DOI: 10.5061/dryad.wdbrv15w4
title: Data from: Advances and shortfalls in applying best practices to global tree-growing efforts

description: As global tree-growing efforts have escalated in the past decade, copious
 failures and unintended consequences have prompted many reforestation best
 practices guidelines. The extent to which organizations have integrated
 these ecological and socioeconomic recommendations, however, remains
 uncertain. We reviewed websites of 99 intermediary organizations
 that promote and fund tree-growing projects to determine how well they
 report following best practices. Nearly half the organizations stated tree
 or area planting targets, but only 25% had measurable, time-bound
 objectives. Most organizations discussed the benefits local communities
 would receive from trees, but only 38% reported measures of these
 outcomes. Non-profit organizations with greater prior experience converged
 more closely on best practices, and their level of scientific expertise
 was positively associated with clearer project selection standards.
 Although many tree-growing organizations acknowledge the importance of
 clear goals, local community involvement, and monitoring, our results
 raise questions regarding whether long-term benefits are being achieved
 and emphasize the need for stronger public accountability standards.
description: 1. Description of methods used for collection/generation of data
 (see Schubert et al. 2024 and Supporting Information: Extended Methods for
 more details): Data collection occured Jan-Mar 2023. We identified 99
 tree-growing intermediary organizations from recently published studies --
 Bosshard et al. (2021) and Martin et al. (2021) -- and by searching Google
 and online charity platforms. These constituted private sector
 organizations that: (1) fund tree-growing or forest landscape restoration
 projects that are implemented by local organizations and landholders in
 multiple regions (i.e., at least multiple states/provinces within a
 country) (2) have a web presence with information communicating the
 organization’s restoration activities to potential funders. We excluded
 organizations that are primarily funded by government sources that are
 less dependent on web pages to share information with potential donors,
 fundraise for other intermediary organizations, or are exclusively service
 providers for hire (e.g., planted trees as a business). Each organization
 was assessed for data collection by at least two authors, who followed a
 protocol with survey prompts designed to collect information pertaining to
 the ten questions funders should ask about reforestation (Holl and
 Brancalion 2022). Data collection consisted of recording information to
 address a combination of categorical and open-ended questions that
 describe the organizations and their tree-growing practices. All web pages
 of the organizations primary website, in addition to all
 publicly-available annual and financial reports corresponding to
 tree-growing standards were subject to review. These prompt questions are
 detailed in the Extended Methods section of Schubert et al. 2024
 Supporting Information. Cumulative review times ranged 50–170 min per
 organization, depending on the extent of information available. We
 conducted a final search 21–25 March 2023 for new annual reports to ensure
 we used the most updated information. 2. Persons
 responsible for data entry and proofing: K. E. Battaglia, C. N. Blebea, C.
 J. P. Seither, H. L. Wehr, Y. Sheikhvand, and S. C. Schubert
 3. Methods for processing the data: The data presented here have
 been redacted slightly from the original survey spreadsheets for multiple
 reasons. First, we provide a numeric code 1-99 to identify each
 organization rather than actual organization names since the goal of the
 study was to characterize trends rather than evaluate individual
 organizations. Similarly, some descriptive open-ended columns include
 lengthy responses, quoted text, and project names/locations which we hold
 confidential. We have included the data necessary to repeat the
 quantitative analyses in the study. From the data initially collected from
 our online surveys, we calculated an index to evaluate the extent of
 organizations’ adherence and transparency to best practices based on our
 expanded questions, hereafter ‘best practices index’. The index was based
 on a sum of 21 responses with a total possible value of 22 points derived
 from presence and extent of information provided by organizations (e.g.,
 no information = 0, vague response = 0.5, information provided = 1). We
 used multiple regression to test whether certain organizational
 characteristics including organization type (non-profit or for-profit),
 past experience (prior number of trees or area planted/conserved), and
 staff scientific expertise predicted the best practices index. To examine
 relationships between specific ordinal variables, we used Kendall rank
 correlation. Data processing, operations, analysis, and figure rendering
 were performed in R 4.3.0 (R Core Development Team 2023). For further
 information concerning code and additional data collected, send inquiries
 to Spencer Schubert (scschubert11@gmail.com).
description: # Advances and shortfalls in applying best practices to global
 tree-growing efforts ## 1.
 Author Information A. Corresponding Author Contact Information Name:
 Spencer C. Schubert Institution: University of California Santa Cruz
 Email: B. Corresponding Author Contact
 Information (secondary contact) Name: Karen D. Holl Institution:
 University of California Santa Cruz Email: C.
