不同地形条件下植被盖度信息提取技术研究

为系统地研究特定区域的植被盖度信息提取技术, 在不同的地形条件下, 比较了目前流行的多种高光谱遥感植被盖度提取方法。结果表明: 最优高光谱归一化植被指数(NDVI₁)的建模和验证精度均高于其他两种归一化植被指数(NDVI), 直接采用NDVI建立的回归模型对研究区植被盖度的估测能力低于像元二分模型; 阴坡的最佳模型为基于一阶微分的偏最小二乘回归模型(PLSR模型), 其建模决定系数(R²)为0.810, 均方根误差(RMSE)为6.29, 验证R²为0.773, RMSE为8.85; 阳坡的最佳模型为基于二阶微分的PLSR模型, 其建模R²为0.823, RMSE为6.04, 验证R²为0.801, RMSE为7.35; 平原的最佳模型为全受限的线性光谱混合分解模型(FCLS), 其验证R²为0.852, RMSE为5.86。     

内蒙古植被降水利用效率的时空格局及其驱动因素

植被降水利用效率(precipitation-use efficiency, PUE)是评价干旱、半干旱地区植被生产力对降水量时空动态响应特征的重要指标。该研究利用光能利用率CASA (Carnegie-Ames-Stanford Approach)模型估算了2001-2010年内蒙古地区植被净初级生产力(net primary productivity, NPP), 结合降水量的空间插值数据, 分析了近10年内蒙古地区植被PUE的空间分布、主要植被类型的PUE,及其时空格局的驱动因素。结果表明: 2001-2010年内蒙古地区所有植被的平均PUE为0.94 g C·m^-2·mm^-1, 且在105-120° E地带性规律明显,PUE上升速率为每10° 0.55 g C·m^-2·mm^-1。各植被类型间PUE差别较大, 其中灌丛PUE最高, 荒漠PUE最低。在不同的降水量区域, 植被PUE的空间分布与气候因子的关系有较大差别, 0-75 mm降水量区间内, PUE随降水量、气温的升高显著下降(R² = 0.226, p < 0.05); 175-300 mm降水量区间内, 植被 PUE的空间变化与降水量和气温呈极显著相关关系(R² = 0.878, p < 0.001), 且随降水量的增加显著上升( R² = 0.94, p < 0.001), 变化速率约为每100 mm降水0.57 g C·m ^-2·mm^-1; 在降水量大于475 mm的区域, 植被PUE的空间分布与降水量、气温的相关性显著(R² = 0.19, p < 0.05), 且随着气温的上升、降水量的下降而增加, 其中气温的贡献是降水量的8.61倍。在不同的降水量区域, 植被 PUE的年际波动与气候因子的关系也有较大差别, 对于年降水量0-220 mm的地区, PUE的年际波动与降水量呈正相关性、与气温呈负相关性; 在年降水量为220-310 mm的地区, PUE的年际波动主要受降水量的控制, 受气温影响较小; 在年降水量>310 mm的地区,PUE的年际波动与降水量、气温均呈正相关关系, 但在降水量越高的地区, PUE的年际波动与降水量的相关性越弱, 与气温的相关性越强。植被覆盖度与PUE的空间分布极显著相关(R² = 0.73, p < 0.001), 且与 PUE的年际波动也存在线性相关关系(R² = 0.11, p < 0.001); 叶面积指数( LAI)与PUE的年际波动呈线性相关关系(R² = 0.42, p < 0.001), 而当 LAI < 3.15时, PUE的空间分布随LAI增加而呈线性增加。     

