Antimony uptake by <Emphasis Type="Italic">Zea mays</Emphasis> (L.) and <Emphasis Type="Italic">Helianthus annuus</Emphasis> (L.) from nutrient solution

We investigated the extent of Sb uptake by maize (Zea mays) and sunflower (Helianthus annuus) from nutrient solutions containing concentrations from 3 to 24 mg/L of potassium antimonate, with the aim of determining the potential of Sb to enter the food chain. The maximum shoot Sb concentrations in Z. mays and H. annuus were 41 mg/kg and 77 mg/kg dry weight, respectively. There was no significant difference in Sb uptake between species. The average bioaccumulation coefficients (the plant/solution concentration quotients) were 1.02 and 1.93 for Z. mays and H. annuus, respectively. Phosphate addition did not affect plant growth or Sb uptake. Antimony uptake by both Z. mays and H. annuus is unlikely to pose a health risk to animals and humans.     

Googling Trends in Conservation Biology

Web‐crawling approaches, that is, automated programs data mining the internet to obtain information about a particular process, have recently been proposed for monitoring early signs of ecosystem degradation or for establishing crop calendars. However, lack of a clear conceptual and methodological framework has prevented the development of such approaches within the field of conservation biology. Our objective was to illustrate how Google Trends, a freely accessible web‐crawling engine, can be used to track changes in timing of biological processes, spatial distribution of invasive species, and level of public awareness about key conservation issues. Google Trends returns the number of internet searches that were made for a keyword in a given region of the world over a defined period. Using data retrieved online for 13 countries, we exemplify how Google Trends can be used to study the timing of biological processes, such as the seasonal recurrence of pollen release or mosquito outbreaks across a latitudinal gradient. We mapped the spatial extent of results from Google Trends for 5 invasive species in the United States and found geographic patterns in invasions that are consistent with their coarse‐grained distribution at state levels. From 2004 through 2012, Google Trends showed that the level of public interest and awareness about conservation issues related to ecosystem services, biodiversity, and climate change increased, decreased, and followed both trends, respectively. Finally, to further the development of research approaches at the interface of conservation biology, collective knowledge, and environmental management, we developed an algorithm that allows the rapid retrieval of Google Trends data.     

大气污染影响下凯里植物氮、硫含量分析

对大气污染影响下凯里植物氮、硫质量分数进行测定分析。结果表明:植物的氮质量分数为0.8%～2.8%,平均值为1.5%;硫质量分数为0.4%～1.4%,平均值为0.8%。植物的氮、硫质量分数都高于对照点植物,为对照点植物的1.4倍、1.9倍,表明该区植物已受到了大气污染的影响。不同植物间的氮、硫质量分数差异达到3.5倍和2.5倍。不同类型植物的氮、硫质量分数也存在差异,氮质量分数中:藤本>草本>灌木>乔木,硫质量分数中:藤本>草本>乔木>灌木;落叶植物的氮、硫质量分数>常绿植物的氮、硫质量分数。不同研究点植物的氮、硫质量分数存在差异,均表现为:玻璃厂>火电厂>水泥厂。     

电解铝厂氟化物对周围农作物的影响评价

通过对某电解铝厂周围的大气环境及农作物中氟化物含量的监测,分析评价电解铝生产过程中排放的氟化物对其农作物的影响,并提出氟化物的治理措施及建议。     

Response of C and N cycles to N fertilization in Sphagnum and Molinia-dominated peat mesocosms

Plant communities play an important role in the C-sink function of peatlands. However, global change and local perturbations are expected to modify peatland plant communities, leading to a shift from Sphagnum mosses to vascular plants. Most studies have focused on the direct effects of modification in plant communities or of global change (such as climate warming, N fertilization) in peatlands without considering interactions between these disturbances that may alter peatlands' C function. We set up a mesocosm experiment to investigate how Greenhouse Gas (CO₂, CH₄, N₂O) fluxes, and dissolved organic carbon (DOC) and total dissolved N (TN) contents are affected by a shift from Sphagnum mosses to Molinia caerulea dominated peatlands combined with N fertilization. Increasing N deposition did not alter the C fluxes (CO₂ exchanges, CH₄ emissions) or DOC content. The lack of N effect on the C cycle seems due to the capacity of Sphagnum to efficiently immobilize N. Nevertheless, N supply increased the N₂O emissions, which were also controlled by the plant communities with the presence of Molinia caerulea reducing N₂O emissions in the Sphagnum mesocosms. Our study highlights the role of the vegetation composition on the C and N fluxes in peatlands and their responses to the N deposition. Future research should now consider the climate change in interaction to plants community modifications due to their controls of peatland sensitivity to environmental conditions.     

