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Residential management of urban front-yard landscape: A random process?
Landscape and Urban Planning 40 Ž1998. 295–307
Residential management of urban front-yard landscape: A random process? Jean Zmyslony, Daniel Gagnon
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´ Groupe de Recherche en Ecologie Forestiere, ` UniÕersite´ du Quebec ´ a` Montreal, ´ C.P. 8888, Succursalle Centre Õille, Montreal, ´ Quebec, ´ Canada H3C 3P8 Received 6 January 1997; revised 22 September 1997; accepted 19 November 1997
Abstract In order to understand the management dynamics of urban residential vegetation at local scales, we studied nonvegetated areas and the vegetation composition, distribution and structure of front yards in 17 successive residential street sections of Hochelaga–Maisonneuve District, Montreal. ´ We systematically sampled 646 front yards. A total of 250 descriptors were used to characterize the landscape Žcontent. of every front yard. We then measured the similarity of vegetation and nonvegetated areas in each front yard in relation with distance for all street sections. Mantel correlograms allow us to examine the spatial structure of front-yard landscape at local scales. Results show that front-yard landscape is Ž1. an autocorrelated Žor regionalized. variable, Ž2. that the spatial structure of the vegetation and nonvegetated areas is of contagious form and Ž3. that distribution and structure of the vegetation is the most repeated Žcopied. feature at local scales. A statistically distinct neighbor influence occurs among front yards in all street sections, which often exceeds the probability level p s 0.00001. This strong neighbor ‘mimicry’ effect has potential use in municipal environment improvement strategies that rely on resident actions. q 1998 Elsevier Science. All rights reserved. Keywords: Contagious distribution; Residential vegetation; Mantel correlogram; Mimicry; Spatial structure; Street section
1. Introduction Most investigations of urban vegetation and greenspaces have focused on public areas, and especially on trees of the urban forest ŽRowntree, 1984b, 1986, 1988.. Very little interest has been shown to the urban vegetation of private lots. The main reasons for this lack of interest are probably Ž1. the )
Corresponding author. Tel.: q1-514-987-3000-7751; fax: q1-514-987-4647; e-mail: [email protected].
great diversity of this type of vegetation, Ž2. the large number of owners or managers, Ž3. the difficulty involved in quantifying anthropic processes and Ž4. this type of vegetation and greenspaces has not generally been a direct subject of public policy and decisions. For comparison purposes, according to Richards et al. Ž1984., public street sides, public parks and residential greenspaces account respectively for 7%, 9% and 48% of the total greenspaces in Syracuse, NY. The study of Last et al. Ž1976., one of the few urban tree inventories to include residen-
0169-2046r98r$19.00 q 1998 Elsevier Science B.V. All rights reserved. PII S 0 1 6 9 - 2 0 4 6 Ž 9 7 . 0 0 0 9 0 - X
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tial vegetation, revealed that 84% of the trees of Edinburgh, Scotland, were on residential lots. Residential vegetation, although evidently prominent, remains an overlooked urban resource. Previous studies of urban and residential vegetation were carried out at large scales, such as districts or cities. Rowntree Ž1984a., Sanders Ž1983., Sukopp and Werner Ž1983. described land use as a major factor of urban tree composition and distribution. Schmid Ž1975. has associated the development of urban vegetation to socioeconomic characteristics of residents and age of development. Sanders Ž1984. mentioned that urban forest is determined by three broad factors: urban morphology, natural factors and human management systems. As Sanders Ž1984. noted, we consider that urban vegetation management systems are presumably as varied as the number of actors that impinge upon them. However, at local scales, we suggest that similarities exist among the vegetation and nonvegetated areas managed by different residents in a street section, and therefore give rise to generalizations and regularities worth studying. Richards et al. Ž1984. wrote that the observation of front yards in residential lots with detached houses, as in Syracuse and many other communities, suggests the interaction of residents within the neighborhood. Jim Ž1993. mentioned that proximity of homes Žin the same street. in a suburb of Hong Kong could lead to the adoption of similar tree species. Routaboule et al. Ž1995. noted that residents propagate landscape forms in their neighborhood mainly through observation. Resident interaction can be associated to various types of behaviours. Residents may, for example, reproduce what they see in the front yards of their street section. Routaboule et al. Ž1995. noticed a driving effect in the residential areas of Montreal. ´ These authors suggested that residents first observe what neighbors do in their garden, then they copy, they adapt and occasionally exchange plants among themselves. Also, Eveillard Ž1991. mentions that in Montreal ´ residential districts, a number of plants found in resident front yards are the results of neighbors’ suggestions. The actions of residents that copy, adapt, exchange plants and suggest ideas at a local scale are good examples of mimicry. If all of these combined resident actions included in the mimicry effect are important, similar plants and landscape
elements will be propagated in the neighborhood. Eventually, spatial regularities will emerge in front yards that can be detected by appropriate spatial statistical methods Ži.e., Legendre, 1985.. Some residents may react differently. They may intentionally avoid copying the content of neighboring front yards and manage their front garden with plants of different species, shapes or colors. Others may seem totally indifferent to the landscape of the front yards in the street section, including their own, while a few may create a totally new arrangement of plants, colors and shapes in their neighborhood. Such new arrangements of plants and landscapes can then provide new models for nearby residents to mimic. In our investigation, we hypothesize that residential front-yard landscape is a dependent variable, which is to say that the vegetation and the nonvegetated areas of residential front yards are not randomly distributed in a street section. To test this hypothesis, we will try to demonstrate that the landscape of residential front yards is an autocorrelated Žor regionalized. variable at a local scale. The existence of spatial autocorrelation assumes that any object in space is affected by the objects around it, and that closer objects have more effect than those which are further away ŽTobler, 1970.. Autocorrelation also implies that it is possible to predict various descriptors of front-yard landscape at some points in space within a street section. Our study of residential vegetation in Hochelaga–Maisonneuve is part of a greater case study of the processes responsible for the development of vegetation within street sections. Our goal is to understand the dynamics of urban residential vegetation at local scales in order to propose management strategies for the greening of urban environments, centered on resident actions.
2. Methods 2.1. Hochelaga–MaisonneuÕe district study area The Hochelaga–Maisonneuve District ŽFig. 1. was founded originally before 1870 as two independent cities in the eastern part of Montreal, ´ near the 1976 Olympic Stadium. It covers an area of 8.2 km2 . Its economical and industrial development reached a
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Fig. 1. General location of the Hochelaga–Maisonneuve District on Montreal ´ Island.
peak before the Great Depression. In the sixties, the old industrial structures of Hochelaga–Maisonneuve started to collapse. Its population began to drift towards new urban districts and the suburbs. Today, Plante and Simoneau Ž1986. estimate the population at about 53,000 inhabitants, 90% being Francophones. The Hochelaga–Maisonneuve District was chosen for this study because Žas at the time of its annexation to Montreal ´ in 1918. it remains a city within a city, with its own industrial, institutional, commercial and residential zones. Such a district allows us to analyse the residential vegetation and landscape at the scale of a true urban ecosystem. Consequently, our results could be generalized to other urban ecosystems in North America. The sampled residential area is situated in the northern part of Hochelaga–Maisonneuve, a relatively homogeneous section of the District. Its population belongs to the middle class and shares common socioeconomic characteristics. Over 71% of the residences were built between 1946 and 1970 ŽPlante and Simoneau, 1986.. The sampled area is roughly a rectangle bordered by major discontinuities, providing greater homogeneity. These discontinuities are, in the north, Sherbrooke Street and the Montreal ´ Olympic Park, in the east, part of the Praimont Industrial Sector, in the south, Hochelaga Street Žwhich like Sherbrooke St.
is a main commercial and transportation artery. and in the west, the Canadian Pacific Railway tracks. This area is composed of 17 successive residential street sections, all of them parallel, with a more or less north–south orientation ŽFig. 2.. The 17 street sections contain 646 residences, each of which has a private front-yard garden space. The residences are
Fig. 2. Study area Žshaded. and sampled street sections in the northern sector of Hochelaga–Maisonneuve District. Nicolet, Charlemagne and Pie-IX streets were not sampled because they are nonresidential.
