The relationship between water velocity,energetic costs,and microhabitat use in four North American stream fishes

Freshwater crayfish are key members of aquatic communities due to their large size and abundance. Although most commonly regarded as herbivores and detritivores, they are also selective predators. The crayfish plague fungus Aphanomyces astaci (Schikora) led to the elimination of a stock of white-clawed crayfish, Austropotamobius pallipes (Lereboullet) from Lough Lene, Co. Westmeath, in 1987. Samples taken of the flora and benthic communities of two Irish lakes, one (Lough Bane) formerly containing crayfish and the other (Lough Lene) immediately following a plague outbreak, were compared to similar samples taken a year later and ecological shifts were noted and compared to laboratory feeding results. Over time, Chara strands increased in mean length, and molluscs became more abundant.     

Extirpation or Coexistence? Management of a Persistent Introduced Grass in a Prairie Restoration

Abstract Introduced perennial grasses are one of the greatest constraints to prairie restoration. Herbicides suppress but do not eliminate introduced grasses, so we explored the interaction of herbicide with two additional controls: heavy clipping (to simulate grazing) and competition from native species. A 50‐year‐old stand of the introduced perennial grass Agropyron cristatum (crested wheatgrass) in the northern Great Plains was seeded with native grasses and treated with herbicide annually for 7 years in a factorial experiment. Clipping was applied as a subplot treatment in the final 3 years. Both herbicide and clipping significantly reduced the cover of A. cristatum, but clipping produced an immediate and consistent decrease, whereas herbicide control varied among years. The cover of A. cristatum decreased significantly with increasing cover of a seeded native grass, Bouteloua gracilis (blue grama), suggesting that both top‐down (i.e., grazing) and bottom‐up (i.e., resource competition) strategies can contribute to A. cristatum control. No treatment had any effect on the seed bank of A. cristatum. Even in the most effective control treatments, A. cristatum persisted at low amounts (approximately 5% cover) throughout the experiment. The cover of B. gracilis increased significantly with seed addition and herbicide, and, after 7 years, was similar to that in undisturbed prairie. The total cover of native species increased significantly with clipping and herbicide, and species richness was significantly higher in plots receiving herbicide. Clipping season had no effect on any variable. In summary, no method extirpated A. cristatum, but clipping reduced its cover by 90% and doubled the cover of native species. Extirpation might not be a realistic goal, but relatively simple management allowed coexistence of native species.     

The role a botanical institute can play in the conservation of the terrestrial biodiversity in a developing country

The need to integratein situ conservation into the planning process is outlined, and the importance of vegetation survey to determine conservation priorities and to identify areas suitable forin situ conservation is stressed. A case is presented, drawing on experience gained in Zimbabwe, of how a botanical institute can become an integral part of biological conservation. The institute should consist of a herbarium, a botanical garden, a gene bank and a vegetation survey unit. The function of each section, how they interlink, and how they can be integrated are discussed.     

典型矿区植被覆盖度时空分布特征及影响因素

植被状况可以直接或间接地反映采煤对生态环境的影响。以长河井工煤矿、离柳井工煤矿、平朔露天煤矿3个典型矿区为研究区域。以Landsat数据为数据源，基于地形调节植被指数的像元二分模型提取植被覆盖度；采用趋势分析、线性回归斜率、稳定性分析方法，分析了3个典型矿区2001-2016年植被覆盖度的时空变化特征；运用"以时间换空间"的方法，采用相关分析方法对植被覆盖度变化的自然影响因素进行了分析。结果表明：（1）近16年3个典型矿区植被覆盖度呈增加趋势，长河、离柳、平朔矿区的增长速率分别为0.09%/10 a、0.10%/10 a、0.08%/10 a（P > 0.05）。（2）空间上，长河、离柳、平朔矿区植被覆盖度变化不明显比例分别占到66.63%，59.90%，62.25%，呈增加趋势的比例仅分别占28.14%、32.55%、27.81%，而呈减少趋势的比例分别占到5.23%、7.55%、9.94%。长河矿区明显改善的区域位于自然植被和耕作区的北部和东北部，离柳矿区明显改善的区域位于以低植被覆盖度为主的北部，平朔矿区明显改善的区域位于复垦的中西部。（3）不区分植被类型时，3个矿区的植被覆盖度变化与高程、高程与温度的交互作用表现出显著相关性（P < 0.01），与各自然因素的相关性总体表现为长河 > 离柳 > 平朔矿区；区分植被类型时，草地与坡度的相关性不显著（P > 0.05），与降雨量、高程存在显著正相关（P < 0.05）；灌木林与温度相关性不显著，与高程和降雨量的交互作用存在显著正相关；旱地与高程、高程与温度的交互作用存在显著相关性；疏林地与坡向、降雨量与坡向坡度的交互作用均没有表现出相关性；有林地与高程降雨量的交互作用表现出显著正相关性。探讨不同植被类型对自然因素的响应，可为矿区植被结构的选择，矿区复垦提供参考依据。     