 Co-authors K. E. Battaglia, C. N. Blebea, C. J. P. Seither, and H. L. Wehr
 ## 2. Date of data collection 2023-Jan-09 to 2023-Mar-21 ## 3. Geographic
 location of data collection compiled from webpages accessed from Santa
 Cruz, California, USA ## 4. Information about funding sources: MacArthur
 Foundation University of California Endowed Chair (held by KDH) #
 SHARING/ACCESS INFORMATION ## Recommended citation for this dataset
 Schubert, Spencer et al. (Forthcoming 2024). Advances and shortfalls in
 applying best practices to global tree-growing efforts [Dataset]. Dryad.
 # DATA & FILE OVERVIEW
 ## 1. Summary The data we provide on this Dryad link represent the
 information extracted from our online survey of 99 websites of
 intermediary tree-growing organizations. These data -- in addition to
 characterizing background, administrative structure, geography of
 organizational activities, etc... -- address an itemized list of prompts
 expanding upon the ten questions funders should ask about reforestation
 (Holl and Brancalion 2022). We calculated a Best Practices Index to
 measure transparency and adherence to these principles based on the sum of
 an itemized scoring approach (see Schubert et al. 2024 and Supplementary
 Extended Methods for more details). ## 2. File List
 "Schubert_ConLet_TreeOrgs_11Jan2024.csv" - data file for online
 survey of 99 selected intermediary tree-growing organizations ## 3. Date
 Last Modified 9/25/2023 -- additional data collected upon revision of the
 manuscript (see Carbon.credits) # METHODOLOGICAL INFORMATION ## 1.
 Description of methods used for collection/generation of data (see
 Schubert et al. 2024 and Supporting Information: Extended Methods for more
 details) Data collection occured Jan-Mar 2023. We identified 99
 tree-growing intermediary organizations from recently published studies --
 Bosshard et al. (2021) and Martin et al. (2021) -- and by searching Google
 and online charity platforms. These constituted private sector
 organizations that: (1) fund tree-growing or forest landscape restoration
 projects that are implemented by local organizations and landholders in
 multiple regions (i.e., at least multiple states/provinces within a
 country) (2) have a web presence with information communicating the
 organization’s restoration activities to potential funders. We excluded
 organizations that are primarily funded by government sources that are
 less dependent on web pages to share information with potential donors,
 fundraise for other intermediary organizations, or are exclusively service
 providers for hire (e.g., planted trees as a business). Each organization
 was assessed for data collection by at least two authors, who followed a
 protocol with survey prompts designed to collect information pertaining to
 the ten questions funders should ask about reforestation (Holl and
 Brancalion 2022). Data collection consisted of recording information to
 address a combination of categorical and open-ended questions that
 describe the organizations and their tree-growing practices. All web pages
 of the organizations primary website, in addition to all
 publicly-available annual and financial reports corresponding to
 tree-growing standards were subject to review. These prompt questions are
 detailed in the Extended Methods section of Schubert et al. 2024
 Supporting Information. Cumulative review times ranged 50–170 min per
 organization, depending on the extent of information available. We
 conducted a final search 21–25 March 2023 for new annual reports to ensure
 we used the most updated information. ## 2. Persons responsible for data
 entry and proofing K. E. Battaglia, C. N. Blebea, C. J. P. Seither, H. L.
 Wehr, Y. Sheikhvand, and S. C. Schubert ## 3. Methods for processing the
 data The data presented here have been redacted slightly from the original
 survey spreadsheets for multiple reasons. First, we provide a numeric code
 1-99 to identify each organization rather than actual organization names
 since the goal of the study was to characterize trends rather than
 evaluate individual organizations. Similarly, some descriptive open-ended
 columns include lengthy responses, quoted text, and project
 names/locations which we hold confidential. We have included the data
 necessary to repeat the quantitative analyses in the study. From the data
 initially collected from our online surveys, we calculated an index to
 evaluate the extent of organizations’ adherence and transparency to best
 practices based on our expanded questions, hereafter ‘best practices
 index’. The index was based on a sum of 21 responses with a total possible
 value of 22 points derived from presence and extent of information
 provided by organizations (e.g., no information = 0, vague response = 0.5,
 information provided = 1). We used multiple regression to test whether
 certain organizational characteristics including organization type
 (non-profit or for-profit), past experience (prior number of trees or area
 planted/conserved), and staff scientific expertise predicted the best
 practices index. To examine relationships between specific ordinal
 variables, we used Kendall rank correlation. Data processing, operations,
 analysis, and figure rendering were performed in R 4.3.0 (R Core
 Development Team 2023). For further information concerning code and
 additional data collected, send inquiries to Spencer Schubert
 (). # DATA-SPECIFIC INFORMATION FOR:
 "Schubert.et.al\_ConLet\_TreeOrgs\_11Jan2024.csv" ## 1. Number
 of variables: 69 ## 2. Number of cases/rows: 99 ## 3. Overview and
 Comments on Interpreting Data Definitions of acronyms and terms used
 across the data set: "Y" - yes "Vague” - This response
 signifies that whether or not the organization met the criteria for a
 particular column was inconclusive but plausible. This response was
 designated for cases in which organizations mentioned or provided brief
 reference to the subject of the prompt, but provided no detailed
 information/examples/data that we could further analyze "N" - no
 "NI" - no information "DOP" - depends on project. All
 intermediary organizations supported multiple restoration projects and in
 some cases information was only presented for select projects, indicating
 that the criteria is met for select projects, but not necessarily
 universally applied/required for all sponsored projects. “Other summary
 statistics”: reported numeric figures on other variables such as the
 number of sites planted, nurseries established, individuals/communities
 impacted without specifically reference measures of tree-growing
 parameters. Considered as “Vague” in best-practices index score.
