Article Figures & Data
Figures
- Figure 1.
A simple version of the urban forest social-ecological systems (UFSES) framework.
- Figure 2.
The expanded urban forest social-ecological systems (UFSES) framework. See main text for a full verbal explanation. An earlier version of this visual was published in Vogt (2020b). See Tables 3 through 9 in this paper for an expanded list of second-, third-, and fourth-tier variables and citations to the literature that informed the development of the framework.
- Figure S1.
The Ostrom social-ecological systems (SES) framework. Used with permission from McGinnis and Ostrom (2014).
Tables
- Table 1.
Definitionsa of key concepts for understanding complexity in SESs, with examples from urban forestry. These words appear in italics when first used in the main text. UFSES (urban forest social-ecological system); SES (social-ecological system).
Concept Definition Example or application to urban forest systems Case study “An in-depth study of a single unit (a relatively bounded phenomenon) where the scholar’s aim is to elucidate features of a larger class of similar phenomena” (Gerring 2004). Insights generated from case studies are transferable to similar cases, but not generalizable. Most urban forest research that utilizes data from a single city is case study research, either explicitly (e.g., Mincey and Vogt 2014; Conway and Yip 2016; Schmitt-Harsh and Mincey 2020; Vogt and Abood 2021; Freeman-Day and Fischer 2022; Geron et al. 2023) or implicitly (e.g., Burghardt et al. 2022; Bigelow et al. 2024). Multicity studies or meta-analyses are relatively rare, although see the recent multicity studies by Esperon-Rodriguez et al. (2022) and Chambers-Ostler et al. (2024). Complexity “An interconnected network of components that cannot be described by a few rules; generally manifest in structure, order and functioning emerging from the interactions among diverse parts” (Levin 2000). Why a particular tree or collection of trees exists in a particular urban place cannot be accounted for by a simple explanation but rather is a function of a large set of interacting components (social, ecological, economic, historical, etc.) through time. Endogenous, endogeneity Features or components of the system (performance/function, dynamics, trends, etc.) arising from within the system. At a given level of analysis, endogenous variables influence and are influenced by other aspects of the system (cf., Levin 2000). Endogenous factors that influence urban forest outcomes are numerous, including everything from the biophysical characteristics of tree species and growing environments to management decisions and the wealth and resources of human communities. (See also Table 3 through Table 8.) Exogenous, exogeneity Features or components of the system that arise from outside of the system. At a given level of analysis, exogenous variables influence but are not influenced by endogenous system components (or the relative influence of endogenous on exogenous system components is relatively small)(cf., Levin 2000). Exogenous factors to the UFSES include Earth system processes, such as climate change, and also national-level politics that influence funding, such as the Inflation Reduction Act of 2022 which provided funding for urban and community forestry in the United States (USDA 2023). (See also Table 9.) Feedbacks Linkages between components of a system that ultimately connect back and influence one another, also a “chain of influence” (Levin 2000). A decline in tree canopy cover in a residential neighborhood precipitated by a pest may influence and be accompanied by overall disinvestment in that neighborhood, leading to further neglect of trees due to lack of resources to care for the urban forest (through planting trees, pest management, etc.), leading to a further decline in canopy cover. Hierarchies, hierarchical organization The nested-ness or couplings across levels. “Systems organized in such a way as to create a larger system. Subsystems within systems” (Meadows 2008). For example, trees nested within urban forest patches, nested within a neighborhood, nested within a municipality, nested within a larger metropolitan area, etc. Indirect effects Effects of one system component on another through an indirect series of interactions (where a direct effect is the direct impact of one component on another); may be difficult to predict and thus unanticipated. Sometimes indirect effects are also unintended or undesirable consequences. Indirect effects that are desirable may be conceived of as synergies. Planting trees in an underserved area of the city with low tree canopy cover without consulting neighborhood residents may have the intended effect of increasing canopy and access to the benefits of trees, but it may also have the indirect effect of gentrifying the neighborhood and actually result in excluding (now priced-out, former) residents from access to the benefits of these planted trees (e.g., Donovan et al. 2021; Wolf-Jacobs et al. 2023). Institutions The “rules, norms, and strategies” that structure the interactions of individuals and groups and between people and our environments (Ostrom 2005a; Mincey et al. 2013). All kinds of planning management practices from pruning to tree inventorying to urban forest master planning can be considered institutions. Norms of individuals regarding trees, such as the misconception that trees cause sewer pipe damage, are institutions also. (See also Table 7.) Legacy effects The “cumulative and evolving impacts of past interactions in CHANS [coupled human-natural systems] on current and future conditions” (Liu et al. 2007). Current tree species composition in a given city is influenced by past pest and disease exposure, the human decisions to treat or not treat when infestations occur, historical trends in tree species popularity, economic trends influencing the financial ability of the municipality to replace and replant public trees lost during an infestation, etc. (Roman et al. 2018). Levels The “different positions on a scale” (Cash et al. 2006). See also the definition of Scales in this table. As-in level of analysis. Urban forest dynamics might be examined at the level of the individual property owner or parcel or at the level of the entire city, for example. Longitudinal data, longitudinal studies Repeated observations of the same units (trees, people, cities, urban forests) through time. Street tree inventories may generate longitudinal data if they inventory the same trees at multiple points in time and connect the observations of the same tree across multiple years using unique identifiers or other methods; see Roman et al. (2020) regarding tree monitoring methods. Nonlinearity, nonlinear relationship “A relationship between two elements in a system where the cause does not produce a proportional (straight-line) effect” (Meadows 2008). The relationship between tree diameter and the many functions and benefits of trees (e.g., those associated with leaf surface area, such as air pollution removal and evapotranspiration) is nonlinear as trees grow. Tree mortality rates are nonlinearly related to tree age/size. Polycentricity “Many centers of decision making which are formally independent of each other”; decision making entities may “function independently, or instead constitute an interdependent system of relations” where they “take each other into account in competitive relationships, enter into various contractual and cooperative undertakings or have recourse to central mechanisms to resolve conflicts”; polycentric systems may or may not yield “consistent and predictable patterns of interacting behavior” (Ostrom et al. 1961). Trees in a metropolitan area may be influenced by decisions made by the local city and county governments; regional planning agencies; water, gas, and electric utilities; nonprofit greening organizations; institutional landowners such as schools or hospitals; private-sector arborists and landscaping companies; individual urban residents; and many others. Resilience The “capacity of a system to absorb disturbance and re-organize while undergoing change so as to still retain essentially the same function, structure, identity and feedbacks” (Folke 2006); that is, a system’s ability to “still maintain the same relationships between populations or state variables” despite perturbation (Holling 1973). A resilient urban forest is one that can withstand some kind of disturbance and still maintain its function as an urban forest and producer of ecological, social, and economic benefits. (See also Table 4, O8-1. Social-ecological resilience). Scales The “spatial, temporal, quantitative, or analytical dimensions used to measure and study any phenomenon” (Cash et al. 2006). Scales relevant to urban forests include the jurisdictional (e.g., municipality), spatial/geographic (e.g., watershed), temporal (e.g., 5-year planning horizon), analytical (e.g., social, political, economic), etc. Transferability The extension of research findings from one system to another system that shares similarities to the study system; “the degree to which an inference about a particular sending context fits or generalizes to a particular receiving context” (Tashakkori et al. 2020). Findings about planted street tree survival rates in one city may be transferable or applicable to planted street trees in another city if the planting and management contexts are sufficiently similar. For instance, street trees planted in tree pits in Philadelphia may be transferable to street trees in tree pits in New York City; however, street tree research in the Northeastern United States is likely not transferable to understanding the dynamics of trees planted in urban-adjacent golf courses in Miami. Vulnerability The “…degree to which a system, subsystem, or system component is likely to experience harm due to exposure to a hazard, either a perturbation or a stress/stressor” (Turner et al. 2003; Steenberg et al. 2017). An urban forest with low species diversity may be particularly vulnerable and experience long-lasting damage to a pest infestation affecting a particularly abundant tree species. (See also Table 4, O8-4. Urban forest vulnerability). ↵a Definitions in this table draw substantially from those in two classic texts on complexity and systems thinking (Levin 2000; Meadows 2008).