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Table 1 Street section and front-yard characteristics Street sectionsa
Number of front yards
Single-family
Two-family
Several-family Ž3–6.
Multi-family Ž7 q .
Width Žm.
Depth Žm.
Spatial structure
Moreau Prefontaine ´ Dezery ´ St-Germain Darling Davidson Cuvillier Aylwin Joliette Chambly Valois Bourbonniere ` D’Orleans ´ Jeanne D’Arc Desjardins La Salle Letourneux
37 24 30 25 28 41 46 39 47 23 8 59 64 49 48 48 34
1 y y y y 2 y 1 9 y y y y y y y y
22 20 13 16 25 27 19 21 27 y 8 24 32 35 39 39 28
9 y 17 9 y 4 19 1 2 y y 21 24 3 8 8 3
5 4 y y 3 8 8 16 9 23 y 14 8 11 1 1 3
11.1 13.3 9.2 11.4 7.7 9.6 9.3 9.7 9.5 9.8 11.9 8.8 9.4 10.1 8.9 8.9 12.3
5.2 6.3 5.8 5.6 7.3 6.3 6.2 6 7.6 6.7 8.2 5.4 4.2 4.9 4.5 4.5 5.6
strong intermediate strong intermediate strong strong strong strong strong strong strong weak strong strong intermediate weak weak
a Street sections are ordered from West to East in the column. The widths and depths of the gardens are average numbers. The spatial structure of the landscape in the street is divided into three different classes: strong, intermediate and weak.
predominantly duplexes Ž383., triplexes Ž129. and multiplexes Ž121.. A few single-family homes Ž13. are also found. Further characteristics of street sections are given in Table 1. 2.2. Sampling scale In order to study vegetation management in the residential front yards, we decided to proceed at the scale of a residential street section. We consider the street section as being the most appropriate ecological system to study the effects of resident interaction processes on the development of residential vegetation. The street sections in Hochelaga–Maisonneuve are composed of 8 to 64 residences and constitute the immediate environment of each resident. The main crossroads at both ends of the 17 street sections are the first psychological and visual discontinuities encountered by the residents. Such barriers increase the feeling of belonging of the residents to the street section. In these conditions, if forms of resident interaction are present, they should flow freely among residents and eventually be expressed by spatial patterns within the residential vegetation and front-yard
nonvegetated areas. The 646 front-yard gardens were sampled from June 5 to August 25, 1992. 2.3. Sets of descriptors Because 196 species were found in the sampled area ŽZmyslony, 1997., the first set of sampled descriptors contains 196 composition binary descriptors, each of them indicating the presence or absence of a species in every front yard.
Fig. 3. Illustration of the six front-yard zones: Ž1. the wall zone; Ž2. the foundation zone; Ž3. the entrance zone; Ž4. the center zone; Ž5. the side zone; and Ž6. the front zone, ŽA. is the walkway and ŽB. the sidewalk.
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The second set of sampled descriptors is used to describe the structure and distribution of the vegetation in each front-yard garden. In order to assess the Table 2 Description of the 49 descriptors of the structural matrix 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49
% Area or front border zone Presence or absence of annuals Presence or absence of perennials Presence or absence of shrubs Presence or absence of trees % Area of center border zone Presence or absence of annuals Presence or absence of perennials Presence or absence of shrubs Presence or absence of trees % Area of foundation border zone Presence or absence of annuals Presence or absence of perennials Presence or absence of shrubs Presence or absence of trees % Area of side border zone Presence or absence of annuals Presence or absence of perennials Presence or absence of shrubs Presence or absence of trees % Area of entrance border zone Presence or absence of annuals Presence or absence of perennials Presence or absence of shrubs Presence or absence of trees Presence or absence of wall zone Presence or absence of annuals on wall Presence or absence of perennials on wall Number of flower boxes on the first storey Presence or absence of white flowers Presence or absence of red flowers Presence or absence of blue flowers Presence or absence of yellow flowers Number of flower boxes on the second storey Presence or absence of white flowers Presence or absence of red flowers Presence or absence of blue flowers Presence or absence of yellow flowers Number of flower boxes on the third storey Presence or absence of white flowers Presence or absence of red flowers Presence or absence of blue flowers Presence or absence of yellow flowers % Area of lawn Tidiness of front yard on a scale of 1 to 10 % residence visibility from the sidewalk % tree coverage Number of planted trees Number of spontaneous trees
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distribution of the vegetation, we divided the front yards into six separate zones ŽFig. 3. and estimated in percent area each vegetation zone. The front zone is where we usually find the fence andror the hedge. The side zone is where we find mostly fences, hedges, perennials and annuals. The entrance zone is where are often planted annuals or two pyramid-like shrubs, ‘standing guard’. The foundation zone is where residents plant shrubs, perennials and annuals to hide the foundations of the residence. The center zone, which can in some occasions occupy 100% of the front-yard garden, is generally covered by grass with a tree, a shrub, perennials or annuals planted in the center. Finally, the frontwall zone is where flower boxes and pots are found, as well as climbing species. In the case of the frontwall zone, the descriptors indicate the number of flower boxes for the first, the second and the third storey, the presence or absence of red, white, yellow or blue flowers for each storey, as well as the presence or absence of climbing species. For the assessment of the vegetation structure, we used binary descriptors to indicate the presence or absence of annual herbs, perennial herbs, shrubs and tree strata for each of the six front-yard zones. We also added semiquantitative descriptors to measure in percent cover the lawn area in every front-yard garden, the visibility of the residence from the sidewalk Žto determine if the landscape is closed or open. and the tidiness of the gardens. This second set of descriptors, characterizing the distribution and structure of the vegetation in a front yard, are the structural descriptors ŽTable 2.. The third set of descriptors, the abiotic descriptors, describe the nonvegetated areas: the presence or absence of a fence, percent area of the walkway and of surfaces deprived of vegetation generally found along the foundations of the residences. Additional descriptors needed to characterize the nature of nonvegetated areas indicate the presence or absence of bare earth, cement, asphalt, paving stones, cement blocks, limestone, white gravel or mulch for the walkway and for all surfaces deprived of vegetation. 2.4. Raw data matrices Four raw data matrices were created for every street section. The first matrix, the total matrix,
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contains all of the 250 descriptors. The second matrix includes only the abiotic descriptors. The third matrix, the structural matrix, has all of the descriptors quantifying and characterizing the distribution and structure of the vegetation. The fourth matrix, the composition matrix, is composed of the species descriptors. The organization of the descriptors into four raw data matrices allows us to measure the repetition of front-yard elements at four different levels of interpretation Žor perception.. As an example, let us consider the presence of a Fir and a Spruce in two front gardens. Because the interpretation of a resident varies from one to another, some of them will make the distinction between the two trees, whereas others will consider them both as ‘Christmas trees’. The same situation occurs for hedges, shrubs, perennials and annuals where the height, shape and location of the greenery, as well as the color of the flowers, will prevail for many residents over the species of the plants. The four categories of matrices also allow us to measure four levels of interpretation, or perception, ranging from detail to general features. For example, in the case of the composition matrix, two hedges, one of Honeysuckle and the other of Cotoneaster, each located in two different front yards will indicate a degree of similarity of 0 on a scale of 0 to 1 with the Jaccard coefficient. On the other hand, the similarity coefficient in the structural matrix will be 1, since both species are part of the shrub stratum. Finally, in the case of the total matrix, both scores will be computed to produce a similarity value of about 0.5, depending on the similarity coefficient chosen.
