From 0e71945a195f5ff6aab01cd02fe760bd2e66cf4b Mon Sep 17 00:00:00 2001 From: arunherb Date: Fri, 6 Sep 2024 05:23:57 +0000 Subject: [PATCH] Updated Methods Vocabs - COndition Module V2 --- .../condition/condition-protocol.ttl | 1158 +++++++---------- 1 file changed, 453 insertions(+), 705 deletions(-) diff --git a/vocab_files/methods_by_module/condition/condition-protocol.ttl b/vocab_files/methods_by_module/condition/condition-protocol.ttl index 5ef3b8a11..959d0f6b6 100644 --- a/vocab_files/methods_by_module/condition/condition-protocol.ttl +++ b/vocab_files/methods_by_module/condition/condition-protocol.ttl @@ -28,96 +28,86 @@ PREFIX xsd:
  • References
  • Appendices
    • -

    Module overview

    -

    Available protocols

    -

    Each of the field measures in the Condition Module describe -biodiversity condition. The module provides procedures and guidelines -for recording a set of core attributes, in combination with measures -from the Recruitment, Coarse Woody Debris, Fire Severity and the Herbivory and -Physical Damage Modules, which collectively form the condition set of -protocols. The results from other modules, including Floristics, Cover -and Signs-based Fauna Surveys also feed into condition assessments. This -protocol includes step-by-step instructions for the core set of -condition measures. Refer to the Recruitment, Coarse Woody Debris, Fire -and Herbivory and Physical Damage Modules for survey guidelines for -these measures (links to the relevant sections are provided below).

    -

    Relationships to other -modules

    +

    Module Overview

    +

    Available Protocols

    +

    The Condition Module includes a Condition attributes protocol, which +provides procedures and guidelines for recording data for a set of core +biodiversity condition attributes, including the growth stage, life +stage, height, diameter at breast height (DBH), health measures (e.g. +dieback, mistletoe, hollows, insect damage) and associated litter depth +of trees and shrubs within the plot.

    +

    The module also provides information on other modules/protocols that +should be completed as part of condition monitoring to assess structure, +function and composition, including the Plot Description, Floristics, +Recruitment, Coarse Woody Debris, Basal Area, Cover Module, Fire Severity, +Herbivory and Physical Damage, and Sign-based Fauna Surveys Modules +(refer to each module for specific procedures and guidelines).

    +

    Relationships to other modules

    Complete prior to the Condition Module

    -

    Complete concurrently with the Condition Module

    +

    Complete concurrently with the Condition Module

    Optional complementary modules to gather additional information relating to condition:

    - """^^rdf:HTML ; - dcterms:source """ -

    References

    +"""^^rdf:HTML ; + dcterms:source """

    References

    Baker, TR, Chao, KJ, 2011. Manual for coarse woody debris measurement in RAINFOR plots. Version 2.

    Bleby, K, Harvey, J, Garkaklis, M, Martin, L (2008) Resource @@ -407,24 +397,23 @@ Aboriginal land management in central Arnhem Land, northern Australia: a tradition of ecosystem management. Journal of Biogeography 28, 325-343.

    """^^rdf:HTML ; rdfs:isDefinedBy ; - skos:definition """ -

    Key definitions and + skos:definition """

    Key definitions and terminology

    -

    Table 1. Key -definitions and terms used in the Condition Module.

    + - + - + - + + + + + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - +

    Table 1. Key +definitions and terms used in the Condition Module.
    Term Definition
    Benchmark (reference state) A standard vegetation-condition reference point relevant to the vegetation type that is applied in vegetation condition assessments. @@ -435,13 +424,17 @@ al. 2017). Benchmark values are often based on the average value from a range of sites in the reference state in order to capture natural variability (Eyre et al. 2017).
    BOOBest on offer
    Browsing Browsers are those herbivores which substantially feed on the foliage of non-grassy plants including trees, shrubs and palms (McDonald and Brandle 2009).
    Coarse woody debris (CWD) Defined here as whole fallen trees, branches and pieces of fragmented wood ≥ 50 cm (or ≥30 cm in some systems) in length with a @@ -450,37 +443,37 @@ does not include live material, standing dead trees, stumps, dead foliage, separated bark, nonwoody pieces, roots or the part of the trunk below the root collar (Waddell 2002).
    Condition Biodiversity condition is a measure of the status of the biota at an assessment site described by key attributes that reflect structure, function and composition.
    Condition subplot The central 40 x 40 m area within a plot, defined by the 30 m and 70 m transects of a 100 m x 100 m plot.
    Diameter at breast height (DBH) The straight-line distance in centimetres across the centre of a standing tree trunk or stem measured at 1.3 m above the ground.
    EIA Environmental impact assessment
    Growth form The form or shape of individual plants, e.g. tree, shrub, grass (NCST 2009).
    Growth stage Provides a measure of age class structure, including recruiting, resprouting, mature, senescent or dead.
    GRS Densitometer™ Instrument developed by Geographic Resource Solutions for measuring canopy cover during point-intercept sampling. A vertical sighting tube @@ -489,135 +482,135 @@ immediate canopy coverage. Internal, offset levelling vials ensure accurate readings of the canopy directly above each point-intercept.
    Intervention Planned activities designed to achieve a set of clear objectives within a given timeframe and budget.
    Large tree Native trees with a DBH equal to or greater than the threshold -diameter specific for that vegetation type (see Appendix; Eco Logical +diameter specific for that vegetation type (Appendix X; Eco Logical Australia 2013). Large trees can be classified post-survey using DBH measurements obtained from the tree survey.
    Juvenile Trees: individuals with a DBH between 5-10 cm. Shrubs: has not reached maximum height, apical dominance. Not reproductive.
    Leaf litter Leaf matter or fine woody material such as twigs that are detached and lying on the ground.
    Life-stage Measure of reproductive stage, including seedling, sapling, vegetative, budding, flowering, immature fruit, mature fruit, or recently shed (Heard and Channon 1997).
    NRM Natural Resource Management
    Monitor Field data collection app for Ecological Monitoring System Australia. Collects data using the Biodiversity Information Standard for delivery to the Australian Biodiversity Data Repository managed by the Department of Climate Change, Energy, the Environment and Water.
    Partially downed tree Standing dead tree that is no longer self-supported (not fully rooted in the ground) (Puletti et al. 2019). A partially downed tree may be suspended in the air with support.
    Percent canopy A measure of vegetation health, based on an estimate of the percent of canopy present.
    Plot The specific survey area where information is collected (generally 100 m x 100 m; 1 ha). Final plot location is determined in the field, with preference given to homogeneous areas representative of the broader project area, with a constant mix of vegetation, relief and soil.
    Point-intercept Method designed to sample species, growth-form, substrate cover and health by placing a point-intercept staff along a transect at 1 m intervals and determining the points that ‘hit’ (or intercept) vegetation or substrate.
    Recruitment Evidence of immature plants that have survived for at least one year since germination or first establishment (Michaels 2006).
    Sapling Young woody plant with a DBH between 1-5 cm and a height <1.5 m.
    Seedling Very young plant, herbaceous to slightly woody, with a DBH < 1 cm. The leaves are adolescent and often the cotyledons (first leaves) are still present.
    Senescence The ageing process in a plant or plant part from full maturity to death (Eco Logical Australia 2013).
    Shrub Woody plant, multi-stemmed at the base (or within 200 mm from the ground), or if single stemmed, less than 5 m tall. Not always readily distinguishable from small trees (NCST 2009).
    Standing dead spar Standing dead tree that has shattered below 1.3 m (DOC 2019).
    Standing dead tree Dead tree with a height >1.3 m that is not lying on the ground (Puletti et al. 2019; Didion and Abegg 2022)
    Substrate cover The percentage of the vertical projection of substrate, characterised by substrate type, present in a specific area (in this case the number of point-intercept hits as a percentage of the total number of point-intercepts).
    Tree Woody plant greater than 2 m in height usually with a single stem, or branches well above the base. Includes trees, tall shrubs, or palms with DBH ≥10 cm (global forest ecology standard; Wood et al. 2015), and mallee and mulga with a DBH ≥5 cm (TERN 2015).
    Tree stump Standing upright portion of dead trees above ground surface <1.3 m that remains after cutting or natural processes have occurred (Puletti et al. 2019; Didion and Abegg 2022)
    Trimble® R1 A rugged, compact, lightweight Global Navigation Satellite System (GNSS) receiver (configured with the GNSS Status app) that provides professional-grade positioning information to any connected mobile device using Bluetooth® connectivity.
    Vegetation cover The percentage of the vertical projection of vegetation, characterised by species, growth-form and height of lower, mid and upper @@ -625,7 +618,7 @@ vegetation strata, present in a specific area (in this case the number of point-intercept hits as a percentage of the total number of point-intercepts).
    Woody debris (WD) Woody material less than 10 cm (or 5 cm in some systems) and greater than 1 cm in diameter (Woldendorp et al. 2002; Woldendorp and @@ -633,8 +626,7 @@ Keenan 2005; Eyre et al. 2015).
    """^^rdf:HTML ; - skos:note """ -

