European Farmland Bird Distribution Explained by Remotely Sensed Phenological Indices

Birds are important components of biodiversity conservation since they are capable of indicating changes in the general status of wildlife and of the countryside. The Pan-European Common Bird Monitoring Scheme (PECBM) has been launched by the BirdLife Partnership in Europe, where the European Bird Census Council has been collecting data from 20 independent breeding bird survey programs across Europe over the last 25 years. These data show dramatic declines in European farmland birds. We suggest that seasonal characteristics of vegetation cover derived from high temporal resolution remote sensing images could facilitate the monitoring the suitability of farmland bird habitats, and that these indicators may be a better choice for monitoring than climate data. We used redundancy analysis to link the PECBM data of the estimated number of farmland birds in Europe to a set of phenological and climatic indicators and to the biogeographic regions of Europe. Variance partitioning was used to account for the variation explained by the phenological and climate variables and by the area of the environmental strata individually, to define the pure effect of the variables, and to extract the total explained variance. The analysis revealed high statistical significance (p < 0.001) of the correlations between species and environment. Phenological indices explained 38% of the variance in community composition of the 23 farmland bird species, whereas climate explained 30% of the variance. After partitioning the other variables as covariables, the pure effect of phenology, climate, and environmental strata were 16%, 8%, and 16%, respectively. Based on the probability results, we suggest that phenological indicators derived from remote sensing may supply better indicators for continental scale biodiversity studies than climate only. In addition, these indicators are cost and time effective, are on continuous scale, and are readily repeatable on a large spatial coverage while supplying standardized results.     

Variations in seasonal phytoplankton assemblages as a response to environmental changes in the surface waters of a hypo saline coastal station along the Bhagirathi�CHooghly estuary

Due to the close proximity of the Bay of Bengal and the freshwater inflow of Bhagirathi-Hooghly, Diamond Harbour appeared as an important coastal station of the Bhagirathi-Hooghly estuary. The spatial and temporal composition and abundance of microphytoplankton species was examined in relation to physical and chemical surface water variables (i.e., salinity, nutrient, and temperature).The primary objective of the study was to observe the variations in phytoplankton species assemblages as a response to environmental variables. Hierarchical cluster analysis and non-metric multidimensional scaling were used to find out distinct seasonal groups based on the composition of phytoplankton. The results indicate that several key environmental factors like temperature, DIN content, and molar ratio of nutrients like DIN-DIP and DIN-DSi influenced seasonal phytoplankton assemblages within the estuary. The distribution of phytoplankton population showed two main groups where the blue-green and green algal populations favored the warmer conditions of summer and monsoon months, whereas the diatom population primarily flourished in the cooler months of autumn and winter.     

Live diatoms as indicators of urban stormwater runoff

Diatom bioassessment of streams/rivers does not distinguish between live (cells with intact chloroplasts) and dead (empty cells) individuals, even though most diatom samples collected from the field will be composed of a mixture of both. This study aimed to evaluate whether percentage of live diatoms (PLD), live diatom density and chlorophyll a, and diatom species compositions can be used as indicators of hydrologic disturbance in an urban stream. We deployed artificial substrates on a monthly basis and collected periphyton samples weekly over the course of one calendar year (n = 182) in three tributaries of urbanized Ruddiman Creek (Michigan, USA). We also collected samples before and after six major storm events (>0.5 cm rain). We found no temporal patterns in PLD (Mann-Kendall test p > 0.05) or species composition (non-metric multidimensional scaling (NMDS) ordination), which may be explained by a diatom composition already tolerant to frequent disturbance. There was no difference in PLD before and after storm events, which might partially be explained by their disturbance resistance due to different assemblage ages (1, 2, and 4 weeks old) before the storms. High flow had differential effects on diatom species; loosely attached Navicula and Nitzschia species were more easily removed compared to stalk-forming Gomphonema parvulum. The most important environmental variable that was found to affect live diatom density and chlorophyll was stream width, which has an indirect effect (as a measure of discharge) on periphyton assemblages. In conclusion, PLD was found to be unsuitable metric for assessing stormwater runoff in urban streams where periphyton may not have enough time to form mature communities.     

湖泊微生物群落构建机制及研究展望

湖泊微生物生态过程研究是深入了解湖泊生态系统结构与功能的关键。论述了湖泊微生物多样性时空分布规律及群落构建机制研究进展,总结了微生物群落构建机制的分析方法,介绍了微生物生态网络构建原理及应用。群落构建机制分析方法分为统计分析法、模型推断法和生态网络分析法。统计分析法包括群落结构差异分析、群落结构-环境因子关联分析和方差分解分析等,此类方法能够初步识别驱动群落组成与结构时空差异的影响因子,判别空间因素与已知环境变量对群落构建过程的相对贡献;模型推断法包括中性群落模型方法和零模型方法等,能够进一步实现对群落构建生态过程的区分,量化和比较随机性因素及确定性因素的相对重要性;生态网络分析法可用于揭示物种共现模式,探究作为确定性因素的生物相互作用,也可用于物种-环境响应关系的研究,探究环境选择过程对群落结构的影响。     