2.6. Distance matrices The spatial variable is represented in the form of a matrix of relative distances Žcalculated with the Euclidean distance coefficient.. Although the average width of the front yards varied from about 8 to 14 m, we standardized the width of every front yard and gave them all a value of 1. Our greatest distance calculated is 33.1, corresponding to the two front yards located at both ends of D’Orleans street section. Also, the distances among all pairs of front yards in the street sections were grouped into distance classes. For every street section, the number of distance classes equals the greatest number of front yards, of either sides of street sections, minus one. 2.7. Mantel correlograms To measure the relationship between the landscape of the front yards and distance in a street section, we used Mantel correlograms. This statistical method illustrates the relationship existing between the ecological matrices Žcomposed of frontyard vegetation and nonvegetated area similarity values. and distance class matrices Žincluding all distance classes among the front yards of a street section.. The result is a Mantel multivariate correlogram in which the values of the normalized Mantel statistic Ž r . is plotted against the distance classes. The r value associated to each distance class is tested for significance either by permutation or by Mantel’s normal approximation ŽLegendre and Fortin, 1989..
3. Results 2.5. Similarity matrices 3.1. Total matrix In order to be able to compare the similarity of the landscape of all the front yards in the 17 street sections, the four raw data matrices were transformed into association matrices using for each a different similarity coefficient ŽSteinhaus similarity coefficient for the total matrix, Jaccard community coefficient for the composition matrix, Gower asymmetric coefficient for the structural matrix, Gower symmetric coefficient for the abiotic matrix..
3.1.1. Complete street sections Mantel correlogram results of the front-yard vegetation and nonvegetated areas for the 17 street sections can be divided into four groups. Fig. 4a,b,c and d show a typical correlogram for each group of street sections. Group one is composed of 10 street sections and is represented in Fig. 4a by the Aylwin street section.
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Group two contains three street sections and is represented in Fig. 4b by the Desjardins street section. This group of street sections shows intermediate values in the first classes. Values range from 0.1 to 0.2393 for class one. The first two or three classes, as well as one to four middle classes, remain significant in each correlogram. There is overall significance in the correlograms of group two, at least two values exceed the Bonferroni-corrected level in each correlogram. Group three is composed of three street sections. Letourneux street section in Fig. 4c is typical of this group. It has low values in the first classes compared to both previous groups. Class one values range from 0.04927 to 0.08393. Middle classes show few significant values. Although the r values are low, there is overall significance at a local scale, since the first class in each street section exceeds the Bonferronicorrected level. The fourth group is composed of only the Valois street section ŽFig. 4d.. This street section is unique in our study because there are only eight residences on the street Ža football field occupies the west side street section., and the semidetached residences, as well as the dimensions of their front yards, are identical, as opposed to the other street sections. These duplexes were built in 1953 in a common project. As seen in Fig. 4d, there are only seven distance classes. The r values for the first and the fifth class are respectively, 0.34558 and y0.43854. These values are high and significant. However because Valois street section has only eight front yards, the r values must be higher to obtain overall significance of the correlogram. Fig. 4. Four types of front-yard spatial structures identified in Hochelaga–Maisonneuve street sections.
This group of 10 streets has high values of r in the first classes. The r values in class one range from 0.3 to 0.51. The first three or four classes are significantly spatially autocorrelated. Middle classes are also significant but at values ranging from y0.05 to y0.1959. There is overall significance in the correlograms, since several of the individual values exceed the Bonferroni-corrected level, p s 0.05rnumber of classes.
3.1.2. Same side street sections Mantel correlograms of front-yard vegetation and of nonvegetated areas were also performed on same side street sections. The orientation of the sampled street sections is North–South. We therefore performed Mantel correlograms on east and west sides of all street sections. An example of complete street section, east and west side street section results is illustrated in Fig. 5a,b and c with D’Orleans street correlograms. The shapes of the east and west side correlograms resemble the ones of the complete street sections. There is a positive autocorrelation zone in
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most autocorrelated or regionalized variables are those of Ž1. the structural matrix representing the distribution and structure of the front-yard vegetation Ž11 out of 17., Ž2. the abiotic matrix corresponding to the front-yard nonvegetated areas Ž4 out of 17., and Ž3. the composition matrix containing all plant species Ž2 out of 17.. An example of correlograms of these variables is given in Fig. 6a,b,c and d with the Moreau street section. The shapes of these correlograms are similar to the ones in the complete street
Fig. 5. Comparison of front-yard spatial structure of the complete street section, east and west side street sections for D’Orleans ´ street.
the first classes; however, it generally extends one or two classes further than for the complete street sections. The negative autocorrelation zone is also present in the east and west sides of the street sections, but it is situated at greater distances. Also noticeable is the steeper drop from positive to negative values in complete street sections for the fifth class. Although in some cases, the first class value in east and west side correlograms is higher, less classes are significant because the number of front yards decrease by about half for same side street sections. 3.2. Abiotic, composition and structural matrices Mantel correlograms were performed for each street section on abiotic Žnonvegetated areas., composition Ž196 species. and structural Ždistribution and structure of the vegetation. matrices. These variables are autocorrelated at various degrees. In rank, the
Fig. 6. Comparison of the importance of the various descriptor matrices in detecting patterns in Moreau street section.
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sections and same side street sections. In most street sections the shape of the correlograms of the structural matrix resembles the ones of the total matrix as seen in Fig. 6a and b. 4. Discussion Because there is significant positive autocorrelation in the small distance classes and a significant negative autocorrelation in the middle distances, the overall shape of most correlograms can be attributed to patches of front yards composed of similar vegetation and nonvegetated areas within street sections. The front-yard landscape of a street section is therefore composed of an aggregation of patches, rather than being randomly distributed. Jim Ž1993. mentioned that tree distribution within streets indicated a clear pattern of spatial congregation in a suburban residential neighborhood of Hong Kong. As well, Rowntree Ž1988. suggested that the distribution of tree crowns in a Dayton residential area in Ohio did not reveal the grid pattern of streets and properties but rather a somewhat random array of larger and smaller islands. The patches of similar front yards in Hochelaga–Maisonneuve street sections, as well as the aggregation phenomena noted in Hong Kong and Dayton, can be related to the mimicry activities undertaken at a local scale by nearby residents. As the results indicate, the relationship between similarity of front-yard landscape and proximal distances attains various positive values. The highest value is 0.50990 for a complete street section and 0.81019 for a same-side street section. This translates to an average similarity of 50.9% of front-yard descriptors in first lateral neighboring front yards in Dezery street section ŽFig. 7a. and 81.0% in first neighboring front yards in Joliette west side street section ŽFig. 7b.. The statistical significance of these results is very high Ž p - 0.00001., as well as for most first classes in other street-section correlograms. We can therefore presume the existence of a mimicry process, where repetition of vegetation and of nonvegetated area descriptors occurs in front yards of close neighbors within street sections of Hochelaga–Maisonneuve. In all cases, the zone of significant influence Ž p - 0.05. of multivariate autocorrelation is 1 to 4 distance classes, or front yards. Since front yards
Fig. 7. Some extreme cases of autocorrelated front-yard structure: Ža. the highest values for first distance class in complete street sections; Žb. the highest values in first distance class in same side street sections; Žc. the widest zone of influence Žseven front yards. for a complete street section; Žd. the weakest spatial structure for a complete street section.
have a mean width of about 9 m, the average zone of significant influence extends from 9 to 36 m for all front yards. If we extend our consideration to all first classes with positive autocorrelation Ž r ) 0., Fig. 7c,d, it defines the zone of influence where the vegetation and the nonvegetated areas of front yards have more chances of being similar than dissimilar.