利用聚类算法监测森林乔木物种多样性

该研究基于机载激光雷达(LiDAR)和高光谱数据, 从森林物种叶片的生理化学源头探寻生化特征与光谱特征的内在关联, 探讨生化多样性、光谱多样性与物种多样性之间的响应机制, 选择最优植被指数并结合最优结构参数, 通过聚类方法构建森林物种多样性遥感估算模型, 在古田山自然保护区开展森林乔木物种多样性监测。研究结果表明: (1)从16种叶片生化组分中, 筛选出叶绿素a、叶绿素b、类胡萝卜素、叶片含水量、比叶面积、纤维素、木质素、氮、磷和碳可通过偏最小二乘法用叶片光谱有效模拟(R² = 0.60-0.79, p < 0.01), 并选择有效的植被指数: 转换型吸收反射指数/优化型土壤调整指数(TCARI/OSAVI)、类胡萝卜素反射指数(CRI)、水波段指数(WBI)、比值植被指数(RVI)、生理反射指数(PRI)和冠层叶绿素浓度指数(CCCI)表征相应的最优生化组分; (2)基于机载LiDAR数据利用结合形态学冠层控制的分水岭算法获得高精度单木分离结果(R ² = 0.77, RMSE = 16.48), 同时采用逐步回归方法从常用的森林结构参数中选取树高和偏度作为最优结构参数(R ² = 0.32, p < 0.01); (3)基于6个最优植被指数和2个最优结构参数, 以20 m × 20 m为窗口通过自适应模糊C均值方法进行聚类, 实现了研究区森林乔木物种丰富度(Richness, R ²= 0.56, RMSE = 1.81)和多样性指数Shannon-Wiener (R ² = 0.83, RMSE = 0.22)与Simpson (R ² = 0.85, RMSE = 0.09)的成图。该研究在冠层尺度上获取了与物种多样性相关的生化、光谱和结构参数, 将单木个体作为最小单元, 利用聚类算法直接估算物种类别差异, 无需判定具体的树种属性, 是利用遥感数据进行区域尺度森林物种多样性监测与成图的实践, 可为亚热带地区常绿阔叶林的物种多样性监测提供借鉴。     

Forest species diversity mapping based on clustering algorithm

该研究基于机载激光雷达(LiDAR)和高光谱数据, 从森林物种叶片的生理化学源头探寻生化特征与光谱特征的内在关联, 探讨生化多样性、光谱多样性与物种多样性之间的响应机制, 选择最优植被指数并结合最优结构参数, 通过聚类方法构建森林物种多样性遥感估算模型, 在古田山自然保护区开展森林乔木物种多样性监测。研究结果表明: (1)从16种叶片生化组分中, 筛选出叶绿素a、叶绿素b、类胡萝卜素、叶片含水量、比叶面积、纤维素、木质素、氮、磷和碳可通过偏最小二乘法用叶片光谱有效模拟(R² = 0.60-0.79, p < 0.01), 并选择有效的植被指数: 转换型吸收反射指数/优化型土壤调整指数(TCARI/OSAVI)、类胡萝卜素反射指数(CRI)、水波段指数(WBI)、比值植被指数(RVI)、生理反射指数(PRI)和冠层叶绿素浓度指数(CCCI)表征相应的最优生化组分; (2)基于机载LiDAR数据利用结合形态学冠层控制的分水岭算法获得高精度单木分离结果(R ² = 0.77, RMSE = 16.48), 同时采用逐步回归方法从常用的森林结构参数中选取树高和偏度作为最优结构参数(R ² = 0.32, p < 0.01); (3)基于6个最优植被指数和2个最优结构参数, 以20 m × 20 m为窗口通过自适应模糊C均值方法进行聚类, 实现了研究区森林乔木物种丰富度(Richness, R ²= 0.56, RMSE = 1.81)和多样性指数Shannon-Wiener (R ² = 0.83, RMSE = 0.22)与Simpson (R ² = 0.85, RMSE = 0.09)的成图。该研究在冠层尺度上获取了与物种多样性相关的生化、光谱和结构参数, 将单木个体作为最小单元, 利用聚类算法直接估算物种类别差异, 无需判定具体的树种属性, 是利用遥感数据进行区域尺度森林物种多样性监测与成图的实践, 可为亚热带地区常绿阔叶林的物种多样性监测提供借鉴。     

