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City and Environment Interactions 19 (2023) 100106
Available online 24 April 2023
2590-2520/© 2023 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Effects of open space congurations and development patterns on future
urban wildlife habitats and populations
Homero Marconi Penteado
Wageningen University and Research, Department of Environmental Sciences, Landscape Architecture and Spatial Planning, Droevendaalsesteeg 3, 6708PB Wageningen,
the Netherlands
ARTICLE INFO
Keywords:
Spatial concept
Urban open space
Alternative future scenarios
Urban wildlife
Habitat quantity and quality
Individual-based modelling
ABSTRACT
The viability of wildlife populations in cities is strongly associated to the qualities of urban open spaces and
development patterns. Open space systems can serve as armatures to address adverse effects of urbanization on
biodiversity. Landscape planners and designers use spatial concepts to translate principles of landscape ecology
into working diagrams of land use and land cover to anticipate ecological effects. This paper investigates the
consequences of adopting different open space spatial concepts (corridors, patches, and network) in combination
with development patterns (compact and dispersed), simulated in eight alternative future scenarios with com-
puter model Envision. Two approaches were used to quantify the effects of the different spatial concepts and
urban patterns on Red-legged frog (RLF), Western meadowlark (WML), and Douglas squirrel (DSQ) habitats and
populations in an area of urban expansion. First, the amount of habitats was assessed for the initial landscape (ca.
2010) and for the eight future scenarios (year 2060). Second, using the Individual-Based Model (IBM) HexSim,
populations of the three species were quantied. All scenarios had increased sums of habitat area, but results
showed that differences in open space spatial concepts played a greater role in determining population sizes and
were more inuential than different development patterns. Network scenarios presented more habitats and the
largest populations of RLF. Park and network scenarios showed the most habitats and populations for the WML.
No open space and greenway scenarios did not have enough habitats for the WML, but presented the best results
for the DSQ. Populations in compact development scenarios showed a small advantage over most dispersed
development scenarios. However, in park and network scenarios, dispersed development showed a large inu-
ence in the increase of WML population. The study shows that the adopted framework is useful to predict the
consequences of landscape plans on wildlife species populations, evaluate trade-offs, and inform planning
decisions.
Introduction
As cities expand, urbanization causes habitat loss and fragmentation
as well as adverse impacts on biodiversity: ecological processes, move-
ments, ows of species, and connectivity are affected [33,5,62,64].
Landscape ecology provides a framework to address landscape change
and open space planning [1,32], offering a foundation for biodiversity
protection [15,48,23,46]. Landscape ecology principles can give the
basis for spatial concepts [1,33,6]. Spatial concepts are working dia-
grams that inform planning and design by graphically expressing ideas
and relationships concerning natural and cultural variables on a specic
landscape [29,1]. The challenge for planners and/or designers is
deciding what spatial concepts should be applied to maintain or create a
landscape structure that protects ecological processes while allowing
space for urban land uses [32,47,57].
In an urban context, the various forms that urban open space can
assume have the potential to create an armature for urban expansion
that protects natural patterns and processes [35,33,38]. Urban open
spaces, in the context of this research, are understood as unbuilt areas
that include public or private lands that contain riparian forests, patches
of native vegetation, woodlots, as well as urban farms, parks, greenways,
plazas, or other places that may function as patches or corridors and
offer ecological and sociocultural opportunities (for a full list of open
space types considered, see Supplementary material – Open Spaces).
Fragments of ecosystems associated with corridors form networks of
habitats [22]. Discussions about corridors in urban environments,
particularly, are increasingly present among urban planners and land-
scape architects. Ecological corridors [36], urban green corridors [55],
E-mail address: homero.marconipenteado@wur.nl.
Contents lists available at ScienceDirect
City and Environment Interactions
journal homepage: www.sciencedirect.com/journal/city-and-environment-interactions
https://doi.org/10.1016/j.cacint.2023.100106
Received 15 January 2023; Received in revised form 14 April 2023; Accepted 18 April 2023
City and Environment Interactions 19 (2023) 100106
2
greenways [49,2,16,19] and green infrastructure [67,31] have been
explored as tools to overcome habitat fragmentation and improve the
movements of species in urban areas and to address biodiversity
conservation.
