LOGICALFRAMEOFTHETOOL - Integrated planning tool for ... ·...

LOGICAL FRAME OF THE TOOL (Action B1 Development of integrated planning tool

for sustainable grassland management)

Beneficiary responsible for implementation: BEF LT

Synthesized by: Kestutis Navickas

Vilnius, 2015

The project “Integrated planning tool to ensure viability of grasslands” (LIFE Viva Grass) No LIFE13 ENV/LT/000189 is co-‐financed by the EU LIFE+ Programme, Ministry of Environment of the Republic of Lithuania, Latvian Environmental Protection Fund, Estonian Environmental Investment Centre and the project partners.

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Table of content

Table of content ............................................................................................................................................... 2 Introduction ...................................................................................................................................................... 3 Abbreviations ................................................................................................................................................... 4 Goal and function of the Tool ...................................................................................................................... 5 Stakeholders, ES experts’ expectation on the Tool ........................................................................................... 6

Structure of the Tool ...................................................................................................................................... 7 Status ..................................................................................................................................................................................... 8 Policy objectives (for municipal or national level) ........................................................................................ 12 Land use options ........................................................................................................................................................... 13

Technical requirements for development of the Tool ...................................................................... 13 Map tool functions ........................................................................................................................................................ 13 System functions ........................................................................................................................................................... 14 User groups ..................................................................................................................................................................... 14 Use of the map tool ....................................................................................................................................................... 15

Main use cases ................................................................................................................................................ 17 ES assessment ................................................................................................................................................................ 17 Ecosystem services analysis ..................................................................................................................................... 19

Software architecture ...................................................................................................................... 24 Principal software components ............................................................................................................... 24 Database structure ....................................................................................................................................................... 26 Scale .................................................................................................................................................................................... 29

References ........................................................................................................................................... 30

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Introduction

The aim of the document is to provide guidance for the programmers of the „Integrated planning tool for sustainable grassland management” (Tool) to be able to respond to the vision of the LIFE VivaGrass project partners. On the other hand, this guidance shall help the work package leaders and experts of the project with one document illustrating the progress of the Tool development and to be able to define missing issues.

The goal of the Tool is to function as an instrument to support planning processes and to facilitate decision-‐making for better grassland management in the three Baltic States. Also to help planners and decision makers to understand the overall value of ecosystem services’ impact to its value by changing land use and interaction with different stakeholders groups and their added value for the society. On the other hand, the Tool shall help to see and simulate different driving forces causal of socioeconomic factors.

The Tool shall map and valuate all relevant to grasslands Ecosystem Services (ES) as well as consider major social and economic factors governing driving forces that are currently impacting the loss of Valuable grasslands.

Present document describes: structure and outputs generated by the Tool; its operational logic; ES assessment process; additional indicators based on socio-‐economic criteria; requirements for the design and accessibility of the Tool; specification of processes and their management structure (actors, responsibilities, and other organizational issues); specification of software requirements and solution architecture design; the input criteria (factors) that will formulate specific data needs; intended results; technical and program solution.

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Abbreviations

Term Explanation ES Ecosystem service ES Category Unit Smallest area for storing indicator. Combination of grassland

category, slope category and soil bonitet characteristics in area. ES Assessment Block

Group of ES category units, mainly defined by grassland boundary.

The Tool Integrated planning tool for sustainable grassland management

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Goal and function of the Tool

The goal of the Tool is to function as an instrument to support planning processes and to facilitate decision-‐making for better and efficient grassland management in the three Baltic States – in particular attention should be given to marginal (both from physician and socioeconomic perspective) high nature value grasslands. It shall help planners and decision makers to understand the overall value of ecosystem services’ and its changes according to land use or management practice change.

The Tool is meant to help to plan and improve various agri-‐environmental and nature conservation measures which will be develop by applying ecosystem planning approach, consider and socioeconomic circumstances. Furthermore, the Tool shall help to illustrate and understand the linkage of main socioeconomic factors driving to land use change and grasslands abandonment.

The Tool shall work based on spatial available data sets, experts valuation of different grasslands categories attributed to each ES indicator; however, additional data from the selected sites could be integrated to generate more precise information about values of ES, to create functional maps and features.

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Stakeholders, ES experts’ expectation on the Tool

Summarising interviews with different stakeholders from Baltic States on their expectation from the Tool we synthesised the following suggestions:

● The Tool should be able to provide proposals/ideas/hints for effective resource management by helping to find alternatives for grassland maintenance, business cases and indicate the risk of abandonment.

● It should be an advisory instrument in decision-‐making process to calculate and display most valuable grasslands based on ES valuation criteria and indicators and help to decide locations of “perspective” sites to ensure optimal provisional, regulatory or cultural ES’ output.

● The Tool should provide a generalized information on best measures in terms of biodiversity conservation or in terms of income generation; it shall identify strengths and weaknesses of both and help the planner/decision maker to see what is the most beneficial activity in a particular area.

● It should provide some hints on concrete measures to be applied and propose scenarios for economically valuable grasslands management without RDP payments.

● It shall broaden the view of planners on the planning process itself and support strategic planning processes.

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Structure of the Tool

The Tool will consist of 3 integral blocks: ES status; Land use options; Impact to ES through ES trade-‐offs.

Figure 1. Structure of the Tool (municipal/national level)

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Figure 2. Structure of the Tool (farm/site level)

Status

At this stage the Tool should calculate and display current values of ES. The assessment and mapping will be done by applying 3 different methodologies for: the provisional and regulatory ES; cultural ES and risk for abandonment.

Provisional and regulatory ES assessment and mapping The assessment and mapping should be done for each provisional and regulatory indicator. Matrix presented in the Table 1 was developed. Cultural ES will be assessed applying another approach. 5 of the provisional services and 8 regulatory services ES indicators were selected according to the Common International Classification of Ecosystem Services (CICES)1 classification, as the Tool will consider grasslands, arable land and abandoned land only. The value of the indicators is set based on the following land use classes: grasslands types (cultivated, permanent, semi-‐natural); soil quality (bonitet) and relief type (50 classes in total) (Table 1).