- Table 2.
Select frameworks within the field of urban forestry and urban greening. Note that this is not an exhaustive list of frameworks proposed or used in the urban forestry and urban greening field, just those that were influential and useful in the development of the comprehensive framework proposed in this paper. A collection of the visuals (tables and figures) containing the details of these frameworks excerpted from the original papers along with annotations for how the specific components of each framework aligns with the comprehensive UFSES framework presented in this paper is available by request from the author. The “Cit. key” lettering system in the first column of this table gives each framework a shorthand name and appears in the “Other UF framework” column of Table 3 through Table 9 in this paper. Asterisks next to the framework name indicate which informed the evolution of the UFSES perspective and which influenced earlier versions of the UFSES framework. UFSES (urban forest social-ecological system); Cit. key (citation key); UF (urban forest); SES (social-ecological system).
Cit. key Framework name Source(s) Citationsa Description (major system components in italics) SUS Model of urban forest sustainability* Clark et al. (1997) Kenney et al. (2011) 577 total (388) (189) Sustainable urban forests require 3 relatively separate, but equally important, components: Vegetation resource, Community framework, and Resource management approach. There are 20 specific criteria across all of these components. (Appendix B describes this widely applied framework.) INST Institutional analysis for urban forest ecosystems** Mincey et al. (2013) 121 In examining a decision-making situation or process, 7 major types of rules (in parentheses) are linked to the following parts of an “action situation”: Participants (Boundary rules), Positions (Position rules), Actors (Choice rules), Information (Information rules), Control (Aggregation rules), Costs and Benefits (Payoff rules), and Potential outcomes (Scope rules). GOV1 Urban forest governance framework** Lawrence et al. (2013) 191 Urban forest governance can be qualitatively explored through 5 groups of variables: Context, Institutional framework, Actors and coalitions, Resources, and Processes. SES1+ UFSESs perspective Vogt and Fischer (2014) Vogt et al. (2015c) 143 total (32) (111) Urban forest outcomes are produced by the Interactions of 4 major components: Community, Biophysical environment, Tree, and Institutions & management. A set of specific variables can be operationalized for each of these major components. MAIN Urban forest maintenance regimes** Vogt et al. (2015b) 173 A maintenance regime can be described by 6 kinds of information/decisions: Type, Who, Intensity, Frequency, Duration, and Extent. The given Costs of one or more maintenance regime can be evaluated against desired outcomes or financial constraints. CC Urban forestry climate change response framework** Brandt et al. (2016)b 114 A 3-part approach, consisting of Regional assessment of impacts and tree species vulnerability, Local vulnerability assessments, and culminating in Adaptation projects and planning, enables a community to plan and manage their urban forest in the face of climate change. VULN Urban forest ecosystem vulnerability** Steenberg et al. (2017) 73 Exposure (described by Components, stressors and disturbances and the Characteristics thereof) influences the Sensitivity of the urban forest (which is a combination of Urban forest structure and Urban forest function), which in turn impacts the Potential impacts and Adaptive capacity of the system. LEG Human and biophysical legacy effects in urban forests** Roman et al. (2018) 191 Biophysical legacies (inclusive of Ecological disturbance) and Human legacies (including Legacies of historical periods and Neighborhood and community change) influence Urban forest spatio-temporal dynamics. MOS Mosaic governance of urban green infrastructure*** Buijs et al. (2016) Buijs et al. (2019) 484 total (193) (291) Four “interventions and processes” (Resources, Rules of the game, Discourses, and Actors) connect Local government planning to Interventions in urban greenspaces, which happen through Scaling out and Scaling up processes. MORT Urban tree mortality framework** Hilbert et al. (2019) 104 Urban tree Mortality outcomes are influenced by 3 major levels of factors (Predisposing, Inciting, and Contributing) and at each level, factors in the Human and Biophysical parts of the system are considered. SES2+ Comprehensive framework for urban forests as SESs Vogt (2020b) 28 Biophysical factors (Characteristics of the trees in the urban forest and the Surrounding growing environment) and Human factors (Institutions and Characteristics of Human Actors) interact with one another and influence Urban forest outcomes. These 5 core factors are also influenced by the Broader Ecosystem Context and Dynamics (especially Ecological disturbances and Ecological “rules”) and the Larger Social, Economic, and Political Context & Dynamics. GOV2 Urban forest governance framework*** Ordóñez et al. (2020)c 67 There are 4 dimensions of urban forest governance processes (Stakeholders, Rules of the Game, Resources, and Discourse), and each dimensions includes numerous themes that can be qualitatively examined. NBS Conceptual model of the SES of nature-based solutions in urban environments*** Tzoulas et al. (2021) 40 In this complex framework, the SES of a site comprises 12 external systems that “function slowly at large scales” and 12 internal systems that “function fast at small, spatial, and temporal scales”. The 12 pairs of internal and external systems are coupled. Social pairs (external systems listed first) include, e.g., Demographic-People and Cultural-Lifestyles; Ecological pairs include, e.g., Biodiversity-Fauna and flora, Land change and N and P flows - Soil and Climate-Weather. These site-level systems pairings are then influenced by the planning and implementation of nature-based solutions along 8 stages of planning, each paired with a design element. BEY Beyond ‘trees are good’ evaluation matrix*** Roman et al. (2021b) 165 Trees and urban forests yield more than just benefits. Instead, a combination of Ecosystem services, Ecosystem disservices, and Management costs can yield Positive synergies, Tradeoffs, and Negative synergies for people in the urban forest. PAT Conceptual model of urban forest patches*** Johnson et al. (2021) 45 Six core factors within “co-produced urban forest assemblages” interact: People, Multilevel governance network, Regional economies, Forest patch condition, Local biophysical factors, and Landscape configuration. These are influenced by Macro-scale social drivers and Macro-scale biophysical drivers, and iterations of these interactions through time yield Legacies that also influence patch dynamics. ↵a Number of citations according to Google Scholar as of 2024 March 11.
↵b See also the report covering the climate change response framework for forests that includes a section on urban forests (Swanston et al. 2016), as well as the companion report that examines urban forests, climate change, and human health (Janowiak et al. 2021).
↵c The GOV2 framework of Ordóñez et al. (2020) is based in part on the GOV1 framework of Lawrence et al. (2013).
↵+ Indicates earlier versions of the UFSES framework presented in this paper.
↵* Influenced version 1 (SES1)(Vogt and Fischer 2014; Vogt et al. 2015d).
↵** Influenced version 2 (SES2)(Vogt 2020b).
↵*** Newly influential for the comprehensive UFSES framework.
- Table 3.