    Additional guidelines

    + skos:note """

    Additional guidelines

    General

    • Partitioning the sub-plot into more manageable units using @@ -647,14 +639,16 @@ method described in the Plot Selection and Layout Module.

      • fauna, record fire scar height, and document age class structure, growth and life-stages, and health of the perennial species present.

    • Assessment of fire extent and severity is undertaken in the Fire -Module (which is carried out within the Cover Module). If a condition +Module (which is carried out within the Cover ModuleCover Module). If a condition survey is to be undertaken, ensure that the fire option has been -activated in the Cover Module.

      • +activated in the Cover Module.

    -

    Tree survey

    +


    +

    +

    Tree survey

    • A tree is considered in the plot if than 50% of the base of the -trunk is within the plot (Figure 3).

      • +trunk is within the plot (Figure 3).

    • Tree height can be estimated using a forestry rangefinder for rapid and accurate height measurements. The person entering the data into the Monitor app can carry the rangefinder on a lanyard over their @@ -665,8 +659,11 @@ estimated using the following methods:

      • Clinometer and tape (Department of Environment and Climate Change 2007)

        • -

      • Mobile phone applications

        • -
      New Image Description

      Figure 3. Rule set to be determined if a tree is in or out of the plot.

      +

    • Mobile phone applications

      • +
    +

    Figure 3: Rule set to determine if a tree is in or out of the +plot

    +

    adapted from Wood et al. (2015).

    Tree health

    Canopy cover
      @@ -779,12 +776,59 @@ Ensure that the tool used is consistent throughout the survey.

    • The same individual should conduct all leaf litter measurements to reduce error.

    - """^^rdf:HTML ; +

    Post-field survey tasks

    +

    Sample curation

    +

    No samples are collected directly as part of this module although +vegetation voucher samples (collected with the Floristics) will +be used to verify the field identifications used in the components of +this module.

    +

    Data submission

    +

    Data from the Condition Module is collected in the field using the +Monitor app. Data entry is completed in the app, photos are taken using +the app (or later linked if taken on other devices), and voucher +barcodes are scanned in the app to link voucher numbers to the unique +data. All data is checked for correctness and completeness in the app +before it is submitted.

    +

    Once all data is finalised, and marked as completed, the data is +submitted from the Monitor app to the staging server by an explicit user +action. If the device is offline at the time, the data will be pushed as +soon as it is reconnected to a network (i.e. either back in mobile phone +range or a wi-fi network). Once data reaches the staging server it is +prepared in an export interface for delivery to the Biodiversity Data +Repository. DCCEEW is then responsible for managing the data. In the +future, it is anticipated that data curation tools will be made +available to project personnel.

    +

    Data use and reason for +collection

    +

    Future use of the data

    +

    Monitoring change in condition is important for NRM projects, as it +enables changes in condition to be tracked following interventions (DOE +2013). Policy demands and expectations have conceptualised vegetation +condition as a major component of native vegetation management, +primarily to assist with decision making for developmental approvals, +incentive payments and market-based investments (Keith and Gorrod 2006; +Eyre et al. 2015). Regional NRM groups are also interested in +vegetation condition, given its listing as a national environmental +indicator for reporting targets (Eyre et al. 2015). The ability +to assess and monitor vegetation condition is also essential for +governments to administer legislation relating to the landscapes and +biodiversity covered by their jurisdiction (Eyre et al. +2015).