1 The Common International Classification of Ecosystem Services. http://cices.eu/

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Table 1. ES assessment matrix

ES/LU class Provisioning services Regulating services

Cultivated crops

Reared animals and their outputs

Fodder

Biomass-‐based energy source

Herbs for medicine

Bio-‐remediation

Filtration/storage/accumulation by ecosystems

Control (water) erosion rates

Pollination and seed dispersal

Maintaining habitats for plant and animal nursery and reproduction

Weathering processes/soil fertility

Chemical condition of freshwaters

Global climate change regulation

Grassland type 1-‐N

Arable land

Abandoned land

Based on these indicators an ES assessment matrix was developed. At the matrix intersections, the capacities of the different land cover types to supply particular ES are ranked by selected experts on a scale from 0 (no relevant capacity of the particular land cover type to supply the selected ES) to 5 (very high/maximum relevant capacity).

Experts should be selected considering following criteria: his/her expertise relevance to indicator or land use classes; understanding ES concept and assessment approach; basic understanding of spatial planning and GIS engine. It is highly recommended to have one or two key experts for appropriate indicators i.e., botanist, pollination expert, soil expert and etc. Besides of quality, the quantity (number of interviewed persons) of experts is also important. Although it is difficult to provide a generally valid number, 8-‐12 experts may be sufficient in most cases. It has to be considered that the interviewed persons need to be (at least) familiar with the region. A background in ES science and application is highly advantageous but can (due to the novelty of the approach) not be expected in all cases. Then, the concept and the aim of the grassland ES assessment need to be clearly explained (the best, based on prepared material and commonly accepted definitions).

The final assessment matrix filled by the project partners and experts is available at Annex No. 1.

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Finally, the ES shall be mapped by the Tool linking the assessment values to the functional units (natural boarders of grasslands type, arable and abandoned land).

Cultural ES assessment and mapping The cultural ES assessment and mapping has two dimensions: if the relevant to cultural ES object has point based record then spatial “impact” zone is drawn by visual impact criteria; if object has spatial dimension than overlapping areas with assessment polygon will have a value. Criteria in details are presented in the Table 2.

Table 2. Criteria for cultural ecosystem services

Ecosystem services

Indicators Criteria to calculate impact zone

1. Physical and experiential interactions (recreational)

● 1.1 Rural recreational enterprises

– 3km

Binary value 1/0 (there is/there is none)

● 1.2 Watching towers 1km radius. Binary value 1/0

● 1.3 Trails 300 m distance. Binary value 1/0

● 1.4 Social gathering sites 300 m distance. Binary value 1/0

● 1.5 Camping sites 300 m distance. Binary value 1/0

2. Educational ● 2.1 Educational trails 300 m distance. Binary value 1/0

● 2.2 Educational sites 300 m radius. Binary value 1/0

3. Cultural heritage

● 3.1 Monuments in rural areas 300 m distance or actual buffer zones where available. Binary value 1/0 (excluding manor houses)

● 3.2 Farmsteads before and in 19th century

300 m distance. Binary value 1/0, (manors from monument list)

● 3.3 Traditional land use Binary value 1/0. Each national team should come up with land use types which could be considered “traditional”

4. Aesthetics ● 4.1 Share of abandoned land There are no abandoned land in 300m distance value=1, there is value=0

● 4.2 Scenic roads 300m distance or where available actual sight zones. Binary value 1/0

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Risk for abandonment Farmland abandonment is a complex process with interlinked economic, environmental and social aspects and is often associated with social and economic problems in rural areas. It can be defined as the cessation of agricultural activities on a given surface of land (Pointereau, 2008). Abandonment includes a change towards a less intensive pattern of land use (Baudry, 1991) thus elimination and polarization of landscape mosaics and loss of landscape heterogeneity. Grasslands are agricultural ecosystems which are exposed to higher risk of abandonment than other types of farmland due to their rather marginal economic position (Strijker, 2005).

To assess a risk of abandonment we used composite method of combining analysis of number of drivers for abandonment at several scales. At site/farm level we have chosen to base assessment on both biophysical and socio-‐economic factors. To evaluate biophysical conditions we have chosen variables that have been proved to have greater impact on farmland abandonment: land quality (expressed as bonitet), relief, land-‐use and size of grassland (Vinogradovs et al., 2016). Based on calculations of relative risk hierarchical matrix of risk levels for grassland categories were created.

Additional site level socio-‐economic factors (Terress, 2013) were explored through questionary of land owners, thus supplementing previous studies and revealing importance of such factors as farmers/land owners age, residence, presence of successor and spatial parameters of farm (size, fragmentation) as well as legal status and possible burdens. It would be possible to improve results by adding data on comparison of farm income compared to regional/national average and share of subsidies in farm’s income.

To represent situation on national level and clarify context of site/farm specific risks (works also opposite) we analysed drivers of farmland abandonment on regional/municipal level. At regional or national levels, imbalanced economic development between sectors (agriculture, industry and services) increases the risk of abandonment. Same has been reported for inactive land market (Terres et al., 2015). Presence of high share of abandoned land (>20%) and natural afforestation is considered as important indicator of risk of farmland abandonment. Remoteness from regional centres, low population density and decline of population are traditional indicators for marginalization and thus were used for risk assessment as additional correction indices.

Matrix for risk of abandonment was created (Annex No.2); as base categories were used -‐ class of dominating site level risk (where available) or dominating land cover type. We do not intend to equalize these divisions but rather substitute former with later as a potentiality to assess rough results before detailed assessment was done. The weight of the indices is assessed using expert judgment method. Till this is done default index +1 is used.