System Definition (SYS). Endogenous second-tier variables defining the system of interest in the UFSES framework. Abbreviations in the “Other UF frameworks” column correspond to shorthand citation keys for frameworks described in Table 2. Notes for Table 3 through Table 9 appear in Appendix D. SYS (system definition); UFSES (urban forest social-ecological system); UF (urban forest).
Number Second-tier variable Third-a and fourth-tierb variable(s) Description and possible values Other UF frameworks SYS1 System Identifying features and characteristics of the entire system GOV1 SYS1-1 Identifiera Name or other definitional descriptor of the UFSES of interest SYS1-2 Sizea Land area (or land and water area if appropriate) SYS1-3 Urban forest typea A classification of the collection of trees/urban forests area or areas in question. Types might include: street trees, manicured park trees, naturalized park trees, urban forest patches (may include vacant lots), residential or yard trees, communally managed forests or woodlands, trees on large institutional landowners (e.g., university or hospital or business campuses, which may or may not look and function like manicured parks), and so on. There may be more than one kind of urban forest relevant to any given analysis, and in complex ecologies or management situations, it may be necessary to capture the set of second- and third-tier variables for each SYS1-3. Urban forest type (Note 1). SYS2 System boundaries Scale(s) and level(s) of interest (Note 2). GOV1, CC, MOS SYS2-1 Geographic boundariesa Level of geographic interest: e.g., single lot; larger site, such as a college campus; neighborhood or community area; entire community or collection of communities; regional level such as a metropolitan statistical area or multicounty planning region or watershed; larger levels than these likely encompass nonurban areas but may be useful geographic boundaries in unique circumstances. SYS2-2 Jurisdictional boundariesa Level of jurisdictional control of interest (e.g., city/municipality; county; a single park; institutional land management, such as university or hospital campuses). PAT SYS2-3 Other boundary characteristics/analytical dimensions of relevancea E.g., only publicly managed trees (along streets and in parks), trees along stream corridors, or other meaningful boundaries or characteristics that define the system of interest (Note 3). TIME-X Time period Time 0 (baseline), Time 1, Time 2, etc.b What time period(s) are of interest or being examined (year, season, decade); may be multiple time periods if data is gathered at more than one point in time or examines change. PAT - Table 4.
Urban Forest Outcomes (O). Second-, third-, and fourth-tier variables relating to (O), one of the five core first-tier factors in the UFSES framework. Abbreviations in the “Other UF frameworks” column correspond to shorthand citation keys for frameworks described in Table 2. Notes for Table 3 through Table 9 appear in Appendix D. UFSES (urban forest social-ecological system); UF (urban forest); DBH (diameter and breast height); RGR (relative growth rate).
Number Second-tier variable Third-a and fourth-tierb variable(s) Description and possible values Other UF frameworks O1 Urban forest composition At a system- (e.g., entire city) or sub-system (e.g., neighborhood, block face) level. LEG, PAT O1-1 Richness or diversitya Number of taxa (genera, species, cultivars) represented in a particular area; number of native (noninvasive) species; biodiversity metrics (that take into account both the number of taxa present as well as the number of individual trees of each taxa)(Note 4). VULN, LEG O1-1a Species distributionb Follows a desired rule (“10-20-30”, “5-10-15”); or that no single species (or genus) comprises more than X% of population in a particular boundary. SUS O2 Individual tree structure These metrics can be aggregated to the level of the urban forest or evaluated on their own in statistical models that predict individual tree outcomes (Note 5). O2-1 Tree growtha Increase in DBH or circumference; for smaller trees, perhaps caliper (diameter 6” from the base of the tree) or total tree height. Could also use RGR calculated as the difference in the natural logs of tree DBH taken at 2 points in time divided by the length of time in between measurements. SES1 O2-2 Tree conditiona Qualitative (e.g., good, fair, poor, dead) or numeric-based (e.g., tree appraisalbased) overall condition rating. SUS, VULN O2-3 Tree survival/mortalitya Alive, standing dead, removed/missing, stump. SES1, MORT O2-X Other individual tree outcomea Any individual tree metric deemed meaningful by the relevant community and stakeholder groups and measurable either in qualitative or quantitative terms (e.g., pest presence, native species or not). O3 Urban forest structure At a system- (e.g., entire city) or sub-system (e.g., site, neighborhood, block face) level. VULN, PAT O3-1 Tree size (age) distributiona Distribution of tree sizes (or age, as calculated by either tree planting date or using a formula based on tree size and species) into bins (e.g., < 6” DBH, 6” to 12” DBH, etc.) to reflect the relative maturity of the trees. SUS, VULN O3-2 Total canopy cover (relative canopy cover)a % of total land area covered by tree canopy (relative canopy cover indicates % of plantable land area covered by tree canopy and excludes buildings from denominator). SUS, LEG O3-3 Total number of treesa Total # of stems or total # planted or removed; net # of trees planted or removed. O3-4 Basal areaa Calculated using the diameter or circumference of trees to determine the total cross-sectional area occupied by tree stems (generally expressed as something like square feet per acre when used by foresters)(Note 6). O3-5 Stocking levela For a particular part of the urban forest, generally used for street trees, where stocking indicates the % of plantable public right-of-way, street-adjacent spaces occupied by trees. O3-6 Natural areasa Area or percentage of land in natural areas (e.g., remnant woodlots, “trees managed extensively”)(Kenney et al. 2011). SUS O3-X Other metric of overall urban forest structurea Any urban forest structure metric deemed meaningful by the relevant community and stakeholder groups and measurable either in qualitative or quantitative terms (e.g., percent native species, leaf area index). O4 Urban forest function and benefits (& monetary value) Also called “ecosystem services” (Note 7). INST, VULN, BEY O4-1 Individual function or benefita A particular benefit of interest (e.g., reduction in asthma rates) or category of benefits (improvements in human health and well-being). O4-2 Monetary value of an individual benefita This is most commonly calculated via the tree benefits tools in the i-Tree software suite (i-Tree Tools, www.itreetools.org). O4-3 Aggregated benefits (for a category of benefits expressed in comparable terms)a Total value of measurable benefits (all benefits that can be calculated in terms of money value, all benefits included in the i-Tree software/tools, etc.; expressed in $ or local currency, # of lives saved or increased life expectancy years for health benefits, carbon dioxide equivalencies for climate benefits, or other means of standardizing different kinds of benefits). O4-1a, O4-2a, O4-3a Annual benefitsb Annualized benefits provided by the urban forest of interest (e.g., carbon sequestered annually) or benefits accruing annually. For an individual function/benefit (O4-1a), monetary value (O4-2a), or aggregated benefits (O4-3a). O4-1b, O4-2b, O4-3b Total benefitsb Total benefits provided by the urban forest at any given point in time (e.g., carbon stored). For an individual function/benefit (O4-1b), monetary value (O4-2b), or aggregated benefits (O4-3b). O5 Urban forest ecosystem disservices & costs Some disservices and costs could be conceptualized of as “externalities” in an economic sense (Note 8). INST, VULN, BEY O5-1 Infrastructure interference costs (private cost)a Repair of sewer/water infrastructure due to tree root interference with aging pipes; removal of tree limbs or debris blocking signage, power lines, storm drains, etc.; lost revenue/repair costs from tree-initiated power outages; etc. (Note 9). O5-2 Liability costsa “Damages paid from a lawsuit or settlement awarded when trees or parts of trees cause injury to persons or property, such as an improperly cared for tree falling on a house, vehicle, or person” (Vogt 2020b)(Note 9). O5-3 Opportunity costsa Costs resulting from the opportunities forgone when spaces in which trees are planted “cannot be allocated to other competing uses, such as parking, bike lanes, sidewalk cafés, etc.; shade from trees may preclude use of sunny areas for installation of solar panels or for gardening” (Vogt 2020b)(Note 9). O5-4 True ecosystem disservices (externality-related costs)a Disservices are “ecosystem