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Ordóñez Barona, C., C. Sonkkila, J. M. Baumann, C. G. Threlfall, D. F. Hochuli, R. A. Fuller, M. Davern, and S. J. Livesley. 2023. The role of diverse cultural identities in the perceived value of urban forests in Melbourne, Australia, and implications for urban ecosystem research and practice. Ecology and Society 28(4):3.ABSTRACT
Urban nature management is usually guided by the most common, frequently mentioned, or easily elicited perceptions expressed by a dominant cultural group. This is unlikely to encourage widespread community support or foster urban nature stewardship in the long run. Considering how people representing diverse cultural identities perceive the value of urban nature is key to meeting diverse community needs. In this study we explore how people not born in Australia, people who speak a language-other-than-English (LOTE), and people who self-identify as speaking a minority language, perceive the value of urban treed sites, trees at these sites, and the wildlife at these sites. We used an intercept questionnaire to collect empirical perception data, delivered in 12 different sites, including parks and streets, located in and near the Greater Melbourne Area, an ethno-culturally diverse urban area in the state of Victoria, Australia. We analyzed 1127 responses collected over 2 years using contingency- and regression-based procedures. We found that people who were not born in Australia rated the importance of treed sites and trees at these sites higher than other respondents, and LOTE respondents rated the importance of treed sites and trees at these sites lower than other respondents. Also, LOTE and some language minority respondents associated more psychological themes (i.e., stress reduction, feeling good) with treed sites than other respondents. These differences account for the influence of other cognitive, behavioral, and social-ecological context factors, such as nature relatedness, knowledge of trees, exposure to trees, demographics, and type of site (i.e., parks or streets). We discuss what these results mean for urban nature research with consideration of diverse cultural communities in cities, including integrating cultural diversity as a complement to the dominant consideration of socioeconomic patterns for understanding urban nature dynamics, accounting for conflicting values, and better communicating with and engaging these communities.
INTRODUCTION
Urban nature can help solve urban environmental problems and provide ecosystem services to urban communities (Vierikko et al. 2016, UN-HABITAT 2018). Urban nature is becoming the dominant experience of nature for many people (Oh et al. 2021), with around 70% of the global population predicted to live in urban areas by 2050 (UN-DESA 2019). Many cities are aiming to enhance and protect urban nature, and urban forests are a key aspect of this, with many cities aiming to increase the number of urban trees and enhance urban tree canopy cover (e.g., TNC 2019). The success of this agenda is not only contingent on technical knowledge about how to maintain and protect urban trees, but also on how policies and planning respond to the importance and meanings that diverse communities attach to urban nature (Wolch et al. 2014, Rishbeth et al. 2019, Kronenberg et al. 2021).
People’s perceptions are critical to understanding what urban nature means to urban communities, urban nature contributions to people, and the human drivers of urban ecosystems. Today urban ecosystems are conceived as social-ecological, meaning systems where natural and human components influence each other (Stagoll et al. 2012, Díaz et al. 2015, Vierikko et al. 2016, Groffman et al. 2017). Human drivers of urban ecosystems, which include human perceptions, can influence the composition and functioning of urban ecosystems (Grove et al. 2006, Stagoll et al. 2012, Díaz et al. 2015, Larson et al. 2016, Vierikko et al. 2016, Groffman et al. 2017, Schmitt-Harsh and Mincey 2020, Kronenberg et al. 2021). For example, human decisions about urban trees can alter urban forest ecological structure and function (Fraser and Kenney 2000, Kendal et al. 2012, Ives and Kendal 2014, Avolio et al. 2015, 2018, Schmitt-Harsh and Mincey 2020). Urban forest structures, such as tree abundance and diversity, are usually associated with socioeconomic patterns, such as income (Luck et al. 2009, Kendal et al. 2012, Schwarz et al. 2015; Gerrish and Watkins 2018, Locke et al. 2021). Moreover, because perceptions are built from people’s experiences of nature, they can help us understand how people generate cognitions about nature and how they may cognitively respond to changes in nature (Dietz et al. 1998, Schultz et al. 2004, Tadaki et al. 2017). For instance, how people attach importance to and give meaning to urban forests can influence community reactions about urban trees (Jay and Schraml 2009, Byrne 2012, Carmichael and McDonough 2019, Rishbeth et al. 2019, Kendal et al. 2022, Ordóñez et al. 2022), such as how people respond to the removal or addition of urban trees, or changes to urban-tree diversity and arrangement (Shwartz et al. 2014, Veitch et al. 2014, Carmichael and McDonough 2019).
The research on how people perceive urban nature is vast but it lacks depth regarding the role of human cultural diversity. Most of this research emanates from Europe and North-America (Kendal et al. 2020, Ordóñez et al. 2022) and is based on perception assessments from general populations and participants from a predominant European linguistic, migrant, and ethno-cultural or -racial background, in European, North-American, and Australian contexts (Byrne and Wolch 2009, Jay and Schraml 2009, Dai 2011, Byrne 2012, Kendal et al. 2012, Wolch et al. 2014, Ordóñez 2017, Rishbeth et al. 2019). People from different linguistic, migrant, and ethno-cultural or -racial backgrounds in these same contexts may perceive the importance of urban nature differently and attach different meanings to urban nature (Byrne and Wolch 2009, Jay and Schraml 2009, Dai 2011, Byrne 2012, Kendal et al. 2012, Wolch et al. 2014, Ordóñez 2017, Rishbeth et al. 2019). Many cities in European, North-American, and Australian contexts are culturally diverse (Dai 2011, Kendal et al. 2012, Rigolon 2016, Egerer et al. 2019), and some have developed or are developing policies aimed at engaging culturally diverse communities with urban nature (Byrne and Wolch 2009, Dai 2011, Wolch et al. 2014, Carmichael and McDonough 2019). However, current understandings of perceptions of urban nature usually extrapolate results from a culturally narrow set of people. This may perpetuate a culturally narrow understanding about the relationship of humans with urban nature and the worth of urban nature to humans (Ordóñez et al. 2022). In addition, it may amplify inequities in urban nature distribution. It is well documented that in cities in Europe, North America, and Australia, more ethnically diverse communities usually have fewer trees and less canopy cover (Rigolon 2016, Ferguson et al. 2018, Locke et al. 2021, Mushangwe et al. 2021). What is less understood is how these communities perceive the importance of and give meaning to urban nature, because most of this work is carried out without empirical data on people’s perceptions. Understanding this perception is a fundamental aspect of addressing diverse cultural needs and enhancing equity in urban ecosystems (Buijs 2009, Byrne 2012, Wolch et al. 2014, Egerer et al. 2019, Gwedla and Shackleton 2019, Rishbeth et al. 2019, Ordóñez et al. 2022).
Although early research has shown that the diverse cultural identities of people living in European, North-American, and Australian contexts may play a role in how diverse people give meaning to urban nature (Fraser and Kenney 2000, Buijs et al. 2009, Byrne 2012, Egerer et al. 2019, Rishbeth et al. 2019), this research also has some gaps. These gaps include focusing on a narrow set of cultural identities (e.g., immigrant / non-immigrant; European / non-European); conflating less abstract perception responses or cognitive constructs, such as preferences, with more abstract perception responses or cognitive constructs, such as value perceptions; and focusing on the perception of urban landscapes with and without natural elements in broad terms, rather than the perception of specific natural elements (Jay and Schraml 2009, Ordóñez 2017, Egerer et al. 2019, Ordóñez et al. 2022). These gaps must be filled to gain a better understanding of the role of human cultural diversity in urban ecosystems.
In this study we explore how people representing culturally diverse identities attach importance and give meaning to urban forests, with a focus on urban treed-sites, urban trees, and urban wildlife. We explored this through the concept of ecosystem values. The objectives were to identify and compare these value perceptions across people representing various cultural identities and assess the influence of these identities upon these perceptions considering other cognitive, behavioral, demographic, and social-ecological context factors that may influence these perceptions. Considering the current gaps in the literature, this study contributes to the existing literature by, (1) considering a wider range of diverse cultural identities; (2) focusing on ecosystem values, a concept that can describe how people attach importance and give meaning to ecosystems; and (3) by examining perceptions specifically associated with the social-ecological connections of urban forests, including urban sites with trees, and tree-dependent urban wildlife.
We conducted this study in selected sites in Victorian local government authorities (LGAs), in south-eastern Australia. These LGAs are culturally diverse: 35% of the population of the state of Victoria and 40% of the Greater Melbourne Area (GMA) is born overseas; 38% of people in Melbourne speak a language-other-than-English at home (ABS 2016, 2018). Also, most Victorian LGAs have initiatives to enhance urban forests, and the GMA just developed a metropolitan-wide urban forest strategy across the 32 LGAs in the GMA (TNC 2019). These characteristics allowed us to better understand how diverse cultural identities play a role in how people perceive the value of urban forests. We first provide a conceptual framework to define the interaction between urban forests, people’s perceptions, with a focus on value perceptions, and diverse cultural identities. We then describe the data collection and analysis procedures, and then present and discuss results.
CONCEPTUAL FRAMEWORK
Ecosystem values
How we conceptualize perception responses, and their associated cognitive constructs, is a fundamental aspect of perception research. Perception can be broadly defined as how people mentally process the information derived from their sensory experiences and their interactions with the environment around them (Schultz et al. 2004). People cognitively process this information in different ways, resulting in many different cognitions. In other words, there are different ways of perceiving something.
A useful way to understand how something is being perceived, as well as the diverse cognitive constructs that may be generated in the person perceiving, and the perception responses that may be studied, is through the cognitive model. This model distinguishes these constructs and responses in terms of their level of abstraction, number, ease of change, among other characteristics (Dietz et al. 1998, Schultz et al. 2004). The model includes the constructs of values (what is important to people or how people give abstract meaning to something; see Schwartz 1992, Dietz et al. 2005, Ford et al. 2012, Tadaki et al. 2017), beliefs (things people accept as true, or the consequences of doing something, or how something should be; see de Groot and Steg 2007), attitudes (people’s judgements or disposition toward things; see Dietz et al. 1998, Schultz et al. 2004, Heberlein 2012), and preferences (how much people like things; see Sommer and Summit 1995, Summit and Sommer 1999, Schroeder et al. 2006). In this model, values and beliefs are thought to be more abstract, less in number, and more resistant to change, whereas attitudes and preferences are thought to be less abstract, more in number, and easier to change, and influenced by values and beliefs. These constructs are widely used in many disciplines, including environmental and natural resource studies, environmental psychology, environmental sociology, and environmental geography, with various variations, including values-beliefs-attitudes (VBA), values-beliefs-norms (VBN), among others.