Urban development patterns strongly inuence the conguration of
open space and, consequently, affect ecological processes
[34,62,17,64,42]. Compact patterns of urbanization, in contrast to
dispersed patterns, prevent excessive consumption of land and protect
open space through densication, clustering, changing the mix of
housing densities and types, reducing single family development;
increasing the percentage of town-homes and small-lot single family
homes; and densifying commercial development [4,18,12,41,33,11].
Conversely, dispersed development demands the expansion of infra-
structure, more notably the road network, which increases conicts and
barriers for wildlife.
This study employs an alternative futures framework to investigate
the effects of the interaction between different open space congura-
tions and development patterns on the amount and quality of habitats
and on consequent wildlife populations. It draws on an earlier study
developed by the Northwest Pacic Ecosystem Research Consortium
[9]. In that study, three future scenarios – Plan Trend 2050 (based on
contemporary policies and trends), Development 2050 (reecting a
loosening of policies), and Conservation 2050 (with increased emphasis
on protecting and restoring ecosystems) – developed on assumptions
about land and water use on the 30,000 km
2
Willamette Basin in Ore-
gon, USA, and were contrasted to historic (ca. 1850) and ca. 1990
conditions [8,39]. Here, I focus on a much smaller portion of that
landscape to investigate eight scenarios of land use and land cover
(LULC) that simulate urban expansion in the eastern edge of Portland,
Oregon, and the effects for the populations of three key species [53].
They combine three spatial concepts of open space – corridors, patches,
and networks – with two patterns of urban development – compact and
dispersed. Two scenarios adopted only minimal conservation policies,
with no spatial concept for open space.
The aim is to assess the effects of applying spatial concepts and
development patterns in urbanization plans on populations of Northern
Red-legged frog (Rana aurora aurora), Western meadowlark (Sturnella
neglecta) and Douglas squirrel (Tamasciurus douglasii). Many metrics to
quantify the multiple aspects of landscape pattern have proliferated in
the recent decades [25]. This study adopts a relatively simple but
important measure of landscape quality – the capacity to support viable
populations of key wildlife species [61], measured in two different ways
that may be useful to planners and stakeholders. The rst uses species-
habitat preference data to obtain the quantity and quality of habitats
measured in land use and land cover maps. The second estimates the
amount of individuals supported by each landscape depiction using an
individual-based dispersal model (IBM) that utilises area needs, sur-
vival, reproduction and movement data [61,60]. IBMs are useful
modelling tools to assess the effects of landscape pattern on wildlife
movements [28]. Both assessments are performed for the starting con-
ditions (ca. 2010) and future scenarios (2060). The results of both as-
sessments are then compared and contrasted to investigate where they
agree or disagree and, more specically, if the amount and quality of
habitats sufce to sustain viable populations of the three species. This
approach is premised on the notion that the evaluation of scenario
outcomes and its implications can enhance decision-making in the
planning process (Mahmoud et al. 2009), in this case, for the specic
objective of the viability of the populations of the selected species.
Methods
Overview
This research adopted a multi-step method (Fig. 1) consisted of: 1)
mapping the existing LULC ca. 2010 of a study area; 2) projecting the
population ca. 2060; 3) determining representative wildlife species; 4)
developing scenario assumptions; 5) developing open space spatial
concepts and urban development patterns; 6) writing policies to
implement scenarios; 7) simulating urban expansion according to eight
future scenarios (year 2060); 8) adopting mean scenario representations
to perform assessments; 9) calculating the amount and quality of habi-
tats in the existing landscape (ca. 2010) and in the eight future scenarios;
10) modelling wildlife using an IBM to quantify wildlife populations in
all scenarios; 11) comparing and contrasting the amount and quality of
habitats with the resulting wildlife populations.
Study area and population projection
The study area is located in the south-eastern portion of the metro-
politan region of Portland, Oregon, USA, adjacent to the city of Dam-
ascus (Fig. 2). Portland’s metropolitan administration adopts Urban
Reserves (UR) to expand its Urban Growth Boundary (UGB). This study
focuses on two of those URs (Damascus Urban Reserves in Fig. 2). A ca.