亚热带地区常绿阔叶林SPAC系统水分的氢氧稳定同位素特征

森林的土壤-植物-大气连续体(SPAC)是陆地重要的水循环连续界面过程。本研究通过分析亚热带常绿阔叶林的降水、大气水汽、土壤水、叶片水的同位素组成,探讨森林SPAC系统水分的氢氧同位素组成特征以及植物蒸腾与叶片性状和环境因子的关系。结果表明: 研究区大气降水、土壤水、竹柏枝条水、竹柏叶片水和大气水汽的δD-δ¹⁸O线性回归方程分别为: δD_P=7.97δ¹⁸O_P+12.68(R²=0.97)、δD_S=4.29δ¹⁸O_S-18.62(R²=0.81)、δD_B=3.31δ¹⁸O_B-29.73(R²=0.49)、δD_L=1.49δ¹⁸O_L-10.09(R²=0.81)、δD_V=3.89δ¹⁸O_V-51.29(R²=0.46)。在降水→土壤水→植物水的界面水输送过程中,氢氧同位素逐渐富集,而从土壤蒸发和从植物蒸腾的水汽同位素贫化。在降水和蒸发作用的影响下,土壤水同位素随深度增加有贫化的趋势,而且整体上旱季土壤水同位素比雨季富集。观测期间,枝条水同位素比土壤水略微富集,说明水分在植物体内运输过程中存在受到蒸腾富集作用的可能性。旱季,乔木的枝条水同位素比灌木贫化,说明根系分布更深的乔木植物更倾向于利用深层土壤水。由于在叶片性状、蒸腾速率以及对环境因子的响应程度等方面存在差异,不同植物的叶片水同位素组成随叶龄增长的变化特征有所不同。雨季的环境条件更有利于叶片蒸腾,使雨季的叶片水同位素比旱季富集。叶片水同位素组成与植物叶片含水量呈正相关关系,与相对湿度呈负相关关系,综合反映了植物应对环境变化的水分调控功能。     

温带-亚热带栓皮栎种子形态的变异及其与环境因子的关系

在区域尺度上(25.14°-40.25° N, 99.87°-122.07° E), 采集20个栓皮栎(Quercus variabilis)种群的种子样品, 测定种宽、种长, 并计算宽长比形态指标, 探讨了区域尺度上种子形态变异特点及其与环境因子的关系。结果表明, 栓皮栎种子的宽度和长度变化幅度分别为1.21-2.18 cm和1.20-2.96 cm; 宽长比的变化幅度为0.57-1.10。栓皮栎的种宽与种长呈显著的正相关关系。单因素方差分析表明, 种宽、种长和宽长比在种群间差异显著(p < 0.001)。种长与等效纬度呈负线性(R² = 0.18; p = 0.05), 与经度呈凸型的变异关系(R² = 0.43; p = 0.009)。种宽和种长与最热月平均气温呈极显著正相关(R² = 0.35; p = 0.006; R² = 0.30; p = 0.012), 而与最湿季降水量呈显著负相关(R² = 0.28, p = 0.019; R² = 0.24, p = 0.017)。种子宽长比没有明显的变化趋势, 大致趋于恒定(0.88 ± 0.08)。     

基于辐射和温度热效应的温室水果黄瓜叶面积模型

依据温室黄瓜(Cucumis sativus)叶片生长与温度和辐射的关系,构建了适合我国种植技术的黄瓜叶面积模拟模型,并利用不同品种、播期的试验资料对模型进行了检验。结果表明,该模型比传统的积温法和比叶面积法更准确地模拟温室水果黄瓜的叶面积。该模型对黄瓜叶面积指数的模拟结果与1∶1直线之间的决定系数R²和回归估计标准误差RMSE分别为0.879 2和0.398 0,比用积温法和比叶面积法模拟叶面积指数的精度分别提高了37%和74%。     

极端干旱区多枝柽柳叶片气孔导度的环境响应模拟

气孔通过调节植物体水分散失和CO₂吸收在植物适应环境变化和环境胁迫中发挥重要作用。该文在对极端干旱区多枝柽柳(Tamarix ramosissma)叶片气体交换参数观测的基础上, 引入诊断函数f(H)对BWB模型和BBL模型提出的气孔导度(g_s)模型中的空气湿度(h_s或D_s)进行了评价, 并将评价结果引入叶子飘和于强推导出的g_s机理模型。结果表明: (1) BWB和BBL模型对h_s (或D_s)的模拟效果存在很大差异: BWB模型拟合效果较好(R² = 0.5354), BBL模型的结果显著但效果较差(R² = 0.1103)。试验结果显示: 随h_s(或D_s)的增大, g_s呈先增大后减小的趋势, 可用Gauss模型进行拟合, R²分别为0.593和0.258, 说明g_s与h_s的关系要比D_s更密切; (2)叶子飘和于强给出的简化模型(Simple模型)和该文给出的指数模型(Gauss-h模型)均具有较好的模拟效果(R²分别为0.8707和0.8286), η值分别为0.1245和0.0171, 其值均介于0-1之间; (3)模型验证中Gauss-h模型较Simple模型明显低估了观测值, 当观测条件无限趋近于Simple模型的假设时, Simple模型的拟合效果可得到显著提高(R² = 0.9606)。     