generated functions, processes and attributes that result in perceived or actual negative impacts on human wellbeing” (Shackleton et al. 2016; Roman et al. 2021b); examples include “emissions of biogenic volatile organic compounds (VOCs) by trees; allergies due to tree pollen; release of carbon dioxide during decomposition of trees or tree debris or by maintenance equipment (gas-powered chain saws, lift trucks used to access tree canopy during maintenance, etc.); leaf/debris clean-up,” etc. (Vogt 2020b)(Note 9). O5-X Other disservices or costsa Any metric of disservices/costs deemed meaningful by the relevant community and stakeholder group and measurable either in qualitative or quantitative terms. O6 Urban forest sustainability & persistence Overall metric of change over time; usually requires collecting data from at least 2 points in time, but sometimes it is possible to assess change retroactively such as through aerial photos, historical records, or other tools (Note 10). VULN O6-1 Change in canopy covera % increase or decrease in canopy cover between time 0 and time x. O6-2 Survival (or mortality) ratea A proportion or percentage of a tree population or sample surviving or dying, calculated annually or cumulatively over a particular time period. O6-2a Annual survival (mortality) rateb “...proportion of individuals [trees] surviving [dying] over a year, from time x to time x + 1” (Roman et al. 2016)(Note 11). MORT O6-2b Survivorship (cumulative survival)b “...proportion of a cohort surviving from planting to year x (in other words, cumulative survival)” (Roman et al. 2016)(Note 11). MORT O6-3 Net change in stocking levela Number of trees planted during time 1 less number of trees removed during time 1; can be expressed as a percentage or proportion of total number of trees (if available) or as a ratio (# planted:# removed) where > 1 indicates more plantings than removals and < 1 indicates fewer plantings than removals. O6-4 Change in average tree sizea Change in average tree size (as indicative of a decline in overall urban forest maturity and consequential loss of benefits). O6-X Other metric of urban forest sustainability/persistencea Any sustainability/persistence metric deemed meaningful by the relevant community and stakeholder groups and measurable either in qualitative or quantitative terms (e.g., does the tree population meet a sustainable age distribution, achieve a desirable cost-benefit ratio, produce a certain level of net benefits; community-determined satisfaction with urban forest resources; is there an increase or decrease in the number of plantable spaces along street right-of-way, or of plantable area in the city). O7 Urban forest multifunctionality Outcomes related to measuring and achieving multiple urban forest functions simultaneously O7-1 Multifunctionalitya Ability of the urban forest to meet multiple desired functions simultaneously, including environmental, ecological, social, economic, human health, etc. MOS O7-2 Positive synergiesa “‘A win-win situation that involves a mutual improvement of two ecosystem services,’ with an implied reduction in disservices; more broadly speaking, positive synergies are situations in which the holistic impact is greater, and more beneficial, than each individual component” (Felipe-Lucia et al. 2015; Roman et al. 2021b)(Note 12). BEY O7-3 Negative synergiesa “A lose-lose situation that involves a mutual increase in ecosystem disservices, with an implied reduction in ecosystem services; also called ‘jointly negative’ outcomes; more broadly speaking, negative synergies are situations in which the holistic impact is worse than each individual component” (Roman et al. 2021b)(Note 12). BEY O7-4 Tradeoffsa “A ‘[s]ituation in which land use or management actions increase the provision of one ecosystem service and decrease the provision of another’, but could also refer to a situation in which an ecosystem service increases while disservice(s) also increase (i.e., win-lose)” (Felipe-Lucia et al. 2015; Roman et al. 2021b) (Note 12). BEY O7-X Other multifunctionality metrica Any multifunctionality metric deemed meaningful by the relevant community and stakeholder groups and measurable either in qualitative or quantitative terms (e.g., a ratio or other comparison of selected/relevant urban forest benefits and disservices). O8 Urban forest response to disturbance Outcomes related to how the urban forest reacts when perturbed or disturbed by natural or human pressures O8-1 Social-ecological resiliencea Demonstrated or predicted ability of the UFSES to withstand perturbation/disturbance from pests, fire, climate disturbances, etc., after the Folk (2006) definition of resilience as “capacity of a system to absorb disturbance and re-organize while undergoing change so as to still retain essentially the same function, structure, identity and feedbacks” (Note 13). O8-2 Institutional robustnessa Demonstrated or predicted ability of urban forest social institutions, policies, etc. to “maintain some desired system characteristic despite changes in the behavior of its components parts, circumstances that contribute to long-enduring or sustainable systems overall” (Anderies et al. 2004; Mincey et al. 2013). Robust institutions are functional across a range of social-ecological characteristics (Note 14). INST O8-3 Urban forest adaptive capacitya Demonstrated or predicted “capacity for a system to shift or alter its conditions to reduce its vulnerability or to improve its ability to function while stressed” (Adger 2006; Steenberg et al. 2017)(Notes 15, 16). VULN O8-4 Urban forest vulnerabilitya How much the urban forest will be harmed or damaged after exposure to a stressor or hazard, for example pest infestations, storms, or climate change (Steenberg et al. 2017)(Note 17). VULN, CC - Table 5.
Characteristics of Trees in the Urban Forest (T). Second-, third-, and fourth-tier variables relating to (T), one of the five core first-tier factors in the UFSES framework. Abbreviations in the “Other UF frameworks” column correspond to shorthand citation keys for frameworks described in Table 2. Notes for Table 3 through Table 9 appear in Appendix D. UFSES (urban forest social-ecological system); UF (urban forest); DBH (diameter at breast height).
Number Second-tier variable Third-a and fourth-tierb variable(s) Description and possible values Other UF frameworks T1 Tree taxonomy Family, genus, species, cultivar; native/nonnative/invasive; seed sourceb Taxonomy influences tree form, size-at-maturity, average growth rate, drought/flood tolerance, nutrient requirements, pest vulnerabilities, climate change vulnerability, etc. (Note 18). SUS, SES1, CC, VULN, MORT T1-1 Tree traitsa Tree traits are nested within T1. Tree taxonomy as traits are directly connected to the species/cultivar of a tree. T1-1a Tree typeb Deciduous, coniferous, evergreen, fruit trees, palms, etc. T1-1b Stature/expected size-at-maturityb Large, medium, small, ornamental, etc. T1-1c Tree form/growth habitb Excurrent, decurrent, columnar, etc. T1-1d Drought or flood toleranceb How well a tree is expected to be able to withstand periods of low or no rainfall/water or excessive moisture during periods of flooding; connected to tree species and cultivar. T2 At-planting parameters Planting packaging type/size, nursery of origin, size/age of tree at time of planting, planting season, etc.b Legacy effects of nursery growing conditions impact tree outcomes during the establishment phase, 3 to 5 years post-transplanting, especially; less relevant for larger, mature trees, unless the tree is planted improperly or the planting packaging is left on (Notes 18, 19). SES1, MORT T3 Current tree size DBH, caliper, total height of tree, width of crown, proportion of tree in live crown, etc.b Impacts the provision of benefits, likelihood of survival, risk assessment, etc. (Note 18). SES1, VULN, MORT T4 Canopy condition Crown dieback, crown exposure to light, leaf density, leaf condition such as presence and degree of chlorosis, canopy pest presence, etc.b Canopy condition affects tree health/vigor and the level of urban forest benefits (Note 18). SES1, VULN, MORT T5 Trunk condition Presence of a root flare, damage to lower trunk, trunk pest presence, etc.b Trunk condition affects tree health/vigor and overall condition; extensive damage to the trunk can be a contributing factor to tree mortality (Note 18). SES1, MORT T6 Overall tree condition Evidence of other damage to tree, overall good-fair-poor or numeric condition rating, hazard rating, etc.b Overall assessment of condition affects tree health/vigor, vulnerability to pests and diseases, etc. (Note 18). SES1, MORT T7 Tree age Date of planting, years (or days) since planting, number of growth rings, estimated ageb Calculated or estimated age from size or from known planting date or from number of growth rings (Note 18). SES1, MORT - Table 6.