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Policy objectives (for municipal or national level)

The Tool should have a possibility to simulate ES trade-‐offs in the scope of management plans with spatial dimension (landscape management plans, nature frame, NATURA 2000 network and etc.). This should help for decision makers or planners to plan interventional measures or develop managerial and financial measures based on ecosystem approach. It should allow to calculate ES value in selected polygons and see ES trade-‐offs by changing land use.

Summary of cross logic of relevant policies targeted to the grassland management, developed within action A1, concluded:

Environmental/nature conservation policy has high positive impact in the Baltic States. It creates preconditions for management of semi-‐natural grasslands, sets objectives for restoration, maintenance of ecosystems by grazing and mowing, biodiversity protection provides guides and rules for good management of grasslands, defines conditions for nature conservation subsidies for management of semi-‐natural grasslands (case in Estonia), etc. It also defines concrete targets to be reached e.g.:

● Rural development policy gives strong direct and mostly positive impact. Besides providing support and subsidies for farmers and landowners, it sets requirements for management and maintenance of biologically valuable grasslands, ensuring long term (at least 5 years) management. It requires not decreasing the total area of supported grasslands, requests mowing and gazing, removal of the excess grass from the meadow, prohibits land cultivation, requests elimination of invasive species, and provides guidelines for management of biologically valuable grasslands. However there are several policy shortcomings. For example, in Latvia, subsidies are envisaged only for the already existing and approved biologically valuable grasslands, thus not contributing to the increase of overall coverage of grasslands in the country. Moreover, the support available for maintenance of grasslands is in the range from 55-‐330 EUR/ha (for maintenance by grazing 25-‐58 EUR/ha) that might not be attractive enough. Subsidies for cultivation of arable land are more beneficial than for maintenance of biodiversity in grasslands. Even for organic farming subsidies are higher (97-‐485 EUR/ha).

Agri-‐environmental measures of RDPs in general contribute mostly positively to delivery of ecosystem services, with exception of measures for afforestation of non-‐used agriculture land, which are limiting the potential for provisioning of crops and products from reared animals as well as resulting in loss of cultural landscape and related services. The measures for support of agriculture production, including single area payments, mostly have positive impact on provisioning services, while can have adverse impact on regulating and cultural services.

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Land use options

The Tool shall provide to planners or decision makers the possibility to simulate land use change and to see variations of ES values. The users should know whether and to which extent land use change will affect the delivery of an ES and to see identified its optimum location. The model of the Tool shall help to decide on the current ES values and provide a proposal for optimal land use and to see an assessed risk for the land to be abandoned. The model shall help planners to understand which land use composition will generate biggest value of public goods. However, for this purpose the model must not only consider grasslands land cover but also the arable and abandoned land.

Technical requirements for development of the Tool

Map tool functions

Integrated planning tool functions are performed interactively using a map tool. Tool should be supported by the main Internet browsers (Internet Explorer, Mozilla, Chrome) without a need of additional plugin installation.

Map tool integrates map data review and analysis functions, detailed in the table below. Business specific functions for grasslands assessment and analysis are detailed in chapter “Main use cases”.

Table 3. Map functionality

No. Function Description 1. Navigate Use map navigation functions: display map, pan, zoom. 2. View data layers Review accessible layers list, turn on or off, show legend. 3. Authenticate users Provide authentication dialog for non-‐public map applications.

Check user roles, limit displayed content to user groups. 4. Find location Find location on the map by entering place name. 5. Identify objects Show attribute information of selected object. 6. Show attribute tables Display attributes of current layer in table. Attribute table must have

interactive selection methods, capabilities to limit attribute count by currently visible map area.

7. Filter attributes Interactively filter attribute list in the table by constructing queries. 8. Edit attributes Edit and update attribute information of selected object. If the

attribute is used to display features, cartographic symbol must change to correspond new value.

9. Measure Interactively measure coordinates, length and area on the map. Allow to change measurement units.

10. Swipe layers Select layer in list and swipe it over the rest of visible layers. This functionality provides capability to interactively compare two layers.

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11. Communicate with geoprocessing services

Map tool must have capabilities to interact with services, providing server-‐side processing functionality, review results as text, tables and graphic objects.

12. Analyse ES in area Interactively perform summarization of ES indices in defined area. Detailed description in use case “Ecosystem services analysis”.

13. Assess ES Interactively assign ES assessment index value to units in selected area. Detailed description in use case “ES assessment”.

System functions

Supportive functions to maintain and update data are required for the map tool. Functions are performed by a GIS professional in internal network and are related to data update and map publishing.

Table 4. System functions

No. Function Description 1. Limit content to

authenticated users Allow user authentication functionality, enable control user groups, limit access to content to specific user groups

2. Upload data Load data into database using direct connection to database. 3. Assign assessment data to ES

units using external tables Join tables from external data sources (provided by experts) and calculate assessment values.

4. Add new assessment index Manual configuration of data structures and services, required to introduce new assessment index to system.

5. Update administrative division of Assessment Unit

Tool, which automatically updates assignment of unit to country and municipality by performing spatial intersection.

6. Update municipality assignment to country

Tool, which automatically updates assignment of municipality to country by performing spatial intersection.

User groups

Map application must be publicly available on the Internet with capability to limit specific content to user groups. Public user has a capability to use map navigation functions, view and identify layers. Functionality related to data editing, services assessment and analysis are limited to professional experts. GIS administrators are a specific user group, performing data maintenance tasks on the internal network.

Table 5. User gruops

No. User group Description 1. Public user Not registered user, has an access to public map data and

functions. 2. Analyst Analyses particular area and indicators. Has an access to analysis

tool.

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3. Assessment manager Assessment of ecosystem service values in particular area using assessment form and map application.

4. GIS administrator GIS data administrator, has a capability to directly access and manage data stored in database. The role is responsible for classifiers, GIS data management, services publishing.

Use of the map tool

The map tool is main component of the integrated planning tool, providing user interface to map services and analysis tools. Map tool has a control of displaying map, attributes, identification results and specific analysis functionality.

