Reconciling agricultural production with biodiversity conservation. Группа авторов
href="#ulink_d6229d74-048e-54e4-a9c0-123013059d61">Goulson et al., 2015; Potts et al., 2010), the quantification of the losses and of the impacts on ecosystem services, the increased understanding of the causes and the awareness of knowledge gaps (IPBES, 2016) are factors that have strongly influenced the availability of funds for research as well as the adoption by the European Commission, on 1 June 2018, of the EU initiative on pollinators (EC, 2018).
The main aims of the initiative are to improve the scientific knowledge about insect pollinator decline, tackle its main known causes and strengthen collaboration between all the actors concerned. The initiative is organized around three priorities:
i improving knowledge of pollinator decline, its causes and consequences,
ii tackling the causes of pollinator decline, and
iii raising awareness, engaging society-at-large and promoting collaboration.
One of the main knowledge gaps that is identified concerns species distribution and abundance of pollinators, it is estimated in fact that half of the bee species in Europe is data deficient (IEEP & IUCN, 2018). Scattered monitoring programmes for bees and butterflies are in place, but not much is known about all other pollinator species. Under the first priority it is therefore planned that a common EU monitoring scheme is developed. Once implemented, this scheme should generate data that will enable the full assessment of the problem and the effectiveness of mitigation actions. Action 1A of the pollinators Initiative explicitly states ‘The Commission will devise and test an EU-wide pollinator monitoring scheme to ensure the provision of good quality data for assessing the status and trends of pollinator species in the EU and developing a pollinator indicator. A technical expert group will be set up to support this work’.
Discussions have started (UN WCMC, 2017; IEEP and IUCN, 2018) and an expert group has been set up and work on the monitoring scheme13 and the proposal for the indicator. Common monitoring and standardization of data and approaches to monitoring are seen as essential requirements under this premise; suggested methods for monitoring are a combination of passive methods (that do not rely on attracting insects), such as standardized transect walks, and active methods (that rely on attracting insects) such as pan-trapping.
An example of standardized transect is the bumblebee transect count method, which is similar to the butterfly method, and it is structured as follows: volunteers walk fixed transects of 1–2 km (divided into 4–10 sections with different habitat types) each month from March to October (on sunny days between 11:00 and 17:00) recording all bumblebee species in an imaginary 4 m × 4 m box on either side and in front, if necessary by catching bees in net or pot (Bumblebee Conservation Trust, 2017; Comont and Dickinson, 2018).
Interesting features are that data from new recorders are not used in the first two years to ensure data quality by allowing the recorder to develop sufficient skills in identification, and to put in place a mentoring system of experienced recorders tutoring new recorders.
The bee pan-trapping method has been standardized at the EU level by the FAO (2016): it uses bowl or pan traps, which are small plastic bowls or cups, coloured white, fluorescent blue or fluorescent yellow, filled with water mixed with a small amount of detergent, which acts as a surfactant. Twenty-four bowls should be placed on a line or transect 5 m apart, alternating the three colours and left for 24 hours or a fixed shorter period (to be noted), avoiding heavy shade. Catches are sieved and placed in 70% alcohol in container or sample bag (large-bodied non-Hymenoptera insects need to be removed first) which can be sent to the laboratory for identification. Samples should be stored in a freezer if they are not processed within one or two days. The processing of the samples includes washing, drying, pinning, labelling and maintaining the specimens. Lastly, the data from the specimens should be entered into a database system, together with validation and double-checking procedures.
The species to be monitored should include both common (with regional-specific lists) and key indicator species, and cover different pollinator groups, including wild bees, hoverflies and butterflies.
In parallel, a monitoring scheme for the products of the beehive (pollen, nectar, honeybee bread and honey) could be rolled out to monitor pesticide residues and other environmental pollutants.
Soil represents a complex habitat sustaining a huge diversity of organisms that are structured by and embedded within the physical matrix (Geisen et al., 2019). Despite its importance for a range of ecosystems and ecosystem services, from nutrient cycle regulation to soil erosion control (Barrios, 2007), it is recognized that our knowledge of the soil habitat is limited (Jeffery et al., 2010). Currently, there are no specific policy measures or designated protection areas in the European Union targeting soil biodiversity. In a perspective of filling this gap, a pilot campaign was launched within the soil module of the 2018 ‘Land Use/Cover Area frame statistical Survey’ (LUCAS Soil), to test a sampling protocol for soil biodiversity. The campaign collected samples from 1 000 locations with diverse land cover and use. This is currently the most extensive EU assessment of soil biodiversity, based on DNA meta-barcoding (Orgiazzi et al., 2015).
The main aims of the survey are:
i to be able to develop a quantitative indicator of soil biodiversity, based on the genetic signatures,
ii to look for correlations between the DNA evidence and land cover/land use, especially in intensive agricultural areas,
iii to match the DNA data with residues of plant protection products. Information on the latter is available from a separate analysis of the concentrations of 70 active ingredients and metabolites in around 3000 LUCAS samples, and
iv eventually to expand the analysis to look at functional groups.
The DNA meta-barcode analysis will cover different types of soil-living organisms, from micro-organisms to macrofauna, and precisely (Orgiazzi et al., 2018):
• bacteria and archaea – target region 16S ribosomal DNA (rDNA),
• fungi – target region internal transcribed spacer (ITS), and
• eukaryotes other than fungi – target region 18S ribosomal DNA (rDNA).
Possibly, nematodes, arthropod mesofauna, and earthworms will be included. The protocol defined by the Earth Macrobiome Project (EMP, 2017) will be applied.
Soil samples should be frozen as soon as possible after collection. This requires precise logistical arrangements (Fernandez-Ugalde et al., 2017): the surveyors need to prepare freezer packs well in advance of the sampling and place them in a polystyrene box the day of the survey, wash the sampling material before each sampling with alcohol and water and wear plastic gloves during the collection of the sample. Once sealed in the polystyrene box, the sample, wherever the sampling point is located in Europe, should reach the final storage location preferably within 48 hours.
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