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.     

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。     

Vascular plant species richness along latitudinal and altitudinal gradients: a contribution from New Zealand temperate rainforests

Vascular plant species richness is known to often decrease with both increasing latitude and increasing altitude. However, a number of studies have shown the reverse trend and the primary cause of these gradients remains unknown. In the present work, generalized linear models were used to assess the relative importance of latitude and altitude as well as of a number of other factors (mean annual precipita-tion, slope, substrate and forest type) on species richness in temperate rainforests of New Zealand. The effect of Southern beech ( Nothofagus spp.) as dominant canopy species on total species richness was shown to be much smaller than postulated in most previous studies. Within the region studied, altitude had by far the strongest effect on species richness. This effect was independent of latitude and was significant for woody but not for herbaceous vegetation.     

Bird sensitivity to disturbance as an indicator of forest patch conditions: An issue in environmental assessments

An Environmental Assessment (EA) is one of the steps within the Environmental Impact Assessment process. Birds are often used in EA to help decision makers evaluate potential human impacts from proposed development activities. A “sensitivity to human disturbance” index, created by Parker III et al. (1996) for all Neotropical species, is commonly considered an ecological indicator. However, this parameter was created subjectively and, for most species, there have been no rigorous field test to validate its effectiveness as such. Therefore, in this study, we aim to: (1) evaluate if, at the local scale, birds from forest patches in a human-modified landscape (HML) may differ in sensitivity from Parker's sensitivity classification; (2) evaluate the effectiveness of the species richness value at each sensitivity level as an ecological indicator; (3) gather information on how often and in which manner Parker's classification has been used in EA. To do so, bird sampling was performed in eight forest patches in a HML over one year. Then, we created a local sensitivity to disturbance using information about threat, endemism, spatial distribution and relative abundance of all species in the study area. We found that 37% of the forest birds showed different local sensitivity levels when compared with Parker's classification. Our results show that only the richness of high-sensitivity species from our local classification fitted the ecological indicator assumptions helping the environmental conditions evaluation of the studied patches. We conclude that species richness of each Parker's bird sensitivity levels do not necessarily perform as an ecological indicator at the local scale, and particularly in HML. Nevertheless, Parker's Neotropical bird sensitivity classification was used in 50% of EA we reviewed. In these, 76% assumed that it was an accurate ecological indicator of the local forest conditions for birds. The lack of clear criteria used in Parker's classification allows diverse interpretations by ornithologists, and there is no agreement about the ecological meaning of each sensitivity level and what environmental conditions each level may indicate of. Therefore, the use of Parker's classification in EA may jeopardize accurate interpretations of proposed anthropogenic impacts. Furthermore, because a bird species’ sensitivity often varies between locations, we argue that Parker's generalized classification of bird sensitivity should not be used as an indicator of forest environmental conditions in EA throughout HMLs in Neotropics. Rather, local bird ecological indices should be explored, otherwise, erroneous predictions of the anthropogenic impacts will continue to be common.     

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.