# Trees and the City: Diversity and Composition along a Neotropical Gradient of Urbanization

Authors: Rubén Ortega-Álvarez; Hernando A. Rodríguez-Correa; Ian MacGregor-Fors
Journal: International Journal of Ecology
 (2011)

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## Abstract

In this study we assessed tree species richness, density, and composition patterns along a gradient of urbanization of a megacity. Our results show that total, native, and exotic tree densities were highest in green areas where larger spaces are considered for greening purposes. Conversely, total, native, and exotic tree species richness were highest in land uses with intermediate levels of urban development (residential, residential-commercial areas). Not finding highest tree species richness in less developed urban areas suggests that cultural factors may shape the array of species that are planted within cities. Supporting this, tree composition analyses showed that green areas are comprised of different tree species when compared to the rest of the studied urban land uses. Thus, our results suggest that, to increase the ecological quality of cities, residents and managers should be encouraged to select a greater variety of trees to promote heterogeneous green areas.


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## Body

## 1. Introduction

Natural habitats are transformed by urbanization processes to satisfy housing needs and support human activities [1–4].Such man-made systems include physical, biological, and social processes and result in the development of urban infrastructure such as buildings and streets/roads, often leaving little space for vegetation [5].  Among urban green patches trees commonly comprise the main component, highly represented by exotic species that can become invasive in periurban areas [6].  Thus, urbanization implies not only the alteration of habitat structure, but also the modification of the diversity and composition of its vegetation component [7].Urban vegetation, comprised of plants from parks, greenways, median strips, playgrounds, cemeteries, gardens, and sidewalks have important ecological and social implications [8–10].  In particular, trees are critical for the maintenance of some urban ecological processes [11] and have been identified as the most important habitat component known to affect wildlife diversity within urbanized systems [12–15].  Additionally, aggregated trees in recreational areas (e.g., parks, playgrounds) allow the interaction of people, although they have also been related to socioeconomic barriers [16, 17].In this study we examined changes in tree species richness along a neotropical gradient of urbanization in the Metropolitan Area of Mexico City (hereafter Mexico City), assessing patterns of native and exotic species.  We also evaluated tree density and composition patterns along this gradient to provide a context for our species richness results.  We expected tree species richness to be similar between residential and residential-commercial areas.  In contrast, we predicted low species richness and high tree density in urban green areas.  Finally, we expected to find a high number of exotic species in all the studied urban land uses (i.e., green areas, commercial areas, residential-commercial areas, commercial areas).


## 2. Study Area

We performed this study in Mexico City, one of the most populated urban areas in the world [18] (Figure 1).  This city covers a current area of >1000 km2, houses a human population that surpasses 20 million inhabitants [19], and has an annual population growth of 0.8% [20].  Although the establishment and continuous growth of this megacity have negatively affected wildlife, it still holds considerable biodiversity values [21–23].  Similar to other Latin American cities, Mexico City is represented by four main urban land uses: (1) commercial, (2) residential, (3) industrial, and (4) green areas.Figure 1
Map of study area. Green: green area, Comm.: commercial area, Res.: residential area, R.-C.: residential-commercial area.We focused our sampling effort in the central and southwestern section of the city, where industrial areas are practically absent.  We established a gradient of urbanization considering the four major urban land uses, from green to commercial areas, including residential and residential-commercial areas.  To discriminate among highly developed urban areas (i.e., residential, residential-commercial, commercial areas) and green areas, we followed the classification of urban development proposed by Marzluff et al. [24].  We used the presence of commercial lots to differentiate between commercial and residential urban land uses, and determined areas as residential-commercial where both residential and commercial components were present.  As reported in a previous study [23], the four studied urban land uses represent  a gradient that affects birds, from less developed (green areas) to highly developed urban sites (commercial areas).


## 3. Methods

### 3.1. Tree Surveys

We surveyed trees within 25 m radius circular plots at green, commercial, residential, and residential-commercial areas (modified from [25]) during June-July 2007.  We sampled 30 plots within each urban land use, separated by a minimum distance of 250 m to represent independent sampling units, giving a total of 120 plots along the gradient of urbanization.  We located survey plots along our study area to meet two main criteria: (1) that the land use was homogeneous in surrounding areas, and (2) that they were heterogeneously distributed along our study area.  At each plot, we recorded the number of trees and identified each individual to species level or classified them as morphospecies.