 “Engagement only”: the website indicated the number of people or
 communities impacted by a project without specifying the type or extent of
 impact (e.g., number of community events, number of people affected).
 Considered as equivalent to “Vague” in best-practices score Calculated
 Columns for Best Practices Index All columns beginning with Q#. correspond
 to Table 1 of Schubert et al. 2024 and are organized around the ten
 questions funders should ask about reforestation (Holl and Brancalion
 2022) ## 4. Variable List: \
 "Intermediary.org.identifier" - Numeric; coded integer
 representing each organization "Year.founded" - Numeric; Year
 organization was founded "Org.type" - Categorical; Organization
 model; options: Non-profit, B-Corps/Social Enterprise, For-profit Company
 "Registered" - String/Description; Country in which the
 organization is registered/headquartered "Staff.number" -
 Categorical; Number of staff in the organization; options: &lt;10, 11-25,
 26-50, 51-75, 76-100, 101-150, 151-200, &gt;200, NI
 "Staff.regional" - Categorical; Are personnel or offices
 permanently established in regions where projects are implemented?;
 options: Y, DOP, Vague, N, NI "Geography" - String/Description;
 Countries in which the organization supports projects & partners. Up
 to 10 countries listed or, if more than ten, described as global
 "Staff.science" - Categorical; Extent of scientific expertise of
 project staff; options: NI, Some staff have Bachelor’s degree or
 certification in relevant field, At least one staff with advanced degree
 (Masters/PhD); Team(s) of designated advisors/experts (Masters/PhD)
 "Purpose.for.trees" - String/List; Goals/cited benefits for tree
 growing. List of all that apply: Air quality, Biodiversity (conservation),
 Carbon (sequestration), Climate change (other/general), Human wellbeing
 (other/general), Ecological restoration, Ecosystem services
 (other/general), Food security, Human livelihood, Recreation, Resiliency,
 Soil quality, Timber, Water supply OR water quality
 "Strategy.for.trees" - String/List; Methods used to grow trees.
 List of all that apply: Agroforestry, Natural regeneration (assisted),
 Planting/Transplanting (seedlings), Protecting forests, Seeding, NI
 "Native.nonnative" - Categorical; Types of trees planted;
 options: Native only, Native and non-native, Native and agricultural
 trees, NI "Time.bound.objectives" - Categorical; Does the
 organization have time-bound objectives that are measurable beyond 1 year?
 options: Y, DOP, Vague, NI "Reforested.area" - Numeric; Area
 that an organization claims to have reforested. Units = hectare (ha)
 "Protected.area" - Numeric; Area that an organization claims to
 have protected. Units = hectare (ha) "Planted.quant" - Numeric;
 Number of trees that an organization claims to have planted.
 "Experience.bin" - Categorical/Ordinal; Logarithmic scale of 1-5
 representing an estimate of total trees grown; We determined the relative
 tree-growing experience of organizations as follows. Intermediary
 organizations that reported to have grown fewer than 100,000 trees were
 placed into the lowest category (1). Subsequent categories were scaled
 logarithmically, extending to the highest category (5) for organizations
 that planted more than 100,000,000 trees. The equivalent measure for area
 reforested was 250 hectares (i.e., 800 trees = 1 ha reforested). And the
 equivalent measure in category 1 for forested area protected (but not
 actively planted) was 1000 hectares (i.e,, 1 ha reforested = 4 ha
 protected). We considered that organizations generally require fewer
 resources to implement forest protection and natural regeneration than to
 actively plant and maintain sites. "Project.criteria" -
 Categorical; Does the organization have explicitly stated criteria or
 conditions that determine whether to support local projects and partners?