一种基于数码相机图像和群落冠层结构调查的草地地上生物量估算方法

草地地上生物量是影响其生态系统功能最重要的因素之一, 也是草地生态学研究中不可或缺的监测指标。草地地上生物量监测多采用收割法进行, 但这种破坏性取样方法会对研究区域带来巨大干扰, 尤其是面积较小的长期定位监测或者控制实验研究样地, 从而使得地上生物量监测的频次受到很大限制。因此, 通过获取某些原位易测变量, 建立地上生物量的估算方法具有重要意义。该研究依托内蒙古典型草地刈割控制实验平台, 通过数码照片获取不同土地利用方式下的植被覆盖度, 并对样方内的叶面积指数、植被高度、物种多样性等参数进行了测定, 最后利用一元回归模型、逐步回归模型和随机森林模型对地上生物量进行估算。结果表明, 植被覆盖度、叶面积指数、植被平均高度、植被最大高度和物种丰富度是影响地上生物量的主要驱动因素。通过构建适宜于本地的逐步回归模型, 可以实现草地地上生物量的准确预测。在该研究区域中, 预测模型的决定系数(R²) = 0.91, 均方根误差(RMSE) = 35.60 g·m^-2。该研究提供了一种快速、准确且非破坏性测定草地地上生物量的方法, 可作为传统收割法的有效补充。     

基于无人机的冬小麦拔节期表层土壤有机质含量遥感反演

快速监测大面积分布的盐渍化麦田土壤有机质含量,可为推进盐渍土改良和促进碳循环研究提供数据支撑。通过野外采样与获取无人机遥感影像,分别基于裸土和植被情况,采用多元线性回归(MLR)、偏最小二乘回归(PLSR)和支持向量机回归(SVR)3种方法,建立区域有机质含量遥感模型,并进行检验和对比,确定最优的土壤有机质含量反演模型;最后基于最优模型进行研究区表层土壤有机质的反演,并与插值结果进行比较。结果表明: 经5×5的中值滤波处理后的光谱与土壤表层有机质对应最优;3种模型中,SVR模型的预测精度最高,PLSR次之,MLR效果最差。对比两种变量的建模效果,基于植被的SVR建模效果最好,其建模决定系数(R²)、均方根误差(RMSE)分别为0.89、0.20,验证R²、RMSE分别为0.82、0.24;基于裸土的建模效果不理想,最优的也是SVR模型,其建模R²、RMSE分别为0.63、0.26,验证R²、RMSE分别为0.61、0.25。根据最优模型反演得到该区域有机质含量为17.51～22.53 g·kg^-1,平均值为19.51 g·kg^-1,与实地调查结果较为一致;插值结果与反演结果相比,精度受到限制。综上,基于无人机多光谱可以对盐渍土冬小麦拔节期土壤有机质含量进行快速、大范围精准估测。     

干旱区植物叶片大小对叶表面蒸腾及叶温的影响

利用热及物质交换原理, 并结合前人研究成果, 在单叶尺度上建立了简单的叶温和水气蒸腾模型。模型通过预设值驱动, 预设值参照干旱区环境及植物叶片特征设置。模拟结果显示: 随气孔阻力的增加, 叶片蒸腾速率降低, 叶温升高; 同一环境下, 具有低辐射吸收率的叶片蒸腾速率和叶温更低, 并且气孔阻力越大, 这种差异越明显。另外, 叶片宽度及风速是影响叶片蒸腾及叶温的重要因子。干旱地区植物生长季节, 风速小于0.1 m·s ^-1、气孔阻力接近1000 s·m ^-1时, 降低叶片宽度不仅有利于降低叶片温度, 而且能够降低叶片蒸腾速率, 从而实现保持水分, 增强植物适应高温、干旱的能力。     

The Heat and Mass Transfer Analysis of a Leaf

Understanding the heat and mass transfer processes of plant leaves is essential for plant bionic engineering. A general thermophysical model was established for a plant leaf with particular emphasis on the transpiration process. The model was verified by the field measured stomatal resistance and temperature of a camphor leaf. A dynamical simulation revealed that diurnal transpiration water consumption is dominated by the solar irradiance and the day-average temperature of the leaf is dominated by the ambient air temperature; transpiration plays an important role in the cooling of the leaf, in average it could dissipate around 32.9% of the total solar energy absorbed by the leaf in summer. To imitate the thermal infared characteristic of the real leaf, the up surface of the bionic leaf must have emissivity and solar absorptivity close to those of a real leaf and its shape and surface roughness must be similar to those of the real leaf. The key point is that the bionic leaf must be able to evaporate water to simulate the transpiration of a plant leaf, appropriate adsorbent can be used to realize this function.     