沈阳市城市污水处理厂现状及提标改造技术对策分析

为达到国家《城镇污水处理厂污染物排放标准》(GB18918—2002)一级A要求,对沈阳市污水处理厂实施提标改造工程。通过对沈阳市城市污水处理厂现状、处理工艺特征及运行情况调研分析,根据沈阳市城市污水处理厂需要提标改造存在的问题,提出工艺优化以及提标改造解决对策,为沈阳市城市污水处理厂提标改造的工程建设提供技术支撑。     

Sustained dynamic transience in a Lotka-Volterra competition model system for grassland species

Theoretical approaches, such as the Lotka-Volterra framework, enable predictions about long term species coexistence based on stability criteria, but generally assume temporal constancy of system equations and parameters. In real world systems, temporal variability may interfere with the attainment of stable states. Managed grassland ecosystems in Northwestern Europe experience structural periodic fluctuations in environmental conditions: the seasons. In addition, periodic disturbances such as cutting are very common. Here we show, using a Lotka-Volterra system applied to grassland species with empirically derived parameters, that seasonal variability can result in a time dependent equilibrium and redirection of displacement processes.Parameter estimates differed between species and - in most cases - between the seasons. As a result, five of the fifteen tested species combinations had different outcomes of species interactions between seasons. This indicates that systems remain in dynamic transience over the year as the equilibrium changes and the species composition of the system follows the equilibrium without ever attaining it. The non-attainment of the steady state enables coexistence of species even if there is competitive exclusion in one of the seasons. For three of the fifteen species combinations, cutting frequency affected the long-term coexistence patterns. Cutting resets the biomass of competing species and favours during regrowth those species that have a high growth rate, which can alter species coexistence in comparison to a Lotka-Volterra model without cutting. The Lotka-Volterra framework with seasonally changing empirical parameters predicts coexistence as a possible outcome of systems that in component seasons are characterised by exclusion, and vice versa.     

Scale-dependent relations in land cover biophysical dynamics

The exploration of the relationships between plant biotic dynamics and scale can reveal important information on ecosystem spatial organization by addressing preservation of information integrity in upscaling/downscaling procedures of land-surface parameterization for environmental modeling applications. Scale-dependent relations of vegetation dynamics are investigated in this study by using emergent biophysical characteristics obtained through a predictive multidimensional model of vegetation anomalies derived from remote-sensing observations. In particular, the analysis is focused on the spatial organization of some phenological parameters including deterministic variations (seasonal range, interannual variability, jump discontinuities) and stochastic components (plant memory, spatial correlations). The analysis is performed using MODIS-based Normalized Difference Vegetation Index (NDVI) 16-day composites for the period from March 2000 to December 2006 over Italy at different levels of spatial aggregation (1-8 km). Scale-dependences of the statistical moments of the phenological parameters are quantified through simple power laws for five distinct vegetated land covers. Results suggest that some biophysical characteristics, especially deterministic components, show no preferential spatial scale for important coverage. In particular, broad-leaved forests and natural grasslands are characterized by deterministic and low-distance spatial components well explained by scale relationships, which are modulated by possible spatiotemporal dynamics of climatic drivers. Agricultural lands show high scale-dependent relations on short-term biophysical memory sources and low-distance spatial components of phenology likely related to hierarchical interactions of anthropogenic and ecological processes; whereas mixed patterns of croplands and natural areas generally present no consistent scaling relations.     

A coffee agroecosystem model: I. Growth and development of the coffee plant

This paper is the first of three on the coffee production system consisting of (1) the coffee plant, (2) coffee berry borer (CBB) and (3) the role of CBB parasitoids. A previous simulation model of the coffee plant was developed using data from Brazil where coffee phenology is characterized by distinct seasonal flowering (Gutierrez et al., 1998). In contrast, flowering in Colombia is continuous with low seasonality. To capture the differences in coffee phenology and growth in the two climatic regions, the Gutierrez et al. (1998) model was modified using new data from Colombia.The modifications to the model include:

(1)

The effect of solar radiation on floral buds initiation;

(2)

An age structure population model to track the daily input and development of the floral buds;

(3)

The effect of leaf water potential on breaking dormancy in flower buds, and hence on the timing and intensity of flowering;

(4)

The incorporation of both the vegetative and the reproductive demands to predict the photosynthetic rate.

(5)

The effect of low temperature on photosynthesis and defoliation.

Other aspects of the model were re-interpreted and refinements made to generalize its structure for use across coffee varieties and geographic areas. The model, without modification, realistically simulates field data from Brazil and two Colombian locations having different varieties, patterns of rainfall and hence flowering phenology.The model will be used as the base trophic level for incorporating CBB and high tropic levels effects, and for the analysis of management options in the coffee production system.