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Fig. 8. A strong mimicry is evident in these two adjacent front-yard gardens ŽDesjardins street.. Both have a front hedge of the same species and the two yards are separated by a common iron fence. Even though species may differ, the structure of both yards is identical: grassed center zone with a central element Žurn planter on the left, Hostas on the right.; plants on side of middle fence; plants along foundations and sides of walkways. The house on the left differs by having balcony flowers.
The gap between recurring patch centers of similar front yards varies from two front yards Ž18 m for the La Salle street section which has the weakest spatial structure. to seven front yards Ž63 m for the
Joliette street section which has the greatest average gap between recurring patch centers.. As described above, it seems that in Hochelaga– Maisonneuve residential street sections, there exists a
Fig. 9. Mimicry in several adjacent front-yard gardens ŽLa Salle street.. All show identical front hedges, grassed center zones, white gravel areas under the balcony, annuals near foundation walls, and two coniferous ball shrubs on each side of the stairsrwalkways.
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Fig. 10. Adjacent front-yard gardens ŽLetourneux street. all showing very simple and similar structure of grassed area with large plants Ž Hydrangea, Ribes, Cornus, Viburnum. hiding the foundations.
contagious form of mimicry where vegetation and nonvegetated area characteristics are repeated at local scales Žtwo to seven front yards., see Figs. 8–10. Such results support the feasibility of the concept of nonrandom management of urban residential front yards in Hochelaga–Maisonneuve and in other similar cities of Canada and of the United States. In some areas of the sampled street sections of Hochelaga– Maisonneuve, we have observed almost exact reproductions of front yards, mostly in a linear pattern, thus exhibiting strong mimicry by the concerned residents. Residents on the opposite side of a street also seem to be influenced by the landscape of opposite front yards, but in a much more subtle fashion. Instead of mimicking exactly what they see in opposite front yards they seem to modify, or avoid, the more relevant features of the vegetation and nonvegetated areas in order to remain original in relation to their facing neighbors. Jim Ž1993. noted two somewhat opposing forces in the composition of front-garden trees in a suburb of Hong Kong, uniformity vs. diversification, or conformity vs. individualism. Overall, the same spatial patterns apply for same side street sections, except that Ž1. Mantel r values are slightly higher, Ž2. that the zone of influence is
generally larger and Ž3. that we notice a smoother drop in the negative r values than in the case of complete street sections. This could suggest that complicity among residents of a same side street section is greater than across street sections. As for the steeper drop in the fifth distance class in complete street section correlograms, it supports the interpretation of the resident ‘originality behavior’ phenomenon observed in opposite street side front yards, because opposing gardens on each side of a street are five distance classes apart Žone distance class for each sidewalk and two distance classes for the street.. The analysis of the composition, structural and abiotic matrices shows that structural descriptors Ždistribution and structure of vegetation. are the most repeated Žcopied. ones in proximal front yards Že.g., Fig. 8.. As can be seen in Fig. 6a and b, the distribution and structure of the vegetation Ž49 descriptors. is responsible for the overall shape and values of the general correlogram of Moreau street section, as well as for 10 other street sections. The combined results of composition and abiotic matrices is given in Fig. 6c. This result suggests that residents in Hochelaga–Maisonneuve are not influenced by plant species as much as by the shape, color and
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location of the vegetation. As mentioned earlier, a Spruce and a Fir remains a ‘Christmas tree’ for most residents. The same occurs for a Honeysuckle or a Cotoneaster hedge. Residents do not always make the distinction; most of them will be satisfied to reproduce in their front yard a hedge of any species that simply looks like the one in the neighbor’s yard. Red Begonias and red Impatiens in flower boxes look more similar to many residents than Begonias Žor Impatiens. of differing colors.
5. Conclusion The findings of this study provide strong support of our initial hypothesis, that management of frontyard vegetation and nonvegetated areas in a street section is not a random process. On the contrary, spatial structures of contagious form of all front-yard variables analysed suggest the existence of resident interactions in all Hochelaga–Maisonneuve street sections sampled. The resident interactions are more specifically of mimicry type, where proximal front yards share significantly more common characteristics than distal yards. This mimicry process reaches its highest expression in the distribution and structure of front-yard vegetation at local scales. This strongly suggests that residents in a street section are influenced by the shape, color and location of the vegetation they see in the front yards of nearest neighbors. The landscape spatial regularities found in all the street sections of Hochelaga–Maisonneuve are an expression of a contagious mode of landscape management that can be generalized to many types of urban areas. Because the process of contagion studied is fundamentally an anthropic phenomenon, we can presume of its existence in suburban and rural ecosystems as well. Finally, we believe that to better understand the dynamics of vegetation and landscape in cities, one cannot exclude the concept of anthropic contagion based on mimicry.
Acknowledgements This paper represents part of a thesis submitted to the Universite´ du Quebec a` Montreal ´ ´ in partial ful-
fillment for the PhD degree in Environmental Sciences. We thank Pierre Legendre and Alain Vaudor who provided a copy of their ‘R package’ statistical computer program, as well as documentation and valuable comments on the methods used. We also thank Pierre Dansereau for sharing his immense knowledge of human ecosystems, Patrick Nantel for all our conversations, which were very helpful all throughout this research, as well as Marc Lavarenne for his contribution in producing the figures. This research was partially supported by internal funds of the Universite´ du Quebec a` Montreal. This ´ ´ manuscript also benefited from the comments of Gerald Domon ŽUniversite´ de Montreal ´ ´ . and of two anonymous reviewers.
References Eveillard, C., 1991. Montreal ´ cote ˆ ´ jardins. Master’s thesis, Universite´ de Montreal, ´ 122 pp. Jim, C.Y., 1993. Trees and landscape of a suburban residential neighbourhood in Hong Kong. Landscape Urban Planning 23, 119–143. Last, F.T., Good, J.E.G., Watson, R.H., Gried, D.A., 1976. The city of Edinburgh—its stock of trees: a continuing amenity and timber resource. Scott. For. 30, 112–126. Legendre, P., 1985. The ‘R’ package for multivariate data analysis. Departement de sciences biologiques, Universite´ de Mon´ treal, ´ Montreal, ´ Canada. Legendre, P., Fortin, M.-J., 1989. Spatial pattern and ecological analysis. Vegetatio 80, 107–138. Plante, S., Simoneau, L., 1986. Hochelaga–Maisonneuve, Atlas socio-economique. Atelier d’histoire Hochelaga–Maison´ neuve. Richards, N.A., Mallette, J.R., Simpson, R.J., Macie, E.A., 1984. Residential greenspace and vegetation in a mature city: Syracuse, NY. Urban Ecol. 8, 99–125. Routaboule, D., Asselin, V., Eveillard, C., 1995. Le paysage de l’interieur ou expressions paysageres dans l’ıle ´ ` residentielles ´ ˆ de Montreal. ´ Report to the Canadian Mortgage and Housing Corporation, 116 pp. Rowntree, R.A., 1984a. Forest canopy cover and land use in four eastern United States cities. Urban Ecol. 8, 55–67. Rowntree, R.A., 1984b. Ecology of the urban forest: Part I. Structure and composition. Urban Ecol. 8, 1–178, Special Issue. Rowntree, R.A., 1986. Ecology of the urban forest: Part II. Function. Urban Ecol. 9, 227–434, Special Issue. Rowntree, R.A., 1988. Ecology of the urban forest: Part III. Mapping, preferences and planning. Landscape Urban Planning 15, 1–224, Special Issue.