2010 LULC vector map was produced to represent the study area in a
Geographic Information System (GIS). A 30 ×30 m grid was overlaid to
guarantee a maximum cell size of 900 m
2
. Each cell received multiple
attributes, including scores that value each LULC class for its suitability
for each of the selected species according to life history traits identied
in the literature [61,54]. Those scores served to quantify the amount of
habitats and to generate suitability maps for the IBM.
Based on the region’s projected population [8], a population of
approximately 16,000 people was estimated in those URs in year 2060
and adopted in all scenarios. Scenario modelling included Damascus and
a 800 m buffer to provide context. Scenario evaluations were limited to
the URs.
Wildlife species
The study targeted three species that demand small territories but are
vulnerable to habitat fragmentation and to the proximity to the urban
matrix. They are associated with a variety of the region’s habitat types
that may be affected by urbanization. The Red-legged frog (RLF) breeds
in shallow water bodies where emergent vegetation abound; they
seasonally migrate between moist forests and breeding habitats
Fig. 1. Research framework.
H.M. Penteado
City and Environment Interactions 19 (2023) 100106
3
[26,50,24,43,20]. The Western meadowlark (WML) prefers interiors of
grasslands and prairies larger than six hectares for foraging and nesting
[37,40], which may be comprised of several patches [27]. Douglas
squirrels’ (DSQ) home range is <0.6 ha in old-growth conifer forests
[50], but may be abundant in second-growth or mature stands [56].
Scenario assumptions
All scenarios assume the conservation of the most important habitats
and protection of breeding and migration habitats from development for
all three species. Buffers protect breeding habitats and riparian corridors
from development. Depending on width, they may provide opportu-
nities for recreational uses. In some scenarios, areas near conservation
zones accommodate recreation, low-density housing, and community
gardens. No development occurs within 60 m-wide buffers from streams
to provide an armature for dispersal [22]. Underpasses reconnect wet-
lands, streams, and patches bisected by roads.
Assumptions about urban development designate the allocation of
inhabitants and employment areas. Compact development is conducted
towards areas of lower ecological value, minimally expanding the urban
footprint and the road network. Development policies create denser,
mixed-use urban centres containing housing and employment areas.
Density decreases as distances to centres increase. In dispersed devel-
opment scenarios, development occurs in any developable, non-
conservation areas, with a higher proportion of single-family develop-
ment. Employment areas have easy access to major arterials in areas of
lower ecological value in all scenarios (Forman 2004).
Open space spatial concepts and development patterns
The eight scenarios combine spatial concepts that represent open
space and urban development patterns (Fig. 3). Open space spatial
concepts are based on landscape ecology principles that focus on habitat
patches, corridors and networks. Principles for patches aimed at habitat
conservation and restoration, parks, and other vegetation-dominated
urban LULC. Principles for corridors guided spatial concepts for green-
ways and stream corridors. Combinations of patches and corridors
produced a spatial concept to implement networks. Urban development
followed compact and dispersed patterns.
Scenarios and policies
Eight scenarios combined open space spatial concepts with urban
development patterns. Two scenarios, Compact Development (CD) and
Dispersed Development (DD), projected urban expansion with no spatial
concept for open space. Greenway and Compact Development (GCD) and
Greenway and Dispersed Development (GDD) scenarios emphasized open
space corridors using mainly streams as a framework for dispersal and
for protecting and restoring riparian forest. Park System and Compact
Development (PCD) and Park System and Dispersed Development (PDD)
scenarios relied on various types of park to create a framework of
patches and stepping-stones to explore the ability of the chosen species
to move through a fragmented landscape. Network and Compact Devel-
opment (NCD) and Network and Dispersed Development (NDD) scenarios
combined corridors with habitat patches and stepping-stones to create
open space networks.
Policies capture decision rules to implement spatial concepts and
scenario assumptions (see online supplementary material for Policies
Syntax). Open space policies address restoration, protection, and con-
servation of habitats; creation of corridors; and implementation of open
space. Urban development policies allocate population and employment
zones. Urban expansion modelling was driven by 24 open space policies
and 14 for urban land uses. From these, 8 express spatial concepts for
compact or dispersed development in the URs, while 6 address devel-
opment within Damascus. Combinations of policies determined differ-
ences among scenarios (Table 1).
Fig. 2. Study area in the metropolitan context.
Fig. 3. Spatial concepts used in the study: a. no spatial concept; b. patches; c. corridors; d. network; and urban development patterns: e. compact development; f.
dispersed development.