    +

    The condition attributes collected here can be used to assess changes +in condition (or changes in individual attributes) following +interventions or development. It is likely that these measures could +also be used to monitor changes or recovery following natural +disturbances, such as fires or flooding, or recovery from drought. Data +can also be used to track changes in individual attributes, such as +mistletoe abundance and spread, canopy dieback and DBH size class +distributions. The potential exists for data to contribute to regional, +state of national condition assessments. The collection of reference +data could contribute to nationwide condition databases.

    """^^rdf:HTML ; skos:prefLabel "Condition Module" ; schema:url "https://github.com/ternaustralia/dawe-rlp-vocabs/tree/main/vocab_files/methods_by_module/condition/condition-protocol.ttl"^^xsd:anyURI ; - tern:appendix """

    Appendices

    -

    Appendix 1. Assessing -crown damage and calculating the Crown Damage Index (CDI).

    + tern:appendix """

    Appendices

    +

    Appendix 1. Assessing +crown damage and calculating the Crown Damage Index (CDI).

    The Crown Damage Index (CDI) is created by visually assessing the incidence (extent of damage over the entire canopy), and severity (percentage of each leaf affected), of missing, damaged and discoloured @@ -792,12 +836,12 @@ foliage (Stone et al. 2003).

    There are three types of damage:

    1. Defoliation – where entire leaves or parts of leaves are missing -(Figure A5.1)

      2. +(Figure A1)

      -

    1. Necrosis – presence of dead leaf tissue (Figure A2)

      2. +

    2. Necrosis – presence of dead leaf tissue (Figure A2)

    3. Discolouration – non-green leaf tissue including yellowing or -reddish-purple discolouration, chlorotic spots or margins (Figure A2). +reddish-purple discolouration, chlorotic spots or margins (Figure A2). Natural variation of leaf colour needs to be considered when assessing discolouration, for example eucalyptus leaves can change colour as they develop.

      4. @@ -818,8 +862,8 @@ the canopy (I = 15%)

      each leaf affected (S = 15%)

      = (50 x 30)/100 + (20 x 15)/100 + (15 x 10)/100 = 15 + 3 + 1.5

      CDI = 19.5

      -

      Table A1. Example for calculating the crown damage index based on -types of damage present

      +

      Table A5.1. Example for calculating the crown damage index based on +types of damage present

      @@ -828,33 +872,35 @@ types of damage present

      - - - - - + + + + + - + - + - + - + @@ -865,8 +911,8 @@ types of damage present

      Alternatively, if estimating CDI by dividing the canopy into smaller sections and looking at total damage in each portion, the calculations might look like this:

      -

      Table A2. Example for calculating the crown damage index based on -portions of the crown

      +

      Table A5.2. Example for calculating the crown damage index based on +portions of the crown

      Damage typeDamage Incidence (%)Damage Severity (%)Product
      Damage typeDamage Incidence +(%)Damage Severity +(%)Product
      Defoliation 30 50 (30 x 50)/100 = 15
      Necrosis 15 20 (15 x 20)/100 = 3
      Discolouration 10 15 (10 x 15)/100 = 1.5
      Crown Damage Index
      @@ -875,33 +921,35 @@ portions of the crown

      - - - - - + + + + + - + - + - + - + @@ -913,16 +961,18 @@ portions of the crown

      (i.e. each type of damage for sections of the crown). The default in the App is a single row for an overall assessment of damage across the crown.

      -

      Appendix 2. Evidence -of insect damage to foliage.

      -

      Insect_damage

      +
      +appendix-img2 +

      Figure A1. Evidence of insect damage to foliage.

      +

      Source: South Australian Bushland Condition Monitoring Manual (Milne et al. 2008)

      -

      Figure A1. Evidence of diseased foliage and insect damage 1.

      -

      Galls

      -

      Source: South Australian Bushland Condition Monitoring Manual -(Milne et al. 2008).

      -

      Figure A2. Evidence of diseased foliage and insect damage 2.

      """^^rdf:HTML ; +

      appendix-img3

      +

      Figure A2. Evidence of insect damage to foliage (Continued).

      + +

      Source: South Australian Bushland Condition Monitoring Manual (Milne et al. 2008).

      +
      +"""^^rdf:HTML ; tern:equipment """

      Equipment

      General:

      @@ -946,692 +996,390 @@ accuracy

      """^^rdf:HTML ; tern:instructions """ -

      Instructions and procedures

      +

      Condition attributes +protocol

      +

      Field collection

      +

      Pre-requisites

      +

      Pre-requisites for completing this protocol:

      +
        +

      • The plot must be established using the Plot Layout and Selection +Module prior to conducting the Condition attributes protocol.

        • +
      +

      Time requirements

      +

      Survey activity time estimates will vary depending on the number of +trees to be measured, the optional fields that are measured, and the +density of vegetation to traverse. As a general guide, to collect the +condition attributes of this protocol:

      +
        +

      • Allow 1–2 hours for survey planning.

        • +

      • Allow 20–40 minutes for plot set-up and laying tape-measures +(assuming the plot has been previously set-up using the Plot Selection +and Layout Module).

        • +

      • Allow 1–3 hours to complete the survey.

        • +

      • Refer to the mandatory and optional complementary modules for the +time requirements for each protocol that is being completed as part of +the condition monitoring.

        • +
      +

      Personnel requirements

      +

      Number of personnel and skills:

      +
        +

      • The Condition attributes protocol is best completed with two +personnel. This enables one person to complete the required measurements +(DBH, tree height, leaf litter depth, etc.) and the other to record the +data directly into the Monitor app simultaneously. The second person may +also assist with taking measurements.

        • +

      • A third person can improve data collection workflow during the +tree survey by measuring the tree height whilst DBH is being +measured.

        • +

      • Personnel should be familiar with and experienced in identifying +growth stages and life stages of tree species.

        • +

      • Personnel should be familiar with and experienced in identifying +the characteristic features of tree health, including but not limited to +insect damage, human-induced damage and the presence of +mistletoe.

        • +

      • Personnel should be familiar with and experienced in identifying +traits specific to tree species and how to distinguish different species +from one another. If personnel are not confident, time should be +dedicated to practising, using field reference guides, and seeking +advice prior to conducting this protocol.

        • +

      • Personnel must be familiar with the use of a diameter tape and/or +a 5–10 m tape measure as well as with the use of a rangefinder and +binoculars.

        • +

      • The Condition Module does not involve interference with +vegetation or wildlife. Therefore, scientific permits and wildlife +ethics approvals are unlikely to be required but always check with your +local authority. Access permissions will likely be required.