 options: Y, DOP, Vague, NI "Land.tenure" - Categorical; Does the
 organization address the role of land tenure in securing the long-term
 success of projects? options: Requires, Considers, NI
 "Drivers.deforestation" - Categorical; Does the organization
 describe past or potential drivers of deforestation that would threaten
 current/future projects? options: Y, DOP, Vague, NI
 "Drivers.deforestation.type" - String/List; What drivers of
 deforestation does the organization reference? List of all that apply:
 Agriculture, Disease, Development, Firewood, Fires, Fisheries, Insect
 outbreaks, Livestock ranching, Logging (timber), Mining, Salt production,
 Severe weather, NI "Drivers.deforestation.address" -
 Categorical; Does the organization invoke a strategy or plan of action to
 minimize deforestation threats? options: Y, DOP, Vague, NI
 "Negative.consequences" - Categorical; Does the organization
 describe potential negative consequences of growing trees? options: Y,
 DOP, Vague, NI "Negative.consequences.type" - String/List; What
 negative consequences of reforestation does the organization reference?
 List of all that apply: Displacement, Destroying low tree cover native
 habitat, Increasing albedo, Increasing social conflicts, Loss of income,
 Reducing biodiversity, Reducing water supply, Spread of invasives, NI
 "Negative.consequences.address" - Categorical; Does the
 organization invoke a strategy or plan of action to minimize negative
 consequences? options: Y, DOP, Vague, NI "Community.engagement"
 - Categorical; To what extent is the involvement of local stakeholders
 discussed across organization webpages? options: No mention of local
 stakeholder engagement, Mention local stakeholder engagement vaguely,
 Mention that projects are locally led but no details, Provide detailed
 discussion of local stakeholder engagement "Community.benefits"
 - String/List; Benefits the organization cites as being provided to local
 stakeholders across various projects. List of all that apply: Cultural,
 Ecosystem services, Education, Energy, Food security, Income (financial,
 employment), Social equity (indigenous, gender), Tools (technology),
 Water, Wellness (medicine, lifestyle improvement, recreation)
 "Community.goals" - Categorical; Does the organization describe
 how local communities contribute to setting project goals? options: Y,
 DOP, Vague, NI "Community.planning" - Categorical; Does the
 organization describe how local communities contribute to planning how and
 where projects will be developed? options: Y, DOP, Vague, NI
 "Community.implementation" - Categorical; Do locals participate
 as employees or volunteers in the initial establishment of projects?
 options: Y, DOP, Vague, NI "Community.maintainence" -
 Categorical; Does the organization describe how locals are involved in
 maintaining conditions after initial project establishment? options: Y,
 DOP, Vague, NI "Community.monitoring" - Categorical; Does the
 organization describe how locals participate in monitoring project
 outcomes in the years after establishment? options: Y, DOP, Vague, NI
 "Reports" - Categorical; What reports are available on the
 organization’s website? options: Annual reports, Financial reports, Both,
 None "Past.data" - Categorical; Are quantitative data available
 for past projects? (other than planting/area totals). options: Y, DOP,
 Other summary statistics, Vague, NI "Community.benefits.data" -
 Categorical; Are data available for outcomes concerning stated benefits to
 local communities? options: Y, DOP, Engagement only, Vague, NI
 "Monitoring.discussed" - Categorical; Does the organization
 provide information about protocols that will be used to collect data and
 evaluate outcomes in the years after initial project establishment?
 options: Y, DOP, Vague, NI "Tree.survival" - Categorical; Are
 data available on the percentages of tree survival at project sites?
 options: Y, DOP, Vague, NI "Tree.survival.per" - Numeric;
 Percent tree survival reported. In cases where multiple survival
 percentages were available, a single midpoint or mean value is presented.
 "Monitoring.years" - Numeric; How many years after initial
 establishment are projects monitored? "Maintenance.years" -
 Numeric; How many years after initial establishment are projects cared
 for? "Follow.up.bin" - Categorical/Ordinal; Binned numeric
 category of maintenance or monitoring commitment in years. options: &lt; 1
 OR Unclear, 1-5, 5-10, &gt; 10 years "Maintainence.responsible"
 - Categorical; Who is responsible for project maintenance? options:
 Intermediary staff, Implementing staff, Local landholders, Third party
 (e.g., park staff), NI "Cost.split" - Categorical; Does the
 organization provide information about the proportion of funding dedicated
 to local tree growing projects versus implementing organization
 administrative costs? options: Y, DOP, Vague, NI
 "Cost.split.programs" - Numeric; Percentage value of funding
 that goes to local programs. "Cost.split.maintenance" -
 Categorical; Is part of the funding to local programs explicitly
 designated for maintenance activities? options: Y, DOP, Vague, NI
 "Cost.split.landowners" - Categorical; Is part of the funding to
 local programs explicitly devoted to compensating landholders? options: Y,
 DOP, Vague, NI "Funding.committment.bin" - Categorical/Ordinal;
 Binned numeric category of funding commitment in years. options: &lt; 1 OR
 Unclear, 1-5, 5-10, &gt;10 "Carbon.credits" - Categorical; Does
 the organization sell carbon credits as part of its revenue model?