Large and mesoscale meteo-oceanographic patterns in local responses of biogeochemical concentrations

Investigations surrounding the variability of productivity in upwelling regions are necessary for a better understanding the physical-biological coupling in these regions by monitoring systems of environmental impacts according to the needs of the regional coastal management. Using a spatial and temporal database from National Centers for Environmental Prediction (NCEP) and National Center for Atmospheric (NCAR) Research reanalysis, Quick Scatterometer vector wind, and surface stations from the Southeast coast of Brazil, we investigate the meteorological influences due to the large-scale systems in the variability of the nutrient and larvae concentration, and chlorophyll a, describing statistically relationships between them in upwelling regions. In addition, we used multivariate analysis, such as PCA and clustering to verify spatial and temporal variances and describe more clear the structure and composition of the ecosystem. Correlation matrix analyses were applied for different water masses present in the study area to identify the relations between physical and biogeochemical parameters in a region, where frequently upwelling occur. Statistical approaches and seasonal variability show that the period of November to March is more sensitive to nutrients (1.20?mg/m(3) for chlorophyll a, 2.20?μmol/l for total nitrogen and 5.5?ml/l for DO) and larvae concentrations (120 org/m(3) for most of the larvae, except for cirripedia that presented values around 370 org/m(3)) relating to the influence of large and mesoescale meteorological patterns. The spatial and temporal variables analyzed with multivariate approach show meaningful seasonality variance of the physical and biological samples, characterizing the principal components responsible for this variance in spring and summer (upwelling period), emphasizing the monitoring of species as crustaceans and mussels that are present in the local economy. Then, the spring and summer season are characterized by high productivity due to the occurrence of upwelling in this period.     

CORINE land cover and floristic variation in a Mediterranean wetland

The aims of the present study were to: (1) investigate whether CORINE land cover classes reflect significant differences in floristic composition, using a very detailed CORINE land cover map (scale 1:5000); (2) decompose the relationships between floristic assemblages and three groups of explanatory variables (CORINE land cover classes, environmental characteristics and spatial structure) into unique and interactive components. Stratified sampling was used to select a set of 100-m(2) plots in each land cover class identified in the semi-natural wetland surrounding a lake in central Italy. The following six classes were considered: stable meadows, deciduous oak dominated woods, hygrophilous broadleaf dominated woods, heaths and shrublands, inland swamps, canals or watercourses. The relationship between land cover classes and floristic composition was tested using several statistical techniques in order to determine whether the results remained consistent with different procedures. The variation partitioning approach was applied to identify the relative importance of three groups of explanatory variables in relation to floristic variation. The most important predictor was land cover, which explained 20.7% of the variation in plant distribution, although the hypothesis that each land cover class could be associated with a particular floristic pattern was not verified. Multi Response Permutation Analysis did not indicate a strong floristic separability between land cover classes and only 9.5% of species showed a significant indicator value for a specific land cover class. We suggest that land cover classes linked with hygrophilous and herbaceous communities in a wetland may have floristic patterns that vary with fine scale and are not compatible with a land cover map.     

Biomonitoring acidic drainage impact in a complex setting using periphyton

Acid mine drainage (AMD) often exerts various environmental pressures on nearby water courses: chemical stress from low pH and dissolved metals; physical stress from metal oxide deposits. Affected streams can thus display a spatially variable combination of stress agents that may complicate its biomonitoring using native communities such as periphyton. Here, we have measured water and periphyton variables in four streams that surround an abandoned copper mine to determine which periphyton attributes consistently detected AMD impact in a complex environmental setting. Seventeen years after the end of commercial exploitation, the abandoned mine still decreases water quality in nearby streams: moderate acidification, very high metal load (Al, Ni, Cu, Zn), and a conspicuous presence of metal oxide deposits with diverse composition. Even under the resultant complex pattern of polluted conditions, periphyton was a reliable bioindicator of AMD. Epilithic diatom taxa tolerant of acidic conditions increased in AMD sites and, at severely impacted locations, species richness decreased. Also, algal biomass may have been negatively affected in some stream reaches affected by metal oxide deposits. Other periphyton attributes (total biomass, diatom diversity) seemed mostly unrelated to AMD. Diatom assemblage composition was the most sensitive and consistent bioindicator of mine drainage; besides, it rendered a biological assessment of AMD impact that largely coincided with the physicochemical evaluation. Still, including other taxonomic (proportion of acid-tolerant diatom species, diatom richness) and non-taxonomic (algal biomass) attributes in the biomonitoring procedure rendered a more comprehensive assessment of the negative consequences generated by AMD.     

