片和植株含水率。     

Differences in regeneration between hurricane damaged and clear-cut mangrove stands 25 years after clearing

The effect of human disturbance on mangrove forest may be substantially different from the effects of natural disturbances. This paper describes differences in vegetation composition and structure of five vegetation types in two mangrove areas near Darwin, Australia, 25 years after disturbance. The vegetation in clear-felled forest showed more adult Avicennia marina than in the hurricane-affected forest, and a virtual absence of A. marina juveniles and saplings. This indicates that A. marina will be replaced by other species in the canopy, showing a multi-phase vegetation development in mangrove forest after human disturbance. The mechanism of disturbance and the conditions after clearing therefore affects the vegetation composition for at least 25 years after this disturbance took place.