Effect of temperature on drought resistance and growth of cotton plants

In cotton plants ( Gossypium hirsutum L. cv. B.J.A.) the temperature of the roots affected both root and shoot growth, as did the temperature of the shoot. Drought resistance increased when the temperature imposed on roots (27°C) was lower than that imposed on shoots (17°C); the result was a decrease in both transpiration and flow of root sap. Stomatal characteristics as measured by density, index and resistance, depended only on shoot temperature. Differences in drought resistance, depended only on shoot temperature. Differences in drought resistance seem to be a result of changes in transpiration flow modulated by the amount of absorbed water.     

Transpiration directly regulates the emissions of water‐soluble short‐chained OVOCs

Most plant‐based emissions of volatile organic compounds are considered mainly temperature dependent. However, certain oxygenated volatile organic compounds (OVOCs) have high water solubility; thus, also stomatal conductance could regulate their emissions from shoots. Due to their water solubility and sources in stem and roots, it has also been suggested that their emissions could be affected by transport in the xylem sap. Yet further understanding on the role of transport has been lacking until present. We used shoot‐scale long‐term dynamic flux data from Scots pines (Pinus sylvestris) to analyse the effects of transpiration and transport in xylem sap flow on emissions of 3 water‐soluble OVOCs: methanol, acetone, and acetaldehyde. We found a direct effect of transpiration on the shoot emissions of the 3 OVOCs. The emissions were best explained by a regression model that combined linear transpiration and exponential temperature effects. In addition, a structural equation model indicated that stomatal conductance affects emissions mainly indirectly, by regulating transpiration. A part of the temperature's effect is also indirect. The tight coupling of shoot emissions to transpiration clearly evidences that these OVOCs are transported in the xylem sap from their sources in roots and stem to leaves and to ambient air.     

基于冠层温湿度模型的日光温室黄瓜霜霉病预警方法

利用温室环境参数构建室内微环境模拟模型,并结合温室病害模型进行预警,便于开展病害生态防治,以减少农药使用,从而保护温室生态环境和保证农产品质量安全.本文利用温室内能量守恒原理和水分平衡原理,构建了日光温室冠层叶片温度和空气相对湿度模拟模型.叶片温度模拟模型考虑了温室内植物与墙体、土壤、覆盖物之间的辐射热交换,以及室内净辐射、叶片蒸腾作用引起的能量变化;相对湿度模拟模型综合了温室内叶片蒸腾、土壤蒸发、覆盖物与叶面的水汽凝结引起的水分变化.将温湿度估计模型输出值作为参数,输入黄瓜霜霉病初侵染和潜育期预警模型中,估计黄瓜霜霉病发病日期,并与田间观测的实际发病日期比较.试验选取2014年9月和10月的温湿度监测数据进行模型验证,冠层叶片温度实际值与模拟值的均方根偏差（RMSD)分别为0.016和0.024 ℃,空气相对湿度实际值与模拟值的RMSD分别为0.15%和0.13%.结合温湿度估计模型结果表明,黄瓜病害预警系统预测黄瓜霜霉病发病日期与田间调查发病日期相吻合.本研究可为黄瓜日光温室病害预警模型及系统构建提供微环境数据支持.     

