Cultivation of GMO in Germany: support of monitoring and coexistence issues by WebGIS technology

Genetic engineering was introduced to improve plant breeding. It enables to establish new varieties of plant species with specific input and output traits [1]. The cultivation of GMO aims at increasing yield, but also to improve product quality [2, 3]. Input traits include resistances against different herbicides or insect pests and viruses. Output traits aim to improve the quality of agricultural products, e.g. increasing fibre or lowering the fat content. Worldwide, the cultivation of GMO increased from 1.7 Mio ha in 1996 up to 134 Mio ha in 2009 [4]. According to the agricultural statistical survey 2009, for example in the USA, 90% of the cropland is used to cultivate GMO varieties of soy or cotton. In the USA, the percentage of genetically modified (GM) maize is already 85%. In Germany, GMO (99% Bt-maize MON810) were cultivated from 2005 until 2008 with a total number of 239 fields and a total acreage of 3,171 ha in 2008.

In contrast to the contained use of GM products in medicine, the introduction of GMO in agricultural ecosystems may cause unwanted, uncontrollable and irreversible impacts.

According to EU Directive 2001/18/EC, plant breeders willing to introduce GMO on the market have to accomplish a notification process including an environmental risk assessment (ERA) and a monitoring plan to the competent national and European authorities [5]. This regulatory framework is intended to implement the precautionary principle and to enable handling potential adverse environmental effects still remaining after the ERA [6]. The aim of the EU Directive 2001/18/EC is to safeguard human health and the environment and to restrict the use of GMO so that no unacceptable risks or hazards can emerge [7]. The risk assessment is based on empirical studies with small spatial extent, encompassing laboratories tests, greenhouse experiments, small-scale field release or commercial-scale field release [8–10]. Though, there remains a wide range of uncertainty with small plot and laboratory studies. According to scientific hypotheses, adverse effects are examined in the ERA. However, ERA concentrates at the small-scale level, thus, large-scale effects are difficult to assess. Thus, monitoring of GMO at the landscape scale is required after the GMO have been released to detect adverse environmental effects at regional or larger scale [11]. Accordingly, the EU Directive 2001/18/EC [5] on the deliberate release of GMO into the environment stipulates assessment of direct and indirect effects of GMO on humans and the environment by case-specific monitoring and general surveillance. The latter has to be performed to detect potential unanticipated adverse effects whereas case-specific monitoring is set up to reduce substantial uncertainties in relevant risk scenarios identified in the ERA [5]. In Germany, the Federal Nature Conservation Agency suggests how to implement a monitoring of GMO. Three core issues have to be covered: (1) documentation of exposure, (2) monitoring impacts of the specific GMO and (3) large-scale and long term-effect relationships [12]. The results of GMO monitoring contribute to decisions regarding, e.g. further approval or refusal of the GMO or additional precautions during cultivation. In this context, GMO monitoring provides the basis for an early warning system to react at an early stage in case of reported adverse effects and decide upon counter measures. Relevant topics have to be considered for both, case-specific monitoring and general surveillance, which are, for example, (a) combinatory effects of several genetic modifications accumulating in individual plants of a crop species such as multiple resistances in oilseed rape [13, 14], (b) effects of different Bt-toxins on susceptible butterfly populations [15–17] or (c) long-term effects due to changes in farming practices [18]. The necessity of monitoring adverse GMO effects can be pointed out by means of a few indications, for example, enhanced mortality of non-target organisms [6], hybridisation with related species [19] or neighbouring non-GM crops [20] and adverse agricultural practice changes [21]. According to EU Directive 2001/18/EC [5], a set of appropriate monitoring parameters has to be defined which are described in the guidelines for GMO monitoring as, for instance, published by the Association of German Engineers [22]. These obligate test items have to be considered when integrating and compiling data from already existing environmental monitoring networks [23–25].