Figure 3. Principal user interface of the map tool

Thematic layers are grassland-‐related layers displayed in the layer list. The base layers are used to provide information on topographic situation. User might change base layer from provided list (ESRI background layers, open street map). Thematic layers are published on GIS server and must be shared to user group accessing the map tool. Identification and display of attributes is related to active thematic layer.

Specific analysis tools are placed in widgets having user interfaces for an input parameters and output result display. Analysis requests are sent to GIS servers geoprocessing tasks, results returned to user and added to map and output form. Specific functionality and user forms detailed in „Main use cases “.

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Figure 4. Principal components of the integrated planning tool map application

Table 6. Map layers and layer groups

No. Layer Colour scheme, symbol 1. Administrative division – country boundaries 2. Administrative division – municipality boundaries Layer group: “Grasslands”. Grassland categories and components of grassland categorization displayed as separate layers. 3. Assessment units, symbolized by grassland category Symbols of 33 grassland category units

provided separately 4. Soil fertility

5. Slope category

6. Grassland naturality category

Layer group “Ecosystem services”. Current values of ecosystem services in grassland assessment units

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7. Cultivated crops

8. Reared animals and their outputs

9. Fodder

10. Biomass-‐based energy sources

11. Herbs for medicine

12. Bio-‐remediation

13. Filtration/sequestration/storage/accumulation by ecosystem

14. Control of erosion rates

15. Pollination and seed dispersal

16. Maintaining habitats

17. Weathering processes/soil fertility

18. Chemical condition of freshwaters

19. Global climate regulation

Layer group “Ecosystem services in case of abandonment”. Values of ecosystem services in grassland assessment units in case of abandonment. Layer names and symbology corresponding to layers 7-‐19. Layer group “Ecosystem services in case of arable”. Values of ecosystem services in grassland assessment units in case of converting land to arable. Layer names and symbology corresponding to layers 7-‐19.

Main use cases

Use cases described in this chapter require business specific data processing functionality. Specific server-‐side geoprocessing tools are constructed to support this functionality and user interfaces (forms) to interact with services must be developed.

ES assessment

Ecosystem services assessment is performed by authenticated expert, having required knowledge and familiar with particular territory. The main principle of assessment is to assign evaluation index by ecosystem services to grassland type in particular area.

Steps of ecosystem services assessment:

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1. Select one ES to be assessed. 2. Select analysis area. Area, which intersects with assessment blocks will be included into

assessment. a. Administrative unit allows selecting countries and municipalities to be analysed. b. Define area on the map. Area is defined by interactively drawing rectangle or

polygon on the map. c. Upload zipped shape file. First polygon of first polygon feature class found in

shape file must be used. 3. Enter indices for each grassland type. Indices vary from 0 to 5 (-‐1 is used for unassessed

units). 4. Click “Update assessment”. 5. System assigns indices to ES Category units by grassland category. Report, containing

count of assessed ES units is provided to user.

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Figure 5. Ecosystem services assessment form

Ecosystem services analysis

Ecosystem services analysis performed by authenticated specialist (analyst) is oriented to get summary information and recommendations on particular territory. W

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Figure 6. Analysis input parameters

Steps of analysis:

1. Select analysis area: a. Administrative unit. Allows selecting countries and municipalities to be analysed. b. Define area on the map. Area is defined by interactively drawing rectangle or

polygon on the map. 2. Select (mark) ES to be included into weighted sum of indicators. Define weight of each

selected service to weighted index by %. Total sum of percents entered must be equal to 100.

3. Click “Calculate” and wait for results. Results include: a. Summary report. b. Analysed area drawn on the map and added as layer.

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Figure 7. Output summary information

Mean value of one selected ecosystem service is calculated by summarizing assessment values in selected territory. Each assessment is multiplied by unit area and divided by whole territory area.

𝐸𝑆𝑆 =𝑠!𝑆

!

!!!

∗ 𝑎!

𝑠! – Area o one partial unit

𝑎! – Assessment value in one partial unit

S – Area of selected territory

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Example. Selected area on the map includes 5 ecosystem assessment units, with fodder values as follows:

No. Area of unit (��) Assessment value (��) 1. 10 2 2. 20 0 3. 20 5 4. 40 3 5. 10 4 Total area(S): 100 -‐

Mean assessment value: (10/100*2) +(20/100*0) +(20/100*5) + (40/100*3) + (10/100*4) = 2,8

Weighted index is an average of user selected ES and is calculated considering user-‐defined weight by % of each index value. Mean value of each service is calculated using method described above.

𝑊 =𝐸𝑆𝑆! ∗ 𝑤!100

!

!!!

𝐸𝑆𝑆! -‐ Mean value of selected ecosystem service i.

𝑤! – Weight of selected ecosystem service i.

Example. User has defined 4 ecosystem services and their influence to weighted index as shown in the table.

Ecosystem Service Calculated mean value User-‐defined weight, % Reared animals and their outputs 2 30 Fodder 5 40 Herbs for medicine 2 10 Weathering processes/soil fertility 2 20 Total: 100%

Weighted index: 2*30/100 + 5*40/100 + 2*10/100 + 2*20/100 = 3,2

Calculating cases of abandonment and turning to arable land.

There is a scenario to which land category type land will turn in case of abandonment and after turning into arable land. Abandoned and arable land have different default (predefined) ecosystem service indices.

Simulation workflow:

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1. Define target category type in case of abandoned or arable. Table CAT_CHANGE must be used: FROM_CAT – current category; TO_CAT – category to which index changes; CHANGE_TYPE: ABD – abandonment, ARR – arable.

2. Use default assessment value of defined target category. ES assessment values are defined in table DEFAULT_ASMI. CAT – target category, ASMI_CODE – is the index for which the value is assigned, VAL – index value for category.

There must be separate simulations made for abandonment and arable land. Results summarized in table (Annex No. 1).