With this background, we can define ecosystem values as how people perceive the importance of, and the abstract meanings people attach to, ecosystems (Dietz et al. 1998, Satterfield 2001, Turner et al. 2003, Dietz et al. 2005, Ford et al. 2012, Kendal et al. 2015, Tadaki et al. 2017, Arias-Arévalo et al. 2018, Pedersen et al. 2019, Rawluk et al. 2019). Values can be generally understood as what people consider important (Rokeach 1973), and are abstract, positive, cognitive constructs (Schwartz 1992, Dietz et al. 2005, Tadaki et al. 2017, Rawluk et al. 2019). Based on this definition, research on ecosystem values is not just concerned with what negative or positive things people believe about nature, a notion more fitting to the concept of beliefs; or what type of nature they prefer in specific circumstances, a notion more fitting to the concept of with preferences; but rather how nature is meaningful to people (Dietz et al. 1998, Turner et al. 2003, Dietz et al. 2005, Tadaki et al. 2017). This way of conceptualizing ecosystem values has been useful to explore how people value various ecosystems, including wetlands (Pedersen et al. 2019), and forests (Bengston 1994, O'Brien 2006, Rawluk et al. 2019), among many others, and the wide range of cultural, social, ecological, environmental, economic, and psychological ideas people cognitively associate with these ecosystems. Moreover, ecosystem values research is not limited to utilitarian or anthropocentric reasons for how something is important, but rather focuses on capturing a pluralistic set of value perceptions (Dietz et al. 1998, Turner et al. 2003, Dietz et al. 2005, Kendal et al. 2015, Ordóñez 2017, Arias-Arévalo et al. 2018; Ordóñez et al. 2022).
In some cases, the concept of ecosystem values may overlap with other concepts such as ecosystem services (ES) and nature contributions to people (NCP). There are however some key differences that are worth discussing before continuing.
ES refers to ecosystem functions that have a positive effect on people (Fisher et al. 2009) and that can be quantified (Farber et al. 2002). Although there are cases where the terms ecosystem values and ES are used interchangeably (see MEA 2005, Martín-López et al. 2014, Arias-Arévalo et al. 2018), there are also differences between these concepts. For example, ES inherently implies the notion of ecosystem disservices (Fisher et al. 2009, Vaz et al. 2017), but this positive-negative dichotomy does not fit ecosystem values, since values are conceptualized as abstract and positive cognitive constructs (see Rokeach 1973, Schwartz 1992, Dietz et al. 2005, Ford et al. 2012, Tadaki et al. 2017, Rawluk et al. 2019). Furthermore, ES usually focuses on functionality and the utility of ecosystems, such as their economic and environmental value, in contrast to their psychological or cultural value (Chan et al. 2012, Ruckelshaus et al. 2015, Hegetschweiler et al. 2017). As such, these ideas are overrepresented in ES studies, a common critique that sparked the notion of cultural ecosystem services (CES; Barnaud and Antona 2014, Ruckelshaus et al. 2015, Hegetschweiler et al. 2017). In contrast, ecosystem values research usually captures a wide range of social, ecological, environmental, economic, and psychological ideas (Bengston 1994, O'Brien 2006, Ordóñez 2017, Arias-Arévalo et al. 2018, Rawluk et al. 2019, Ordóñez et al. 2022). Although there are plenty of studies that have assessed how people perceive the CES of urban forests to assess the intangible services that people may associate with urban trees, CES-based studies also have gaps in the way they address the importance and meaning people associate with urban forests.
NCP builds from the ES concept and emphasizes the role of human culture in determining how nature contributes to human quality of life (Díaz et al. 2015, 2018). However, it is still unclear how the NCP concept is operationalized in empirical social research. Ultimately, NCP is derivative from ES and still relies on a positive-negative dichotomy, which does not fit the notion of more abstract, positive cognitive constructs, as does the concept of ecosystem values.
It goes beyond the scope of this article to resolve the divergence or convergence between ES, CES, NCP, and ecosystem values. Ultimately, all these concepts can be seen as complementary, through which we can understand how nature is important to people.
Urban forests
How we define what is being perceived is also fundamental to perception research. Urban forests are commonly defined as all the trees in a city (Rowntree 1984), yet different definitions may exist in different planning and management contexts (Konijnendijk et al. 2006). In some contexts, urban forests may be defined in terms of canopy cover in a two-dimensional space (Nowak 1993). This definition is useful because canopy cover is used to calculate the provision of ecosystem services by urban forests at the scale of the whole city, such as shade and air pollution mitigation (McPherson et al. 2011). However, this definition equates urban forests to urban tree cover abundance, which misses the ecosystem complexity of urban forests.
Urban forests may be defined more broadly as the tree-dominated systems in cities, including woodlands, groups of trees, and individual trees located in urban and peri-urban areas, as well as their social and ecological connections (FAO 2016). These connections reflect the complex, multi-scaled, and interconnected characteristics of urban forests, beyond being just a percentage of leaf cover in a map, or isolated urban trees in a landscape (Steenberg et al. 2019). This broad definition recognizes the different tree-dominated or forest ecosystems that exist around the world, including the different countries, regions, and cities where such forests and trees are located, and the diversity of places that may include trees in cities, places with different tree abundance, diversity, distribution, arrangement, and social-ecological connections.
Conceptualizing urban forests broadly also responds to the diversity of treed places that people perceive day-to-day in the cities where they live, and the diversity of resulting perceptions. People’s perceptions are intrinsically and conceptually framed by what is being perceived. Specific tree-dominated places have specific ecological structures (e.g., species diversity, tree arrangement) and functions (e.g., wildlife habitat, cultural connection). How these places are represented in the research of people’s perceptions of urban nature has consequences on the types of perceptions that are elicited (Voigt and Wurster 2015, Egerer et al. 2019, Oh et al. 2021, Ordóñez et al. 2022).
The diversity of urban forest places is not well represented in the research of people’s perceptions of urban forests. For instance, many studies in this literature, particularly those focused on the perceptions of culturally diverse people, have focused on urban parks (e.g., Sasidharan et al. 2005, Buijs 2009, Seeland et al. 2009, Dai 2011, Byrne 2012, Wolch et al. 2014, Hordyk et al. 2015, Kloek et al. 2017), urban woodlands (Tyrväinen et al. 2007), street trees (Morzillo et al. 2016), private urban gardens or backyards (Fraser and Kenney 2000, Avolio et al. 2015, Pearce et al. 2015), or the entire collection of urban trees (Lohr et al. 2004) or urban biodiversity (Fischer et al. 2018). Consequently, many studies conflate urban nature landscapes with urban treed landscapes, or they do not account for the contextual heterogeneity of treed sites, such as the difference between treed parks and treed streets, or they ignore ecological aspects that are intrinsically connected to urban trees, such as wildlife (Stagoll et al. 2012, Aronson et al. 2017). All these aspects of urban forests are likely to be associated with different perception responses (Ordóñez et al. 2016, Fischer et al. 2018, Egerer et al. 2019, Oh et al. 2021).
Urban forest values
The research on people’s perceptions of urban forests is extensive, with over 200 empirical studies (Ordóñez et al. 2022). As discussed above, how perception responses and the urban natural elements or landscapes being perceived are defined, ultimately determines the research direction. Some studies focus on the most common, frequently mentioned, most strongly held, or average perception response across a population of interest. Other studies focus on the perception of urban landscapes with and without natural elements in broad terms, rather than the perception of specific natural elements or landscapes. For example, a subfield of this research has assessed people’s universal preferences in terms of whether people prefer landscapes (see Menatti and Heft 2020 for a broad discussion on landscape perception) with or without natural elements, and which types and arrangements of natural elements are preferred, including trees (Kaplan 1987, Nisbett 2007, Tyrväinen et al. 2007, Kitayama and Uskul 2011). Other studies assume that shared preferences for tree type reflect underlying cognitive processes that apply to all people (Sommer and Summit 1995, Summit and Sommer 1999). The studies on universal landscape preferences, or on preferred tree form, can support a biological predisposition to natural elements and landscapes and related psychological and physiological effects (Ulrich 1984, Hartig et al. 1991, Ryan 2005) and, more practically, advocate an integration of nature into the urban environment in broad terms (Williams and Cary 2002, Kitayama and Uskul 2011). However, additional and complimentary information about people’s perceptions of urban nature is often needed to better understand the diverse ways people perceive specific natural elements and landscapes in cities (Ordóñez et al. 2022).
Although the research on people’s perceptions of urban forests has focused on a wide range of perception responses, many of these studies do not necessarily capture urban forest values, defined here broadly as the importance of and the abstract meanings people attach to urban forests (Jay and Schraml 2009, Peckham et al. 2013, Hordyk et al. 2015, Shackleton et al. 2015). For instance, some studies have focused on people’s attitudes toward urban tree programs (Jones et al. 2013, Davis and Jones 2014), people’s preferences for different tree attributes (Sommer and Summit 1995, Summit and Summer 1999, Avolio et al. 2015), how people identify and/or rank the benefits of urban trees (Lohr et al. 2004, Schroeder et al. 2006, Morzillo et al. 2016), or whether people perceive that a predetermined list of ecosystem services are being provided by urban forests in specific contexts (Jim and Chen 2009; Baur et al. 2016, Davies et al. 2018, Wang et al. 2022, Drew-Smythe et al. 2023). In some cases, the constructs of benefits, beliefs, services, and values are used interchangeably to mean the same thing, and in many such cases, as mentioned above, perception responses related to functionality and utility are overrepresented. For example, in many studies focused on perception of benefits and services, ideas related to aesthetic (e.g., beauty of trees), environmental (e.g., trees provide shade), and economic (e.g., trees increase the value of property) benefits are the most frequent or highest ranked (e.g., Lohr et al. 2004, Jim and Chen 2009, Baur et al. 2016, Morzillo et al. 2016, Davies et al. 2018, Fischer et al. 2018, Wang et al. 2022, Drew-Smythe et al. 2023). However, other studies focused on perception of values refer to other ecological (e.g., connection to nature), cultural (e.g., city history), and psychological (e.g., feeling good) benefits that are frequently not mentioned in ecosystem services-based studies (Jay and Schraml 2009, Peckham et al. 2013, Hordyk et al. 2015, Pearce et al. 2015, Shackleton et al. 2015, Ordóñez et al. 2016).
