Prioritizing GM crop monitoring sites in the dynamics of cultivation systems and their environment

EU legislation stipulates that GM crops have to be monitored for potential adverse environmental effects. Monitoring preferably should take place in the most exposed areas-the cultivated fields and their neighbouring environment. Current monitoring designs do not give detailed consideration to the different exposure intensities in agricultural practice. At the same time, the selection of specific, more exposed sites is difficult considering the dynamic and diversity of crop cultivation and rotation systems and their environments. We developed an approach for prioritising the monitoring of on-farm and neighbouring sites based on differing exposure levels using a minimum dataset of cultivation and land use information. Applying a Bt-maize cultivation scenario to Brandenburg, Germany, where presently no GM crops are cultivated, we systemised and categorised areas with different spatio-temporal exposure intensities including 50 m, 200 m and 1000 m buffers. These categories correspond to different suitabilities to serve as monitoring sites. Sites are prioritised using a sequential scheme. This yields an improved and objective spatial monitoring design providing detailed exposure information. This methodology is flexible and transferable to any agricultural setting, therefore enabling superior statistical comparisons between locations and regions and thus enhancing monitoring data quality.     

Environmental monitoring of genetically modified crops

Genetically modified (GM) crops are now approved for commercial use in several world areas. In terms of commercial acreage, the majority of these products possess either herbicide tolerance or insect protection traits. Prior to commercialization, each product underwent a country specific review of environmental safety data by independent regulatory authorities. Registration was granted after review of the data allowed authorities to conclude that the risks were minimal or manageable when balanced with the benefits. As a condition of registration, insect resistance management (IRM) has been imposed for insect protected products in most countries. Other world areas have reviewed similar data packages and have not yet been able to grant registration for commercial release. Post-registration environmental monitoring of GM crops is viewed in some world areas as a means of enabling approvals by addressing uncertainty that exists with this technology. Questions such as, who should monitor and who should pay for it, how should monitoring be conducted, what information is necessary to collect and how long should a given product be monitored are yet to be answered. Monitoring methods could be general (surveys and questionnaires) or specific (scientific studies to address specific questions). Independent research currently underway in countries where GM crops are commercial involves monitoring the benefits as well as the risks of these products. Experience with other products has shown that monitoring of GM crops will be of value only if the questions are clearly defined, the methods are appropriate and the end points (data collected) are interpretable.     

The use of artificial neural networks to forecast biological atmospheric allergens or pathogens only as Alternaria spores

The monitoring of atmospheric Alternaria spores is of major importance due to their adverse effects on crops and their role as human allergens. Most species act as plant pathogens, prompting considerable economic losses worldwide on important crops such as potato, tomato or wheat. Fungal spores can also have serious detrimental effects on human health, triggering respiratory diseases and allergenic processes. The aim of this study was not only to examine the relationship between the atmospheric Alternaria spore content and the prevailing meteorological parameters, but also to predict the atmospheric Alternaria spore content in the Northwest Spain using a novel data analysis technique, ANNs (Artificial Neural Networks). A Hirst-type LANZONI VPPS 2000 volumetric 7-day recording sampler was used to collect the airborne spores from 1997 to 2008. Neural networks provided us with a good tool for forecasting Alternaria airborne spore concentration, and thus could help the automation of the prediction system in the aerobiological information diffusion to the population suffering from allergic problems or the prevention of considerable economic worldwide losses on important crops. Our proposed model would be applied to different geographical areas; nevertheless, the adjustment of the model, by using the available and adequate variables, would be realised in each case.     

Quantifying the introgressive hybridisation propensity between transgenic oilseed rape and its wild/weedy relatives

In order to estimate the introgressive hybridisation propensity (IHP) between genetically modified (GM) oilseed rape (Brassica napus) and certain of its cross-compatible wild/weedy relatives at the landscape level, a conceptual approach was developed. A gene flow index was established enclosing the successive steps to successfully achieve introgressive hybridisation: wild/weedy relatives and oilseed rape should co-occur, have overlapping flowering periods, be compatible, produce viable and fertile progeny, and the transgenes should persist in natural/weedy populations. Each step was described and scored, resulting in an IHP value for each cross-compatible oilseed rape wild/weedy relative. The gene flow index revealed that Brassica rapa has the highest introgressive hybridisation propensity (IHP value = 11.5), followed by Hirschfeldia incana and Raphanus raphanistrum (IHP = 6.7), Brassica juncea (IHP = 5.1), Diplotaxis tenuifolia and Sinapis arvensis (IHP = 4.5) in Flanders. Based on the IHP values, monitoring priorities can be defined within the pool of cross-compatible wild/weedy oilseed rape relatives. Moreover, the developed approach enables to select areas where case-specific monitoring of GM oilseed rape could be done in order to detect potential adverse effects on cross-compatible wild/weedy relatives resulting from vertical gene flow. The implementation of the proposed oilseed rape-wild relative gene flow index revealed that the survey design of existing botanical survey networks does not suit general surveillance needs of GM crops in Belgium. The encountered hurdles to implement the gene flow index and proposals to acquire the missing data are discussed.     