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Software architecture

Principal software components

Software architecture is based on ArcGIS products family. Data management, map design, publishing tasks are performed in the internal network of hosting organization using ArcGIS for Desktop (ArcMap). Map services published to ArcGIS for server are managed on Portal for ArcGIS. Portal allows to limit access to specific map and geoprocessing task resources to specific user groups; using portal map different map services are combined into one map resource. This map is basis for the web map application.

Web map tools are built as application using ArcGIS Web application builder. Software itself has a rich set of configurable tools for controlling map appearance, layers, measurement, etc. Specific functionality, required to perform ecosystem assessment and analysis are python-‐based geoprocessing tasks published to ArcGIS for Server, included into web mapping application using customized user interface for input and output parameters (custom widgets). Web applications are built internally and then deployed to web applications hosting site. Web applications, map and geoprocessing resources can be limited to specific user groups using Portal authentication mechanism.

To ensure reachability of the internal web applications in the Internet, hosting organization must configure external web server (reverse proxy), to forward requests to ArcGIS web adaptor and Web applications hosting site.

Table 7. Software components

No. Component Description 1. Reverse proxy server Proxy server of hosing organization, allowing to communicate

external requests and specific internal resources. Enables access of portal and web application sites on public internet.

2. Internet information services Web server based on IIS (internet information services) technology, used to host web applications.

3. ArcGIS Web Adaptor Web application, forwarding web requests to Portal for ArcGIS.

4. Portal for ArcGIS Web application, supports organizations map resource sharing, user management and controlling access to resources to user groups. Portal is used to combine layers from different map services into one map, displayed in web mapping application.

5. ArcGIS for Server GIS server, which supports publishing of map image and feature services, used as layers in the map. Specific data analysis and processing functionality

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6. ArcGIS Web application builder

Tool for constructing web applications with maps. Tool is used internally, built web application is copied and hosted on web applications hosting site.

7. Web applications hosting site Built web applications, published to internet. 8. ArcGIS for Desktop Desktop software for internal management of data structures,

map services, preparing maps for publishing (cartography). 9. Database engine Database, supporting spatial data technology. PostgreSQL

data base engine will be used. Data base is spatially enabled using PostGIS and ArcSDE extensions.

Figure 8. Communication between software components

According to the required functionality, published services count recommended system requirements are provided below. It is recommended to have 3 separate server machines for database server, GIS server and web publishing. ArcGIS for Desktop must be installed on local GIS administrators’ computer.

Table 8. Server hardware requirements

No. Component Characteristics 1. Processor 4 CPU 2. RAM 16 GB 3. Disk storage 500 GB

Table 9. Required licensed software

No. Component Characteristics 1. Windows operating system Windows Server 2012 R2. 2. ArcGIS for Server (4 cores) Standard edition. Including ArcGIS for portal, at least 5 named

users. 3. ArcGIS for Desktop Standard edition, compatible with ArcGIS for Server.

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4. PostgreSQL database engine Open source database engine, supported by ArcGIS server

Database structure

The main business table, storing information about ES values in grasslands is assessment unit (ASM_UNIT). Values of indices are stored in separate columns for each index (ASM_UNIT), index types are described in table CLS_ASMI, column names must match index code. Performing analysis and evaluation of grasslands it’s important to analyse whole block of grasslands (ASM_BLOCK). Each grassland unit is assigned to country (COUNTRY) and municipality (MUNIC).

In case of abandonment and turning land to arable information from views (conv_abd_view, conv_arr_view) is used. Table CAT_CHANGE represents category change from-‐to, table DEFAULT_ASMI represent default assessment index value for each land category type.

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Figure 9. Database diagram

Table 10. ASM_BLOCK -‐ assessment block. Group of ES units

No. Field Type, length Description 1. OBJECTID ObjectID (Long integer) Object ID, controlled by system 2. BLOCK_ID Long integer Assessment block ID

ASM_UNIT (Polygon) – Assessment unit (ecosystem services unit). This is the smallest unit to be evaluated, assessment index values are assigned to every unit. This feature class contains columns for ecosystem services (or other) assessment values. Assessment column count and types have to be defined in table CLS_ASMI.

No. Field Type, length Description

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1. OBJECTID ObjectID (Long integer) Object ID, controlled by system 2. CATEGORY Text, 50 Current category. Values from domain

LAND_CATEGORY 3. LANDUSE Text, 20 Current land use.

GRASS – Grassland ARR – Arable ABD – Abandoned

4. BLOCK_ID Long integer Assessment block ID 5. COUNTRY_C Text, 50 Country code 6. MUNIC_C Text, 100 Municipality code 7. RANIMALS Short integer Reared animals and their outputs 8. FODDER Short integer Fodder 9. BIOMENG Short integer Biomass-‐based energy sources 10. HERBS Short integer Herbs for medicine 11. ERCONTR Short integer Control of erosion rates 12. HABITM Short integer Maintaining habitats 13. WEATNG Short integer Weathering processes/soil fertility 14. CHC Short integer Chemical condition of freshwaters 15. CLIMATE Short integer Global climate regulation 16. CUCROPS Short integer Global climate regulation 17. BIORM Short integer Bio-‐remediation 18. ACCUM Short integer Filtration/storage/accumulation by ecosystems 19. POLLIN Short integer Pollination and seed dispersal Table 11. ASM_UNIT (Polygon)

Table 12. COUNRTY (Polygon) -‐ country territories

No. Field Type, length Description 1. OBJECTID ObjectID (Long integer) Object ID, controlled by system 2. CODE Text, 50 Country code 3. NAME Text, 100 Country name Table 13. MUNIC (Polygon) -‐ territories of municipalities

No. Field Type, length Description 1. OBJECTID ObjectID (Long integer) Object ID, controlled by system 2. CODE Text, 50 Municipality code 3. NAME Text, 100 Municipality name 4. COUNTRY_C Text, 50 Country code (COUNTRY.CODE)

Table 14. CLS_ASMI -‐ classification of assessment indices. Indices described in the table will be added to ASM_UNIT layer as columns. For column name attribute CODE will be used