### 3.2. Data Analysis

To compare tree species richness among the studied urban land uses, we calculated average tree species richness and 95% confidence intervals using EstimateS [26].  This approach allows comparison among treatments using accumulated abundance, as average species richness is calculated by the repeated resampling of all pooled samples [27].  We calculated tree density per hectare by extrapolating the number of trees recorded at each plot (0.19 ha) to one hectare.  To compare the calculated species richness and density values, we contrasted their 95% confidence intervals [28], assuming statistical differences with nonoverlapping intervals (α < 0.01; M. E. Payton, pers. comm.).  Finally, we used a Bray-Curtis multivariate cluster analysis to compare tree taxonomic composition of the studied land uses [29].  As community diversity patterns could be obscured by the origin of the recorded tree species, we also conducted species richness, density, and composition analyses for each land use distinguishing between native and exotic species.  We considered all species that dwell within the southern region of the valley of Mexico, the area in which Mexico City is located, as native sensu[30], while we considered all others as exotic.


## 3.1. Tree Surveys

We surveyed trees within 25 m radius circular plots at green, commercial, residential, and residential-commercial areas (modified from [25]) during June-July 2007.  We sampled 30 plots within each urban land use, separated by a minimum distance of 250 m to represent independent sampling units, giving a total of 120 plots along the gradient of urbanization.  We located survey plots along our study area to meet two main criteria: (1) that the land use was homogeneous in surrounding areas, and (2) that they were heterogeneously distributed along our study area.  At each plot, we recorded the number of trees and identified each individual to species level or classified them as morphospecies.


## 3.2. Data Analysis

To compare tree species richness among the studied urban land uses, we calculated average tree species richness and 95% confidence intervals using EstimateS [26].  This approach allows comparison among treatments using accumulated abundance, as average species richness is calculated by the repeated resampling of all pooled samples [27].  We calculated tree density per hectare by extrapolating the number of trees recorded at each plot (0.19 ha) to one hectare.  To compare the calculated species richness and density values, we contrasted their 95% confidence intervals [28], assuming statistical differences with nonoverlapping intervals (α < 0.01; M. E. Payton, pers. comm.).  Finally, we used a Bray-Curtis multivariate cluster analysis to compare tree taxonomic composition of the studied land uses [29].  As community diversity patterns could be obscured by the origin of the recorded tree species, we also conducted species richness, density, and composition analyses for each land use distinguishing between native and exotic species.  We considered all species that dwell within the southern region of the valley of Mexico, the area in which Mexico City is located, as native sensu[30], while we considered all others as exotic.