One limitation is that many studies on perceptions of urban forests are dominated by survey questions with predetermined answers that do not allow people to express their values in their own terms. The mechanism of value elicitation is key because values must express notions of importance and relate to a person’s value system (Kendal et al. 2015, Tadaki et al. 2017, Rawluk et al. 2019), so limiting responses to predetermined options may result in less effective value elicitation (Satterfield 2001, Arias-Arévalo et al. 2018). Although surveys can be useful to quickly capture perception responses, using predetermined answers does not allow people to articulate their own thoughts, resulting in a discrepancy between how people respond to predetermined answers and how they actually think (Satterfield 2001, Hitlin and Piliavin 2004, Dietz et al. 1998, Veitch et al. 2014). This is why many survey studies may fail to capture many ecological, cultural, and psychological value perceptions, and how open-ended qualitative responses may result in richer responses (Jay and Schraml 2009, Peckham et al. 2013, Hordyk et al. 2015, Pearce et al. 2015, Ordóñez et al. 2016).
In addition, many studies on perceptions of urban forests capture perception responses without a direct experience with the diversity of urban forest places. Capturing perceptions when and where people have a direct experience of what is being perceived may allow people to express their value perceptions more concretely (Morzillo et al. 2016, Ordóñez et al. 2016, Sonti et al. 2020). Another consideration is that the diversity of urban forest places is not well represented in this research (Voigt and Wurster 2015, Oh et al. 2021), discussed above.
In addressing the current gaps in urban forest values research, we must also consider how these perception responses may be influenced by a wide range of demographic, cognitive, behavioral, and social-ecological context factors. In terms of cognitive factors, and based on the cognitive model discussed above, more concrete, less abstract, and more variable cognitive constructs, such as attitudes and preferences, can be influenced by more general, more abstract, and more stable cognitive constructs, such as values and beliefs (Schwartz 1992, Dietz et al. 1998, Schultz et al. 2004, Dietz et al. 2005, de Groot and Steg 2007, Ford et al. 2012, Heberlein 2012, Kendal et al. 2015, Tadaki et al. 2017). Consequently, some perception responses related to nature may be influenced by cognitive factors, such as people’s level of nature relatedness (Nisbet and Zelenski 2013), and people’s knowledge of nature, in the urban forest case, knowledge of trees (Davis and Jones 2014). Complementarily, perception responses may also be influenced by behavioral and social-ecological context factors that may affect people’s level of exposure to nature. Critical to understanding whether perception responses are dependent on or stable across different contexts is to understand the influence of social-ecological context factors. In urban forests, these may include urban forest composition, arrangement, and function (Williams 2002, Kirkpatrick et al. 2012, Avolio et al. 2015). These factors may include, in urban forests, proximity to, and frequency of visits to, urban trees or treed spaces (Davis and Jones 2014, Oh et al. 2021), as well as having a tree in front of the home (Schroeder et al. 2006, Jones et al. 2013). In general, many studies on people’s perceptions of urban forests do not explore the pathways that connect people’s more abstract perception responses, such as urban forest values, with these other cognitive, behavioral, and social-ecological context factors (e.g., nature relatedness, knowledge, proximity, frequency of use, tree in front of home), with some exceptions focused on attitude toward urban forest programs (Jones et al. 2013, Davis and Jones 2014).
Diverse cultural identities
Studies on people’s perception of urban nature have many choices regarding how they address the diversity of human populations. These choices may include assessing perception responses across general populations, assessing the uniqueness of perception responses of one group, or assessing the differences of perception responses between groups. For instance, some studies extrapolate findings from demographically validated social samples to make inferences about how general populations perceive urban nature (Sommer and Summit 1995, Summit and Summer 1999, Lohr et al. 2004, Kirkpatrick et al. 2012, Jones et al. 2013, Davis and Jones 2014, Avolio et al. 2015, Morzillo et al. 2016, Fischer et al. 2018). Other studies explore the range of perception responses held within a defined population of interest (Jay and Schraml 2009, Byrne 2012, Kendal et al. 2012, Hordyk et al. 2015). Yet others may show how groups of people, such as those sharing age, gender, level of income, and ethnic and cultural background, may share perceptions (Lohr et al. 2004, Buijs et al. 2009, Schroeder et al. 2006, Kendal et al. 2012, Jones et al. 2013, Ordóñez 2017).
Acknowledging that diverse culture identities exist within and across human populations is key to understanding human-nature relationships. By identity we mean broadly the characteristics, physical and cognitive, that make a person who they are. Identities can be understood through demographics, such as how those who have a more positive attitude toward urban trees tend to be women, younger, high-income, homeowners, and affiliated with environmental organizations (Lohr et al. 2004, Schroeder et al. 2006, Jones et al. 2013, Avolio et al. 2015, Morzillo et al. 2016, Gwedla and Shackleton 2019). These attitudes may in turn be reflected in how tree abundance and diversity are usually associated with socioeconomic patterns, such as income (Grove et al. 2006, Luck et al. 2009, Kendal et al. 2012, Avolio et al. 2015, Schwarz et al. 2015, Avolio et al. 2018, Gerrish and Watkins 2018, Locke et al. 2021). However, level of income is not the only identity that defines people. Identities can also be understood through ethnic (i.e., shared social, racial, and cultural characteristics of a population; Amin 2002), racial (i.e., socially constructed categorizations based on alleged physiognomic differences; Crenshaw et al. 1995), and cultural (i.e., shared system of symbols, such as language, values, and norms of a group of people; Taylor 1994, Kitayama and Uskul 2011) differences. Examples of this is how non-Whites in U.S. cities (e.g., Lohr et al. 2004, Byrne 2012) and non-European immigrants in European cities (e.g., Buijs et al. 2009, Jay and Schraml 2009, Kloek et al. 2017) perceive urban nature in different ways to non-Whites and European non-immigrants, respectively, and how more ethnically diverse communities usually have fewer trees and less canopy cover (Rigolon 2016, Ferguson et al. 2018, Locke et al. 2021, Mushangwe et al. 2021).
A cultural diversity research approach can be useful to explore diverse cultural needs by the community in multicultural urban contexts (Dai 2011, Rigolon 2016, Egerer et al. 2019). Not all countries or cities identify themselves as multicultural. Also, different countries have different cultural narratives and recognize cultural diversity in different ways. However, countries like Canada and Australia identify multiculturalism as a key principle for understanding the diversity of populations within the country through multicultural policies (ABS 2016, Statistics Canada 2021). Consequently, in these countries, the notion of culture—conceived in this context as a defining feature of a person’s individual or collective identity—is not a given, not homogenous, and not a monolith (Taylor 1994, Qadeer 2016). In these contexts, extrapolating results on people’s perceptions of urban nature from a culturally narrow set of participants, such as participants with a predominant European linguistic, migrant, and ethno-cultural or -racial background as defined by European, North-American, and Australian contexts (Byrne and Wolch 2009, Jay and Schraml 2009, Dai 2011, Byrne 2012, Wolch et al. 2014, Ordóñez 2017, Carmichael and McDonough 2019, Rishbeth et al. 2019, Ordóñez et al. 2022), may perpetuate a culturally narrow understanding about the relationship of humans with urban nature.
Key to studying the intersection of cultural diversity and urban forest values are context and the mechanisms of cultural identity classification and values elicitation. Context defines how we differentiate culturally diverse identities, such as how we differentiate between Western and Eastern cultures in a global Western context (Nisbett 2007); how we differentiate between immigrants and non-immigrants (e.g., those from non-European countries in European countries; see Buijs et al. 2009, Jay and Schraml 2009, Kloek et al. 2017); between those who speak English and those who speak a language-other-than-English (LOTE) or English-as-second-language in Australian (ABS 2016, Mushangwe et al. 2021) and Canadian contexts (Statistics Canada 2021), respectively; and between Latinos and non-Latinos in a U.S. context (Byrne 2012). A research approach focused on cultural identity is one that allows people to self-identify as being culturally diverse (Hopkins 2019), in contrast to a research approach that indirectly characterizes communities based on existing demographic data (Rigolon 2016, Ferguson et al. 2018, Locke et al. 2021, Mushangwe et al. 2021). Also, these identities are intersectional (Hopkins 2019), meaning for example that people do not perceive urban nature through a single identity (e.g., as an immigrant) but rather through a multiplicity of identities (e.g., as an immigrant and a linguistic minority). As such, research on cultural diversity should allow people to identify with as many cultural identities as possible and to assess how these interact, instead of focusing on one identity, which may result in homogenizing classifications of diversity (Crenshaw et al. 1995, Jay and Schraml 2009, Dai 2011, Byrne 2012). Finally, allowing people to express their values in their terms via open-ended questions, and studying perception responses in-situ may result in better urban forest values elicitation. Although there are some examples of in-situ studies in urban forest perception research (e.g., Peckham et al. 2013, Morzillo et al. 2016, Ordóñez et al. 2016, Oh et al. 2021), these do not focus on comparing results across people representing diverse cultural identities.