No. Field Type, length Description 1. OBJECTID ObjectID (Long integer) Object ID, controlled by system

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2. CODE Text, 10 Assessment index code, field with code name will be created in ESS_UNIT table

3. GRCODE Text, 10 Assessment index group: PROV – Provisional. REGM – Regulation and maintenance. CULT – Cultural.

4. DESCR Text, 50 Description, explanation of index 5. VALTYPE Text, 10 Type of value (Text, Integer, Double) 6. MINVAL Text, 50 Minimum value of index 7. MAXVAL Text, 50 Maximum value of index 8. NDVAL Text, 10 No data value

Table 15. CAT_CHANGE -‐ category change used for land use change scenario (turning into arable, abandoned)

No. Field Type, length Description 1. OBJECTID ObjectID (Long integer) Object ID, controlled by system 2. FROM_CAT Text, 10 Current category 3. TO_CAT Text, 10 Category to which land changes 4. CHANGE_TYPE Text, 50 Type of category change (scenario):

ABD -‐ abandonment ARR -‐ arrable

Table 16. DEFAULT_ASMI -‐ default assessment index values by category. Values may vary in different territories -‐ countries and municipalities

No. Field Type, length Description 1. OBJECTID ObjectID (Long integer) Object ID, controlled by system 2. ASMICODE Text, 10 Assessment index code (CLS_ASMI.CODE) 3. CAT Text, 50 Category, assigned to unit 4. VAL Short integer Default value, assigned to category 5. COUNTRY_C Text, 50 Country code 6. MUNIC_C Text, 50 Municipality code

Scale

The project team agreed that the minimum unit for data gathering and processing will be from municipality level down to farm level; accordingly, the map scale shall be ranging from 1:50 000 to 1: 5 000.

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References

Strijker, D., 2005. Marginal lands in Europe—causes of decline. Basic and Applied Ecology, 6(2), pp.99-‐106.

Terres, J.M., 2013. Assessing the risk of farmland abandonment in the EU. Publications Office.

Terres, J.M., Scacchiafichi, L.N., Wania, A., Ambar, M., Anguiano, E., Buckwell, A., Coppola, A., Gocht, A., Källström, H.N., Pointereau, P. and Strijker, D., 2015. Farmland abandonment in Europe: Identification of drivers and indicators, and development of a composite indicator of risk. Land Use Policy, 49, pp.20-‐34.

Pointereau, P., 2008. Analysis of farmland abandonment and the extent and location of agricultural areas that are actually abandoned or are in risk to be abandoned. EUR-‐OP.

Baudry, J., 1991. Ecological consequences of grazing extensification and land abandonment: role of interactions between environment, society and techniques. Options Mediterraneennes. Serie A: Seminaires Mediterraneens (CIHEAM).

Vinodradovs I., Nikodemus O., Tabors G., Krūze I., Elferts D. 2016. Assessment of factors of landscape change in mosaic type landscape: a case study of Vidzeme, Latvia. Proceedings of the 19th Conference of Junior researchers "Science -‐ future of Lithuania. Vilnius

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T h e p r o j e c t “ I n t e g r a t e d p l a n n i n g t o o l t o e n s u r e v i a b i l i t y o f g r a s s l a n d s ” ( L I F E V i v a G r a s s ) N o L I F E 1 3 E N V / L T / 0 0 0 1 8 9 i s c o -‐ f i n a n c e d b y t h e E U L I F E + P r o g r a mm e , M i n i s t r y o f E n v i r o n m e n t o f t h e R e p u b l i c o f L i t h u a n i a , L a t v i a n E n v i r o n m e n t a l P r o t e c t i o n F u n d , E s t o n i a n E n v i r o n m e n t a l I n v e s t m e n t C e n t r e a n d t h e

p r o j e c t p a r t n e r s .

LOGICAL FRAME OF THE TOOL A n n e x N o . 1 . E c o s y s t e m S e r v i c e a s s e s s m e n t m a t r i x

1

Provisioning Regulation & Maintenance

Culti

vate

d cr

ops

(t /ha

per y

ear)

Rear

ed an

imals

and

their

out

puts

Num

ber

of a

nimals

unit

s (n/

ha)

Fodd

er

Stan

ding s

tock (

t /ha p

er ye

ar)

Biom

ass-

base

d en

ergy

sour

ces

Stan

ding s

tock (

t /ha p

er ye

ar)

Herb

s for

med

icine

(n

umbe

r of s

pecie

s/1m2

) Bi

o-re

med

iatio

n by

micr

o-or

ganis

ms, p

lants

and a

nimals

; Indic

ator:

???

Filtr

atio

n/st

orag

e/acc

umul

atio

n by

ec

osys

tems;

Indica

tor: S

oil ca

pacit

y to

store

/accu

mulat

e nutr

ients

(Kg h

a-1)*

Cont

rol o

f (wa

ter)

eros

ion

rate

s Sl

ope s

teepn

ess (

degr

ees,

o), c

onten

t of s

oil

partic

le siz

e – sa

nd, s

ilt,cla

y (%

) Po

llinat

ion

and

seed

disp

ersa

l; Ind

icator

: Di

versi

ty an

d occ

urre

nce o

f inse

cts po

llinato

rs (n

umbe

r of s

pecie

s and

numb

er of

ind

ividu

als/ha

)

Main

tain

ing

habi

tats

for p

lant a

nd an

imal

nurse

ry an

d rep

rodu

ction

; Indic

ator:

Numb

er

of sp

ecies

per 1

m2 (

exce

pt inv

asive

spec

ies)