J. Zmyslony, D. Gagnonr Landscape and Urban Planning 40 (1998) 295–307 Sanders, R.A., 1983. Configuration of tree canopy cover in urban land use. Geogr. Perspect. 51, 49–53. Sanders, R.A., 1984. Some determinants of urban forest structure. Urban Ecol. 8, 13–27. Schmid, J.A., 1975. Urban vegetation: a review and Chicago case study. University of Chicago, Department of Geography, Research Paper No. 161. Sukopp, H., Werner, P., 1983. Urban environments and vegeta-
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tion. In: Holzner, W., Wegner, M.J.A., Ikusima, I. ŽEds.., Man’s Impact on Vegetation. W.H. Junk, The Hague, pp. 247–260. Tobler, W.R., 1970. A computer movie simulating urban growth in the Detroit region. Econ. Geogr. 46, 234–240. Zmyslony, J., 1997. La contagion du paysage des jardins-fac¸ades urbains: demonstration, modelisation et theorisation. PhD the´ ´ ´ sis, Universite´ du Quebec a` Montreal, ´ ´ 132 pp.
Residential management of urban front-yard landscape: A random process? Jean Zmyslony, Daniel Gagnon
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´ Groupe de Recherche en Ecologie Forestiere, ` UniÕersite´ du Quebec ´ a` Montreal, ´ C.P. 8888, Succursalle Centre Õille, Montreal, ´ Quebec, ´ Canada H3C 3P8 Received 6 January 1997; revised 22 September 1997; accepted 19 November 1997
Abstract In order to understand the management dynamics of urban residential vegetation at local scales, we studied nonvegetated areas and the vegetation composition, distribution and structure of front yards in 17 successive residential street sections of Hochelaga–Maisonneuve District, Montreal. ´ We systematically sampled 646 front yards. A total of 250 descriptors were used to characterize the landscape Žcontent. of every front yard. We then measured the similarity of vegetation and nonvegetated areas in each front yard in relation with distance for all street sections. Mantel correlograms allow us to examine the spatial structure of front-yard landscape at local scales. Results show that front-yard landscape is Ž1. an autocorrelated Žor regionalized. variable, Ž2. that the spatial structure of the vegetation and nonvegetated areas is of contagious form and Ž3. that distribution and structure of the vegetation is the most repeated Žcopied. feature at local scales. A statistically distinct neighbor influence occurs among front yards in all street sections, which often exceeds the probability level p s 0.00001. This strong neighbor ‘mimicry’ effect has potential use in municipal environment improvement strategies that rely on resident actions. q 1998 Elsevier Science. All rights reserved. Keywords: Contagious distribution; Residential vegetation; Mantel correlogram; Mimicry; Spatial structure; Street section
1. Introduction Most investigations of urban vegetation and greenspaces have focused on public areas, and especially on trees of the urban forest ŽRowntree, 1984b, 1986, 1988.. Very little interest has been shown to the urban vegetation of private lots. The main reasons for this lack of interest are probably Ž1. the )
Corresponding author. Tel.: q1-514-987-3000-7751; fax: q1-514-987-4647; e-mail: [email protected].
great diversity of this type of vegetation, Ž2. the large number of owners or managers, Ž3. the difficulty involved in quantifying anthropic processes and Ž4. this type of vegetation and greenspaces has not generally been a direct subject of public policy and decisions. For comparison purposes, according to Richards et al. Ž1984., public street sides, public parks and residential greenspaces account respectively for 7%, 9% and 48% of the total greenspaces in Syracuse, NY. The study of Last et al. Ž1976., one of the few urban tree inventories to include residen-
0169-2046r98r$19.00 q 1998 Elsevier Science B.V. All rights reserved. PII S 0 1 6 9 - 2 0 4 6 Ž 9 7 . 0 0 0 9 0 - X
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tial vegetation, revealed that 84% of the trees of Edinburgh, Scotland, were on residential lots. Residential vegetation, although evidently prominent, remains an overlooked urban resource. Previous studies of urban and residential vegetation were carried out at large scales, such as districts or cities. Rowntree Ž1984a., Sanders Ž1983., Sukopp and Werner Ž1983. described land use as a major factor of urban tree composition and distribution. Schmid Ž1975. has associated the development of urban vegetation to socioeconomic characteristics of residents and age of development. Sanders Ž1984. mentioned that urban forest is determined by three broad factors: urban morphology, natural factors and human management systems. As Sanders Ž1984. noted, we consider that urban vegetation management systems are presumably as varied as the number of actors that impinge upon them. However, at local scales, we suggest that similarities exist among the vegetation and nonvegetated areas managed by different residents in a street section, and therefore give rise to generalizations and regularities worth studying. Richards et al. Ž1984. wrote that the observation of front yards in residential lots with detached houses, as in Syracuse and many other communities, suggests the interaction of residents within the neighborhood. Jim Ž1993. mentioned that proximity of homes Žin the same street. in a suburb of Hong Kong could lead to the adoption of similar tree species. Routaboule et al. Ž1995. noted that residents propagate landscape forms in their neighborhood mainly through observation. Resident interaction can be associated to various types of behaviours. Residents may, for example, reproduce what they see in the front yards of their street section. Routaboule et al. Ž1995. noticed a driving effect in the residential areas of Montreal. ´ These authors suggested that residents first observe what neighbors do in their garden, then they copy, they adapt and occasionally exchange plants among themselves. Also, Eveillard Ž1991. mentions that in Montreal ´ residential districts, a number of plants found in resident front yards are the results of neighbors’ suggestions. The actions of residents that copy, adapt, exchange plants and suggest ideas at a local scale are good examples of mimicry. If all of these combined resident actions included in the mimicry effect are important, similar plants and landscape
elements will be propagated in the neighborhood. Eventually, spatial regularities will emerge in front yards that can be detected by appropriate spatial statistical methods Ži.e., Legendre, 1985.. Some residents may react differently. They may intentionally avoid copying the content of neighboring front yards and manage their front garden with plants of different species, shapes or colors. Others may seem totally indifferent to the landscape of the front yards in the street section, including their own, while a few may create a totally new arrangement of plants, colors and shapes in their neighborhood. Such new arrangements of plants and landscapes can then provide new models for nearby residents to mimic. In our investigation, we hypothesize that residential front-yard landscape is a dependent variable, which is to say that the vegetation and the nonvegetated areas of residential front yards are not randomly distributed in a street section. To test this hypothesis, we will try to demonstrate that the landscape of residential front yards is an autocorrelated Žor regionalized. variable at a local scale. The existence of spatial autocorrelation assumes that any object in space is affected by the objects around it, and that closer objects have more effect than those which are further away ŽTobler, 1970.. Autocorrelation also implies that it is possible to predict various descriptors of front-yard landscape at some points in space within a street section. Our study of residential vegetation in Hochelaga–Maisonneuve is part of a greater case study of the processes responsible for the development of vegetation within street sections. Our goal is to understand the dynamics of urban residential vegetation at local scales in order to propose management strategies for the greening of urban environments, centered on resident actions.