Because this study was conducted in Australia, we defined diverse cultural identities through the classifications of Australian born, LOTE, and language minority (ABS1999, 2016). These classifications are useful given that one of the drivers of cultural diversity in Australia is immigration (Akbari and MacDonald 2018). These classifications correlate strongly with socioeconomic indicators, including levels of income and education (ABS 1999, Mushangwe et al. 2021). Existing international research on how cultural identities play a role in people’s perceptions of urban nature cannot be extrapolated to the Australian context. Many studies in the U.S. focus on race as the key defining factor of population diversity, such as the differences between Latino, Asian, Black, and White (Lohr et al. 2004, Dai 2011, Byrne 2012, Jones et al. 2013, Carmichael and McDonough 2019, Locke et al. 2021). European studies focus on region of origin and immigration status, such as studies focused on immigrants from non-European countries (Jay and Schraml 2009, Buijs et al. 2009, Seeland et al. 2009, Spartz and Shaw 2011, Main 2013, Neal et al. 2015, Peters et al. 2016, Kloek et al. 2017, Fischer et al. 2018, Rishbeth et al. 2019). These represent a narrow set of diverse cultural identities and do not reflect the diverse cultural identity classifications in Australia. For instance, country of birth does not always overlap with language minorities, but language minorities, despite their immigration status, may still identify as culturally diverse (Amin 2002; Ordóñez 2017, Egerer et al. 2019).
METHODS
Ethical approval for this research study was granted by the Human Research Ethics Committee of The University of Melbourne (Ethics ID Number: 1750822.1). Informed consent was obtained from all participants by describing the study verbally during intercept questionnaires and by handing out a consent format and plain language statement of the research to all participants.
Research design
This study was based on a mixed-method concurrent design approach that combined qualitative and quantitative research procedures (Creswell 2018). By qualitative we mean exploratory, descriptive, and explanatory research procedures that recognize the constructive/subjective nature of knowledge and that use data collection and analysis techniques that rely heavily on the direct view of participants (Hay and Cope 2021). By quantitative we mean confirmatory and explanatory research procedures that consider the positivistic/objective nature of knowledge and that use data collection and analysis techniques that rely heavily on data variables (Agresti 2013, Rosner 2015).
The foundation of the qualitative research approach was the tradition of grounded theory, which seeks to explain social phenomena, discover concepts, and generate theory, through the interpretative analysis of textual data (Glaser and Strauss 1967). Grounded theory involves the use of inductive, thematic coding techniques to extract themes and subthemes across the database, densify data into a manageable set of ideas, and structure these ideas according to their hierarchical relationships and level of abstraction (Corbin and Strauss 2015). In many cases, these thematic coding techniques are applied through a positivistic lens, meaning with the aim of densifying, reducing, structuring, and quantifying codes (Braun and Clarke 2006, Terry et al. 2017). However, we recognize that grounded theory can also be based upon other, more constructivist approaches, and through many different conceptual and theoretical frameworks and traditions (Smith and McGannon 2018, Hay and Cope 2021). Coherent with qualitative research methods, grounded theory studies are not interested in generalizing across populations, but rather in exploring issues in depth using a smaller number of participants (Corbin and Strauss 2015), or in scaling up the analysis to make comparisons with other case studies, as this is methodologically incongruous (Hay and Cope 2021). The objectives of grounded theory studies is to construct, enrich, and complement existing explanations on how people perceive or experience a social phenomenon, using research procedures that allow people to express themselves in their own terms, to say what they really think, not basing their responses on predetermined answers in a survey, which are usually restricted to the biases of the researcher (Smith and McGannon 2018).
In this study we used positivistic and reductionist thematic coding procedures to help fill the gaps in the literature, as identified in the Introduction: (1) considering a wider range of diverse cultural identities; (2) focusing on values to describe how people attach importance and give meaning to urban forests; and (3) examining perception responses specifically associated with urban sites with trees, urban trees, and urban wildlife at these sites. In some qualitative studies, the number of participants is small, so the range of culturally diverse identities is narrow, and the results are presented in narrative form, making it difficult to compare responses across groups. Although some quantitative studies overcome the small sample size, with added statistical analyses, in most cases the responses from participants are based on predetermined answers, and the range of culturally diverse identities may also be narrow. So, by using a mixed qualitative-quantitative approach we can fill these gaps and meet the objectives of the research, chiefly identifying and comparing perception responses across people representing various cultural identities and assessing the influence of these identities upon these perceptions considering other cognitive, behavioral, socio-demographic, and social-ecological context factors.
Despite the different ways of dealing with data, mixed qualitative-quantitative studies can enhance results (Creswell 2018). In practical terms, this mixed approach in this research meant that empirical data were treated both qualitatively, via interpretation, densification, reduction, structuring, and quantification of data, and quantitatively, by relating quantified variables. In other words, we generated data on perception responses through interpretation by applying coding techniques, and then analyzed these data using quantitative analytical approaches as described in the Data Analysis section. To relate quantified variables, we used our conceptual framework to develop and test a theorized model of the associations between cognitive, behavioral, socio-demographic, and social-ecological context factors with value perceptions (Fig. 1).
We used an intercept questionnaire to collect empirical data on people’s perceptions at the time the experience of urban nature occurred (i.e., on site or in situ). The design and delivery of the questionnaire builds from previous studies, including Veitch et al. (2014), Ordóñez et al. (2016), and Sonti et al. (2020), based on a non-selective, convenience recruitment strategy (Dillman et al. 2014). Through this survey, we also collected data on people’s diverse cultural identities.
Diverse cultural identity classifications were grounded in the Australian context, including Australian born, LOTE, and language minorities. We recognize that there were other classifications we did not consider, such as ethnicity, race, country of origin, year of arrival to Australia, among others (ABS 2016). These data are difficult to capture directly from people through intercept questionnaires.
To better account for social-ecological context factors, we also collected data from selected local government authorities (LGAs) in and around Greater Melbourne Area (GMA) in Victoria, Australia, including a central business district, inner suburbs, and one regional city. We chose treed parks and treed streets within the boundaries of these LGAs. To account for treed-site heterogeneity, sites were grouped per LGA, and each group was similar in terms of size and tree composition to reduce combined variability in type of site and LGA (more details in Appendix 1; Fig. 2).
Coherent with our mixed methods design, we analyzed the data on perception responses and diverse cultural identities using a mix of qualitative and quantitative techniques. This analysis was guided by our research objectives: (1) identify value perceptions; (2) compare these value perceptions across people representing various cultural identities; and (3) assess the influence of these identities upon these perceptions considering other cognitive, behavioral, demographic, and social-ecological context factors that may influence these perceptions. To identify value perceptions, we qualitatively analyzed open-ended responses on value perceptions provided through the survey. To compare these value perceptions across cultural identities, we quantified these value perceptions and compared these quantities across simplified cultural identity classifications using contingency analysis. To assess the influence of cultural diversity upon these perceptions, while accounting for other factors, we undertook a structural equation model analysis to test the associations theorized in Figure 1. Later, we undertook a generalized linear model analysis to explore the associations between value perceptions and diverse cultural identities, while accounting for other factors of influence.
Study areas
We conducted this study in four Victorian LGAs: Melbourne, Yarra, Moreland (today called Merri-bek), and Ballarat. Victoria has a population of 6.4 million people (ABS 2018) and a heterogeneous temperate climate ranging from a dry and hot northwest to a cool and wet southeast. The state comprises 79 LGAs, 32 of which are in the GMA. The capital of the state of Victoria is the City of Melbourne, which is located at the center of the GMA. The City of Yarra and the City of Moreland are also located in the GMA and considered to be inner LGAs. Around the GMA we find the regional LGAs of Ballarat, Bendigo, and Geelong, the largest non-GMA and regional LGAs in the state. Many Victorian LGAs are culturally diverse, with cultural diversity in Australia being classified by Australian born, LOTE (excluding aboriginal Australian languages), and language spoken (ABS 1999, 2016). About 35% of residents in Victoria were not born in Australia (ABS 2016), higher than the 33% for the whole of Australia. The City of Melbourne is more diverse, with 46% having both parents born overseas (ABS 2018).
The LGAs used in this study have set planning agendas for urban forests (TNC 2019). Some of the strategic policy and planning priorities for these cities include retaining and planting trees in areas facing intensified urban development, increasing urban tree species diversity, reducing the uneven distribution of tree canopy, and mitigating the impacts of climate change on urban trees (City of Melbourne 2012, City of Moreland 2017, City of Yarra 2017, City of Ballarat 2019).
We chose 12 sites, four parks and eight streets. Eight of these sites, four parks and four streets, were located in Melbourne and Ballarat and were dominated by exotic English Elms, an exotic tree species that represents about 10% of all urban trees in the City of Melbourne and the City of Ballarat (City of Melbourne 2012, City of Ballarat 2019). The sites in Moreland, four streets, were dominated by native eucalypt tree species, which represent 69% of all street trees in Moreland (City of Moreland 2017; Fig. 2; details in Appendix 1).
Questionnaire content
The questionnaire included five sections designed to collect information on (1) value perceptions of urban forests; (2) knowledge of trees; (3) exposure to sites and their trees; (4) nature relatedness; and (5) demographics. We used existing and validated questions and scales wherever possible (details in Appendix 3). All questions and associated perception responses are captured at the individual response level.
Section 1 included a simple values-based question about the level of importance people assigned to treed sites, trees at these sites, and wildlife at these sites, measured in a 5-point scale of importance adapted by Ordóñez et al. (2016) from Schroeder et al. (2006). After each rating, we asked people to tell us why they considered these aspects of urban forests important, answered in an open-ended manner and then we pre-coded up to three responses based on people’s own words, following procedures by Ordóñez et al. (2016) and Egerer et al. (2019). We obtained two types of value perceptions data: the importance ratings; and up to three value perception responses.
Section 2 included the knowledge of trees scales developed and validated by Davis and Jones (2014). The scales include a scale of knowledge of trees measured in a 5-point level of knowledge, and a knowledge of tree species scale measured in a 3-point level of knowledge (i.e., 1 = unknown, 2 = only type of tree, 3 = tree species).
Section 3 included questions and measures based on Veitch et al. (2014), chiefly living distance from site measured in a 3-point distance scale (i.e., 1 = very close, defined as < 2km; 2 = near, defined as within 2 to 10 km; 3 = far, defined as > 10km), and visitation frequency measured in a 3-point frequency scale (i.e., 1 = low, defined as never to once or twice per year; 2 = middle, defined as weekly to once per month; 3 = high, defined as daily to more than once a week). We also used the simple yes/no questions used by Davis and Jones (2014), including whether people had planted a tree in the last 5 years, whether they had visited trees or forests in the last 10 years, and whether they had a tree in front of their home.