Wea

ther

ing

proc

esse

s/soi

l fer

tility

Nu

trients

avail

able

for pl

ant u

ptake

by m

ost

impo

rtant

soil t

extur

e clas

ses

Chem

ical c

ondi

tion

of fr

eshw

ater

s Ab

sorp

tion o

f nutr

ients

in so

il

Glob

al cli

mat

e reg

ulat

ion

Carb

on se

ques

tratio

n in v

egeta

tion a

nd so

ils

1. Cultivated grassland on plain relief, low soil fertility 0 3 2 2 1 2 2 0 2 2 2 2 2

2. Cultivated grassland on plain relief, medium soil fertility 0 4 3 3 1 3 3 0 2 2 3 3 2 3. Cultivated grassland on plain relief in, high soil fertility 0 5 4 4 1 3 4 0 2 2 4 4 2 4. Cultivated grassland on plain relief, organic soils 0 4 3 3 1 4 4 0 2 2 0 3 3 5. Cultivated grassland on gentle slope in low soil fertility 0 3 2 2 1 2 2 2 2 2 2 2 2 6. Cultivated grassland on gentle slope, medium soil fertility 0 4 3 3 1 3 3 2 2 2 3 3 2 7. Cultivated grassland on gentle slope, high soil fertility 0 5 4 4 1 3 4 3 2 2 4 4 2 8. Cultivated grassland on gentle slope, organic soil 0 4 3 3 1 4 4 0 2 2 0 3 3 9. Cultivated grassland on steep slope low soil fertility 0 3 2 2 1 2 2 3 2 2 2 2 2 10. Cultivated grassland on steep slope, medium soil fertility 0 4 3 3 1 3 3 3 2 2 2 3 2 11. Permanent grassland on plain relief in, low soil fertility 0 2 1 1 3 3 2 0 4 4 2 3 3 12. Permanent grassland on plain relief, medium soil fertility 0 3 2 2 2 4 3 0 4 3 3 4 3 13. Permanent grassland on plain relief, high soil fertility 0 4 3 3 2 4 4 0 4 3 4 5 3 14. Permanent grassland on plain relief, organic soils 0 3 2 2 2 5 4 0 4 3 0 3 4 W

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15. Permanent grassland on gentle slope, low soil fertility 0 2 1 1 3 3 2 4 4 4 2 3 3 16. Permanent grassland on gentle slope, medium soil fertility 0 3 2 2 2 4 3 3 4 3 3 4 3 17. Permanent grassland on gentle slope, high soil fertility 0 4 3 3 2 4 4 3 4 3 4 5 3 18. Permanent grassland on gentle slope, organic soils 0 3 2 2 2 5 4 0 4 3 0 3 4 19. Permanent grassland on steep slope, low soil fertility 0 2 1 1 3 3 2 5 4 4 2 3 3 20. Permanent grassland on steep slope, medium soil fertility 0 3 2 2 2 4 3 5 4 3 2 4 3 21. Semi-natural grassland on plain relief, low soil fertility 0 1 1 1 5 4 2 0 5 5 2 3 4 22. Semi-natural grassland on plain relief, medium soil fertility 0 2 2 2 4 5 3 0 5 4 3 4 4 23. Semi-natural grassland on plain relief, high soil fertility 0 3 3 3 3 5 4 0 5 3 4 5 4 24. Semi-natural grassland on plain relief, organic soils 0 3 3 3 4 5 4 0 5 4 0 3 5 25. Semi-natural grassland on gentle slope, low soil fertility 0 1 1 1 5 4 2 4 5 5 2 3 4 26. Semi-natural grassland on gentle slope, medium soil fertility 0 2 2 2 4 5 3 4 5 4 3 4 4 27. Semi-natural grassland on gentle slope, high soil fertility 0 3 3 3 3 5 4 4 5 3 4 5 4 28. Semi-natural grassland on gentle slope, organic soils 0 3 3 3 4 5 4 0 5 4 0 3 5 29. Semi-natural grassland on steep slope, low soil fertility 0 1 1 1 5 4 2 5 5 5 2 3 4 30. Semi-natural grassland on steep slope, medium soil fertility 0 2 2 2 4 5 3 5 5 4 2 4 4 31. Arable land on plain relief, low soil fertility 1 0 3 3 1 1 1 0 1 1 1 1 1 32. Arable land on plain relief, medium soil fertility 3 0 4 4 1 1 2 0 1 1 2 2 1 33. Arable land on plain relief in, high soil fertility 5 0 5 5 1 1 3 0 1 1 3 2 1 34. Arable land on plain relief, organic soils 2 0 4 4 1 2 3 0 1 1 0 3 0 35. Arable land on gentle slope in low soil fertility 1 0 3 3 1 1 1 0 1 1 1 1 1 36. Arable land on gentle slope, medium soil fertility 3 0 4 4 1 1 2 0 1 1 2 2 1 37. Arable land on gentle slope, high soil fertility 5 0 5 5 1 1 3 0 1 1 3 2 1 38. Arable land on gentle slope, organic soil 2 0 4 4 1 2 3 0 1 1 0 3 0 39. Arable land on steep slope low soil fertility 0 0 3 3 1 1 1 0 1 1 1 1 1 40. Arable land on steep slope, medium soil fertility 0 0 4 4 1 1 2 0 1 1 2 2 1 41. Abandoned land (with shrub) on plain relief, low soil fertility 0 0 0 3 3 3 3 0 3 3 3 4 5 42. Abandoned land (with shrub) on plain relief, medium soil fertility 0 0 0 2 2 4 4 0 3 3 4 5 5 W

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43. Abandoned land (with shrub) on plain relief in, high soil fertility 0 0 0 1 2 4 5 0 3 3 5 5 5 44. Abandoned land (with shrub) on plain relief, organic soils 0 0 0 3 2 5 5 0 3 3 0 4 5 45. Abandoned land (with shrub) on gentle slope in low soil fertility 0 0 0 3 3 3 3 4 3 3 3 4 5 46. Abandoned land (with shrub) on gentle slope, medium soil

fertility 0 0 0 2 2 4 4 4 3 3 4 5 5

47. Abandoned land (with shrub) on gentle slope, high soil fertility 0 0 0 1 2 4 5 5 3 3 5 5 5 48. Abandoned land (with shrub) on gentle slope, organic soil 0 0 0 3 2 5 5 0 3 3 0 4 5 49. Abandoned land (with shrub) on steep slope low soil fertility 0 0 0 3 3 3 3 5 3 3 3 4 5 50. Abandoned land (with shrub) on steep slope, medium soil

fertility 0 0 0 2 2 4 4 5 3 3 4 5 5

Explanations: plain relief: 0-3° gentle slope: 4-14° steep slope: >15° low soil fertility value: ≤ 30 medium soil fertility value: 31 -50 high soil fertility value: > 50