Model-Assisted Analysis of Spatial and Temporal Variations in Fruit Temperature and Transpiration Highlighting the Role of Fruit Development

Fruit physiology is strongly affected by both fruit temperature and water losses through transpiration. Fruit temperature and its transpiration vary with environmental factors and fruit characteristics. In line with previous studies, measurements of physical and thermal fruit properties were found to significantly vary between fruit tissues and maturity stages. To study the impact of these variations on fruit temperature and transpiration, a modelling approach was used. A physical model was developed to predict the spatial and temporal variations of fruit temperature and transpiration according to the spatial and temporal variations of environmental factors and thermal and physical fruit properties. Model predictions compared well to temperature measurements on mango fruits, making it possible to accurately simulate the daily temperature variations of the sunny and shaded sides of fruits. Model simulations indicated that fruit development induced an increase in both the temperature gradient within the fruit and fruit water losses, mainly due to fruit expansion. However, the evolution of fruit characteristics has only a very slight impact on the average temperature and the transpiration per surface unit. The importance of temperature and transpiration gradients highlighted in this study made it necessary to take spatial and temporal variations of environmental factors and fruit characteristics into account to model fruit physiology.     

滴灌条件下温室番茄需水量估算模型

基于修正后的Pnman-Monteith方程,通过分析作物系数与积温的关系,构建了基于常规气象资料的滴灌条件下温室番茄需水量估算模型,并分别采用2009年5月2-13日(开花坐果期)和6月9-20日(成熟采摘期)2个时段内的实测蒸腾量和实测棵间土壤蒸发量对模型模拟结果进行验证.结果表明:修正后的Penman-Monteith方程适用于温室参考作物需水量(ET0)的计算;温室番茄作物系数与积温呈抛物线关系;所建需水量模型模拟值的平均相对误差小于10%,可用于估算滴灌条件下温室番茄需水量.     

Changes in diffusion resistance of apple leaves undergoing rapid fluctuations in leaf temperature

Transpiration was measured in apple leaves (Malus sylvestris Mill.) which were enclosed in a leaf chamber and subjected to rapid changes in leaf temperature. Fluctuations in leaf temperature produced parallel fluctuations in transpiration. The change in transpiration rate with change in temperature was found to be less than the theoretical value calculated from the change in water vapour density gradient from leaf to air. The results suggest the presence of a small and rapidly varying resistance to water vapour loss from the leaf. The magnitude of this additional resistance increased to a maximum value of approximately 1.5 s cm^-1 as the magnitude of the temperature change increased to a maximum of approximately 12°C.     

干热河谷主要植被恢复树种蒸腾作用

以金沙江干热河谷区10多种自然生长树种为试材,探讨了不同季节典型晴天里各树种叶片水平的蒸腾速率日动态规律,以揭示极端干热生境条件下供试树种蒸腾作用的动态特征.实验结果表明:在干旱生境(3月份)转向干热生境(5月份)时,大多数供试树种蒸腾速率的日变化峰值有所提前,蒸腾作用受到明显限制,而当干热胁迫解除、湿润生境(10月份)来临时,蒸腾作用受限程度减轻或消失,多数供试树种呈现出比较典型的峰状曲线;在干旱、干热以及湿润季节里,供试树种均可分为高、亚高、亚低和低蒸腾速率树种等4个类别,且随着季节的变化,树种所属类别或蒸腾速率大小排序存在明显变动,体现了树种特性在水分生理反应上的多样性表达;随着干热胁迫的加深,供试树种蒸腾速率的变化可分为增强型、减弱型及稳定型3种;树种蒸腾速率的变化方向与气孔导度的变化方向存在不一致的现象,树种蒸腾速率的季节性增减可能表现为气孔因素为主与非气孔因素为主两种控制形式.     

Effect of air and soil temperature on water balance of jojoba growing under controlled conditions

Jojoba [ Simmondsia chinensis (Link) Schneider] cuttings were grown in pots under constant light intensity and vapour pressure deficit at wir temperatures of 18 and 27°C in climate-controlled cabinets. Leaf conductance and transpiration rate decreased exponentially as the xylen water potential (Ψ_x) decreased concurrently with the drying out of the soil. At high Ψ_x'leaf conductance and transpiration rate were much higher at the higher air temperature, and as Ψ_x declined both parameters decreased more rapidly at 27°C than at 18°C. When soil temperatures were decreased from 27 to 13°C, leaf water potential was not affected at either air temperatures, but transpiration rate was reduced. A linear negative correlation was found between transpiration rates and soil temperatures. It is suggested that the low soil temperature may restrict reducion of water flux in turn reduces stomatal conductance and transpiration without affecting the water potential in the shoot. The releavance of the response to changes in soil or air temperature to the performance of the plant in its semi-arid habitat is discussed.