Surrounding Growing Environment (E). Second-, third-, and fourth-tier variables relating to (E), one of the five core first-tier factors in the UFSES framework. Abbreviations in the “Other UF frameworks” column correspond to shorthand citation keys for frameworks described in Table 2. Notes for Table 3 through Table 9 appear in Appendix D. UFSES (urban forest social-ecological system); UF (urban forest); SOM (soil organic matter); CEC (cation exchange capacity).
Number Second-tier variable Third-a and fourth-tierb variable(s) Description and possible values Other UF frameworks E1 Near-tree considerations Features of the growing environment nearest to the tree or trees. E1-1 Interference with aboveground infrastructure’ Whether the tree is touching or otherwise interfering with buildings, fences, signs, lighting, aboveground utility wires, or other aboveground infrastructure. SES1 E1-2 Interference with at/belowground infrastructurea Whether the tree roots are interfering with building foundations; sidewalks, curbs, roads, or other paved surfaces; water/sewer lines, underground utility wires, etc. SES1 E1-3 Ground cover under the canopy and/or at the base of the treea Impervious/pervious surface; kind of ground cover present (turf grass, perennials, planted annuals, soil, weeds, concrete, mulched ground, etc.). SES1 E2 Planting area characteristics Features related to the space in which the trees is located. MORT E2-1 Type of planting areaa Boulevard/tree lawn, tree pit, median, road shoulder, park, front or back yard, etc. SES1 E2-2 Planting area dimension(s)a Width, length, depth; total available rooting volume. SES1 E2-3 Planting substratea Kind of medium into which the tree has been planted: soil, structural soil, gravel, etc. E2-X Other planting area characteristicsa Elevation relative to nearby roads or other paved or impervious surfaces (above or below grade); presence/intactness of a curb; previous land use/brownfield status, etc.; impact of exposure to pollutants, water infiltration, etc. SES1 E3 Proximity to other features in the urban environment Other trees or vegetation, roads, sidewalks, buildings, bodies of water, other above or belowground infrastructure, etc.b Influences competition for light and space, exposure to heat and pollutants, etc. SES1 E4 Urban form Physical characteristics of surrounding growing environment; can be defined locally (e.g., within a particular distance of a tree or forest of interest) or for an entire system or part of a system (e.g., a census tract or neighborhood/community area). LEG, MORT E4-1 Impervious surfacesa Percentage of land area in pavement, buildings, other nonpermeable surfaces. SES1 E4-2 Zoning and/or land use type—currenta Macrolevel land use categorization (residential vs. commercial vs. industrial use; single vs. mixed use); microlevel land use (residential-estate, residential-high density, etc.), or specific land use (hospital, residential apartment building with 6+ units, office building, school, playground, vacant lot, etc.). PAT E4-3 Age of buildings/neighborhooda Date of construction of a particular building, the average building in a neighborhood, or date of the founding of a neighborhood. E4-4 Lot size and designa Total lot dimensions; design might include building type and height, setback from street, etc. E4-5 Constructiona Extent, intensity, recency of construction of any kind (roads, curbs/sidewalks, buildings, other infrastructure repair) in the vicinity. MORT E4-X Other important characteristics of urban forma The width/type/busyness of nearby roads/sidewalks, etc. E5 Ecological and environmental characteristics of nearby urban environment Overall site suitability, site connectivity, site size (# acres, # trees planted), watershed catchment area, open greenspace or canopy cover in vicinity, local microclimate, etc.b A huge variety of nearby ecological parameters might be relevant; which should be considered depends on the system and the urban forest outcomes of interest, where system boundaries are drawn, and how much variability there is across the system within the boundaries. SUS, SES1, VULN, MOS, MORT, NBS, PAT E6 Soil/substrate conditions Substantially impact tree outcomes and can vary widely across the urban forest. PAT, NBS E6-1 Soil volumea In cubic feet or meters, how much soil growing volume is available to the tree’s root system. VULN E6-2 Soil physical propertiesa Temperature, evaporation, infiltration/retention/drainage rates, splashing, soil density, soil porosity, compaction (Note 20). E6-3 Soil chemical propertiesa SOM content, CEC, pH/acidification, plant nutrient availability, micronutrient chelation, toxic material binding potential, salinization (Note 20). VULN E6-4 Soil biological propertiesa Carbon resource, energy supply, microflora activity/biomass, mineralization capacity, bio-aggregation, soil fauna, bio-pores (Note 20). - Table 7.
Management & Institutions (M). Second-, third-, and fourth-tier variables relating to (M), one of the five core first-tier factors in the UFSES framework. Abbreviations in the “Other UF frameworks” column correspond to shorthand citation keys for frameworks described in Table 2. Notes for Table 3 through Table 9 appear in Appendix D. UFSES (urban forest social-ecological system); UF (urban forest); NLCD (National Land Cover Database).