        • +
      +

      Instructions and procedures

        -

      1. Ensure the Plot Selection and Layout Module has been completed to +

      2. Ensure the Plot Selection and Layout Module has been completed to mark out the plot boundary, the sub-plot boundary and to define the current plot and visit in the Monitor app.

        3. -

      3. Select Condition Module > Condition attributes -protocol.

        4. +

      4. Select the Condition Module and then the Condition attributes +protocol.

      5. Select plot size using the drop-down (100 x 100 m or 40 x 40 m).

        6. -

      6. Select the equipment that will be used to measure -diameter and height (diameter tape, 5-10 m tape measure, rangefinder, -clinometer).

        7. -

      7. Select the optional sub-protocols that will be completed -using the check-boxes (leaf litter, tree stumps, partially downed trees, -disturbance).

        8. -

      8. Select the optional attributes of interest that -will be recorded during the Tree health component using the check-boxes -(CDI, mistletoe, trunk condition, insect damage, human induced damage, -additional stressors, abnormal growth).

        -

      9. Time and date will be automatically recorded. This can be edited if -necessary.

        10. Plot_layout -

        Figure 1. Plot layouts -for the 100 x 100 m core plot 40 x 40 m sub-plot.

        +

      10. Select the DBH instrument (diameter tape, tape measure, +tree caliper) and height instrument (rangefinder, clinometer, +other).

        11. +

      11. Save the survey set-up component. The time and +date will be automatically recorded. Update if +required.

      -

      Tree survey

      -
        +
        +Figure-1 +

        Figure 1. +Plot layouts for the 100 x 100 m core plot 40 x 40 m +sub-plot.

        +
        +

        1. Systematically traverse the plot or sub-plot searching for perennial species with a DBH ≥10 cm and height >2 m (hereby referred to as ‘tree’). For mallee and mulga systems, record all individuals with a DBH ≥5 cm.

          2. -

        2. Follow the Basal Area Module - DBH protocol to record -DBH measurements simultaneously.

        3. For each tree encountered, select add tree and -record:

          +record:

          4. +
          -

        • if the tree is mallee or mulga.

          • -

        • if the tree is dead. When dead is selected, completion +

        • If the tree is a mallee or mulga.

          • +

        • If the tree is dead. When dead is selected, completion of the growth stage and reproductive life stage fields is not required.

          • -

        • if the tree is dead and partially downed, select the -partially downed tree check-box.

          • -

        • the species name or assigned field name. If the -species identification is unknown (only species recorded as part of the -Floristics Module will be available for selection) select add new -species and fill in the relevant information. If the individual -cannot be recorded to species, the genus name can be used (i.e. -Eucalyptus sp.).

          • -

        • the growth stage of the tree (mature, recruiting, -resprouting or senescent), refer to Table 2 and Figure 2 for more +

        • If the tree is dead and partially downed, select the +partially downed tree check-box.

          +

          The floristics voucher.

          • +

        • The growth stage of the tree (recruiting, resprouting +mature, senescent, dead) Refer to Table 2 and Figure 2 for more information. If resprouting, indicate if basal or epicormic (both can be selected).

          • -

        • the reproductive life-stage, refer to Table 3 for more -information.

          • -

        • if flowering, record the intensity (percentage -of the canopy in flower).

          • -

        • the height (m) of the tree using a rangefinder or -equivalent.

          -

          Table 2. Description -of growth stage classes.

          • +

        • The life stage, refer to Table 3 for more information. +If flowering, record the intensity (percentage of the +canopy in flower).

          • +

        • The height (m) of the tree using a rangefinder or +equivalent.

          • +

        • The DBH (cm) and POM (m). See the Basal Area +Module for measurement instructions, including for multi-stemmed and +buttressed trees.

          • +

        • Tree health, including:

          +
            +

          • The percentage of canopy cover present versus dieback. +Use the South Australian Bushland Assessment Manual (Native +Vegetation Council 2020) to assist with the determination.

            • +

          • Crown damage, including the incidence and +severity of discoloured, necrotic and missing foliage.

            +
              +

            • Enter the type of damage into the description column, +followed by incidence and severity values (see +Appendix 1). The product will be automatically calculated. Use the add +row button to add additional damage or crown portion measures (Appendix +1).

              • +
            • +

          • The number of mistletoes alive and mistletoes +dead. If no number is recorded, the app will automatically populate +the field with 0.

            • +

          • Add any hollows and record:

            +
              +

            • The size (cm) of the hollow.

              • +

            • The direction (°) of the hollow opening.

              • +

            • The height (m) of the hollow.

              • +
            • +

          • The presence of deep cracks or crevices present +using the check-box.

            • +

          • The presence of abnormal growth using the +check-box.

            • +

          • If the tree bark is loose using the check-box.

            • +

          • The presence of insect bores using the +check-box.

            • +

          • The incidence and severity of insect damage on +the foliage.

            +
              +

            • Select the damage type (gall, lerp, scale, blistering, +skeletonization), followed by incidence and severity +values). Use the South Australian Bushland Condition Monitoring +Manual (Milne et al. 2008) or similar to assist with determination +(examples available in Appendix 2).

            • +

          • Any human induced damage (lopping, logging, ringbarking, +poisoning) or input a custom value present.

            • +

          • Any obvious signs of any other abiotic stressors or +biotic stressors.

            • +
          • +
        +
          +

        1. If there is leaf litter present at the base of the tree:

          2. +
        +
          +

        • Record the direction from tree (°) and distance from +tree (m) that the litter depth will be recorded. These parameters +should remain consistent for each tree surveyed where possible.

          • +

        • Create a small clearing in the litter and remove any coarse +material then place the flat end of the leaf litter measurement tool on +the soil surface. Slide the disc component down until it contacts the +leaf litter surface. Apply light pressure to the disc and use the screw +to tighten it into position. Read and record the litter depth +(mm) where the top of the disc intersects the ruler. Instructions for +building the tool can be found in the supplementary document Leaf litter +tool instructions.

          • +

        • If there is no leaf litter present, select no litter using the +check-box.

          • +

        • Replace any litter or woody debris moved during the +process.