H.M. Penteado
City and Environment Interactions 19 (2023) 100106
4
Scenario modelling
Land-use modelling software Envision [14,13] modelled urban
expansion from the GIS representation of the existing ca. 2010 land-
scape. In Envision, human population growth creates a demand for res-
idential and employment areas; sets of policies (Table 1) that express
spatial concepts and development patterns operationalize scenario as-
sumptions and drive allocation of open space and urban development.
Twenty runs of a given scenario in Envision produced variations in nal
patterns of LULC (ca. 2060), each of them an alternative future consis-
tent with the assumptions of its guiding scenario.
Habitat quantity and quality
Scenario modelling produced metrics of habitat quantity and quality.
Three indicators were used to contrast ca. 2060 future scenarios with
each other and against ca. 2010: Weighted habitats is the total area of
habitats multiplied by their suitability scores, which expresses habitat
quality [61] for the three species as a group; Weighted breeding habitats
uses a similar calculation, but accounts for breeding habitats for the
three species; High-quality habitats quanties area of the high-scored
habitats for breeding, foraging and dispersal for each species.
Because the goal of this analysis was to evaluate quantity and quality
of habitats, two indicators means, weighted habitats and mean weighted
breeding habitats, were used as criteria for selecting mean scenarios.
Mean scenario is the alternative future representation in maps and
numbers that is closest to the mean weighted habitats and weighted
breeding habitats among the 20 Envision runs conducted for each sce-
nario. Mean scenarios were used for comparing and contrasting total
amount of suitable habitats and breeding habitats across the three spe-
cies, and high-quality habitats for individual species.
Individual-based modelling (IBM)
The next phase consisted of measuring the abilities of the species to
disperse and nd new territories to establish new populations for each
scenario mean and for the initial landscape ca. 2010. Scenario maps
served as the basis for producing IBMs for the three species using com-
puter model HexSim [59,60], to obtain the number of individuals of each
species sustained in each scenario. In other words, the IBMs assessed if
scenarios were able to support populations of each species.
HexSim simulates a wide range of life history events [60] and eval-
uates the ability of the future scenarios’ landscape structure to sustain
overall populations and individual’s ability to disperse. Life history
events considered in this study include reproductive capacity, home
range, dispersal distance, and territory sizes [54]. The measure obtained
with this assessment was average population size of each species in each
scenario. Means from 20 multi-run replicates of each alternative future
scenario were used to compare the number of breeding individuals
(individuals capable of establishing breeding territories), oaters (in-
dividuals that remain searching for territories), and total population (the
sum of breeding individuals and oaters).
Contrasting amount and quality of habitats with resulting populations
The results from the Envision models were contrasted with the results
obtained with HexSim to understand the relationship between amount
and quality of habitats with the resulting modelled populations for each
Table 1
Scenario Policy Assignment. See Supplementary online material “Policies Syntax Envision” for descriptions and goals of all policies.
PolicyScenario → CD DD GCD GDD PCD PDD NCD NDD
Conservation of breeding habitats for RLF (wetlands) X X X X X X
Conservation of migration corridors for RLF (riparian forests) X X X X
Conservation of high-quality habitats for WML (grasslands) X X X X X X
Conservation of high-quality habitats for WML (oak savanna) X X X X X X
Conservation of high-quality habitats for DSQ (forests) X X X X X X
Creation of habitat corridor X X X X
Creation of underpasses for RLF in wetlands X X X X
Creation of underpasses for RLF in streams X X X X
Creation of underpasses for DSQ X X X X
Protection of breeding habitats for RLF X X X X
Protection of grasslands for WML X X X X
Protection of oak savannas for WML X X X X
Protection of habitats for DSQ X X X X
Restoration of breeding habitats for RLF X X X X
Restoration of riparian corridors X X X X
Restoration of habitats for WML (grasslands) X X X X
Restoration of habitats for WML (oak savanna) X X X X
Management of golf course for WML X X X X
Management of grasslands for WML X X X X
Creation of greenways as habitats X X X X
Creation of greenways for recreation and mobility X X X X X X
Creation of parks near residential areas X X X X X X
Creation of community gardens X X X X X X
Creation of urban farms X X X X X X
Creation of centres X X X X
Creation of high-density residential zones X X X X
Creation of mid-density residential zones X X X X
Creation of low-density residential zones X X X X
Creation of conservation residential zones X X X X
Creation of general employment areas in the URs X X X X X X X X
Creation of parking spaces in industrial and commercial areas X X X X X X X X
Change zones for dispersed development (all densities) X X X X
Allocation of population in residential/commercial zones in Damascus X X X X X X X X
Allocation of population in high density residential zones X X X X X X X X
Allocation of population in mid-density residential zones X X X X X X X X
Allocation of population in low-density residential zones X X X X X X X X
Allocation of population in conservation residential zones X X X X X X X X
Allocation of commercial and industrial uses in Damascus X X X X X X X X
H.M. Penteado
City and Environment Interactions 19 (2023) 100106
5
scenario. High-quality habitat area (which includes the best habitats for
breeding, foraging and movements) was contrasted with the Total pop-
ulation of each species. While the rst assessment reports the amount of
habitat, the second assessment allows inferring the role of how habitats
are arranged in the landscape on population viability.