Abandoned land - not used for more than 10 years and overgrowing with shrubs and trees

* - Polution retention - Filtration/storage/accumulation by ecosystems -

in case of draned soils the value shall be lowered by 1 unit

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LOGICAL FRAME OF THE TOOL A n n e x N o . 2 . Matr ix for r i sk o f abandonment

1

Correction indices Additional correction indices

TOTA

L

Grassland categories Level of risk of abandonment

If area of a

ssessm

ent

block is < 5ha

If area of a

ssessm

ent

block is < 3ha

If farm

ers a

ge is >60

Not local residen

ce

Fragmen

ted farm

structure

Great sh

are of

subsidies in income

>75%

Legal burde

ns

Lack of farm

successor

Low income <2

5% of

natio

nal average

1. Cultivated grassland on plain relief, low soil fertility MODERATE (2) + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1

2. Cultivated grassland on plain relief, medium soil fertility LOW (1) + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1

3. Cultivated grassland on plain relief in, high soil fertility LOW (1) + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1

4. Cultivated grassland on plain relief, organic soils MODERATE (2) + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1

5. Cultivated grassland on gentle slope in low soil fertility MODERATE (2) + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1

6. Cultivated grassland on gentle slope, medium soil fertility LOW (1) + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1

7. Cultivated grassland on gentle slope, high soil fertility LOW (1) + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1

8. Cultivated grassland on gentle slope, organic soil MODERATE (2) + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1

9. Cultivated grassland on steep slope low soil fertility HIGH (3) + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1

10. Cultivated grassland on steep slope, medium soil fertility HIGH (3) + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1

11. Cultivated grassland on steep slope, high soil fertility HIGH (3) + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1

12. Permanent grassland on plain relief in, low soil fertility MODERATE (2) + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1

13. Permanent grassland on plain relief, medium soil fertility LOW (1) + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1

14. Permanent grassland on plain relief, high soil fertility LOW (1) + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1

15. Permanent grassland on plain relief, organic soils MODERATE (2) + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1

16. Permanent grassland on gentle slope, low soil fertility MODERATE (2) + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1

17. Permanent grassland on gentle slope, medium soil fertility LOW (1) + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 Wor

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18. Permanent grassland on gentle slope, high soil fertility LOW (1) + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 19. Permanent grassland on gentle slope, organic soils MODERATE (2) + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1

20. Permanent grassland on steep slope, low soil fertility HIGH (3) + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1

21. Permanent grassland on steep slope, medium soil fertility HIGH (3) + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 22. Permanent grassland on steep slope, high soil fertility HIGH (3) + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1

23. Semi-‐natural grassland on plain relief, low soil fertility HIGH (3) + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1

24. Semi-‐natural grassland on plain relief, medium soil fertility MODERATE (2) + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 25. Semi-‐natural grassland on plain relief, high soil fertility MODERATE (2) + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1

26. Semi-‐natural grassland on plain relief, organic soils HIGH (3) + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1

27. Semi-‐natural grassland on gentle slope, low soil fertility HIGH (3) + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 28. Semi-‐natural grassland on gentle slope, medium soil fertility MODERATE (2) + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1

29. Semi-‐natural grassland on gentle slope, high soil fertility MODERATE (2) + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1

30. Semi-‐natural grassland on gentle slope, organic soils HIGH (3) + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1

31. Semi-‐natural grassland on steep slope, low soil fertility HIGH (3) + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1

32. Semi-‐natural grassland on steep slope, medium soil fertility HIGH (3) + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1

33. Semi-‐natural grassland on steep slope, high soil fertility HIGH (3) + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1

34. Arable land on plain relief, low soil fertility MODERATE (2) + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1

35. Arable land on plain relief, medium soil fertility LOW (1) + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1

36. Arable land on plain relief in, high soil fertility LOW (1) + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1

37. Arable land on plain relief, organic soils MODERATE (2) + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1

38. Arable land on gentle slope in low soil fertility MODERATE (2) + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1

39. Arable land on gentle slope, medium soil fertility LOW (1) + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1

40. Arable land on gentle slope, high soil fertility LOW (1) + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1

41. Arable land on gentle slope, organic soil MODERATE (2) + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1

42. Arable land on steep slope low soil fertility HIGH (3) + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 Wor

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43. Arable land on steep slope, medium soil fertility HIGH (3) + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 44. Arable land on steep slope, high soil fertility HIGH (3) + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 45. Abandoned land (with shrub) on plain relief, low soil fertility DIV/0!

46. Abandoned land (with shrub) on plain relief, medium soil fertility DIV/0!

47. Abandoned land (with shrub) on plain relief in, high soil fertility DIV/0!

48. Abandoned land (with shrub) on plain relief, organic soils DIV/0! 49. Abandoned land (with shrub) on gentle slope in low soil

fertility DIV/0!

50. Abandoned land (with shrub) on gentle slope, medium soil fertility DIV/0!

51. Abandoned land (with shrub) on gentle slope, high soil fertility DIV/0!

52. Abandoned land (with shrub) on gentle slope, organic soil DIV/0! 53. Abandoned land (with shrub) on steep slope low soil

fertility DIV/0!

54. Abandoned land (with shrub) on steep slope, medium soil fertility DIV/0!

55. Abandoned land (with shrub) on steep slope, high soil fertility DIV/0!

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