Determining Ecoregions for Environmental and GMO Monitoring Networks

A representative environmental monitoring network at the regional scale cannot use raster-based or random sampling designs, but requires a stratified sampling procedure integrating different information layers, and it has to occur in ecologically differing homogeneous regions (ecoregions). These we have determined using a set of spatial strata with ecological variables which we analysed with classification and regression trees (CART). We present a framework for environmental monitoring, that covers different scales, and we transfer the framework to a potential GMO (genetically modified organisms) monitoring network. We use ecoregion and other environmental strata together with existing environmental monitoring networks to determine GMO monitoring sites more precisely.     

基于GIS云平台的环境监测数据三维表征设计与应用初探

三维可视化是描绘和理解模型的一种手段,是数据体的一种表征形式。环境监测数据是空间数据场,可实现三维可视化的科学表达。监测数据的表征,可结合相关环境要素共同还原场景,以直观形象地表达环境状况的空间分布特征。不同的监测数据具有不同的特征,可分别进行表征方式的设计。通过研究水体污染、大气污染、噪声污染等数据场的三维表征设计,探索了三维可视化在深度数据挖掘、说明环境问题等方面的应用价值。     

Initial results from a multi-institutional collaboration to monitor harmful algal blooms in South Carolina

The rapid rate of development in the South Carolina (SC) coastal zone has heightened public concern for the condition of the state's estuaries, and alerted scientists to the potential that novel and adverse effects on estuarine ecosystems may result. Although well-developed databases from long-term monitoring programs exist for many variables valuable in predicting and following system responses, information on phytoplankton distributions in SC estuaries has lagged. Knowledge of the dynamical relationship between environmental (e.g., nutrient quantity and quality) and biological (e.g., grazing) regulation, and phytoplankton biomass and composition is critical to understanding estuarine susceptibility to eutrophication or harmful algal blooms (HABs). Recently, SC scientists from federal, state, and academic institutions established a collaborative monitoring program to assess HAB distribution and ecology statewide. The South Carolina Harmful Algal Bloom Program includes: a) intensive temporal monitoring at areas of known HAB occurrence or those exhibiting symptoms potentially related to HABs (e.g., prevalent fish lesions), b) extensive spatial monitoring in coordination with existing statewide efforts, c) a citizen volunteer monitoring network, d) nutrient response bioassays, and e) laboratory-based physiological experiments on HAB isolates. By combining trip-wire surveillance and rapid response systems, routine monitoring of environmental parameters and HAB distribution, and process-oriented studies examining the physiological functioning of HAB species, an enhanced understanding of the impact and environmental control of HABs in SC estuaries will be achieved. The application of this approach to studies on the distribution and physiological ecology of a new widespread SC red tide, and to the discovery of several potentially toxic blooms (including Pfiesteria) in SC holding ponds, are described.     

Monitoring of cyclic organochlorines in the marine environment

Cyclic organochlorines are highly hydrophobic chemicals which usually possess a high persistence to microbial breakdown. These behavioural aspects determine the suitability of each environmental compartment for monitoring purposes, which is discussed.It is concluded, that monitoring of (cyclic) organochlorines should only be executed for compounds about which solid information is available on their environmental behaviour in abiotic and biotic environmental compartments. Under these conditions benthic invertebrates which use glycogen as their main energy-depot, appear to be the most suitable tool for environmental monitoring of lipophilic compounds. Concentrations should be expressed on the basis of (total) extractable lipids.The organisms to be compared should be sampled at a time when they have a similar physiological condition. This does not automatically mean synoptic sampling.Multi-component mixtures, such as PCB's, should be monitored on the basis of (selected) individual components in order to account for differences in behaviour of each component between different environmental compartments and animal species.Some representatives of the compounds discussed are strong inducers of mixed function oxygenase (MFO) enzyme systems. Therefore it should be investigated, if monitoring of MFO activity in addition to concentrations can be regarded as an early warning system of additive effects.     