In this context, a Web-based geographical information system (WebGIS) is appropriate to build up a data infrastructure for GMO monitoring and data exchange [26]. The objective of the article at hand is to describe how to complement and support GMO monitoring by the implementation of a WebGIS as suggested by Aden et al. [25]. The WebGIS enables access to relevant geodata like basic environmental information, existing monitoring networks related to GMO issues, details on GMO fields and information on protected areas as well as tools for collecting, processing and mapping monitoring results. Implemented GIS tools that do not require any additional software but an Internet browser at the client's computer should help in assessment of possible GMO impacts in a spatially discriminated context. On that score, the WebGIS can facilitate the approval process. Secondly, it could be used to manage coexistence of GMO, conventional and organic farming as well as with nature conservation issues by detecting or avoiding possible conflicts already during planning stage [27]. Moreover, the Web-based application will provide spatial information on the locations of the Bt-maize fields which can be used for modelling cross-pollination of GM maize pollen at field scale, for instance, to check, e.g. whether distance regulations between Bt-maize and conventional maize fields are sufficient or not [28].

GMO monitoring should take place in areas exposed to GMO, preferably cultivated fields and their environment, but should include also regions with no or unknown GMO exposure. On a case-by-case basis depending on the GMO characteristics, the selected indicators, checkpoints and related analytical methods should consider relevant different spatial and temporal scales [49, 22]. Hence, the monitoring of ecological effects of GMO must be standardised with regard to parameters, methods, survey intervals and sites so that data are comparable in terms of measurement methods and, thus, can be analysed statistically and interpreted meaningfully [22]. This comprises standards concerning molecular-biological detection methods, vegetation mapping and faunistic surveys to evaluate changes in population density and behaviour of endangered species, for example. This standardisation is to ensure a Germany-wide comparability of sampling data and to provide legal certainty for the user [50]. Accordingly, the WebGIS GMO monitoring should support realisation of particular parts of the guideline VDI 4330 [22]: "Monitoring the ecological effects of genetically modified organisms - Basic principles and strategies" (VDI 4330, part 1), "Pollen monitoring: Pollen sampling using pollen mass filters (PMF) and Sigma-2 samplers" (VDI 4330, part 3), "Pollen monitoring: Biological sampling by honey bees" (VDI 4330, part 4). In this context, Reuter et al. (2006, 2010) [23, 24] developed a concept of an information system for GMO monitoring (ISMO). The database concept encompasses three components: The "Knowledge Database" comprises information related to different levels of biological organisation being affected by GMO cultivation. Therein, scientific hypotheses regarding ecological effects of GMO as well as checkpoints for monitoring possible impacts were described in detail. The "Monitoring Database" should provide GMO monitoring data and interfaces to existing environmental information systems being of relevance for GMO monitoring issues. The WebGIS GMO monitoring is designated to be part of the monitoring database enabling data retrieval, mapping and analysis of relevant monitoring data and geodata. The "Administrative Database" structures all data necessary for the approval process. ISMO enables support by competent authorities in the notification process and post market monitoring of environmental effects [24]. Checkpoints defined by ISMO were used to compile and integrate appropriate environmental monitoring programmes in the WebGIS GMO monitoring.

Compared with the public register of the BVL, advantages of the WebGIS GMO monitoring are obviously the possibility to map registered GMO fields as well as to perform spatial analyses by additional relevant geodata useful for GMO monitoring issues and environmental risk assessment. The use of licence-free open source software for assembling the application is another advantage compared with the public register of the BVL which is based on proprietary software. The WebGIS GMO monitoring is not intended to compete with the public register of the BVL, but it serves as a supplement for more transparency regarding the localisation and management of single GMO fields and agricultural patterns.

The Federal Nature Conservation Agency provides another WebGIS application [51] which allows displaying Natura 2000 reserves as well as predefined buffer zones of 1,000 m around them. An interactive query offers additional information on the respective nature reserve, like name and site code. Specific information on protected species in general or species that might be affected by GMO cultivation individually is not provided.

Another application called "Risk Register Genetic Engineering Agriculture" [52] displays, for instance, all Bt-maize fields cultivated in 2009 and 2010 in Germany. The respective field geometries were derived by using Google Maps. Additional thematic maps were integrated on the basis of the official GMO location register of the BVL displaying static density maps of GMO cultivation on different administrative levels and for different periods and crops. However, this application just visualises GMO fields, whereas the WebGIS GMO monitoring additionally enables performing GIS procedures. Furthermore, interactive dynamic generation of buffers and intersection with additional geodata enhance the WebGIS functionalities in terms of spatial analysis. For instance, it is possible to intersect data on Bt-maize fields with additional geodata like related monitoring sites or distribution maps of the corn borer as being the target object for Bt-maize cultivation. Furthermore, the WebGIS GMO monitoring facilitates linkage to PortalU [53] as being the German realisation of the European INSPIRE directive [33] which aims at "establishing an infrastructure for spatial information in Europe to support Community environmental policies, and policies or activities which may have an impact on the environment". Accordingly, data from the WebGIS GMO monitoring will enhance the database of PortalU and enable remote geodata access without implementation of a local GIS software at the client PC.