Number Second-tier variable Third-a and fourth-tierb variable(s) Description and possible values Other UF frameworks M1 Operational level maintenance activities Specifics of on-the-ground maintenance activities, including tree care activities as well as planting and site preparation. SUS, MAIN, MOS, VULN, NBS, PAT M1-1 Type of maintenancea Planting (including site preparation), pruning, watering, mulching, staking, soil and nutrient management (aeration, fertilizing), tree removal, pest treatment(s), other cultural management practices, etc. MAIN, SES1 M1-2 Party performing the maintenancea Municipal crews (forestry staff, generalist public works staff), public utility (electric, gas) company, contracted arborists/landscapers, local nonprofit staff, homeowners, volunteers (including who manages the volunteers), etc. MAIN, SES1 M1-3 Intensitya How much maintenance is performed, (e.g., how much of the crown is pruned, how much water is given). MAIN M1-4 Frequencya How often maintenance is performed (e.g., on a 4- or 6-year pruning cycle, watering once per week). MAIN M1-5 Durationa For how long maintenance is performed (e.g., for just the first growing season, throughout a tree’s life). MAIN M1-6 Extenta What part of a tree, or which trees, are maintained (e.g., removing branches below a desired clearance height or removing no more than X% of total canopy, maintaining only trees on heavily trafficked streets). MAIN M1-7 Seasonal timinga When during the year (e.g., year-round, leaf-on, April–November). M1-8 Maintenance costsa Monetary costs of operational-level maintenance activities; may also include the monetary value of unpaid volunteers who perform tree maintenance; different from total municipal tree budget (H9-3). MAIN, BEY, GOV2 M2 Data/record keeping practices What kind of data is collected; when and how data is collected; in what form and/or for what reason/purposes data is used; how regularly is it updated; etc. (e.g., 100% public tree inventory kept up-to-date with planting and removal activities, prunings, and other tree maintenance entered into record-keeping system when performed). NBS M2-1 Street tree inventory practicesa On-the-ground, virtual (street-level imagery), windshield, or other. SUS M2-1a Method of data collectionb On-the-ground inventory with smartphones, paper records, Lidar-based individual tree inventory, etc. M2-1b Frequency of updatingb Sporadically/as needed, at regular intervals, as work is performed, etc. M2-1c Specific variables gathered during inventoryb List of variables included in inventory, such as species, location information, condition/maintenance needs, etc. M2-2 Canopy cover dataa What kind of spatial data is the canopy cover data generated from? Lidar/high-resolution images, NLCD data, photo interpretation, digitized aerial photos, etc. SUS M2-2a Resolution of canopy datab 30-m resolution, 3-m resolution, point sampling, etc. M2-2b Frequency of updatingb Sporadically/as needed, at regular intervals, etc. M2-3 Tree care recordsa Tree care work: most salient for public trees, trees in parks or along the public right-of-way (or, for institutional urban forests, semipublic trees on institutional properties, e.g., college campuses). M2-3a Planting records/locationsb How/are records of tree planting locations kept, how often is planting data updated, etc. M2-3b Pruning records/locationsb How/are records of tree pruning/trimming activities kept/updated, etc. M2-3c Removal records/locationsb How/are records of tree removals kept/updated. M2-3x Other maintenance records/locationsb Inspections, pest treatments, etc. M2-4 Transparency of dataa Data availability and transparency to other interested parties, the general public. M2-5 Data/record keeping costsa Direct, monetary costs of data/record keeping. M2-X Other data/record keeping practicesa Private property tree data, etc. M3 Proactive management activities Urban tree and forest management activities separate from operational level maintenance activities (M1)(Note 21). GOV1, VULN, MOS, GOV2, NBS M3-1 Urban forestry strategic or master planning effortsa More holistic than day-to-day management planning or operations level plans; may involve strategic assessments of planting opportunities, greenspace or greenway plans, etc.; master planning efforts may involve some or all of M3-2 through M3-9. SUS, MOS M3-2 Tree preservation planninga Plans, policies, or procedures, including permitting, to protect trees during construction or redevelopment efforts, including municipal capital improvements; protecting existing mature trees and tree canopy is crucial to ensuring the continued benefits these existing trees provide. SUS M3-2a Tree preservation planning (during new construction/development)b Practices to manage/protect trees (on both private property and public right-of-way) during the construction of completely new buildings on previously non-built-up lands (e.g., remnant woodlands or other semitreed habitat, treed vacant lots, farmlands with tree breaks). M3-2b Tree preservation planning (during redevelopment/renovations)b Practices to manage/protect trees (on both private property and public right-of-way) on existing built-up lands during construction that could include razing existing structures, digging new foundations, creating additions, or otherwise altering a property on an existing urban lot. MORT M3-2c Tree preservation planning (during municipal capital improvements)b The extent to which municipal improvement projects in the public right-of-way (e.g., water/sewer, road, sidewalk repairs or upgrades) preserve or fail to preserve mature trees in the right-of-way; indicates how the city values green infrastructure as an asset class relative to the improvement of grey infrastructures like roads and sewer lines. M3-3 Climate change planninga Plans, policies, or procedures to consider or alter urban forest maintenance and management practices in response to the changes in precipitation, temperatures, storm frequency and intensity, and other local- to regional-level impacts resulting from global climate changes. CC M3-4 Risk assessment proceduresa Plans, policies, or procedures to assess tree risk or hazard potential, either after a physical disturbance, such as a storm or fire, or in response to resident requests (and follow-through on these plans). SUS, MORT, BEY M3-5 Pest/disease management planninga Plans, policies, or procedures for how to proceed in managing major tree pests or disease infestations (e.g., emerald ash borer [Agrilus planipennis]). M3-6 Natural areas planninga Plans, policies, or procedures for how to manage natural areas, nature preserves, or larger tracts of more “intact” urban forest/woodlands, including plans for the connectivity of natural areas or greenways. SUS M3-7 Equity considerations in planninga Considerations made for the equitable distribution of trees/urban forest resources and of maintenance/management efforts based on race/ethnicity, income, or other socio-demographic dimensions, as well as based on existing trees/canopy. MOS M3-8 Knowledge transfer activitiesa Public education efforts of stakeholder groups such as municipal governments, nonprofits, universities, and others; includes fact sheets, workshops, advertising/social media campaigns, etc. GOV1, GOV2 M3-9 Evaluation and assessmenta Program evaluation, quality improvements, assessments, audits by internal or external parties, etc.; response to the results of these evaluations could also be documented. GOV1 M3-9a Participation in standards programsb Participation in urban forestry assessment or standards programs, such as the Arbor Day Foundation Tree City/Campus/Line programs and similar (Note 22). M3-10 Proactive management costsa Direct, monetary costs of proactive management (e.g., cost of a consultant-prepared urban forest management plan). M4 Other reactive management activities Response to storms, pests, or other disturbances, resident/311 requests like debris pick-up (Note 23). VULN, MORT M4-1 Costs of reactive managementa Direct, monetary costs of reactive tree maintenance activities (e.g., storm clean-up costs, tree removal costs due to lack of pest management, etc.). BEY M5 Collective-choice level institutions Rules and strategies about operational level maintenance, record keeping, and proactive management activities (e.g., who and how it is decided that tree maintenance is conducted at a particular intensity, frequency, etc.); monitoring and enforcement of operational level maintenance activities (Note 24). GOV1, VULN, MOS, GOV2, PAT M5-1 Enforcement of ordinances and contractsa Procedures (and adequate resources) for enforcing ordinances (e.g., tree preservation ordinances) and contracts with private companies for tree care (e.g., ensuring quality tree planting occurs and evaluating tree survival and pursuing any warranty guarantees per tree condition). NBS M5-2 through M5-X Collective-choice level: Boundary rules, Position rules, Choice rules, Information rules, Aggregation rules, Payoff rules, Scope rulesa Seven kinds of rules that help specify the kinds of institutions relevant to operational-level tree maintenance decisions; see Figure 3 in Mincey et al. (2013) for a fully specified example with all rule types; some of these kinds of rules may be inside M3. Proactive management activities (Note 25). INST M5-Y Other collective-choice level institutionsa Additional kinds of rules, norms, strategies about the operational-level management decisions M6 Constitutional-choice level institutions Rules and strategies about who makes collective-choice level rules (e.g., the ordinance, case-law, policy, informal tradition, or other decision-making enabling authority that specifies who and how operational level maintenance decisions are made)(Note 24). GOV1, MOS, GOV2, PAT M6-1 through M6-X Constitutional-choice level: Boundary rules, Position rules, Choice rules, Information rules, Aggregation rules, Payoff rules, Scope rulesa Seven kinds of rules that help specify the kinds of institutions relevant to collective-choice level decision-making; see Figure 4 in Mincey et al. (2013) for a fully specified example with all rule types (Note 25). INST M6-Y Other constitutional-choice level institutionsa Additional kinds of rules, norms, strategies about the collective-choice level institutions (e.g., who can make the collective-choice level rules, norms, strategies) M7 Meta-constitutional level institutions Rules and strategies about the manner in which constitutional-choice level decisions are made (e.g., the enabling authority); kind/style of government (e.g., mayor-council at municipal level; “right to work” state; constitutional democracy at national level)(Note 24). GOV1, GOV2, PAT M8 Property rights regimes, Land ownership, access rights, use rightsb Ownership of and/or legal responsibility for tree and/or tree-planting space (Note 26). GOV1, GOV2, PAT M9/MX Legal institutions Ordinances, laws, regulations, and judicial precedents/case law regarding the planting, preservation, care, removal, and liability issues related to trees (including procedures for sanctioning violators); might be specified inside M5 and M6 for those legal institutions which specify collective-choice or constitutional-level institutions (Note 27). GOV1, GOV2 M10/HX Norms/behaviors Individual and/or shared view/values on trees/yards/lawns and their benefits, costs, risks, level of tree care, invasive species management, aesthetic preferences, etc.; “civic ecology” behaviors on private yards such as lawncare activities, leaf management, vegetable, perennial, or native gardening, etc. (Note 28). SUS, GOV1, MOS, MORT - Table 8.