Application of GNSS-RTK derived topographical maps for rapid environmental monitoring: a case study of Jack Finnery Lake (Perth, Australia)

In environmental monitoring, environmental impact assessments and environmental audits, topographical maps play an essential role in providing a means by which the locations of sampling sites may be selected, in assisting with the interpretation of physical features, and in indicating the impact or potential impact on an area due to changes in the system being monitored (e.g., spatially changing features such as wetlands). Global Navigation Satellite Systems (GNSS) are hereby presented as a rapid method for monitoring spatial changes to support environmental monitoring decisions and policies. To validate the GNSS-based method, a comparison is made of results from a small-scale topographic survey using radio-based real-time kinematic GNSS (GNSS-RTK) and total station survey methods at Jack Finnery Lake, Perth, Australia. The accuracies achieved by the total station in this study were 2 cm horizontally and 6 cm vertically, while the GNSS-RTK also achieved an accuracy of 2 cm horizontally, but only 28 cm vertically. While the GNSS-RTK measurements were less accurate in the height component compared to those from the total station method, it is still capable of achieving accuracies sufficient for a topographic map at a scale of 1:1,750 that could support environmental monitoring tasks such as identifying spatial changes in small water bodies or wetlands. The time taken to perform the survey using GNSS-RTK, however, was much shorter compared to the total station method, thereby making it quite suitable for monitoring spatial changes within an environmental context, e.g., dynamic mining activities that require rapid surveys and the updating of the monitored data at regular intervals.     

Pesticide monitoring in the Netherlands: can it be improved?

In the Netherlands, pesticide monitoring of the surface water is separately managed by different water authorities. These water authorities can decide when, where, and what pesticide will be monitored and at what frequency. To help make the decisions more reasonable and make the monitoring system more efficient and systematic, three new types of monitoring maps were developed. The maps are based on actual pesticide measurement from current monitoring system and crop data. Combined temporal and spatial distribution maps give an overview of the pesticide problem in the whole Netherlands. It can be used to develop a strategy in which season and where the pesticide should be intensively monitored. Temporal distribution map, together with the pesticide usage prediction map, provide information of individual pesticide. They help to find out when and at what frequency and which pesticide be monitored, based on which monitoring facilities can be applied more efficiently.     

Effects of geomorphology, habitat, and spatial location on fish assemblages in a watershed in Ohio, USA

In this paper, we evaluate relationships between in-stream habitat, water chemistry, spatial distribution within a predominantly agricultural Midwestern watershed and geomorphic features and fish assemblage attributes and abundances. Our specific objectives were to: (1) identify and quantify key environmental variables at reach and system wide (watershed) scales; and (2) evaluate the relative influence of those environmental factors in structuring and explaining fish assemblage attributes at reach scales to help prioritize stream monitoring efforts and better incorporate all factors that influence aquatic biology in watershed management programs. The original combined data set consisted of 31 variables measured at 32 sites, which was reduced to 9 variables through correlation and linear regression analysis: stream order, percent wooded riparian zone, drainage area, in-stream cover quality, substrate quality, gradient, cross-sectional area, width of the flood prone area, and average substrate size. Canonical correspondence analysis (CCA) and variance partitioning were used to relate environmental variables to fish species abundance and assemblage attributes. Fish assemblages and abundances were explained best by stream size, gradient, substrate size and quality, and percent wooded riparian zone. Further data are needed to investigate why water chemistry variables had insignificant relationships with IBI scores. Results suggest that more quantifiable variables and consideration of spatial location of a stream reach within a watershed system should be standard data incorporated into stream monitoring programs to identify impairments that, while biologically limiting, are not fully captured or elucidated using current bioassessment methods.     

Forest cover change and fragmentation using Landsat data in Maçka State Forest Enterprise in Turkey

In this study, Grey model (GM) and artificial neural network (ANN) were employed to predict suspended solids (SSeff) and chemical oxygen demand (CODeff) in the effluent from a wastewater treatment plant in industrial park of Taiwan. When constructing model or predicting, the influent quality or online monitoring parameters were adopted as the input variables. ANN was also adopted for comparison. The results indicated that the minimum MAPEs of 16.13 and 9.85% for SSeff and CODeff could be achieved using GMs when online monitoring parameters were taken as the input variables. Although a good fitness could be achieved using ANN, they required a large quantity of data. Contrarily, GM only required a small amount of data (at least four data) and the prediction results were even better than those of ANN. Therefore, GM could be applied successfully in predicting effluent when the information was not sufficient. The results also indicated that these simple online monitoring parameters could be applied on prediction of effluent quality well.     