2. Methods 2.1. Hochelaga–MaisonneuÕe district study area The Hochelaga–Maisonneuve District ŽFig. 1. was founded originally before 1870 as two independent cities in the eastern part of Montreal, ´ near the 1976 Olympic Stadium. It covers an area of 8.2 km2 . Its economical and industrial development reached a
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Fig. 1. General location of the Hochelaga–Maisonneuve District on Montreal ´ Island.
peak before the Great Depression. In the sixties, the old industrial structures of Hochelaga–Maisonneuve started to collapse. Its population began to drift towards new urban districts and the suburbs. Today, Plante and Simoneau Ž1986. estimate the population at about 53,000 inhabitants, 90% being Francophones. The Hochelaga–Maisonneuve District was chosen for this study because Žas at the time of its annexation to Montreal ´ in 1918. it remains a city within a city, with its own industrial, institutional, commercial and residential zones. Such a district allows us to analyse the residential vegetation and landscape at the scale of a true urban ecosystem. Consequently, our results could be generalized to other urban ecosystems in North America. The sampled residential area is situated in the northern part of Hochelaga–Maisonneuve, a relatively homogeneous section of the District. Its population belongs to the middle class and shares common socioeconomic characteristics. Over 71% of the residences were built between 1946 and 1970 ŽPlante and Simoneau, 1986.. The sampled area is roughly a rectangle bordered by major discontinuities, providing greater homogeneity. These discontinuities are, in the north, Sherbrooke Street and the Montreal ´ Olympic Park, in the east, part of the Praimont Industrial Sector, in the south, Hochelaga Street Žwhich like Sherbrooke St.
is a main commercial and transportation artery. and in the west, the Canadian Pacific Railway tracks. This area is composed of 17 successive residential street sections, all of them parallel, with a more or less north–south orientation ŽFig. 2.. The 17 street sections contain 646 residences, each of which has a private front-yard garden space. The residences are
Fig. 2. Study area Žshaded. and sampled street sections in the northern sector of Hochelaga–Maisonneuve District. Nicolet, Charlemagne and Pie-IX streets were not sampled because they are nonresidential.
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Table 1 Street section and front-yard characteristics Street sectionsa
Number of front yards
Single-family
Two-family
Several-family Ž3–6.
Multi-family Ž7 q .
Width Žm.
Depth Žm.
Spatial structure
Moreau Prefontaine ´ Dezery ´ St-Germain Darling Davidson Cuvillier Aylwin Joliette Chambly Valois Bourbonniere ` D’Orleans ´ Jeanne D’Arc Desjardins La Salle Letourneux
37 24 30 25 28 41 46 39 47 23 8 59 64 49 48 48 34
1 y y y y 2 y 1 9 y y y y y y y y
22 20 13 16 25 27 19 21 27 y 8 24 32 35 39 39 28
9 y 17 9 y 4 19 1 2 y y 21 24 3 8 8 3
5 4 y y 3 8 8 16 9 23 y 14 8 11 1 1 3
11.1 13.3 9.2 11.4 7.7 9.6 9.3 9.7 9.5 9.8 11.9 8.8 9.4 10.1 8.9 8.9 12.3
5.2 6.3 5.8 5.6 7.3 6.3 6.2 6 7.6 6.7 8.2 5.4 4.2 4.9 4.5 4.5 5.6
strong intermediate strong intermediate strong strong strong strong strong strong strong weak strong strong intermediate weak weak
a Street sections are ordered from West to East in the column. The widths and depths of the gardens are average numbers. The spatial structure of the landscape in the street is divided into three different classes: strong, intermediate and weak.
predominantly duplexes Ž383., triplexes Ž129. and multiplexes Ž121.. A few single-family homes Ž13. are also found. Further characteristics of street sections are given in Table 1. 2.2. Sampling scale In order to study vegetation management in the residential front yards, we decided to proceed at the scale of a residential street section. We consider the street section as being the most appropriate ecological system to study the effects of resident interaction processes on the development of residential vegetation. The street sections in Hochelaga–Maisonneuve are composed of 8 to 64 residences and constitute the immediate environment of each resident. The main crossroads at both ends of the 17 street sections are the first psychological and visual discontinuities encountered by the residents. Such barriers increase the feeling of belonging of the residents to the street section. In these conditions, if forms of resident interaction are present, they should flow freely among residents and eventually be expressed by spatial patterns within the residential vegetation and front-yard
nonvegetated areas. The 646 front-yard gardens were sampled from June 5 to August 25, 1992. 2.3. Sets of descriptors Because 196 species were found in the sampled area ŽZmyslony, 1997., the first set of sampled descriptors contains 196 composition binary descriptors, each of them indicating the presence or absence of a species in every front yard.
Fig. 3. Illustration of the six front-yard zones: Ž1. the wall zone; Ž2. the foundation zone; Ž3. the entrance zone; Ž4. the center zone; Ž5. the side zone; and Ž6. the front zone, ŽA. is the walkway and ŽB. the sidewalk.
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The second set of sampled descriptors is used to describe the structure and distribution of the vegetation in each front-yard garden. In order to assess the Table 2 Description of the 49 descriptors of the structural matrix 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49
% Area or front border zone Presence or absence of annuals Presence or absence of perennials Presence or absence of shrubs Presence or absence of trees % Area of center border zone Presence or absence of annuals Presence or absence of perennials Presence or absence of shrubs Presence or absence of trees % Area of foundation border zone Presence or absence of annuals Presence or absence of perennials Presence or absence of shrubs Presence or absence of trees % Area of side border zone Presence or absence of annuals Presence or absence of perennials Presence or absence of shrubs Presence or absence of trees % Area of entrance border zone Presence or absence of annuals Presence or absence of perennials Presence or absence of shrubs Presence or absence of trees Presence or absence of wall zone Presence or absence of annuals on wall Presence or absence of perennials on wall Number of flower boxes on the first storey Presence or absence of white flowers Presence or absence of red flowers Presence or absence of blue flowers Presence or absence of yellow flowers Number of flower boxes on the second storey Presence or absence of white flowers Presence or absence of red flowers Presence or absence of blue flowers Presence or absence of yellow flowers Number of flower boxes on the third storey Presence or absence of white flowers Presence or absence of red flowers Presence or absence of blue flowers Presence or absence of yellow flowers % Area of lawn Tidiness of front yard on a scale of 1 to 10 % residence visibility from the sidewalk % tree coverage Number of planted trees Number of spontaneous trees
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distribution of the vegetation, we divided the front yards into six separate zones ŽFig. 3. and estimated in percent area each vegetation zone. The front zone is where we usually find the fence andror the hedge. The side zone is where we find mostly fences, hedges, perennials and annuals. The entrance zone is where are often planted annuals or two pyramid-like shrubs, ‘standing guard’. The foundation zone is where residents plant shrubs, perennials and annuals to hide the foundations of the residence. The center zone, which can in some occasions occupy 100% of the front-yard garden, is generally covered by grass with a tree, a shrub, perennials or annuals planted in the center. Finally, the frontwall zone is where flower boxes and pots are found, as well as climbing species. In the case of the frontwall zone, the descriptors indicate the number of flower boxes for the first, the second and the third storey, the presence or absence of red, white, yellow or blue flowers for each storey, as well as the presence or absence of climbing species. For the assessment of the vegetation structure, we used binary descriptors to indicate the presence or absence of annual herbs, perennial herbs, shrubs and tree strata for each of the six front-yard zones. We also added semiquantitative descriptors to measure in percent cover the lawn area in every front-yard garden, the visibility of the residence from the sidewalk Žto determine if the landscape is closed or open. and the tidiness of the gardens. This second set of descriptors, characterizing the distribution and structure of the vegetation in a front yard, are the structural descriptors ŽTable 2.. The third set of descriptors, the abiotic descriptors, describe the nonvegetated areas: the presence or absence of a fence, percent area of the walkway and of surfaces deprived of vegetation generally found along the foundations of the residences. Additional descriptors needed to characterize the nature of nonvegetated areas indicate the presence or absence of bare earth, cement, asphalt, paving stones, cement blocks, limestone, white gravel or mulch for the walkway and for all surfaces deprived of vegetation. 2.4. Raw data matrices Four raw data matrices were created for every street section. The first matrix, the total matrix,
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contains all of the 250 descriptors. The second matrix includes only the abiotic descriptors. The third matrix, the structural matrix, has all of the descriptors quantifying and characterizing the distribution and structure of the vegetation. The fourth matrix, the composition matrix, is composed of the species descriptors. The organization of the descriptors into four raw data matrices allows us to measure the repetition of front-yard elements at four different levels of interpretation Žor perception.. As an example, let us consider the presence of a Fir and a Spruce in two front gardens. Because the interpretation of a resident varies from one to another, some of them will make the distinction between the two trees, whereas others will consider them both as ‘Christmas trees’. The same situation occurs for hedges, shrubs, perennials and annuals where the height, shape and location of the greenery, as well as the color of the flowers, will prevail for many residents over the species of the plants. The four categories of matrices also allow us to measure four levels of interpretation, or perception, ranging from detail to general features. For example, in the case of the composition matrix, two hedges, one of Honeysuckle and the other of Cotoneaster, each located in two different front yards will indicate a degree of similarity of 0 on a scale of 0 to 1 with the Jaccard coefficient. On the other hand, the similarity coefficient in the structural matrix will be 1, since both species are part of the shrub stratum. Finally, in the case of the total matrix, both scores will be computed to produce a similarity value of about 0.5, depending on the similarity coefficient chosen.