          • +
        +
          +

        1. Add photo of the tree.

          2. +

        2. Use the comments field for any additional +remarks.

          3. +

        3. Select save when all attributes have been recorded for +the tree.

          4. +

        4. Mark the tree with coloured chalk or equivalent to avoid +unintentional remeasuring.

          5. +

        5. Repeat steps 7–12 for each eligible tree encountered in the +survey area.

          6. +

        6. Select complete to when all trees within the survey area +have been recorded.

          +

          Table 2. Description +of growth stage classes.

      Crown portionDamage Incidence (%)Damage Severity (%)Product
      Crown portionDamage Incidence +(%)Damage Severity +(%)Product
      Top 25% 25 50 (25 x 50)/100 = 12.5
      Middle 25% 0 0 0
      Lower 50% 30 20 (30 x 20)/100 = 6
      Crown Damage Index
      + - + - + - + - + - + - + - + - + - + - +
      Growth stage Description
      Recruiting Trees: From the juvenile and sapling stages to well-developed individuals with a crown of small branches, but below maximum height for a stand, crown exhibits apical dominance – approx. 0-30 years
      Shrubs: Juvenile stage, shrub has not reached maximum height, apical dominance
      Resprouting Trees and Shrubs: Woody perennial which is resprouting after significant loss of foliage. Resprouting can occur from the trunk or branches (epicormic) or from the base (basal).
      Mature Trees: Tree has reached maximum height and crown has reached full lateral development although branch thickening can occur. Apical dominance lost – approx. 30-80 years
      Shrubs: Shrub has reached maximum height, crown has reached full lateral development
      Senescent Trees: Crown form contracting and becoming ‘stag headed’ decrease in crown diameter and crown leaf area. Distorted branches and burls common – approx. >80 years
      Shrubs: Crown form contracting and decrease in crown diameter and crown leaf area. Dead branches more common – approx. >80 years
      Dead Trees: Dead individuals in all stages – from presence of tertiary branches and bark to no remaining crown structure and absence of bark
      Shrubs: Dead individuals in all stages
      -

      Growth stage visual representation examples

      -

      Figure 2. Growth stage -visual representation examples.

      -

      Table 3. Life-stage -classes.

      +

      Figure2

      +

      Figure 2. Growth stage visual representation examples.

      +

      Table 3. Life-stage +classes.

      Adapted from (Heard and Channon 1997). Seedling, sapling and juvenile cannot be selected within this module. To record the presence of seedlings, saplings and juveniles, complete the Recruitment Module.

      --++ - - - + + + - - + + + + + + + + + + +flowering. - - - + + + - + - + - - - + + + - + +shed seeds or fruits within the last 12 months. - + + + + + - + + + + +
      Life StageDefinition
      Life stageDescription
      Budding
      SeedlingTrees: individuals <2 cm DBH. Shrubs: <5cm +height.
      SaplingTrees: individuals <2 m in height and ~2-10 cm DBH. +Shrubs: has not reached maximum height, apical dominance.
      Buds Plants have buds formed in varying stages of development for -flowering
      FloweringPlants are in flower
      FlowersPlants are in flower.
      Immature fruitImmature fruits not shedding seedImmature fruits not shedding seed.
      Mature fruitFruits ripe and/or shedding seed
      MatureFruit fruits ripe and/or shedding seed.
      Recently shed Plants are in a non-reproductive phase which show signs of having -shed seed or fruits within the last 12 months
      Dead/dormantIndicates above-ground material only is dead and includes plant +species that may still have dormant below-ground organs (eg orchids, +lilies etc.).
      VegetativePlants in a non-reproductive phase (i.e. no flowers, buds or unshed -seed), that do not classify as seedlings or saplingsOnly refers to plants in a non-reproductive phase ie. no flowers, +buds or unshed seed.
      RegeneratingWoody perennial which is resprouting after significant loss of +foliage.
      -
        -

      1. If there are obvious signs of browsing, complete the Herbivory -and Physical Damage Module simultaneously.

        2. -

      2. For each tree encountered, select record health and -record:

        3. -
      -
        -

      • the percentage of canopy cover present versus dieback. Use the -South Australian Bushland Assessment Manual (Native Vegetation -Council 2020) to assist with the determination.

        • -
      -
        -

      • the incidence and severity of discoloured, necrotic and missing -foliage. Enter the type of damage into the description column, followed -by incidence and severity values (see Appendix 1). The product will be -automatically calculated. Use the add row button to add additional -damage or crown portion measures (Appendix 1).

        • -

      • the number of alive and dead mistletoes present. If no number is -recorded, the app will automatically populate the field with 0.

        • -

      • the number of hollows present. If no number is recorded, the app -will automatically populate the field with 0.

        -
          -

        • Optionally record the size of the hollow (m).

          • -

        • Optionally record the direction of the hollow opening.

          • -

        • Optionally record the position of the hollow on the -tree.

          • -
        • -

      • the presence of deep cracks or crevices present using the -check-box.

        • -

      • the tree bark is loose using the check-box.

        • -

      • the presence of insect bores using the check-box.

        • -

      • the incidence and severity of insect damage on the foliage.

        -
          -

        • Select the type of damage (gall, lerp, scale, -blistering, skeletonisation, followed by incidence and severity values). -Use the South Australian Bushland Condition Monitoring Manual -(Milne et al. 2008) or similar to assist with determination (examples -available in Appendix 2).

          • -
        • -

      • any human induced damage (lopping, logging, ringbarking, -poisoning) present.

        • -

      • obvious signs of any other biotic or abiotic stressors.

        • -

      • the presence of abnormal growth using the check-box.

        • -
      -
        -

      1. If there is leaf litter present at the base of the tree:

        2. -
      -
        -

      • create a small clearing in the litter and remove any coarse -material then place the flat end of the leaf litter measurement tool on -the soil surface. Slide the disc component down until it contacts the -leaf litter surface. Apply light pressure to the disc and use the screw -to tighten it into position. Read and record the litter depth (mm) where -the top of the disc intersects the ruler. Instructions for building the -tool can be found in the supplementary document Leaf litter tool -instructions.

        • -

      • if there is no leaf litter present, select no litter using the -check-box.

        • -

      • replace any litter or woody debris moved during the -process.

        • -
      -
        -

      1. Add photo of the tree.

        2. -

      2. Use the comments tab for any additional remarks.

        3. -

      3. Select save when all attributes have been recorded for -the tree.

        4. -

      4. Mark the tree with coloured chalk or equivalent to avoid -unintentional remeasuring.

        5. -

      5. Repeat steps 2-11 for each eligible tree encountered in the -survey area.

        6. -

      6. Select complete to when all trees within the survey area -have been recorded.

        7. -
      -

      Table 4. Factors -affecting vegetation health to be recorded in the field.