## 4. Results

We recorded a total of 89 tree species, with 48 in green areas, 64 in residential areas, 43 in residential-commercial areas, and 39 in commercial areas (Table1).  Of the total recorded species, 55 were exotic (61.8%), 30 were native (33.7%), and 4 morphospecies remained uncertain (4.5%).  Total tree species richness differed among the studied land uses when compared at a constant calculated abundance (524 individuals based on the lowest abundance recorded in residential-commercial areas), with highest values in residential areas (49.0 ± 8.1 computed species), followed by residential-commercial areas (44.0 ± 7.3 species), commercial areas (32.3 ± 6.3 species), and green areas (20.2 ± 4.8 species; Figure 2).  This pattern changed when we analyzed native and exotic species separately.  On the one hand, native species richness was highest in residential areas (17.42 ± 4.69 species), followed by residential-commercial areas (13.0 ± 3.38 species), and lastly by green and commercial ones (8.8 ± 3.4 and 6.9 ± 3.0 species, resp.; Figure 2).  On the other hand, exotic tree species richness was highest in residential, residential-commercial, and commercial areas (30.7 ± 6.0, 31.0 ± 6.4, and 23.9 ± 5.2 species, resp.) and lowest in green areas (11.3 ± 2.8 species; Figure 2).Table 1
Tree species recorded along the studied gradient of urbanization.  Numbers represent the total number of individuals recorded in this study.  Species are displayed alphabetically. (N): native species, (E): exotic species (see Section3 for details). Green: green areas, Res: residential areas, Res-Com: residential-commercial areas, Com: commercial areas.
SpeciesGreenComResRes-ComAbies religiosa (Kunth) Schltdl. and Cham. (N)28836Acacia melanoxylon R. Br. (E)13Acacia retinodes Schltdl. (E)17Acer negundo L. (N)11Alnus acuminata Kunth (N)34212Alnus jorullensis Kunth (N)39Anacardiaceae5Araucaria heterophylla (Salisb.) Franco (E)1157Bauhinia sp. (E)1Buddleia cordata Kunth (N)222382211Buddleia  parviflora Kunth (N)15Casuarina  equisetifolia L. (E)75141017Celtis  occidentalis L. (E)1Citrus  limon (L.) Osbeck (E)251Citrus  sinensis (L.) Osbeck (E)2Citrus sp. (E)1Crataegus  mexicana Moc. & Sessé ex DC. (N)319Cupressus  lusitanica Mill. (N)3375118672Cupressus  macrocarpa Hartw. ex Gordon (E)27134Cupressus  sempervirens L. (E)6318047Cupressus sp. (E)11Dombeya  wallichii (Lindl.) K. Schum. (E)1Eriobotrya  japonica (Thunb.) Lindl. (E)13296Erythrina  coralloides DC. (N)193014Eucalyptus spp.1 (E)771484443Euphorbiaceae sp. (E)1Ficus  benjamina L. (E)61237461Ficus  carica L. (E)11Ficus  elastica Roxb. (E)258Ficus  microcarpa L. f. (E)13Ficus sp. (E)41Fraxinus  uhdei (Wenz.) Lingelsh. (N)6842334269Furcraea  bedinghausii K. Koch (N)4Garrya  laurifolia K. Koch (N)3710Grevillea  robusta A. Cunn. ex R. Br. (E)1016Jacaranda  mimosifolia D. Don (E)11332430Juglans  regia L. (E)31Laurus sp. (E)2Liquidambar  styraciflua L. (E)934222Magnolia  grandiflora L. (E)22812Morus  alba L. (E)6Morus  rubra L. (E)2Persea  americana Mill. (E)11Phoenix  canariensis Chabaud (E)22031Phoenix  dactylifera L. (E)2Picea sp. (E)1Pinus  ayacahuite C. Ehrenb. ex Schltdl. (N)51Pinus  leiophylla Schiede ex Schltdl. & Cham. (N)1Pinus  maximartinezii Rzed. (E)42Pinus  montezumae Lamb. (N)1Pinus  patula Schltdl. & Cham. (E)2511Pinus  pseudostrobus Lindl. (N)41Pinus  radiata D. Don (E)6Pinus sp. 13Pinus sp. 21Pinus sp. 31Pinus sp. 4 (E)2Pinus sp. 5 (E)1Pinus sp. 6 (E)1Pinus sp. 7 (E)10Pinus  teocote Schltdl. & Cham. (N)1515Pithecellobium  dulce (Roxb.) Benth. (E)1Pittosporum  undulatum Vent. (E)3Populus  alba L. (E)8112Populus  tremuloides Michx. (E)3111Prunus  domestica L. (E)2341415Prunus  persica (L.) Batsch (E)32173Prunus  serotina Ehrh. (N)4815744Pyrus  communis L. (E)57Pyrus  malus L. (E)115Quercus  castanea Née (N)12Quercus  crassipes Humb. & Bonpl. (N)194Quercus  deserticola Trel. (N)153Quercus  laeta Liebm. (N)32Quercus  laurina Bonpl. (N)179Quercus  obtusata Bonpl. (N)5Quercus  robusta C.H. Mull. (E)8Quercus  rugosa Née (N)42Quercus sp. (N)15Salix  bonplandiana Kunth (N)32Salix  paradoxa Kunth (N)44Sambucus  nigra L. (N)7254Schinus  molle L. (E)924235Taxodium  mucronatum Ten. (N)3Thuja sp. (E)13291Trema sp. (E)8Ulmus sp.6143Washingtonia  robusta H. Wendl. (E)167Yucca  elephantipes Regel ex Trel. (E)512121Eucalyptus globulus and E. camaldulensis are both referred as Eucalyptus spp. due to difficulties in identifying individuals of each species at the time of the year when we carried out our surveys.Computed tree species richness for the studied urban land uses. Values represent average values (±95% confidence intervals) computed at 524, 281, and 243 individuals for total, exotic, and native species, respectively. Letters represent statistical differences.  Green: green areas, Res: residential areas, ResCom: residential-commercial areas, Com: Commercial areas.Total tree density also differed among the studied urban land uses, with highest values recorded in green areas (499.5±128.3 trees/ha), followed by residential areas (157.0±32.0 trees/ha), commercial areas (135.0±42.2 trees/ha), and residential-commercial areas (90.7±22.7 trees/ha; Figure 3).  The same pattern was observed for exotic tree density, with highest values recorded in green areas (183.3±76.9 trees/ha), followed by residential areas (79.8±18.3 trees/ha), commercial areas (79.0±24.2 trees/ha), and residential-commercial areas (46.7±14.5 trees/ha; Figure 3).  The density of native species showed highest values in green areas (301.7±97.2 trees/ha), while no differences existed among the rest of the studied land uses (residential: 77.2±33.3 trees/ha, residential-commercial: 39.5±11.9 trees/ha, commercial: 58.3±29.4 trees/ha; Figure 3).Total, exotic, and native tree species density (ind/ha) average values (±95% confidence intervals) for the studied urban land uses.  Letters represent statistical differences.  Green: green areas, Res: residential areas, ResCom: residential-commercial areas, Com: commercial areas.Finally, total tree species composition was more similar among residential, residential-commercial, and commercial areas (>50% similarity), than green areas, which in turn showed an average dissimilarity of 75% with the rest of the studied land uses (Figure4).  Composition among land uses showed a similar pattern for both native and exotic tree species, with residential and residential-commercial areas exhibiting the highest similarity value among all land uses, followed by commercial areas, and finally by green areas (Figure 4).Figure 4
Abundance-based Bray-Curtis multivariate cluster analysis depicting tree composition similarity among the studied urban land uses.  GA: green areas, RES: residential areas, RES-COM: residential-commercial areas, COM: commercial areas.