Canopy closure estimation in a temperate forest using airborne LiDAR and LANDSAT ETM+ data

Aims　Forest canopy closure is one of the essential factors in forest survey, and plays an important role in forest ecosystem management. It is of great significance to study how to apply LiDAR (light detection and ranging) data efficiently in remote sensing estimation of forest canopy closure. LiDAR can be used to obtain data fast and accurately and therefore be used as training and validation data to estimate forest canopy closure in large spatial scale. It can compensate for the insufficiency (e.g. labor-intensive, time-consuming) of conventional ground survey, and provide foundations to forest inventory.Methods　In this study, we estimated canopy closure of a temperate forest in Genhe forest of Da Hinggan Ling area, Nei Mongol, China, using LiDAR and LANDSAT ETM+ data. Firstly, we calculated the canopy closure from ALS (Airborne Laser Scanning) high density point cloud data. Then, the estimated canopy closure from ALS data was used as training and validation data to modeling and inversion from eight vegetation indices computed from LANDSAT ETM+ data. Three approaches, multi-variable stepwise regression (MSR), random forest (RF) and Cubist, were developed and tested to estimate canopy closure from these vegetation indices, respectively.Important findings The validation results showed that the Cubist model yielded the highest accuracy compared to the other two models (determination coefficient (R²) = 0.722, root mean square error (RMSE) = 0.126, relative root mean square error (rRMSE) = 0.209, estimation accuracy (EA) = 79.883%). The combination of LiDAR data and LANDSAT ETM+ showed great potential to accurately estimate the canopy closure of the temperate forest. However, the model prediction capability needs to be further improved in order to be applied in larger spatial scale. More independent variables from other remotely sensed datasets, e.g. topographic data, texture information from high-resolution imagery, should be added into the model. These variables can help to reduce the influence of optical image, vegetation indices, terrain and shadow and so on. Moreover, the accuracy of the LiDAR-derived canopy closure needs to be further validated in future studies.     

A Temporally Explicit Production Efficiency Model for Fuel Load Allocation in Southern Africa

Abstract We present a regional fuel load model (1 km² spatial resolution) applied in the southern African savanna region. The model is based on a patch-scale production efficiency model (PEM) scaled up to the regional level using empirical relationships between patch-scale behavior and multi-source remote sensing data (spatio-temporal variability of vegetation and climatic variables). The model requires the spatial distribution of woody vegetation cover, which is used to determine separate respiration rates for tree and grass. Net primary production, grass and tree leaf death, and herbivory are also taken into account in this mechanistic modeling approach. The fuel load model has been calibrated and validated from independent measurements taken from savanna vegetation in Africa southward from the equator. A sensitivity analysis on the effect of climate variables (incoming radiation, air temperature, and precipitation) has been conducted to demonstrate the strong role that water availability has in determining productivity and subsequent fuel load over the southern African region. The model performance has been tested in four different areas representative of a regional increasing rainfall gradient—Etosha National Park, Namibia, Mongu and Kasama, Zambia, as well as in Kruger National Park, South Africa. Within each area, we analyze model output from three different magnitudes of canopy coverage (<5, 30, and 50%). We find that fuel load ranges predicted by the model are globally in agreement with field measurements for the same year. High rainfall sustains green herbaceous production late in the dry season and delays tree leaf litter production. Effect of water on production varies across the rainfall gradient with delayed start of green material production in more arid regions.