Compared to the work published by Kleppin et al. (2008) [42], the database was complemented by additional geodata, e.g., on environmental monitoring networks and the respective information on measurement parameters. Apart from that, the WebGIS GMO monitoring was optimised and improved by the implementation of additional sophisticated GIS techniques including buffer and intersect tools. However, long-term risks of GMO cultivation are difficult to assess, in particular, because possible impacts depend on spatially varying conditions [54]. Anticipating risks is often hampered by limitations in scientific knowledge or in availability of data, in particular, in cases where a complex process of change is continuing (e.g. climate change) or a new technological context is added to an established interaction network. An increasing amount of information can be accessed via the Internet. Particular in recent years, attention has focused on the presented WebGIS technology which enables compilation and access to data, e.g., affecting the dispersal of GMO, such as wind speed and direction. However, GIS is not only used for pre-event vulnerability assessment but can be used also for improving preparedness, mitigation, monitoring and response plan activities. Thus, the use of WebGIS provides instructive links with administrative, socioeconomic and other data, and enhances communication of the results to policy makers and the public. This communication dimension is fundamental - local people need to incorporate risk awareness into their culture [55].

According to Wilkinson et al. (2000) [56] and Züghart and Breckling (2003) [57] criteria for selecting monitoring sites and regions include 1) representativeness of sites cultivated with specific GMO, 2) representativeness of ecological regions containing the spectrum of relevant indicators, 3) availability of sites already monitored within other environmental programmes, and 4) areas with environmental conditions facilitating spread or survival of GMO. The WebGIS GMO monitoring supports this task by providing data on the distribution of GMO fields as well as on the distribution of monitoring sites of different environmental monitoring programs and, thus, helps in selecting appropriate monitoring sites. Furthermore, the article at hand demonstrates that the use of the WebGIS GMO monitoring is a useful and efficient tool to assess the individual and spatial risk potential before and during GMO release since it can be used to identify coexistence problems between Bt-maize and conventional maize cultivation on the one hand and between Bt-maize cultivation and conservation issues on the other hand.

Since in the future number and location of GMO fields might change considerably, the integration of geometries of Bt-maize fields into the WebGIS should be improved by an automation of the update procedure. Difficulties arise when no free Web services on ALK data are available to locate the respective GMO fields precisely. This is the case for about one third of all federal states in Germany. A possible solution is to compile the information directly from land registry offices. But this causes additional costs and is very time consuming. In this context, access to the 'Integrated Administration and Control System' (IASC, in German: InVeKoS = Integriertes Verwaltungs- und Kontrollsystem) would be a better and more efficient solution. Referring to this, in 1992 in the course of the reform of the 'Common Agriculture Policy' (GAP) the implementation of an 'IASC' was decided. It was introduced in Germany as per regulation no. 1782/2003 on December 3th 2004 (BGBl. 1 p. 3194) in order to define cultivation premiums. However, a nationwide information system on spatial and temporal cultivation patterns integrating agricultural data of all federal states has not been established, yet. In completion with information provided by the official GMO location register, such information platform could be used for detection of potential conflict regions with regard to conventional and Bt-maize cultivation. Since access to these data is not possible so far, future work aims at detection of maize fields by remote sensing data to integrate these data into the WebGIS application.

Furthermore, pollen dispersal plays an important part in the spread of GMO. Thus, currently the dispersion model AUSTAL2000 developed by the German Environmental Protection Agency [58] is being implemented in the WebGIS GMO monitoring. The Lagrange particle model considers time-dependent emissions from road and industrial sources. Modification of this software should enable simulation of Bt-maize pollen dispersal to quantify pollen load into conservation areas or conventional maize fields. Further, the dispersion model could help to establish a pollen monitoring network based on technical samplers or biological sampling by bees with respect to VDI 4330, parts 3 and 4 described by Hofmann et al. (2010) [45].