Section 4 included the Nature Relatedness Scale (NR6) by Nisbet and Zelenski (2013). NR6 measures subjective connectedness with the natural environment and is reasonably consistent across sociodemographic identities (α = 0.84; M = 3.7, SD = 0.8).
Finally, Section 5 included demographic and cultural identity measures listed in Table 1. Data on language spoken were classified by world regions using procedures by Egerer et al. (2019; Table 2; details in Appendix 4). Although collecting data on generations since immigration and cultural assimilation can be useful, we did not collect these data because of limitations of in-situ, intercept questionnaires.
Questionnaire delivery and recruitment
The questionnaire was designed to take under 10 minutes to answer and was delivered in English. The questionnaire was the same at all sites and kept unaltered throughout the duration of the study. Questionnaire delivery was based on the systematic intercept protocol previously developed by McKenzie et al. (2006), McDonald and Price (2009), and Veitch et al. (2014). This protocol accounts for temporal factors that may influence the use of urban parks and streets. We delivered the questionnaire at time intervals in the morning (08:00–10:00), midday (11:30–13:30), and afternoon (16:00–18:00), avoiding Mondays, Fridays, and Sundays because of limited or different use patterns of urban parks and streets on these days (Veitch et al. 2014) and the fact that national holidays and business closures are frequently on those days (McDonald and Price 2009). Questionnaires were delivered between January 2018 and March 2020, at different intervals including both summer and winter periods. The data collection took 2 years to complete because this allowed us to account for multiple summer and winter periods, and it took that long to complete data collection for all sites given the available resources. An electronic version of the questionnaire in GoogleForms® was used to fill the responses via Smartphone or tablet. All intercepts were recorded to estimate response rates. Two researchers were always present during questionnaire delivery (details in Appendix 2).
Data preparation and validation
Data were collected from a total of 1127 respondents, with the sample profile shown in Table 1. The data were imported into Excel, cleaned and quality checked.
We treated the open-ended perception responses in Section 1 in a qualitative manner. This meant we analyzed the original verbatim responses using interpretative, inductive coding procedures with the goal of converting these responses into a more manageable set of codes. We did this by using the techniques of densification, axial and selective coding, and constant comparative analysis based on a grounded theory approach (Corbin and Strauss 2015). Densification implies reducing qualitative data to a more manageable size by reducing codes into common themes (Creswell 2018). Axial and selective coding implies generating and reducing codes around a central theme until coding saturation is reached. Constant comparative analysis means that the coding process considers the whole collection of data, with codes being generated through constant comparison and contrast with existing codes (Corbin and Strauss 2015). These procedures were preferred in contrast to a pre-determined coding template, which would have forced codes upon intended or assumed meaning (Ordóñez et al. 2016, Egerer et al. 2019).
The analysis was carried out at two levels of abstraction. We first assigned a code (code) to the original data (verbatim responses), and then we assigned a code grouping (theme cluster) to these codes. We ended up with six theme clusters: aesthetics, environmental, socio-cultural, psychological, health, and naturalness and biodiversity (Table 3). These themes are consistent with the classifications in values-based studies (e.g., Bengston 1994, O'Brien 2006, Kendal et al. 2015, Ordóñez et al. 2016, Rawluk et al. 2019). We did not find any responses related to economic themes (e.g., trees increase the value of property) in contrast to Ordóñez et al. (2016), so we did not code for this theme. Although we coded for an “other” theme cluster for codes that did not fit the above themes, this theme cluster represented less than 5% of the data, so we discarded it for further analysis. The six theme clusters were associated with each of the three aspects of urban forests (i.e., treed sites, urban trees, and urban wildlife), or 18 variables in total. These data were converted into two numeric measures: (1) a frequency of mention measure representing the presence/absence of a theme in any of the three possible responses, expressed as a 1/0 binomial variable (e.g., a value of 1.0 meant the theme was mentioned at least once); and (2) a density measure representing the coverage of a theme over the three responses obtained, expressed in a 0-1 scale (e.g., a value of 0.3 meant the theme was only mentioned once). Because no responses were rare (between 1.9% and 8.8% of the pre-coded data depending on the urban forest aspect), its effect on relative theme representation across the dataset was considered minimal. The coding procedure is fully illustrated in Table 3 (details in Appendix 5).
To facilitate quantitative analysis of categorical variables (Agresti 2013) we converted variables based on yes/no questions into single numeric binomial 1/0 measures (e.g., Australian born, where 1 = yes, and 0 = no). Some ranking and categorical measures were collapsed to facilitate analysis, including: knowledge of tree species (species = 1, other = 0); living distance (very close = 1, other = 0); frequency of visitation (high = 1, other = 0); gender (female = 1, other = 0); education (university degree = 1, no degree = 0); occupation student (student = 1, not student = 0; accounted for significant representation of students in Melbourne urban parks), and language (classified by world regions into six groupings, each treated as a binary 1/0 variable; see Table 2; details in Appendix 4). The age information based on decade born was converted into the median of decade born based on the year of response collection (i.e., born in 80s, year of collection 2019, median age = 35). These data manipulations were done to simplify the dataset and avoid overprediction of regression models by an overpopulation of categorial variables (Agresti 2013). All other numeric scales were averaged into a simple numeric index (details in Appendix 6).
Data analysis
The analysis focused on fulfilling the two goals of the study, chiefly, (1) identifying the value perceptions held by people representing diverse cultural identities and assessing how these perceptions differed; and (2) assessing the role of diverse cultural identities on value perception responses in the context of other cognitive, behavioral, socio-demographic, and social-ecological context factors that associate with these perception responses. The analysis focused on the variables of born in Australia (ausborn), LOTE, and language spoken if LOTE. Statistical analyses were performed in R v. 4.1 (R Core Team 2021).
To fulfill the first goal (i.e., how value perceptions differed), we undertook a contingency analysis, also known as analysis of proportions, to analyze the differences of frequency of mention (i.e., as % of total mentions) of the value perceptions (i.e., as theme clusters) across diverse cultural identity classifications, as ausborn, LOTE, and language groupings. We used the “table” function in R to build contingency tables. The significance of the difference was calculated using the Pearson χ2 statistic at a significance level of 95% (p-value < 0.05).
To fulfill the second goal (i.e., the role of cultural identity on value perceptions by considering other factors), we did two things. First, we undertook a regression-based structural equation model (SEM) analysis, which allowed us to test the theoretical associated in Figure 1, building on procedures developed by Davis and Jones (2014). For value perceptions we used the level importance people assigned to treed sites, trees at these sites, and wildlife at these sites. We used the “sem” function in the “lavaan” v 0.6 R package. We added the variable of type of site (i.e., parks or streets) to the model to account for the different landscape types. We used the indexes of comparative fit (CFI), Tucker-Lewis (TLI), root mean square error of approximation (RMSEA), and standardized root mean square residual (SRMR) to assess model-data fit (Kline 2011; details in Appendix 7).
Second, we undertook a generalized linear model (GLM) analysis to understand the strength of association between a response variable (i.e., value perceptions) and a determinant variable (i.e., diverse cultural identities), while accounting for other factors of influence (Rosner 2015), as a complement to the relationships assessed in the previous SEM analysis. To be clear, this analysis was guided by our research questions, with a focus on the influence of cultural diversity upon value perceptions. Accounting for the other cognitive, behavioral, socio-demographic, and social-ecological context factors that may influence these perceptions was important for this analysis, but we only accounted for these factors so we could focus on the relationship between cultural diversity and value perceptions. GLM analysis was applied to the level importance people assigned to treed sites, trees at these sites, and wildlife at these sites, and the measures of reasons of importance, including both the frequency of mention and the density of a theme. We used the “glm” function in R with “logistic” and “beta” family distributions, given the binomial and ranking nature of the frequency of mention and density variables, respectively. Separate models were used to predict each variable. We included the factors of nature relatedness, knowledge of trees, exposure to trees, socio-demographic, type of site, and diverse cultural identities. Cities, sites, and type of site were added as random variables in the models to account for heterogeneity in context. Model and data fit were assessed using diagnostic plots of residual distributions, which help confirm the independence of residuals. The Durbin-Watson statistic was also used to test residual autocorrelation, with values approximating 2.0 showing no residual autocorrelation. The variance inflation factors (VIF) were also checked to address covariance effects (Rosner 2015).
RESULTS
A total of 1127 responses were captured, with 107 responses from Ballarat (9.5% of total), 665 from Melbourne (59.0%), 225 from Moreland (19.9%), and 130 from Yarra (11.5%), including 332 responses from street intercept surveys (29.5%) and 795 from park intercept surveys (70.5%). The same time and personnel effort were applied to obtain survey responses for all sites. Consequently, the variable number of survey responses by site were related to the availability of respondents on site. Some of the socio-demographic characteristics of the respondents were similar to that of the GMA, and/or Australia, while others were atypical, such as level of education (Table 1).
The contingency analysis allowed us to identify which value perceptions were held by the diverse cultural identities considered, and assess the extent to which these perceptions differed. We observed that, in general, the perceptions about treed sites were dominated by aesthetic and socio-cultural themes, while the perceptions about trees at these sites were dominated by aesthetic and environmental themes, and the perceptions about wildlife at these sites were dominated by naturalness/biodiversity and aesthetic themes (Fig. 3). Value perceptions related to psychological themes (e.g., “feel good,” “less stress,” “relaxed,” “calm,” “peaceful”; see Table 3; details in Appendix 6) differed. Respondents not born in Australia and LOTE respondents associated psychological value perceptions with treed sites more frequently than Australian born and non-LOTE respondents (Fig. 3). Also, LOTE respondents associated environmental value perceptions with trees at the sites more frequently than non-LOTE respondents. Although LOTE respondents associated aesthetic and environmental value perceptions with wildlife at the sites less frequently than non-LOTE respondents, there were no statistically significant differences in the proportions of the most dominant theme, naturalness and biodiversity (Fig. 3).