A two-way ANOVA analysed the inuence of the choice of open
space and urban development spatial concepts on metrics. The full
model included the interaction between these two factors. A Tukey’s test
assessed pairwise comparisons. Distributions were checked for ANOVA
normality assumptions and did not require transformation. Signicance
was assessed at the p <0.05 level for all comparisons. Coefcients of
variation among runs ranged from 0.003 to 0.012 (Fig. 4).
Results
Scenario modelling: Habitat quantity and quality
Scenario modelling provided measurements of the amount and
quality of habitats for the three species as a group and individually
(Table 2). Network scenarios presented the best overall results for
weighted habitats and weighted breeding habitats, two indicators that
combine area and suitability scores for the three species taken as a set.
Network scenarios also performed well for high-quality habitats for the
three species, with increases of all indicators. For the DSQ, network
scenarios presented the least benecial results among scenarios.
Notwithstanding, amounts nearly doubled relative to ca. 2010. CD and
DD scenarios also present high amounts of high-quality habitats for the
DSQ, despite the fact that no open space spatial concept was applied.
Because Envision simulates ecological succession, much of unsuitable
habitats for the DSQ turned into mature forests. WML had habitat area
reduced in no open space, greenway, and park scenarios relative to ca.
2010; only network scenarios presented increased high quality habitats
for the WML. Urban development area decreases as habitat area in-
creases across scenarios: network scenarios produced the smallest urban
footprint, while the no open space scenarios had the largest urban
footprint.
Fig. 4. Habitat and population change between ca. 2010 and 2060. CV is the coefcient of variation among scenario runs. Numbers on top of bars indicate signicant
differences among open space patterns; different letters indicate statistically signicant differences between compact and dispersed patterns; percentages indicate
increase or decrease of ca. 2060 relative to ca. 2010. The horizontal axis shows ca. 2010 conditions and 2060 alternative futures in all graphs. Note different scales
and units on the vertical axes: a), c), and e) High Quality Habitat area [53]; b), d) and f) Total Population. Percentages for high-quality habitats (a, c, and e) represent
change between the mean 2060 scenarios and ca. 2010 quantities. Percentages for total population (b, d, and e) report change of averages across the 20 HexSim runs
of mean scenarios [54].
H.M. Penteado
City and Environment Interactions 19 (2023) 100106
6
IBM: Resulting populations
The second assessment obtained the size of the populations of each
species through the number of breeding individuals, oaters, and total
population (Table 3) each scenario could sustain.
Network scenarios performed best for the RLF, followed by park
scenarios. The number of breeding individuals increased in both cases.
PDD and GDD were nearly identical to 2010; PCD scenario was more
different to 2010 and to PDD: compact development differentiated the
park spatial concept. The number of oaters decreased in CD, DD, GCD,
GDD, and PDD scenarios. Populations presented small decreases in no
open space, greenway scenarios and PDD.
Greenway and no open space scenarios were not able to support
populations of WML. PDD and NDD performed best for the WML; park
and network scenarios presented comparable quantities of breeders and
oaters.
All scenarios presented increased populations of DSQ, but greenway
scenarios and PDD performed best. Network scenarios resulted in the
smallest ca. 2060 population among all scenarios.