      +

      Table 4. +Factors affecting vegetation health to be recorded in the +field.

      - - - + + + - + - + - + - + - + - - + - + -
      Health factorDescription
      Health +factorDescription
      Canopy health Canopy cover The percentage of foliage present within the canopy relative to a local reference tree.
      Crown damage index (CDI) An index based on the incidence and severity of discoloured, necrotic or missing foliage [Stone 2003].
      Mistletoe Aerial plant parasite which can be identified by its different foliage from host plant. Number of mistletoes present to be recorded.
      Hollow Cavity that has formed within the trunk or branch of a tree. Number, direction and position recorded.
      Human induced damageAny physical harm caused by a human activity. Presence or absence +Any physical harm caused by human activity. Presence or absence recorded.
      Insect damage The incidence and severity of galls, skeletonization, lerps, blistering and scale on foliage.
      Trunk condition The presence of hollows, cracks, crevices, loose bark and insect bores on the tree trunk.
      -

      Tree stumps

      -
        -

      1. Systematically traverse the plot or sub-plot searching for tree -stumps.

        2. -
      -
        -

      1. For each stump encountered select add stump.

        2. -

      2. Location of the stump is automatically recorded when a stump is -added. Location can be edited and re-recorded if required.

        3. -

      3. Measure and record the height of the stump in cm.

        4. -

      4. Measure and record the diameter of the top end of the stump in -cm.

        5. -

      5. Record the decay class of the stump from the drop-down -list (Table 5).

        6. -

      6. Record the any regeneration on the stump (present or -absent).

        7. -

      7. Add photo of the stump.

        8. -

      8. Repeat steps 2-6 for each stump within the plot.

        9. -

      9. Select complete to when all stumps within the survey -area have been recorded.

        10. -
      -

      Table 5. Coarse woody -debris decay classes which can be applied to stumps

      -

      Adapted from (Meggs 1996; Baker and Chao 2011).

      - ---- - - - - - - - - - - - - - - - - - - - - - - - - - - - -
      Decay classDescription
      Class 1Recently fallen. Structurally intact or almost so; bark or small -branches still attached; few signs of wood decay; wood mostly retains -original colour.
      Class 2Structurally less intact but still hard when kicked; small branches -absent; little or no bark present; early signs of wood decay, bark loss -or discolouration.
      Class 3Clearly decaying but still supports own weight; may be slightly soft -when kicked; may be hollow in places; no bark; moss and fungi may be -prominent.
      Class 4Cannot support its own weight; soft to kick (but may still be hard -in places; in which case may be extensively hollow); moss, fungi and -invading roots likely.
      Class 5No longer retains original shape; wood very soft or largely -disintegrated; sometimes only outline visible beneath moss, invading -roots.
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      Rationale

      -

      Adequate monitoring of condition remains a prerequisite for -environmental decision-making and for tracking progress towards -management goals (Lawley et al. 2016). However, condition data -is patchy and despite a number of approaches being developed there is -still no consistent way to assess condition across the country (NERP -National Condition Working Group 2015). As a result, there is a need for -cost-effective condition assessments that provide robust and rigorous -data (Cook et al. 2010). An understanding of condition is -needed to inform regional priorities, establish policies, design and -evaluate natural resource management (NRM) programs and measure change -(Thackway et al. 2015). At the project scale, monitoring -condition allows the response of ecological attributes such as ground -cover and native plant diversity to be determined in relation to -management interventions or developments. At a broader scale, data from -a range of projects can provide information on the overall performance -of NRM programs, across interventions, vegetation types and regions (DOE -2013; Eco Logical Australia 2013), and for development projects can help -determine if environmental impacts, including impacts on matters of -national environmental significance are being managed appropriately -(Commonwealth of Australia 2020).

      -

      Currently, condition tends to be measured by visual and/or systematic -assessments (Neldner 2006; Casson et al. 2009; Cook et -al. 2010; Eyre et al. 2015), but visual estimates can be -highly variable compared to systematic assessments, especially at small -scales. Observers often simplify their assessments by responding to only -some of the condition parameters, and as a result, more systematic -assessments are needed when management decisions require an -understanding of changes in individual condition attributes (Cook et -al. 2010). In addition, a greater range of analysis options are -available when the data is collected as continuous rather than -categorical data. This information allows changes in individual -attributes to be monitored, aggregated and analysed to explore a range -of issues related to condition (ESCAVI 2007; Williams 2010).

      -

      The approach outlined in this module has been developed to align with -existing condition assessment methods where possible but improves the -way condition is measured across the country by focusing on the -collection of quantitative data. A summary of each attribute, reason for -collection and survey methods are detailed below.

      -

      Age and size class (Condition Module): The size (DBH -and height), growth stage and life-stage are recorded for all trees, -tall shrubs or mallee >2 m tall and with a DBH ≥10 cm present within -the central 40 x 40 m sub-plot. This enables age class structure to be -determined and to assist with the interpretation of changes that occur -over time, particularly following natural disturbance or interventions -(DEC 2012). Trees can be categorised post-survey based on DBH measures -into designated size classes relevant to the study system (see Appendix). -A mix of stem sizes indicates multiple successful recruitment events -have occurred and the presence of very large individuals indicates that -the system retains old-growth characteristics such as tree-hollows and -roosting sites which can be important for a range of fauna species -(Oliver et al. 2007).

      -

      Life-stage (Recruitment and Condition Modules): -Life-stage is recorded for all perennial species present within the 1 ha -plot as part of the Recruitment Module. Life-stage is also recorded in -the central 40 x 40 m sub-plot as part of the Condition tree survey -protocol and in the seedling, sapling and juvenile counts in the -Recruitment Module to provide an overview of the potential for -recruitment. Eight life-stage classes have been defined (seedling, -sapling, juvenile, vegetative, budding, flowering, immature fruit, -mature fruit, recently shed) based on the work by Heard and Channon -(1997).