The SEM analysis allowed us to test the theorized associations between value perceptions and cognitive, behavioral, socio-demographic, cultural diversity, and social-ecological context factors (Fig. 1). The results showed how nature relatedness and exposure to trees were statistically significant influences on the level of importance people ascribe to treed sites, and trees and wildlife at the sites. These influences were mediated by knowledge of trees. Socio-demographics were directly associated with the level of importance, but not cultural diversity (Fig. 4). Cultural diversity was only associated with knowledge of trees. The model had a moderate fit to the data (i.e., CFI and TLI < 0.95; but RMSEA < 0.06 and SRMR < 0.08; details in Appendix 7).
The GLM analysis allowed us to assess the strength of associations between diverse cultural identities and value perceptions, while accounting for the role of other cognitive, behavioral, socio-demographic, and social-ecological context factors. Australian born respondents considered treed sites and trees at these sites as being less important than respondents not born in Australia. LOTE respondents considered treed sites and trees at these sites less important than non-LOTE respondents. LOTE respondents who also spoke a European language considered treed sites and trees at these sites as being more important (Table 4). Although there were no statistically significant associations with the frequency of mention of value perceptions, there were some statistically significant associations with the GLM results replicating the same patterns observed in the contingency analysis, such as how LOTE respondents associated psychological and environmental value perceptions more frequently than non-LOTE respondents. Specifically, LOTE respondents who spoke an East Asian language mentioned psychological themes at a higher density (i.e., psychological themes were more dominant in their responses) for treed sites, and LOTE respondents who spoke a South Asian language mentioned naturalness and biodiversity themes at a lower density, and environmental themes for trees at the sites at higher density (Table 5).
DISCUSSION
Our findings both confirm and help dispel premature conclusions presented in the literature. First, our study showed how diverse cultural identities do not always overlap in terms of how people representing diverse cultural identities perceive the value of urban forests. We found that non-Australian born respondents rated the importance of treed sites and trees at these sites higher than other respondents. A possible explanation comes from previous studies, where participants representing diverse cultural identities have considered urban trees as symbols that imbue urban spaces with meaning, serving as conduits for attachment to place and place making, a key issue for immigrant communities (Jay and Schraml 2009, Spartz and Shaw 2011, Main 2013, Hordyk et al. 2015, Neal et al. 2015, Pearce et al. 2015). We also found that LOTE respondents rated the importance of treed sites and trees at these sites at a lower level than other respondents. Based on previous studies, immigrant, non-European, and cultural minority communities in European and U.S. contexts have expressed a feeling of disconnection from the characteristics and arrangement of treed sites and trees at these sites (Jay and Shraml 2009, Byrne 2012, Shackleton et al. 2015, Peters et al. 2016, Egerer et al. 2019, Rishbeth 2019). Our findings in an Australian context may corroborate some of these findings in other contexts. Either way, our overall findings illustrate that the classifications of immigrant/non-immigrant and language minority do not always overlap. Culturally diverse communities are not homogenous, so there are sometimes nuanced and conflicting ways that these communities express their perceived value of urban nature.
We were able to validate previous findings about how factors such as level of nature relatedness (Nisbet and Zelenski 2013), knowledge of trees, social-ecological context factors, with a focus on exposure to trees (Schroeder et al. 2006, Jones et al. 2013, Davis and Jones 2014), and socio-demographics (e.g., gender, age, education; Sommer and Summit 1995, Lohr et al. 2004, Schroeder et al. 2006, Kendal et al. 2012, Jones et al. 2013, Avolio et al. 2015, Shackleton et al. 2015, Morzillo et al. 2016, Gwedla and Shackleton 2019) influence people’s perceptions of urban forests, defined here as the rating of importance of various urban forest aspects, including treed sites, trees at sites, and wildlife at sites. However, we also found that diverse cultural identities did not directly influence these perceptions when all these other factors were considered.
We also found differences in the reasons of importance across diverse cultural identities. These differences did not replicate across all identities we considered (i.e., Australian born, LOTE, and language minorities). So, we discuss only the differences that did replicate. First, these differences were small and were expressed as the dominance of a theme rather than by the presence or absence of a theme. We found that non-Australian born, LOTE respondents who spoke East Asian languages mentioned psychological themes (i.e., “less stress,” “feel good”) more frequently than other respondents when speaking about the perceived value of treed sites. In previous studies, people have conveyed the meaning they attach to urban nature through their emotional states, thus linking perceptions with urban nature exposure and mental health responses (Jay and Schraml 2009, Main 2013, Hordyk et al. 2015). These differences may also be explained through Eastern and Western ways of perceiving the natural landscape, such as holistic vs. fragmented perceptions, and their influence on emotional responses to these landscapes (Nisbett 2007, Kitayama and Uskul 2011).
Second, these differences can also be explained by the context and mechanism of elicitation. In terms of urban forest context, we can differentiate what is being perceived in terms of the whole ecosystem (“all trees”) or concrete elements of this ecosystem (“that tree”). Our research was focused on the importance and abstract meanings people attach to concrete natural elements and landscapes, instead of the whole ecosystem in an abstract sense (see Lohr et al. 2004, Jim and Chen 2009, Baur et al. 2016, Morzillo et al. 2016, Davies et al. 2018, Fischer et al. 2018, Wang et al. 2022, Drew-Smythe et al. 2023). Nonetheless, we accounted for various urban nature contexts with trees, such as treed parks and streets in different urban settings, to represent the diversity of urban forest spaces. This diversity of urban forest spaces is not well represented in the literature, with most previous research focused solely on urban parks (Sasidharan et al. 2005, Buijs 2009, Seeland et al. 2009, Dai 2011, Byrne 2012, Wolch et al. 2014, Hordyk et al. 2015, Kloek et al. 2017), urban woodlands (Tyrväinen et al. 2007), street trees (Morzillo et al. 2016), or private urban gardens or backyards (Fraser and Kenney 2000, Kendal et al. 2012, Pearce et al. 2015, Avolio et al. 2015, Larson et al. 2016). Consequently, many studies do not account for the contextual heterogeneity of treed spaces. Although our study is limited in that it focuses on more concrete natural elements of the ecosystem (“that tree”), rather than the whole ecosystem (“all trees”), by collecting data from various urban nature contexts, we have better controlled for the influences of context and mechanisms of value elicitation.
In terms of the mechanism of elicitation, we can differentiate how something is being perceived by the perception response and associated cognitive construct being captured. Most research on the role of culture in people’s perceptions of urban nature has focused either on general preferences of urban landscapes with and without natural elements (Kaplan 1987, Hartig et al. 1991, Williams and Cary 2002, Ryan 2005, Tyrväinen et al. 2007, Kitayama and Uskul 2011), on the uses of urban parks (e.g., Sasidharan et al. 2005, Byrne and Wolch 2009, Seeland et al. 2009, Byrne 2012, Fischer et al. 2018), or on the benefits of urban nature, such as urban trees (e.g., Pearce et al. 2015, Morzillo et al. 2016, Gwedla and Shackleton 2019). In the case of landscape preferences, this research usually results in insights on how nature can be integrated into the urban landscapes in very general terms. In the case of uses of urban parks, this research usually results in a dominance of socio-cultural themes that describe why these natural landscapes are important to people (i.e., “recreation,” “social interaction”). And in the case of the benefits of urban nature, including urban trees, this research usually results in the dominance of socio-cultural themes. In contrast, our study focused on level of importance and abstract meanings rather than on general landscape preferences, practical uses, or perception of benefits. This suggests we may have better controlled for the mechanism of value elicitation by asking questions specifically targeting more abstract perception response and associated cognitive constructs.
A key finding was that the importance people assigned to wildlife at the site, and how frequently people mention naturalness and biodiversity as a reason of importance of this wildlife, did not differ across diverse cultural identities. This suggests that this value perception may be more widely shared than those for treed sites and trees at these sites. However, there is no guidance in the literature as to why this is. Previous forest and urban forest values studies (e.g., Bengston 1994, O'Brien 2006, Kendal et al. 2015, Ordóñez et al. 2016) have not considered wildlife. Studies focused on urban biodiversity perceptions (e.g., Fischer et al. 2018, Oh et al. 2021) may conflate what is being perceived, including trees, vegetation, or wildlife. The only guidance emanates from landscape preference studies, which have shown how people in general prefer more functional landscapes as opposed to more natural or conservation focused landscapes (e.g., Tyrväinen et al. 2007), with some studies showing that this is also the case for those representing culturally diverse communities in European and North-American contexts (i.e., non-European; see Fraser and Kenney 2000, Buijs 2009, Buijs et al. 2009, Kloek et al. 2017). However, these studies are not comparable given that they measure different perception responses, specifically, preferences for landscape types. However, the discrepancy in the observations may suggest that, while culturally diverse communities can value urban wildlife for naturalness and biodiversity reasons as well as other communities, this value perception may be expressed differently as a preference for landscape types.
Implications for research
Studies interested in accounting for the role of cultural diversity in urban nature perception must do so in a way that is meaningful to the context and scale of the study. Capturing data on first language spoken may broaden how this is considered beyond narrow and homogenizing categories (e.g., immigrant / non-immigrant; European / non-European; Buijs et al. 2009, Byrne 2012, Rishbeth et al. 2019). However, there is a limitation in this technique. First, using language to classify cultural diversity leads to grouping people that may differ in their perceptions. Second, this measure poorly accounts for European language adoption following colonization of major world regions, particularly Latin America, but also other regions. Third, the measure focuses on broad global differences, disregarding aboriginal and indigenous languages and peoples. Nevertheless, language classifications can help overcome the limitations of previous simplistic classifications and help analyze data beyond simplistic cultural stereotypes. Although obtaining information about country of origin or ethnicity may be ideal, these categorizations may not necessarily result in higher accuracy, given that these measures may also need to be collapsed for meaningful analysis (see Lohr et al. 2004, Buijs et al. 2009, Dai 2011, Jones et al. 2013, Kloek et al. 2017). Ultimately, language correlates with ethnicity (Cavalli-Sforza 1997) and it is an unifying symbol across a population’s cultural identity (Taylor 1994, Amin 2002) that can endure across generations in immigrant communities regardless of cultural adaptation (Jay and Schraml 2009, Kloek et al. 2017). Future studies should continue to test multiple ways of capturing cultural diversity, ways that we did not address here, including religion, immigrant pathways, level of cultural assimilation or adaptation (e.g., level of language proficiency in the host country), and landscape of origin, among others.