## 5. Discussion

Along the studied neotropical gradient of urbanization of Mexico City, total, native, and exotic tree species richness were highest in residential and residential-commercial areas, which represent intermediate levels of urban development.  Thus, the species richness pattern recorded in this study was consistent with the intermediate disturbance hypothesis [31].  This pattern is different from that observed for other wildlife groups (e.g., birds, mammals, reptiles), which exhibit higher species richness in less developed sites, such as green areas [23, 32].  Our results show that higher species richness of both native and exotic trees in Mexico City is related to the residential component of land uses, suggesting that residents promote tree species richness by choosing diverse tree species for their gardens and homesteads.  Thus, tree species richness seems to be molded by cultural forces, as well as by landscaping, horticultural, and recreational practices [33].  Lower tree species richness in land uses with commercial components was not surprising, as the space available for planting trees is often reduced.  In the case of green areas, trees are usually used to achieve greening purposes, which could lead to the creation of stands comprised by few tree species.  Thus, native and exotic tree species richness were low within  such urban land uses.  Moreover, some green areas have original vegetation patches (e.g., shrublands, fir forests; [34]) which are characterized by the presence of a limited number of tree species.Although total tree density also varied among urban land uses, the pattern was contrastingly different to that found for tree species richness.  In fact, highest total, native, and exotic tree densities were recorded in green areas.  This result was expected, as larger spaces  within these areas are used for greening purposes [35] and are generally managed by the city council.  Residential areas showed less total, native, and exotic tree densities than green areas, but exhibited higher values than residential-commercial and commercial areas.  This could result from socioeconomic considerations, reflecting the preponderance of gardens in high-income residential areas [36, 37], as people who live in these sites tend to appreciate and afford greener neighborhoods.  Similar to our tree species richness results, land uses with commercial components (i.e., residential-commercial, commercial areas) had the lowest total, native, and exotic tree density values, mainly because a major proportion of the land is occupied by urban infrastructure components.Our cluster analyses reinforce the point that residents can shape the diversity and density of total, native, and exotic trees in residential areas, even within those that contain commercial components [38, 39].  Higher taxonomic similarity of urban land uses that include residential components could result from a similar incorporation of both exotic and native species by residents.  Differences among the latter land uses and commercial areas could emerge as local managers tend to prefer exotic over native species for aesthetic purposes in commercial sites.  Finally, green areas were highly different from the rest of the studied land uses, likely due to higher densities of few species (e.g., Gum Trees—Eucalyptus spp., Mexican Cypress—Cupressus lusitanica, Mexican Ash—Fraxinus uhdei).Although few studies have analyzed the variation of tree species richness along gradients of urbanization, our results agree with them, indicating that tree species richness, native or exotic, does not decrease with urbanization intensity [32].  Particularly, higher values of plant species richness have been reported within moderately urbanized areas, likely enhanced by different plant cultivation choices [32, 40].  Thus, resident preferences and decisions play a fundamental role in determining the vegetation component of urban systems.  To increase the potential benefits of human activities on the ecological quality of cities, residents and green area managers should be encouraged to select for a greater variety of tree species to avoid monospecific stands, promote heterogeneous green areas that benefit different wildlife groups, and maintain several ecological processes within urban ecosystems [41].  Moreover, further efforts are needed to enhance higher densities of trees outside green areas (e.g., residential areas, residential-commercial areas), which could derive in benefits for urban wildlife and local residents.



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*Source: 704084-2011-10-16.xml*