2.6. Distance matrices The spatial variable is represented in the form of a matrix of relative distances Žcalculated with the Euclidean distance coefficient.. Although the average width of the front yards varied from about 8 to 14 m, we standardized the width of every front yard and gave them all a value of 1. Our greatest distance calculated is 33.1, corresponding to the two front yards located at both ends of D’Orleans street section. Also, the distances among all pairs of front yards in the street sections were grouped into distance classes. For every street section, the number of distance classes equals the greatest number of front yards, of either sides of street sections, minus one. 2.7. Mantel correlograms To measure the relationship between the landscape of the front yards and distance in a street section, we used Mantel correlograms. This statistical method illustrates the relationship existing between the ecological matrices Žcomposed of frontyard vegetation and nonvegetated area similarity values. and distance class matrices Žincluding all distance classes among the front yards of a street section.. The result is a Mantel multivariate correlogram in which the values of the normalized Mantel statistic Ž r . is plotted against the distance classes. The r value associated to each distance class is tested for significance either by permutation or by Mantel’s normal approximation ŽLegendre and Fortin, 1989..
3. Results 2.5. Similarity matrices 3.1. Total matrix In order to be able to compare the similarity of the landscape of all the front yards in the 17 street sections, the four raw data matrices were transformed into association matrices using for each a different similarity coefficient ŽSteinhaus similarity coefficient for the total matrix, Jaccard community coefficient for the composition matrix, Gower asymmetric coefficient for the structural matrix, Gower symmetric coefficient for the abiotic matrix..
3.1.1. Complete street sections Mantel correlogram results of the front-yard vegetation and nonvegetated areas for the 17 street sections can be divided into four groups. Fig. 4a,b,c and d show a typical correlogram for each group of street sections. Group one is composed of 10 street sections and is represented in Fig. 4a by the Aylwin street section.
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Group two contains three street sections and is represented in Fig. 4b by the Desjardins street section. This group of street sections shows intermediate values in the first classes. Values range from 0.1 to 0.2393 for class one. The first two or three classes, as well as one to four middle classes, remain significant in each correlogram. There is overall significance in the correlograms of group two, at least two values exceed the Bonferroni-corrected level in each correlogram. Group three is composed of three street sections. Letourneux street section in Fig. 4c is typical of this group. It has low values in the first classes compared to both previous groups. Class one values range from 0.04927 to 0.08393. Middle classes show few significant values. Although the r values are low, there is overall significance at a local scale, since the first class in each street section exceeds the Bonferronicorrected level. The fourth group is composed of only the Valois street section ŽFig. 4d.. This street section is unique in our study because there are only eight residences on the street Ža football field occupies the west side street section., and the semidetached residences, as well as the dimensions of their front yards, are identical, as opposed to the other street sections. These duplexes were built in 1953 in a common project. As seen in Fig. 4d, there are only seven distance classes. The r values for the first and the fifth class are respectively, 0.34558 and y0.43854. These values are high and significant. However because Valois street section has only eight front yards, the r values must be higher to obtain overall significance of the correlogram. Fig. 4. Four types of front-yard spatial structures identified in Hochelaga–Maisonneuve street sections.
This group of 10 streets has high values of r in the first classes. The r values in class one range from 0.3 to 0.51. The first three or four classes are significantly spatially autocorrelated. Middle classes are also significant but at values ranging from y0.05 to y0.1959. There is overall significance in the correlograms, since several of the individual values exceed the Bonferroni-corrected level, p s 0.05rnumber of classes.
3.1.2. Same side street sections Mantel correlograms of front-yard vegetation and of nonvegetated areas were also performed on same side street sections. The orientation of the sampled street sections is North–South. We therefore performed Mantel correlograms on east and west sides of all street sections. An example of complete street section, east and west side street section results is illustrated in Fig. 5a,b and c with D’Orleans street correlograms. The shapes of the east and west side correlograms resemble the ones of the complete street sections. There is a positive autocorrelation zone in
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most autocorrelated or regionalized variables are those of Ž1. the structural matrix representing the distribution and structure of the front-yard vegetation Ž11 out of 17., Ž2. the abiotic matrix corresponding to the front-yard nonvegetated areas Ž4 out of 17., and Ž3. the composition matrix containing all plant species Ž2 out of 17.. An example of correlograms of these variables is given in Fig. 6a,b,c and d with the Moreau street section. The shapes of these correlograms are similar to the ones in the complete street
Fig. 5. Comparison of front-yard spatial structure of the complete street section, east and west side street sections for D’Orleans ´ street.
the first classes; however, it generally extends one or two classes further than for the complete street sections. The negative autocorrelation zone is also present in the east and west sides of the street sections, but it is situated at greater distances. Also noticeable is the steeper drop from positive to negative values in complete street sections for the fifth class. Although in some cases, the first class value in east and west side correlograms is higher, less classes are significant because the number of front yards decrease by about half for same side street sections. 3.2. Abiotic, composition and structural matrices Mantel correlograms were performed for each street section on abiotic Žnonvegetated areas., composition Ž196 species. and structural Ždistribution and structure of the vegetation. matrices. These variables are autocorrelated at various degrees. In rank, the
Fig. 6. Comparison of the importance of the various descriptor matrices in detecting patterns in Moreau street section.