More broadly, studies on urban nature systems should strive to develop a deeper consideration of the role of cultural diversity as a human driver in these systems. Cultural diversity is important because it goes beyond simplistic socioeconomic explanations that dominate urban nature research. This research defaults to socioeconomic factors to explain observed urban nature patterns and processes (Groffman et al. 2017, Schmitt-Harsh and Mincey 2020, Locke et al. 2021), given that social structure is often characterized only by income and race, particularly in U.S. studies (Grove et al. 2006, Luck et al. 2009, Schwarz et al. 2015, Gerrish and Watkins 2018, Locke et al. 2021). This results in a simplistic explanation regarding socioeconomic marginality, which is a typical explanation as to why culturally diverse communities perceive urban nature differently than other communities (Dai 2011, Wolch et al. 2014, Rigolon 2016, Mushangwe et al. 2021). Although socioeconomic patterns are important (Dietz et al. 1998), and in many cases in European, North-American, and Australian contexts these patterns correlate with cultural diversity patterns (see Kendal et al. 2012, Rigolon 2016, Ferguson et al. 2018, Locke et al. 2021, Mushangwe et al. 2021), this explanation is incomplete, and does not allow researchers to engage with other possible explanations, including the culturally specific ways people experience and perceive urban nature (Buijs 2009, Jay and Schraml 2009, Spartz and Shaw 2011, Díaz et al. 2015, Vierikko et al. 2016, Díaz et al. 2018, Rishbeth et al. 2019). Also, research is usually guided by an interest in private, which results in a simplistic explanation that the only way for people to translate their decisions and perceptions into ecological structure and functions is through their direct involvement in private urban land management (Fraser and Kenney 2000, Grove et al. 2006, Spartz and Shaw 2011, Kendal et al. 2012, Main 2013, Avolio et al. 2015, Neal et al. 2015, Pearce et al. 2015, Peters et al. 2016, Larson et al. 2016, Avolio et al. 2018), thus dismissing their influence on the public realm and at the community-level (Rishbeth et al. 2019). In our study we found no interaction between cultural diversity and demographic variables, and our focus was on public treed spaces. Similarly, we found that diverse cultural identities still influenced value perceptions despite accounting for different demographic variables. This suggests that, at least in some contexts, differences in perceptions cannot be explained by socioeconomic variables alone, such as level of income. Nevertheless, this must be taken with caution. Although we accounted for education, which correlates with socioeconomic status in Australia (ABS 1999), we lacked complementary and explicit data on income. More empirical research based on disentangling the interaction between socioeconomic and cultural diversity factors is needed.
Key to developing a better understanding of the importance and meanings that diverse communities attach to urban nature is strengthening the mechanism of elicitation. This mechanism is inherently linked to how researchers conceptualize how something is being perceived in terms of the perception response and associated cognitive construct. Most research on the role of cultural diversity in people’s perceptions of urban nature has focused either on general preferences of urban landscapes with and without natural elements, on the uses of urban parks, on the preferences in people’s private urban land, or on the benefits of urban nature, such as urban trees (see references in previous subsections). Although this research can be useful, and there are certainly overlaps in these perception responses, there are also limitations. Usually, additional, and complimentary information about people’s perceptions of urban nature is needed to better understand the diverse ways people perceive specific natural elements and landscapes in cities (Ordóñez et al. 2022). As discussed in our conceptual framework, although it is still unclear how the concepts of ecosystem services (ES), nature contributions to people (NCP), and ecosystem values may overlap, and it goes beyond the scope of this article to resolve this, the concept of ecosystem values has some strengths. First, it goes beyond a simplistic positive-negative dichotomy (i.e., benefit/cost, service/disservice), and rather focuses on the notion of how something is important and meaningful to people. Second, it does not only focus on functionality and utility, so it can help capture a pluralistic set of perception responses associated with cultural, social, ecological, environmental, economic, and psychological ideas (see Bengston 1994, Satterfield 2001, Turner et al. 2003, Dietz et al. 2005, O'Brien 2006, Ford et al. 2012, Peckham et al. 2013, Kendal et al. 2015, Ordóñez 2017, Tadaki et al. 2017, Arias-Arévalo et al. 2018, Pedersen et al. 2019, Rawluk et al. 2019). Nonetheless, more research is still needed to understand the cognitive pathways that lead to people having certain value perceptions with urban natural elements and landscapes, and how these value perceptions may influence other perception responses, such as attitudes and preferences regarding the specific abundance, diversity, distribution, arrangement, and social-ecological connections of these landscapes (Kendal et al. 2022).
Implications for practice
Urban ecosystem management, currently dominated by a supply-demand model, assumes that only by providing abundant urban nature, such as planting more urban trees, can we provide the necessary ecosystem services to people. This disregards the other aspects of urban nature that help make urban natural elements and landscapes meaningful to people, including diversity, distribution, arrangements, and social-ecological connections (e.g., wildlife habitat, cultural significance). This means that urban nature does not only need to be abundant but also meaningful to diverse communities (Díaz et al. 2015, 2018, Shanahan et al. 2015, Rishbeth et al. 2019, Oh et al. 2021). To better account for how culture shapes these meanings we should aim to integrate the diverse ways people perceive urban nature, including their values, beliefs, attitudes, and preferences. Clearly, the average person cannot differentiate between these constructs and can fluidly move through various levels of abstraction when describing how they perceive something. In a way, these constructs are for researchers to code how people think, relying on a language sophistication that people usually do not use. Nevertheless, both researchers and practitioners should be able to differentiate perceptions by their level of abstraction, such as liking and not liking something, or valuing something fundamentally (Schwartz 1992, Bengston 1994, Ordóñez 2017, Arias-Arévalo et al. 2018, Rawluk et al. 2019). This differentiation can help us make better sense of perception research and how we mobilize ecosystem values based on the diverse perceptions that may exist, instead of just focusing on what ideas are most commonly shared, frequently mentioned, or easily elicited. This can help us address the enduring processes that reproduce inequality, prejudice, and discrimination for minorities (Buijs 2009, Byrne and Wolch 2009, Byrne 2012, Wolch et al. 2014, Carmichael and McDonough 2019, Rishbeth et al. 2019), and better integrate social and ecological objectives (Ives and Kendal 2014, Vierikko et al. 2016, Kronenberg et al. 2021).
Urban ecosystem management relies on community perceptions to justify community support and to obtain practical insights into what type of urban nature people want, including its abundance, diversity, distribution, arrangement, and social-ecological connections. However, most research on community perceptions only considers the most common, frequently mentioned, or easily elicited perception responses expressed by a dominant cultural group (Byrne and Wolch 2009, Jay and Schraml 2009, Dai 2011, Byrne 2012, Wolch et al. 2014, Rigolon 2016, Ordóñez 2017, Carmichael and McDonough 2019, Egerer et al. 2019, Rishbeth et al. 2019, Kendal et al. 2020, Ordóñez et al. 2022), yet these are unlikely to encourage widespread community support or foster stewardship in the long run. In many cities, the voices of people from cultural groups that are in the minority are often kept outside of the conversation (Byrne 2012, Wolch et al. 2014, Rishbeth et al. 2019). Conversely, a better understanding of what urban nature means to diverse members of the public will result in better stewardship, ownership, and appreciation of urban nature (Dai 201, Ives and Kendal 2014, Ordóñez et al. 2022). These meanings will obviously diverge across populations, as shown in this study. The management of urban nature, and urban forests, should then be comfortable with conflicting values and priorities, and account for contest amongst values, whilst avoiding the promotion of consensuses that exclude others, and instead focusing on engaging with diverse communities (Dai 2011, Rigolon 2016, Ordóñez et al. 2022). To better engage with culturally diverse communities, communications can be tailored by using language that reflects the value perceptions of these groups, such as psychological and socio-cultural benefits, complementing environmental or ecological benefits. Communications must also be translated to as many languages as possible. The goal of these communications should not be to educate or convince people of these other benefits. Rather, it should be to recognize the plurality of urban nature meanings held by diverse communities.
Limitations
The study focused on eliciting perceptions from those people with the most immediate experience of park and streets. Our sample was atypical to the demographic patterns in Australia. We were unable to assess to what extent the demographic profile of our respondents is representative of park and street users because these data do not exist for Australia. Nevertheless, our study shows that accounting for cultural diversity is necessary to examine the factors that influence value perceptions. We recognize that there is little guidance in the present literature on how to model these associations using our analytical approaches (i.e., contingency analyses, structural models, general linear models). We then chose to model these associations in a way that enhanced the internal validity of the analysis but recognize that this may have resulted in the model not fitting the data adequately. Although we recognize the limitations of our models and of the data, we believe we have provided some new and innovative ways to test these associations, while better accounting for the influences of cities, types of sites, and urban forest aspects. The measures and analytical approaches used in this study could be replicated in future studies and we would like to suggest will be useful for future research into the importance of cultural diversity in urban nature. Finally, there may also be other spatial-temporal considerations for analyzing how people’s perceptions may change by, for example, time of the year, season, environmental conditions, such as temperature, wind, rain, and the characteristics of the sites, not just including site type (i.e., street vs. parks, already considered in this study), but also tree species, tree arrangement, vegetation structure, biodiversity abundance, residential surroundings, management regimes, among many of other characteristics. However, the focus in this study was the influence of cultural diversity. More research on how these other variables may influence perceptions would be a valuable line of inquiry for future research.