 options: Y, Vague, NI "Q1.purpose.a" - Numeric; Goal(s) for
 Tree-Growing; Identifies at least one goal that tree-growing addresses;
 calculated score: value = 1 if TRUE "Q1.purpose.b" - Numeric;
 Goal(s) for Tree-Growing; Identifies objectives that are time-bound and
 measurable beyond one year; calculated score: value = 1 if TRUE
 "Q1.purpose.c" - Numeric; Goal(s) for Tree-Growing; Specifies
 criteria used to select and support local projects; calculated score:
 value = 1 if TRUE "Q2.strategy.a" - Numeric; Strategies for
 Tree-Growing; Specifies a strategy to grow trees; calculated score: value
 = 1 if TRUE "Q2.strategy.b" - Numeric; Strategies for
 Tree-Growing; Discusses whether native vs. nonnative trees are planted;
 calculated score: value = 1 if TRUE "Q3.drivers.a"- Numeric;
 Addresses Drivers of Deforestation; Identifies original drivers of
 deforestation in project region(s); calculated score: value = 1 if TRUE
 "Q3.drivers.b" - Numeric; Addresses Drivers of Deforestation;
 Reports measures taken to mitigate destruction/degradation of projects;
 calculated score: value = 1 if TRUE "Q4.locals" - Numeric; Local
 Community Engagement; Extent to which local stakeholder involvement is
 discussed; calculated score: detailed discussion = 2, mention projects
 locally led = 1, mention vaguely = 0.5 "Q5.local.benefits.a" -
 Numeric; Local Benefits; Identifies project benefits to local
 communities/stakeholders; calculated score: value = 1 if TRUE
 "Q5.local.benefits.b" - Numeric; Local Benefits; Measures
 project benefits to local communities/stakeholders; calculated score: Yes
 = 1, Engagement Only, Vague = 0.5 "Q6.negatives.a" - Numeric;
 Minimize Negative Consequences; Identifies potential negative consequences
 of tree-growing to people and the environment; calculated score: value = 1
 if TRUE "Q6.negatives.b" - Numeric; Minimize Negative
 Consequences; Reports measures taken to mitigate negative consequences;
 calculated score: value = 1 if TRUE "Q7.maintenance.a" -
 Numeric; Maintenance; Reports the length of time that projects are
 maintained beyond initial implementation; calculated score: value = 1 if
 TRUE "Q7.maintenance.b" - Numeric; Maintenance; Identifies who
 is responsible for maintaining project sites; calculated score: value = 1
 if TRUE "Q8.monitoring.a" - Numeric; Monitoring; Discusses
 monitoring protocol; calculated score: value = 1 if TRUE
 "Q8.monitoring.b" - Numeric; Monitoring; Reports the length of
 time that projects are monitored; calculated score: value = 1 if TRUE
 "Q8.monitoring.c" - Numeric; Monitoring; Specifies the project
 parameters that will be measured; calculated score: value = 1 if TRUE
 "Q9.outcomes.a" - Numeric; Outcomes of Prior Projects; Reports
 quantitative data on number of trees or area reforested/protected;
 calculated score: value = 1 if TRUE "Q9.outcomes.c" - Numeric;
 Outcomes of Prior Projects; Reports tree survival/mortality or other
 quantitative data (e.g., CO2 sequestered, tree cover estimates, local
 biodiversity) from past project monitoring; calculated score: Yes = 1,
 Other summary statistics = 0.5, Vague = 0.5 "Q10.funding.a" -
 Numeric; Funding; Provides information about the length of time that
 projects are funded; calculated score: value = 1 if TRUE
 "Q10.funding.b" - Numeric; Funding; Provides information about
 the percentage of costs that are allocated to intermediary organizations
 vs. tree-growing projects in the field; calculated score: value = 1 if
 TRUE "score" - Numeric; Best Practices Index; calculated as the
 sum of Q1-Q10 columns; total possible score = 22