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sections and same side street sections. In most street sections the shape of the correlograms of the structural matrix resembles the ones of the total matrix as seen in Fig. 6a and b. 4. Discussion Because there is significant positive autocorrelation in the small distance classes and a significant negative autocorrelation in the middle distances, the overall shape of most correlograms can be attributed to patches of front yards composed of similar vegetation and nonvegetated areas within street sections. The front-yard landscape of a street section is therefore composed of an aggregation of patches, rather than being randomly distributed. Jim Ž1993. mentioned that tree distribution within streets indicated a clear pattern of spatial congregation in a suburban residential neighborhood of Hong Kong. As well, Rowntree Ž1988. suggested that the distribution of tree crowns in a Dayton residential area in Ohio did not reveal the grid pattern of streets and properties but rather a somewhat random array of larger and smaller islands. The patches of similar front yards in Hochelaga–Maisonneuve street sections, as well as the aggregation phenomena noted in Hong Kong and Dayton, can be related to the mimicry activities undertaken at a local scale by nearby residents. As the results indicate, the relationship between similarity of front-yard landscape and proximal distances attains various positive values. The highest value is 0.50990 for a complete street section and 0.81019 for a same-side street section. This translates to an average similarity of 50.9% of front-yard descriptors in first lateral neighboring front yards in Dezery street section ŽFig. 7a. and 81.0% in first neighboring front yards in Joliette west side street section ŽFig. 7b.. The statistical significance of these results is very high Ž p - 0.00001., as well as for most first classes in other street-section correlograms. We can therefore presume the existence of a mimicry process, where repetition of vegetation and of nonvegetated area descriptors occurs in front yards of close neighbors within street sections of Hochelaga–Maisonneuve. In all cases, the zone of significant influence Ž p - 0.05. of multivariate autocorrelation is 1 to 4 distance classes, or front yards. Since front yards
Fig. 7. Some extreme cases of autocorrelated front-yard structure: Ža. the highest values for first distance class in complete street sections; Žb. the highest values in first distance class in same side street sections; Žc. the widest zone of influence Žseven front yards. for a complete street section; Žd. the weakest spatial structure for a complete street section.
have a mean width of about 9 m, the average zone of significant influence extends from 9 to 36 m for all front yards. If we extend our consideration to all first classes with positive autocorrelation Ž r ) 0., Fig. 7c,d, it defines the zone of influence where the vegetation and the nonvegetated areas of front yards have more chances of being similar than dissimilar.
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Fig. 8. A strong mimicry is evident in these two adjacent front-yard gardens ŽDesjardins street.. Both have a front hedge of the same species and the two yards are separated by a common iron fence. Even though species may differ, the structure of both yards is identical: grassed center zone with a central element Žurn planter on the left, Hostas on the right.; plants on side of middle fence; plants along foundations and sides of walkways. The house on the left differs by having balcony flowers.
The gap between recurring patch centers of similar front yards varies from two front yards Ž18 m for the La Salle street section which has the weakest spatial structure. to seven front yards Ž63 m for the
Joliette street section which has the greatest average gap between recurring patch centers.. As described above, it seems that in Hochelaga– Maisonneuve residential street sections, there exists a
Fig. 9. Mimicry in several adjacent front-yard gardens ŽLa Salle street.. All show identical front hedges, grassed center zones, white gravel areas under the balcony, annuals near foundation walls, and two coniferous ball shrubs on each side of the stairsrwalkways.
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Fig. 10. Adjacent front-yard gardens ŽLetourneux street. all showing very simple and similar structure of grassed area with large plants Ž Hydrangea, Ribes, Cornus, Viburnum. hiding the foundations.
contagious form of mimicry where vegetation and nonvegetated area characteristics are repeated at local scales Žtwo to seven front yards., see Figs. 8–10. Such results support the feasibility of the concept of nonrandom management of urban residential front yards in Hochelaga–Maisonneuve and in other similar cities of Canada and of the United States. In some areas of the sampled street sections of Hochelaga– Maisonneuve, we have observed almost exact reproductions of front yards, mostly in a linear pattern, thus exhibiting strong mimicry by the concerned residents. Residents on the opposite side of a street also seem to be influenced by the landscape of opposite front yards, but in a much more subtle fashion. Instead of mimicking exactly what they see in opposite front yards they seem to modify, or avoid, the more relevant features of the vegetation and nonvegetated areas in order to remain original in relation to their facing neighbors. Jim Ž1993. noted two somewhat opposing forces in the composition of front-garden trees in a suburb of Hong Kong, uniformity vs. diversification, or conformity vs. individualism. Overall, the same spatial patterns apply for same side street sections, except that Ž1. Mantel r values are slightly higher, Ž2. that the zone of influence is
generally larger and Ž3. that we notice a smoother drop in the negative r values than in the case of complete street sections. This could suggest that complicity among residents of a same side street section is greater than across street sections. As for the steeper drop in the fifth distance class in complete street section correlograms, it supports the interpretation of the resident ‘originality behavior’ phenomenon observed in opposite street side front yards, because opposing gardens on each side of a street are five distance classes apart Žone distance class for each sidewalk and two distance classes for the street.. The analysis of the composition, structural and abiotic matrices shows that structural descriptors Ždistribution and structure of vegetation. are the most repeated Žcopied. ones in proximal front yards Že.g., Fig. 8.. As can be seen in Fig. 6a and b, the distribution and structure of the vegetation Ž49 descriptors. is responsible for the overall shape and values of the general correlogram of Moreau street section, as well as for 10 other street sections. The combined results of composition and abiotic matrices is given in Fig. 6c. This result suggests that residents in Hochelaga–Maisonneuve are not influenced by plant species as much as by the shape, color and
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location of the vegetation. As mentioned earlier, a Spruce and a Fir remains a ‘Christmas tree’ for most residents. The same occurs for a Honeysuckle or a Cotoneaster hedge. Residents do not always make the distinction; most of them will be satisfied to reproduce in their front yard a hedge of any species that simply looks like the one in the neighbor’s yard. Red Begonias and red Impatiens in flower boxes look more similar to many residents than Begonias Žor Impatiens. of differing colors.
5. Conclusion The findings of this study provide strong support of our initial hypothesis, that management of frontyard vegetation and nonvegetated areas in a street section is not a random process. On the contrary, spatial structures of contagious form of all front-yard variables analysed suggest the existence of resident interactions in all Hochelaga–Maisonneuve street sections sampled. The resident interactions are more specifically of mimicry type, where proximal front yards share significantly more common characteristics than distal yards. This mimicry process reaches its highest expression in the distribution and structure of front-yard vegetation at local scales. This strongly suggests that residents in a street section are influenced by the shape, color and location of the vegetation they see in the front yards of nearest neighbors. The landscape spatial regularities found in all the street sections of Hochelaga–Maisonneuve are an expression of a contagious mode of landscape management that can be generalized to many types of urban areas. Because the process of contagion studied is fundamentally an anthropic phenomenon, we can presume of its existence in suburban and rural ecosystems as well. Finally, we believe that to better understand the dynamics of vegetation and landscape in cities, one cannot exclude the concept of anthropic contagion based on mimicry.
Acknowledgements This paper represents part of a thesis submitted to the Universite´ du Quebec a` Montreal ´ ´ in partial ful-
fillment for the PhD degree in Environmental Sciences. We thank Pierre Legendre and Alain Vaudor who provided a copy of their ‘R package’ statistical computer program, as well as documentation and valuable comments on the methods used. We also thank Pierre Dansereau for sharing his immense knowledge of human ecosystems, Patrick Nantel for all our conversations, which were very helpful all throughout this research, as well as Marc Lavarenne for his contribution in producing the figures. This research was partially supported by internal funds of the Universite´ du Quebec a` Montreal. This ´ ´ manuscript also benefited from the comments of Gerald Domon ŽUniversite´ de Montreal ´ ´ . and of two anonymous reviewers.
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