CONCLUSIONS
Our study aimed to complement the existing understanding of how people’s diverse cultural identities may influence how people perceive urban nature, with a focus on urban forests. The objectives of our research were to identify and compare value perceptions across people representing various cultural identities and assess the influence of these identities upon these perceptions considering other cognitive, behavioral, demographic, and social-ecological context factors that may influence these perceptions. We found that cultural diversity can play a significant role in how people perceive the importance of urban forests, although people’s diverse cultural identities do not always overlap. The study demonstrates that the various aspects of urban forests are imbued with cultural meaning, with this meaning dependent on the ways culturally diverse identities are studied and represented. Our results can challenge normative assumptions about the values people hold in relation to urban forests, such as all people valuing urban trees only for aesthetics, or diverse and minority cultural communities not sharing the same values as other communities. People representing these communities perceive urban forests in ways that complement the values of general populations. Characterizing value perceptions solely by the most widely shared or most frequently mentioned perception response is an oversimplification. By intentionally studying how diverse people perceive the value of diverse urban forest aspects across contexts, we can better identify, compare, and contrast a wider range of values. The variations in perceptions across populations may create different expectations of benefits and how people derive benefits from urban nature. Some, but not all, expectations of benefit can be translated into urban nature management. For example, we do not know how many trees it takes to make people feel better, or how much better. In addition, we do not know what other characteristics of trees, including diversity, distribution, arrangement, and social-ecological connections, can provide what benefits to people. Clearly, planting a lot of trees, or planting a lot of different types of trees, and distributing trees equally across the city space, will not solve all problems or make urban forests more accepted by diverse populations. Urban nature spaces with trees must be acceptable, supported, and even protected by culturally diverse and minority communities if they are to succeed. Diversity should underpin everything in urban nature, including the diversity of urban nature landscapes, elements, and the ways humans experience and perceive nature.
RESPONSES TO THIS ARTICLE
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AUTHOR CONTRIBUTIONS
CO, CGT, and SJL conceived the study and contributed to research design, including questionnaire content and protocols for data collection. CO supervised the collection of the questionnaire data. CO, CS, JB collected and processed the data for analysis. CO conducted all data analyses under the supervision and guidance from CGT, RF, DFH, MD, and SJL. CO led the writing of the manuscript, with significant contributions from CGT, RF, DFH, MD, and SJL for data interpretation, critical revisions, and intellectual content. All authors contributed critically to the drafts and gave final approval for publication.
ACKNOWLEDGMENTS
The authors wish to thank Dr. Dave Kendal of Future in Nature Pty Ltd, Australia, and Dr. Rodney van der Ree of WTP Pty Ltd, Australia, and the University of Melbourne, for their support. We also thank Dave Callow and Kelly Herzog from the City of Melbourne; David Grant, Mary Spencer, Daniel Siemensma, and James Guy of the City of Ballarat; and Alex English from the City of Moreland. We thank the City of Yarra for allowing us to research their city park. Funding for this project was provided by the Australian Research Council (ARC) Linkage Partnership grant (#LP160100780) – Managing urban trees for people and wildlife. Author CGT was supported by the Australian Government’s National Environmental Science Program through the Clean Air and Urban Landscapes Hub (CAUL) and by an Australian Research Council Discovery Early Career Researcher Fellowship (DE200101226). CO was supported by funding provided by the University of Toronto, and a Social Sciences and Humanities Research Council (SSHRC) of Canada Partnership Development Grant (No. 511621).
DATA AVAILABILITY
The data/code that support the findings of this study are available on request from the corresponding author in aggregated form without any personal or identity information. Because of restrictions imposed by the institutional ethics review board (Human Research Ethics Committee of The University of Melbourne) protecting the privacy of research participants, we cannot openly share or make publicly available any of the raw data. Study participants did not consent to the sharing of these data. Ethical approval for this research study was granted by the Human Research Ethics Committee of The University of Melbourne (Ethics ID Number: 1750822.1). Informed consent was obtained from all participants by describing the study verbally during intercept questionnaires and by handing out a consent format and plain language statement of the research to all participants.
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Table 1
Table 1. Social sample profile (n = 1127).
Characteristics | Counts | % of total | Australian census (% of total)1 | ||
Greater Melbourne area | Victoria | Australia | |||
Female | 637 | 56.5% | 51.0% | 50.9% | 50.7% |
Age: 20–34 years | 313 | 27.8% | 23.7% | 22.0% | 21.1% |
35–49 years | 419 | 37.2% | 21.2% | 20.4% | 20.3% |
50–64 years | 148 | 13.1% | 16.8% | 17.8% | 18.3% |
65–79 years | 204 | 18.1% | 10.2% | 11.4% | 11.7% |
> 80 years | 18 | 1.6% | 3.9% | 4.2% | 4.1% |
Australian born | 706 | 62.6% | 59.8% | 64.9% | 66.7% |
Language other than English (LOTE) | 398 | 35.3% | 34.9% | 27.8% | 22.2% |
Education: University degree | 901 | 79.5% | 20.4% | 17.8% | 16.1% |
Occupation: Student | 215 | 19.1% | n.a. | n.a. | n.a. |
Language grouping:† European (not English) |
168 | 14.9% | n.a. | n.a. | n.a. |
African | 8 | 0.7% | n.a. | n.a. | n.a. |
East Asian | 77 | 6.8% | n.a. | n.a. | n.a. |
South Asian | 90 | 8.0% | n.a. | n.a. | n.a. |
Oceanian | 5 | 0.4% | n.a. | n.a. | n.a. |
Western Asian | 25 | 2.2% | n.a. | n.a. | n.a. |
n.a. = not available or not applicable. † Population statistics for these language groupings are not available. European languages only apply for language other than English (LOTE) and exclude English-only speakers (i.e., LOTE inverse, or n = 729). Details in Appendices. 1 ABS 2016. |
Table 2
Table 2. Language groupings by world region and examples of languages from data (n = 1127). Details in Appendix 4.
Language grouping | Example of languages (verbatim data) | Count | % of total | ||||||
African | Shona, Oromo, Amharic | 8 | 0.7% | ||||||
East Asian | Cantonese, Filipino, Mandarin | 77 | 6.8% | ||||||
European (not English) | French, Greek, Italian, Polish, Spanish | 168 | 14.9% | ||||||
Oceanian | Maori, Bislama, Fijian | 5 | 0.4% | ||||||
South Asian | Bahasa, Hindi, Tagalog, Vietnamese | 90 | 8.0% | ||||||
Western Asian | Arabic, Farsi | 25 | 2.2% | ||||||
Table 3
Table 3. Illustration of how the theme clusters for value perceptions emerged, with examples of how people responded to the question, “Why is this [urban forest aspect] important to you?” The table includes the initial responses captured based on verbatim data (verbatim responses), the codes assigned to these initial responses (codes), and the assigned code groupings (theme clusters). The theme clusters are the same categories as those used in Figure 3. Details in Appendix 5 (n = 1127).
Urban forest aspect | Verbatim responses | Codes | Theme clusters | Categories in Figure 3 | |||||
Treed site | “Like the greenery among the buildings” “It’s a shady place” “Great place to walk” “Good place to explore” “Place makes me feel good” “Good for exercise” |
Green Shade Walking Recreation Feel good Exercise |
Aesthetic Environmental Socio-cultural Socio-cultural Psychological Health |
aes env soccul soccul psych health |
|||||
Trees at site | “Large and beautiful” “Good for the environment” “Like the birds and animals on them” “Good shading” “My kids like jumping and going over them” “Good for my wellbeing” “Makes me feel healthy” |
Big trees Environment quality Habitat Shade Recreation Well-being Health |
Aesthetic Environmental Naturalness and biodiversity Environmental Socio-cultural Psychological Health |
aes env natbio env soccul psych health |
|||||
Wildlife at site | “Just nice to have” “It was once habitat but we destroyed it” “Take care of animals” “Part of the ecosystem” “Nice to show kids so they learn” “Healthy communities” |
Nice Habitat Conservation Ecosystem Learning Health |
Aesthetic Naturalness and biodiversity Naturalness and biodiversity Naturalness and biodiversity Socio-cultural Health |
natbio aes natbio natbio soccul health |
|||||
Table 4
Table 4. Results for the general linear regression models (GLMs) assessing the influences on value perceptions (response variable), defined here as the level of importance assigned to treed sites, trees at the site, and wildlife at the sites, by variables indicating diverse cultural identities (determinant variables), including born in Australia (ausborn), language-other-than-English (LOTE), and language spoken if LOTE, while accounting for other factors, as indicated.
Variables | Importance of treed sites |
Importance of trees at the site |
Importance of wildlife at the site |
Coefficient (standard error) | Coefficient (standard error) | Coefficient (standard error) | |
Ausborn | -0.13 (0.05)** | -0.11 (0.05)* | -0.07 (0.05) |
LOTE | -0.19 (0.08)** | -0.28 (0.07)*** | -0.12 (0.08) |
Language: European (not English) | 0.26 (0.08)*** | 0.24 (0.08)** | 0.08 (0.08) |
Language: South Asian | 0.09 (0.08) | 0.11 (0.09) | 0.32 (0.09)*** |
Durbin-Watson test | 1.89 | 1.93 | 1.72 |
All models account for sites and city, nature-relatedness, knowledge of trees (knowledge of trees and knowledge of species scales), exposure to trees (living distance, visitation frequency, and tree in front of home), site type (park or streets), gender (female), education (university), age (median of decade born), and occupation (student). * p < 0.05, ** p < 0.01, *** p < 0.001. |
Table 5
Table 5. Results for the general linear regression models (GLMs) assessing the influences on value perceptions (response variable), defined as the density of themes as reasons of importance of treed sites, trees at the site, and wildlife at the site, by variables indicating diverse cultural identities (determinant variables), including born in Australia (ausborn), language-other-than-English (LOTE), and language spoken if LOTE, while accounting for other factors, as indicated.
Variables | Treed sites, theme: psychological | Trees at the sites, theme: environmental | Trees at the sites, theme: naturalness and biodiversity |
Coefficient (standard error) | Coefficient (standard error) | Coefficient (standard error) | |
Ausborn | -0.01 (0.05) | 0.02 (0.05) | -0.09 (0.05) |
LOTE | 0.04 (0.06) | 0.06 (0.06) | -0.00 (0.00) |
Language: East Asian | 0.25 (0.09)** | -0.00 (0.00) | -0.18 (0.10) |
Language: South Asian | 0.00 (0.09) | 0.18 (0.09)* | -0.39 (0.10)*** |
Durbin-Watson test | 1.87 | 1.81 | 1.94 |
All models account for sites and city, nature-relatedness, knowledge of trees (knowledge of trees and knowledge of species scales), exposure to trees (living distance, visitation frequency, and tree in front of home), site type (park or streets), gender (female), education (university), age (median of decade born), and occupation (student). * p < 0.05, ** p < 0.01, *** p < 0.001. |