      -

      Growth stage (Recruitment and Condition Modules): -Growth stage (recruiting, resprouting, mature, senescent, dead) is -recorded within the central 40 x 40 m sub-plot for every perennial -individual present following the Tree survey protocol in the Condition -Module. In addition, a growth stage summary is recorded across the plot -for each species as part of the Recruitment Module. Multiple growth -stages can be recorded for each species. Additionally, recruiting -individuals (seedling, sapling, and juvenile) are counted as part of the -Recruitment Module. Recording growth stage as a measure of condition is -recommended by a number of sources (Gibbons and Freudenberger 2006b, -2006a; Parkes and Lyon 2006; Bleby et al. 2008), as it helps to -characterise the structural diversity of the system (Milne et -al. 2008). Recording growth stage using two methods allows growth -stage to be recorded for every perennial species present and also -provides an estimate for the abundance of each stage.

      -

      Seedling, sapling and juvenile counts (Recruitment Module): Seedling, sapling and juvenile counts are undertaken -in the central 40 x 40 m sub-plot as part of the Recruitment Module. -Counts are undertaken for an estimate of the number of recruits for the -tree and shrub species present in the system, with counts undertaken on -a per species or per genus basis, where possible (DOC 2019). Recruitment -is an important condition measure because it provides insight into how -well the system is functioning and an indication of the capacity of the -system to regenerate (particularly in degraded systems), and therefore -persist over the long-term (DENR 2011; DEC 2012).

      -

      Vegetation health (Condition Module): Vegetation -health is recorded for every tree and tall shrub present within the 40 x -40 m subplot (excluding seedlings, saplings and juveniles). Health -measures include canopy cover, canopy health (based on an estimate of -damage severity and incidence (Stone et al. 2003), the number -of mistletoes, the presence of any hollows, insect damage and -human-induced damage. Grazing damage is recorded as browse height and -severity. Vegetation health is an important measure of condition, and -several abiotic and biotic factors can contribute to a decline in health -(Department of the Environment 2014). Tree health can serve as a signal -for further investigation, e.g., if high levels of dieback are present -at a site, research into potential causes may be required. High levels -of grazing can result in decline of site condition as it leads to -reduced plant productivity, regenerative capacity, habitat value and -biodiversity, hydrological function and carbon sequestration (Eldridge -and Delgado‐Baquerizo 2017).

      -

      Litter depth (Cover Module and Condition Module Modules): Litter -depth is recorded as an additional measure during the Cover Module -whenever litter is encountered along the four point intercept transects -delineating the sub-plot. Litter depth is the distance between the -mineral soil surface and the top of the litter surface (Hines et -al. 2010). Litter can provide a habitat for some ground-dwelling -fauna and predator invertebrates (McElhinny et al. 2006), a -substrate for the regeneration of plant species (Oliver and Parkes -2003), shelter and food for detritus-feeding invertebrates (Majer et -al. 1997; Oliver and Parkes 2003), and also plays a role in soil -surface stability and can reduce erosion (Casson et al. 2009). -Litter depth information should be used in combination with litter cover -information obtained from the Cover Module.

      -

      Coarse Woody Debris (Coarse Woody Debris Module): -Coarse woody debris (CWD) is recorded for all logs with a diameter of 10 -cm or more within the 40 x 40 m subplot, with the length and diameters -(widest and narrowest) recorded for any pieces present. CWD contributes -to a range of ecosystem processes, including nutrient cycling and -storage, soil formation, stability, and retention, retaining moisture -and enhancing water infiltration, improving thermal conditions, and -providing sites for litter accumulation (Grove and Meggs 2003; -Woldendorp et al. 2004; Manning et al. 2013; Goldin -2020). CWD can also influence fuel loads and fire dynamics (Miehs et al. -2010), and is a preferred habitat feature for a range of fauna, -including shelter, nesting and denning sites for a variety of mammals, -reptiles and some birds (Mac Nally et al. 2001; Threlfall et al. -2021).

      -

      Fire (Fire Severity Module): Fire extent and -severity are determined using transects, with burn distribution, -vegetation char, and scorch height recorded. Fire severity is defined as -the degree of consumption and scorching of live vegetation and dead -fuel, and the degree to which soil properties and processes are altered, -as a result of the combustion process (Smith et al. 2005; -Hammill and Bradstock 2006). The cover measurements are indicative of -fire extent and patchiness (Edwards et al. 2013), while the -height measurements provide insight into the degree of scorching and -charring of the living and dead vegetation in each strata, which are key -indicators of fire severity (Whight and Bradstock 1999; Hammill and -Bradstock 2006; Russell-Smith and Edwards 2006; Chafer 2008; Edwards -et al. 2013; Oliveira et al. 2015). Fire has a major -effect on terrestrial ecosystems and can influence plant diversity, -composition and regeneration, and high frequency burning can result in -the loss of fire sensitive vegetation (Yibarbuk et al. 2001; -Fisher et al. 2009; Etchells et al. 2020).

      -

      Vertebrate pest fauna (Signs-based Fauna Module and Herbivory -and Physical Damage Module): Pest fauna presence will be -recorded at the plot level, with evidence of tracks, scats, warrens, -diggings or other signs/traces recorded (DOE 2013). There will be a -focus on recording evidence of feral cats, foxes, wild dogs, rabbits, -pigs, goats, deer, horses and camels, but other invasive species can -also be included. Pest animals can cause land degradation by promoting -soil erosion and compaction, stream turbidity, the spread of weeds, and -can threaten native plant species and animals through competition, -habitat destruction, over-grazing and predation (Invasive Plants and -Animals Committee 2016). Consequently, the presence of vertebrate pest -fauna can be an indicator of a reduction in condition (Casson et -al. 2009; Pert et al. 2012; Krull et al. -2015).

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      Introduction and Background

      -

      The Condition Module involves the collection of quantitative, -accurate and repeatable measures of condition within the plot, using a -combination of point and plot-based methods. The Condition Module -includes methods for collecting data on plant age class structure, plant -health and size, litter depth, coarse woody debris and recruitment. -Elements of the Coarse Woody Debris Module and Recruitment Module form -part of the Condition Module and data from other modules such as -Floristics, Cover, Fire Severity and Signs-based Fauna Surveys are also -important measures for the overall assessment of condition. The -definition of condition adopted here is revised from the AusPlots Draft -Condition Protocol (Wundke et al. 2015) and is as follows:

      -
        -

      • Biodiversity condition is a measure of the status of the biota at -an assessment site described by key attributes that reflect structure, -function and composition.

        • -
      -

      The Condition Module has been designed to improve consistency and -repeatability in the way condition is measured across Australia and -provide increased opportunities for analysis. The primary aim of the -Condition Module is to collect baseline and revisit data, so any changes -in condition metrics following management interventions can be -evaluated.