Characteristics of the Human Community (H). Second-, third-, and fourth-tier variables relating to (H), one of the five core first-tier factors in the UFSES framework. Abbreviations in the “Other UF frameworks” column correspond to shorthand citation keys for frameworks described in Table 2. Notes for Table 3 through Table 9 appear in Appendix D. UFSES (urban forest social-ecological system); UF (urban forest).
Number Second-tier variable Third-a and fourth-tierb variable(s) Description and possible values Other UF frameworks H1 Size and density At a system (e.g., entire city) or subsystem (e.g., neighborhood, block face) level. GOV1 H1-1 Size of communitya Overall number of people living in the area of interest, or the overall geographic size in terms of area of land (or land and water if significant water resources are present and impactful). H1-2 Population densitya Density of people living in the community (# of people per unit area, # of households per unit area, # of dwelling units per unit area). VULN H2 Socio-demographics Composite characteristics of people within a particular geography (community, neighborhood, etc.)(Note 29). GOV1, LEG, MORT, NBS H2-1 Race/ethnicitya Distribution of racial and/or ethnic identities of individuals living within a geographic area into locally relevant categories. SES1 H2-1a Language spokenb First language or language spoken at home by individuals/households. H2-2 Age of peoplea Mean or median age of community, or a distribution of ages (Note 30). H2-3 Gendera Distribution of individuals into categories of Male, Female, and Other (Note 30). H2-4 Incomea Mean or median of individuals per capita or per household; the most commonly used metric in the USA is that collected by the Census Bureau (median household income). SES1, VULN H2-5 Education levelsa Distribution of individuals into locally relevant categories based on level of education (e.g., less than 8th grade, less than high school, high school graduate or GED, some college, etc.); could use the median level of education as a single metric. SES1, VULN H2-6 Unemployment ratesa Proportion of the working-age population (18+, or other locally relevant cut-off age) who does not have a job. SES1 H2-7 Homeownership/owner occupancy ratea Proportion of households owning their home or proportion of homes in the geographic area that are owner occupied; especially important for neighborhoods with large percentages of single-family homes. SES1, VULN, MORT H2-8 Housing/building vacancy ratea Proportion of buildings, homes, and/or businesses that are vacant and unoccupied. SES1 H2-X Other demographic or socio-economic factorsa E.g., family structure, residence time in neighborhood, home value. SES1, VULN H2-#V Variability (homogeneity or heterogeneity) in socio-demographicsa How much variability there is for any of the relevant socio-demographic factors analyzed; could be expressed as a variance or standard deviation of the mean, 95% confidence intervals for population-level estimates, or as a set of minimum, maximum, or other percentiles (25th, 75th, etc.). H2-#T Change in socio-demographicsa Rate of change in any of the socio-demographic factors can be captured (e.g., H2-1T could be used to express the change in the percentage of a community identifying as nonwhite between decadal censuses; H2-6T could capture the % decrease in the unemployment rate in the past 2 years). LEG, MORT H3 Legacies of historical periods Within community legacies of colonial history, redlining areas, industrial and postindustrial changes in land use, shifting socio-economic and demographic composition of communities, etc.; relevance of these factors vary within the urban forest system of interest (Note 31). GOV1, LEG H4 Community capacity Indicators of capacity might include: social capital (bonding, bridging, linking) and other resources of individuals and community/neighborhood groups influencing the urban forest; practical experience in managing trees, gardens, or other natural resources, or taking care of public space; neighborhood ties, social cohesion, trust, reciprocity, etc.; what relevant variables are indicative of community capacity may vary widely across and even within communities; community-defined capacity may be different endogenously defined (by the community itself) than exogenously defined (by researchers, outsiders). H5 Evidence of tree care Evidence of the community caring (or not caring) for trees/greenspace, including presence of care indicators (e.g., watering bags/irrigation systems, seating areas, bird feeders, yard art near the tree[s]/tree space) or evidence of a lack of care (e.g., trash, vandalism in or near the tree[s]/tree space). SES1, VULN, MORT H6 List of stakeholders List of relevant stakeholders; might be individuals, groups, and/or types of groups as appropriate to the system of interest; includes parties performing operational-level maintenance as well as those engaged in other planning and policy type activities; stakeholders are defined as “actors who influence, interact, and benefit from urban forests” (Vogt and Abood 2021) and might be an individual (e.g., the mayor), a group (e.g., municipal tree crew members), an organization (a nonprofit organization, a private tree care company), or a type of individual (e.g., homeowners); interactions of stakeholders with the trees in the urban forest may be formal/official (e.g., municipal tree care activities) or informal (homeowners benefiting from temperature regulating effects of shade trees)(Note 32). GOV1, MOS, GOV2 H6-1 Core stakeholders (leaders, entrepreneurs, bridging groups)a If applicable, identify those stakeholders who are most deeply and/or broadly connected to urban forestry efforts throughout the system of interest or stakeholders who are local leaders in urban forestry or who otherwise have an outsized influence on the system; core stakeholders could be the formal members of a steering committee, advisory body, or just those who are informally influential. H6-2 Stakeholder network structurea Network structure refers to the connections between stakeholder groups or individuals; could refer to networks with respect to a particular aspect of the system such as knowledge sharing or decision making, or to more general network structure; could identify particular kinds of stakeholders such as boundary actors or bridging organizations, etc. (Note 33). H7 Level of expertise/training of stakeholders/stewards Experience, training, certifications, and/or education of individuals within stakeholder groups; includes the frequency, intensity, formality of professional development activities for paid professionals, retraining requirements for volunteers, compliance/licensing re-up requirements, etc.; professional certifications and licenses, especially for paid staff or contractors (e.g., Certified Arborists®, Board Certified Master Arborists®, TRAQ or other qualifications, Certified Foresters); level of training/volunteer certifications of community volunteers (e.g., Master Gardener, “tree steward” certifications, etc.); formal education in relevant fields (arboriculture, forestry, horticulture, but also, community organizing, etc.). SES1 H7-1 Level of expertise: Municipal staffa LEG H7-2 Level of expertise: Nonprofit staffa LEG H7-3 Level of expertise: Private sectora H7-4 Level of expertise: Volunteersa H7-X Level of expertise: Other stewardsa H8 Stakeholder collaboration, cooperation, & conflict resolution Degree of collaboration, cooperation, and conflict (and conflict resolution) between stakeholders; includes cooperation between public agencies managing trees, support or lack of support from private, nonprofit, and philanthropic organizations, and the green industry; involvement of the general public; bridging or convening groups and collaborative/regional initiatives, etc. SUS, MOS, GOV2 H9 Stakeholder characteristics: Municipal