Limitations of habitats as biodiversity surrogates for conservation planning in estuaries

Increasing pressures on global biodiversity and lack of data on the number and abundance of species have motivated conservation planners and researchers to use more readily available information as proxies or surrogates for biodiversity. “Habitat” is one of the most frequently used surrogates but its assumed value in marine conservation planning is not often tested. The present study developed and tested three alternative habitat classification schemes of increasing complexity for a large estuary in south-east Australia and tested their effectiveness in predicting spatial variation in macroinvertebrate biodiversity and selecting estuarine protected areas to represent species. The three habitat classification schemes were: (1) broad-scale habitats (e.g., mangroves and seagrass), (2) subdivision of each broad-scale habitat by a suite of environmental variables that varied significantly throughout the estuary, and (3) subdivision of each broad-scale habitat by the subset of environmental variables that best explained spatial variation in macroinvertebrate biodiversity. Macroinvertebrate assemblages differed significantly among the habitats in each classification scheme. For each classification scheme, habitat richness was significantly correlated with species richness, total density of macroinvertebrates, assemblage dissimilarity, and summed irreplaceability. However, in a reserve selection process designed to represent examples of each habitat, no habitat classification scheme represented species significantly better than a random selection of sites. Habitat classification schemes may represent variation in estuarine biodiversity; however, the results of this study suggest they are inefficient in designing representative networks of estuarine protected areas.     

Water quality index for agricultural systems in Northwest Uruguay

Agricultural systems have experienced rapid expansion and intensification in the last several decades. In Uruguay, since the beginning of 2000, the most common cropping systems have included soybeans. Currently, this crop is expanding towards lowlands traditionally occupied by rice in rotation with pastures. However, the environmental effects of agricultural intensification and diversification are not well known. Thus, some indices have been proposed to quantify the changes in agricultural production systems and assess water quality. The main goal of this study was to develop a water quality index (WQI) to assess the impacts of the diversification of rice production systems in northwest Uruguay. The study was carried out in an agricultural basin where other summer crops have been incorporated in the rice-pasture sequence. Agriculture intensification and crop diversification indices were calculated using information provided by farmers. Water samples were collected downstream of the production area before crop sowing and after crop harvest (2008–2009 to 2010–2011 and 2016–2017 to 2017–2018). Biochemical oxygen demand, nitrates, total phosphorus, fecal coliforms, and total suspended solids were the variables that mainly explained the effects of the agricultural activities on water quality. The proposed water quality index included these unweighted variables, which allowed for the pre-sowing and post-harvest to be differentiated, as well as the degree of diversification. Therefore, the proposed WQI constitutes a tool that can be used to evaluate the water quality in an agricultural basin. Likewise, it can be used to select agricultural sequences that generate the least possible impacts on the associated water resources.     

Foliar nutrient and metal levels of crops in the Mount Cameroon area—reference values for plant nutrition and environmental monitoring

The growing population number and traffic loads, increasing environmental pressures, agricultural intensification, and the establishment of Mount Cameroon National Park demand farsighted environmental management in the region and the definition of a favorable ecological status. Since plants grow in the interface between soils and the atmosphere they can be used as passive biomonitors for the environmental quality. At the same time, the accumulation of nutrients and pollutants in crops is linked to human health, so that foliar elemental levels can be used as an integrative measure for environmental pollution and impact assessment. In the present study, we collected leaf samples of plantain, cassava, cocoyam, and maize on 28 sites at the southern flanks of Mt. Cameroon and determined 20 chemical elements. Air pollution in the study area comes from biomass and waste burning mainly, but emissions from traffic and a large refinery were believed to also play a significant role. However, spatial patterns in foliar elemental concentrations reflected the geochemistry rather than specific sources of pollution. Significant differences in foliar metal and nutrient levels were observed between the four species, indicating a different demand and uptake of specific elements. The results were compared to published data on nutrient concentrations in the tested species and the so-called reference plant. The data can be used as a baseline for future studies in plant nutrition and the environmental monitoring in inner tropical regions where these crops are grown.     