Visually determined stream mesohabitats influence benthic macroinvertebrate assessments in headwater streams

Mesohabitat components such as substrate and surface flow types are intimately related to benthic macroinvertebrate assemblages in streams. Visual assessments of the distribution of these components provide a means of evaluating physical habitat heterogeneity and aid biodiversity surveys and monitoring. We determined the degree to which stream site and visually assessed mesohabitat variables explain variability (i.e., beta-diversity) in the relative abundance and presence-absence of all macroinvertebrate families and of Ephemeroptera, Plecoptera, and Trichoptera (EPT) genera. We systematically sampled a wide variety of mesohabitat arrangements as they occured in stream sites. We also estimated how much of the explanation given by mesohabitat was associated with substrate or surface flow types. We performed variation partitioning to determine fractions of explained variance through use of partial redundancy analysis (pRDA). Mesohabitats and stream sites explained together from 23 to 32 % of the variation in the four analyses. Stream site explained 8–11 % of that variation, and mesohabitat variables explained 13–20 %. Surface flow types accounted for >60 % of the variation provided by the mesohabitat component. These patterns are in accordance with those obtained in previous studies that showed the predominance of environmental variables over spatial location in explaining macroinvertebrate distribution. We conclude that visually assessed mesohabitat components are important predictors of assemblage composition, explaining significant amounts of beta-diversity. Therefore, they are critical to consider in ecological and biodiversity assessments involving macroinvertebrates.     

Ecosystem classifications based on summer and winter conditions

Ecosystem classifications map an area into relatively homogenous units for environmental research, monitoring, and management. However, their effectiveness is rarely tested. Here, three classifications are (1) defined and characterized for Canada along summertime productivity (moderate-resolution imaging spectrometer fraction of absorbed photosynthetically active radiation) and wintertime snow conditions (special sensor microwave/imager snow water equivalent), independently and in combination, and (2) comparatively evaluated to determine the ability of each classification to represent the spatial and environmental patterns of alternative schemes, including the Canadian ecozone framework. All classifications depicted similar patterns across Canada, but detailed class distributions differed. Class spatial characteristics varied with environmental conditions within classifications, but were comparable between classifications. There was moderate correspondence between classifications. The strongest association was between productivity classes and ecozones. The classification along both productivity and snow balanced these two sets of variables, yielding intermediate levels of association in all pairwise comparisons. Despite relatively low spatial agreement between classifications, they successfully captured patterns of the environmental conditions underlying alternate schemes (e.g., snow classes explained variation in productivity and vice versa). The performance of ecosystem classifications and the relevance of their input variables depend on the environmental patterns and processes used for applications and evaluation. Productivity or snow regimes, as constructed here, may be desirable when summarizing patterns controlled by summer- or wintertime conditions, respectively, or of climate change responses. General purpose ecosystem classifications should include both sets of drivers. Classifications should be carefully, quantitatively, and comparatively evaluated relative to a particular application prior to their implementation as monitoring and assessment frameworks.     

太阳山湿地浮游植物优势功能群季节演替特征及驱动因子分析

为探明太阳山湿地浮游植物优势功能群季节演替规律及其主要驱动因子,于2019年4月(春季)、7月(夏季)、10月(秋季)和2020年1月(冬季)采样分析了太阳山湿地浮游植物的种类组成、优势种、丰度、生物量及季节变化,同时测定了水环境理化因子指标,采用冗余分析方法研究了浮游植物优势功能群的优势度、丰度与水环境因子之间的关系。结果表明:太阳山湿地浮游植物可分为22个功能类群;优势功能群的季节演替和空间分异特征明显,存在一定的规律性。春、秋、冬3个季节的浮游植物以硅藻门为主,夏季以绿藻门和蓝藻门为主。春季优势功能群主要为D、C、P,以硅藻门种类为主;夏季优势功能群主要为J、Lo、TC、M、H1,以硅藻门、绿藻门、蓝藻门种类为主;秋季优势功能群主要为D、S1、MP,以硅藻门、绿藻门种类为主;冬季优势功能群主要为D、X3,以硅藻门种类为主。影响太阳山湿地浮游植物优势功能群季节演替的水环境因子有水温(WT)、pH、溶解氧(DO)、透明度(SD)、盐度(Sal)、氮磷营养元素含量、化学需氧量(COD_Cr)和高锰酸盐指数(COD_Mn)。4个湖区浮游植物优势功能群的时空差异与水环境因子密切相关,其中,西湖区浮游植物优势功能群的季节演替驱动因子为pH、DO、WT、总磷(TP),东湖区为pH、DO、WT、氮磷营养元素含量,南湖区为pH、DO、COD_Cr、五日生化需氧量(BOD₅),小南湖区为pH、DO、WT、BOD₅、COD_Cr、TP。pH、DO、WT、BOD₅、SD等水环境因子的季节差异以及TP、TN、氨氮(NH₃-N)、COD_Mn等水环境因子的湖区差异是太阳山湿地浮游植物优势功能群出现季节演替的主要原因。