Characteristics of the relevant municipal/local government authority(ies)(city, village, town, hamlet, county, etc.) that impact the urban forest (Note 34). MORT, GOV2 H9-1 Municipal department(s) or division(s)a Particular department(s)/division(s) responsible for care of public trees and/or with ordinance enforcement responsibilities for trees on private and public property. H9-2 Municipal human resourcesa Number of staff (individuals, full-time equivalencies), work hours, contracted staff, staff with particular credentials, etc. SUS, GOV2 H9-3 Municipal budget/fiscal resourcesa Budget of the department responsible for tree management (e.g., annual municipal tree budget; contract value); or proportion of the total municipal budget dedicated to the care and management of trees. SUS, GOV1 H9-X Other municipal characteristicsa Any other relevant factors related to the municipal authority and its urban forest management (e.g., if a municipality has made a specific tree planting goal, the mission of this initiative could be relevant). H10 Stakeholder characteristics: Nonprofit Characteristics of any local, regional, or national-level nonprofit organizations (including philanthropic organizations, formal/informal community/neighborhood groups/associations) that impact the urban forest of interest. SUS, MORT, GOV2 H10-1 Nonprofit missiona Overall mission/goal of the nonprofit organization(s)(or program[s]) that impacts the urban forest)(Note 35). MOS H10-2 Nonprofit human resourcesa Number of nonprofit staff (individuals, full-time equivalencies), work hours, level of expertise/education/training, etc. GOV1, GOV2 H10-3 Nonprofit budget/fiscal resourcesa Budget of the authority responsible for tree management (e.g., annual municipal tree budget; contract value). H10-X Other nonprofit characteristicsa Any other relevant factors related to a nonprofit organization and its urban forest management. H11 Stakeholder characteristics: Private sector Characteristics or capacity in the private sector that regularly impact the urban forest, including the involvement of large institutional land holders such as colleges/universities, hospitals, business parks, industrial properties, etc. (e.g., number of local tree care companies, dollar value of local green industry [if available], prevalence/quality of institutional urban forest management plans/practices). SUS, GOV1, GOV2 H12 Stakeholder characteristics: Other Characteristics of additional authorities not specified in H9 through H11. GOV2 H13 Community adaptive capacity & learning Demonstrated or anticipated capacity for adapting to change or learning from past experiences; might be indicated by access to fiscal and other kinds of capital (natural, built, human, social, cultural, political) that often enable adaptation; level of stakeholder buy-in to proposed changes (Note 36). VULN - Table 9.
Exogenous Factors. Second-tier variables relating to the exogenous factors in the broader environmental and social-economic-political systems of which urban forests are a part. Abbreviations in the “Other UF frameworks” column correspond to shorthand citation keys for frameworks described in Table 2. Notes for Table 3 through Table 9 appear in Appendix D. UFSES (urban forest social-ecological system); UF (urban forest).
Second-tier variable Description and possible third-tier variables Other UF frameworks Broader Environmental Context & Dynamics (ENV) Biome characteristics Climate (landscape-level), type of native biome/ecosystem, topography, pre-urbanization vegetation and land cover, etc. MORT, PAT Earth system processes Climate change, stratospheric ozone depletion, atmospheric aerosol loading, ocean acidification, biogeochemical flows, freshwater change, land system change, biosphere integrity, novel entities (Note 37). NBS Polycentricity of Earth systems Nested, multilevel, multiscale; from cellular- to organism- to landscape- and continent-level; from mitosis to global biogeophysical cycles and weather patterns, etc. (Note 38). NBS Ecological Disturbances (ED) “Pulse” disturbances Ecological disturbances that occur at a relatively discrete period in time (measurable in hours or days) and onset is often sudden; can be predictable or unpredictable. Examples include storms and extreme weather events (thunderstorm, tornado, hurricane, derecho/flatline winds, polar vortex/extreme cold, ice storms, blizzard, heat dome/extreme heat events, dust storm, etc.), fires at the wildland-urban interface, some kinds of pest and disease outbreaks, etc. VULN, LEG “Press” disturbances Ecological disturbances that occur more gradually over relatively longer periods of time than “pulse” disturbances, such as gradually increasing temperatures due to climate change, long term changes in precipitation patterns including flood/drought, El Niño/La Niña multiyear weather cycles, etc.; some kinds of pest and disease outbreaks that come on more gradually and persist long term might be “press” disturbances. CC, VULN, LEG Characteristics of these disturbances Magnitude, frequency, duration, extent (Note 39). VULN, CC Ecological Rules (ER)(Note 40) Physical phenomena Urban heat island effect, light penetration, air pollutant dispersal, etc. VULN Biogeochemical phenomena Photosynthesis and flows of nutrients through urban ecosystems, soil processes, etc. Biological/ecological phenomena Competition between individual organisms and between species, natural selection and evolutionary processes, ecological succession, landscape fragmentation and patch dynamics, etc. Larger Social, Economic, and Political Context & Dynamics (SOC) Human legacies Historical decisions around tree planting/care, including species symbolism, civic beautification movements, park creation, street tree planting, national and regional identity as connected to trees or forests, trends in urban design and development, political popularity or unpopularity of trees and forests, etc. (Note 41). LEG Sub-national (state/provincial, county/municipal) government factors Policies, laws, regulations, initiatives, funding, etc. at a level larger or higher up than the level of analysis for the system of interest. MORT National and multinational government factors Policies, laws, regulations, initiatives, funding, etc. at the single country level (e.g., Spain) or higher (e.g., the European Union). MORT Largescale social and economic systems Geopolitical stability, epidemics/pandemics, market economics/incentives, old/new/social media influences, national/global demographic trends, cultural paradigms, etc. PAT, NBS Polycentricity of governance structures Nested multilevel, multiscale; management of urban forests within a single place is nested within larger regional, state/provincial, national, and international levels of governance and across public, private, nonprofit, and informal sectors (Note 42). NBS
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- Article
- Abstract
- Introduction
- Why Frameworks
- Existing Frameworks for Understanding Urban Forests
- A Comprehensive Framework
- Systems Boundaries: Jurisdictional, Geographical, and Temporal Considerations
- A Research Agenda and Database for Urban Forest Social-Ecological Systems
- Conclusion
- Conflicts of Interest
- Acknowledgements
- Literature Cited
- Appendix A. The Ostrom Social-Ecological Systems (SES) Framework for Studying the Commons
- Appendix B. A “Model of Urban Forest Sustainability”—the Clark et al. (1997) Framework
- Appendix C. Frameworks Related to Urban Forest Social-Ecological Systems That Have Not Been Explicitly and Systematically Incorporated into the UFSES Framework Presented in the Main Article Text
- Annex (Frameworks Excluded From the Comprehensive UFSES Framework Described in the Main Text)
- Appendix D. Notes for Table 3 Through Table 9
- Figures & Data
- Info & Metrics
- References
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