      -

      Existing frameworks and procedures to assess condition differ in -their approach, and this is reflective of the range of legislative, -management and policy objectives in place, as well as available -resources (Eyre et al. 2015). Methods and protocols for -assessing and monitoring condition have been developed in all states and -territories (Williams 2010), and include BioCondition in Queensland -(Eyre et al. 2015), the Biodiversity Assessment Method (BAM) in -New South Wales (DPIE 2020), Habitat Hectare Assessment in Victoria (DSE -2004), TasVeg in Tasmania (Michaels 2006), Bushland Condition Monitoring -(BCM) in South Australia (Milne et al. 2008), Vegetation Condition -Assessment in the Northern Territory (Brocklehurst and Price 2008) and -Native Vegetation Condition Assessment in Western Australia (Casson et -al. 2009). However, the degree these methods have been adopted and -utilised varies between states and territories.

      -

      The methods developed by the states and territories have generally -been designed as practical, rapid assessments, appropriate for use by -non-specialists. All have a measure of species composition, plant cover, -life history, weeds and logs (coarse woody debris), and all assess -regeneration or recruitment of canopy or woody species as a measure of -ecosystem function. To measure condition, these methods generally -involve comparison against a reference or benchmark (Williams 2010). The -methods provided here build from the approach developed for the AusPlots -Draft Condition Protocols Manual (Wundke et al. 2015) and align -with existing state and territory methods, where possible.

      -

      As more attributes are assessed, the overall picture of biodiversity -condition becomes more comprehensive (Casson et al. 2009). -However, one of the main challenges for developing condition protocols, -is deciding on a set of attributes that are flexible enough to be -applied across Australia, but are also robust, repeatable and cost -effective (NERP National Condition Working Group 2015). The condition -assessment framework presented here, draws on data from a range of -attributes, sourced from a number of the modules, including a core set -from the Condition Module, as well as data from the Recruitment Module, -Coarse Woody Debris Module, Fire Severity Module, Signs-based Fauna -Surveys Module, Floristics Module, and Cover Module. Where required, -condition assessments can also include data from other modules, -including Vertebrate Fauna Module, Invertebrate Fauna Module and Soils -Module.

      -

      The key attributes that should be considered as part of a condition -assessments include:

      -
        -

      • plant age class structure (Condition Module and Recruitment -Module)

        • -

      • life-stage and growth stage (Condition Module and Recruitment -Module)

        • -

      • plant health (Condition Module)

        • -

      • browsing damage (Herbivory and Physical Damage Module)

        • -

      • litter depth (Condition Module)

        • -

      • seedling, sapling and juvenile counts (Recruitment -Module)

        • -

      • coarse woody debris size and abundance (Coarse Woody Debris -Module)

        • -

      • fire extent and severity (Fire Severity Module)

        • -

      • native plant species diversity (Floristics Module)

        • -

      • native plant cover (Cover Module)

        • -

      • substrate cover (Cover Module)

        • -

      • weed diversity (Floristics Module)

        • -

      • weed cover (Cover Module)

        • -

      • pest vertebrate fauna presence (Signs-based Fauna Survey -Module)

        -

        Additional measures include:

        • -

      • disturbance (Plot Description Module)

        • -

      • vertebrate fauna diversity (Vertebrate Fauna Module)

        • -

      • invertebrate fauna diversity (Invertebrate Fauna Module)

        • -

      • soil characterisation (Soils Module)

        • -

      • bulk density (Soils Module)

        • -

      • soil surface condition and erosion (Soils Module)

        • -
      -

      Analysing condition data

      -

      Condition is generally assessed by measuring a range of features and -then combining these into an index of condition, which is then compared -against a benchmark to generate a condition score (Cook et al. 2010). -Benchmarks are generally based on a pre-European (1750) state, prior to -significant development and disturbance (Thackway et al. 2015), or a -Best on Offer site (BOO, Eyre et al. 2017). Once a set of -benchmarks have been established for a vegetation type, the condition of -any example of that type can be quantified by comparing the site values -with the benchmark values (Parkes et al. 2003; Eyre et -al. 2015). Condition scores can be generated from a mix of field -and remote measures (Eyre et al. 2015; Harwood et al. 2016; Lawley et -al. 2016; McFarlane and Wallace 2019), and to generate condition scores, -primary data is usually converted into an attribute condition score, and -then weighted and aggregated into a single site multi-metric score -(Oliver et al. 2014; Eyre et al. 2015). This approach -can be straightforward and easy to understand, and allows a range of -information to be presented as a simple numeric or visual summary (Pert -et al. 2012). However, multi-metric condition scores have two main -shortcomings including:

      -
        -

      • loss of useful information at the attribute level, and

        • -

      • generation of similar condition scores for very different sites -through attribute eclipsing - the absence of one attribute being -compensated for by the presence of another (Oliver et al. -2014).

        • -
      -

      An alternative approach is to assess each condition attribute -individually against a baseline or reference measure. This approach -avoids masking individual attribute scores, which allows a more thorough -understanding of the outcomes of management actions (ESCAVI 2007; Milne -et al. 2008), and as such is the approach recommended here. In addition, -benchmarks are incomplete and lack consistency across Australia and -given these limitations, alternative analysis options are required (Eco -Logical Australia 2013).

      -

      The collection of condition data using this protocol is focused on -recording continuous rather than categorial data, as this allows -flexibility when analysing and interpreting data. Collecting data in -this way allows changes in individual attributes to be monitored, -aggregated and analysed to explore a range of issues related to -vegetation condition (Williams 2010). Analysis can be undertaken in a -range of ways or a combination of ways, using the data collected, -including:

      -
        -

      • Comparison of intervention (treatment) and control plots over -time, against baseline plot measures.

        • -

      • Generation of benchmarks from suitable nearby reference areas -using the same plot methods, to allow comparison of condition attributes -from intervention or development areas, against relatively unmodified or -best on offer reference areas.

        • -

      • Utilisation of state or territory benchmark data and associated -scoring algorithms, where available, to generate condition scores for -the plots studied.

        • -

      • Generation of a new scoring algorithm using the plot data -collected and benchmark plots, to generate a condition score for each -plot studied (the condition attributes included can be tailored to -project needs and weighted accordingly).

        • -
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