面向水源保护与污染监控的广东地下水环境监测网研究

通过系统整理分析自然资源、水利、生态环境等部门已有地下水监测网,针对广东地下水监测存在的问题和未来地下水环境管理需求,提出较大空间尺度和水质监控的地下水环境监测网建设框架及广东省"三层七级"共237个网点的层级化地下水环境监测网建设方案,并与水文地质单元、浅层地下水功能区划进行了空间叠加分析。结果表明,广东省三大部门监测网在空间上分布总体较为分散,相互补充性好,提出的监测网方案总体上与广东省地下水本底条件、地下水资源开发利用现状、地下水环境功能分区、重点污染源空间分布特征等相匹配,契合地下水饮用水源保护和重点污染源监控两大管理需求,构建的地下水环境监测网框架可为其他地区提供参考,提出的地下水环境监测网建设方案可为广东省地下水环境管理和污染防控提供决策支持。     

Development of the Coastal Intensive Site Network (CISNET)

The U.S. Environmental Protection Agency (EPA), National Oceanic and Atmospheric Administration (NOAA), and National Aeronautics and Space Administration (NASA) have formed a partnership to establish pilot sites for the development of a network known as the Coastal Intensive Site Network (CISNet). CISNet is composed of intensive, long-term monitoring and research sites around the U.S. marine and Great Lakes coasts. In this partnership, EPA and NOAA are funding research and monitoring programs at pilot sites that utilize ecological indicators and investigate the ecological effects of environmental stressors. NASA is funding research aimed at developing a remote sensing capability that will augment or enhance in situresearch and monitoring programs selected by EPA and NOAA. CISNet has three objectives: 1) to develop a sound scientific basis for understanding ecological responses to anthropogenic stresses in coastal environments, including the interaction of exposure, environment/climate, and biological/ecological factors in the response, and the spatial and temporal nature of these interactions, 2) to demonstrate the value of developing data from selected sites intensively monitored to examine the relationships between changes in environmental stressors, including anthropogenic and natural stresses, and ecological response, and 3) to provide intensively monitored sites for development and evaluation of indicators of change in coastal systems.     

Analysis of agricultural drought using vegetation temperature condition index (VTCI) from Terra/MODIS satellite data

The most commonly used normalized difference vegetation index (NDVI) from remote sensing often fall short in real-time drought monitoring due to a lagged vegetation response to drought. Therefore, research recently emphasized on the use of combination of surface temperature and NDVI which provides vegetation and moisture conditions simultaneously. Since drought stress effects on agriculture are closely linked to actual evapotranspiration, we used a vegetation temperature condition index (VTCI) which is more closely related to crop water status and holds a key place in real-time drought monitoring and assessment. In this study, NDVI and land surface temperature (T _s) from MODIS 8-day composite data during cloud-free period (September–October) were adopted to construct an NDVI–T _s space, from which the VTCI was computed. The crop moisture index (based on estimates of potential evapotranspiration and soil moisture depletion) was calculated to represent soil moisture stress on weekly basis for 20 weather monitoring stations. Correlation and regression analysis were attempted to relate VTCI with crop moisture status and crop performance. VTCI was found to accurately access the degree and spatial extent of drought stress in all years (2000, 2002, and 2004). The temporal variation of VTCI also provides drought pattern changes over space and time. Results showed significant and positive relations between CMI (crop moisture index) and VTCI observed particularly during prominent drought periods which proved VTCI as an ideal index to monitor terminal drought at regional scale. VTCI had significant positive relationship with yield but weakly related to crop anomalies. Duration of terminal drought stress derived from VTCI has a significant negative relationship with yields of major grain and oilseeds crops, particularly, groundnut.     

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.     

Species Distribution Models of Freshwater Stream Fishes in Maryland and Their Implications for Management

Species distribution models (SDMs) are often used in conservation planning, but their utility can be improved by assessing the relationships between environmental and species response variables. We constructed SDMs for 30 stream fishes of Maryland, USA, using watershed attributes as environmental variables and presence/absence as species responses. SDMs showed substantial agreement between observed and predicted values for 17 species. Most important variables were natural attributes (e.g., ecoregion, watershed area, latitude/longitude); land cover (e.g., %impervious, %row crop) was important for three species. Focused analyses on four representative species (central stoneroller, creek chub, largemouth bass, and white sucker) showed the probability of presence of each species increased non-linearly with watershed area. For these species, SDMs built to predict absent, low, and high densities were similar to presence/absence predictions but provided probable locations of high densities (e.g., probability of high-density creek chub decreased rapidly with watershed area). We applied SDMs to predict suitability of watersheds within the study area for each species. Maps of suitability and the environmental and species response relationships can help develop better management plans.