High-quality habitats versus total population
In this section, High-quality habitats area (henceforth habitats) from
the rst assessment is contrasted with Total population (henceforth
population) from the IBM. The analysis focused on contrasting percent-
age changes in ca. 2060 scenarios relative to the ca. 2010 quantities,
using mean scenarios obtained with Envision and means obtained with
HexSim (Fig. 4). In both cases, there was a small variability (coefcient
of variation – CV) among the 20 multiple runs of the scenarios (produced
with Envision) and the 20 dispersal model replicates (produced with
HexSim). Quantities are detailed in Table 4.
Red-legged frog
DD, GCD, GDD and PDD scenarios presented percentage increases
and/or decreases of RLF population proportional to habitat area change
(Fig. 4a and b). The PCD scenario presented a decrease of habitat area,
but an increased population of RLF; a small decrease occurred in the
PDD. GCD had an increase in habitat area but a decrease in total pop-
ulation. Network scenarios presented population percentage increases
almost three times (31–36%) larger than the increase of habitat area
(12–13%). All compact development scenarios had more habitat than
dispersed development scenarios, but nearly identical for park and
network scenarios. Only the GDD scenario had larger ca. 2060 pop-
ulations than the compact equivalent, but not statistically signicant.
PCD had a substantially bigger population than PDD, despite their
habitat area having no signicant differences.
Western meadowlark
CD, DD, GCD and GDD scenarios presented a large reduction of
habitat area for the WML (Fig. 4c). The total habitat area indicates the
possibility of having a viable population, but the dispersal model
showed those scenarios promote the extinction of WML in the study
area. The percentage decrease of population in the PCD scenario was
consistent with the decrease of habitat area, as was the increase of
population consistent with the increase of habitat area in the NDD sce-
nario. All compact development scenarios presented more habitat area
than dispersed development scenarios, yet PDD and NDD scenarios had
larger populations. NCD and NDD had more habitats than any other
scenario; PDD presented the highest population density.
Douglas squirrel
All scenario means presented percentage increases of habitat area in
average 4.3 times larger than the percentage increase of total popula-
tion. However, the percentage increases of populations of DSQ are not
consistent with the increases of habitat area (Fig. 4e and f). Most
Table 2
First assessment summary results. Numbers express values from mean scenarios;
“Weihab” (weighted habitats) is the sum of all habitat polygons multiplied by
their suitability scores for all three species; “breedhab” (weighted breeding
habitats) uses the same procedure considering breeding habitats only; “high-
quality habitats” is the total area of suitable breeding, foraging, and dispersal
habitats for each species. Shaded cells are the ones with the highest scores.
Scenario Weihab Breedhab High-quality habitats
(ha)
Urban
ha ×
score
ha ×
score
RLF WML DSQ (ha)
2010 10,542 2,419 597 112 85 0
CD - Compact
Development
10,653 3,508 519 11 195 688
DD - Dispersed
Development
11,139 3,403 504 11 189 786
GCD - Greenway and
Compact
Development
12,341 4,737 601 12 194 629
GDD - Greenway and
Dispersed
Development
12,894 4,736 593 16 194 688
PCD - Park and
Compact
Development
11,975 5,734 553 101 186 592
PDD - Park and
Dispersed
Development
12,556 5,622 552 90 187 652
NCD - Network and
Compact
Development
14,205 6,124 673 140 164 511
NDD - Network and
Dispersed
Development
14,730 6,051 675 134 163 528
Table 3
Summary results from second assessment shows mean values from 20 HexSim replicates. It expresses number of individuals where “BI” represents breeding individuals,
“FL” number of oaters and “TP” the total population. Shaded cells show the best means among scenarios. “Urban” indicates the area occupied by development
(residential and employment areas) in mean scenarios.
Red-legged frog Western meadowlark Douglas squirrel
BI FL TP BI FL TP BI FL TP
2010 647 22,347 22,994 21 62 84 1,009 2,746 3,755
CD 629 21,455 22,084 0 0 0 1,500 3,423 4,923
DD 593 19,734 20,327 0 0 0 1,470 3,158 4,628
GCD 635 22,064 22,699 0 0 0 1,559 3,439 4,998
GDD 646 22,166 22,812 0 0 0 1,569 3,271 4,840
PCD 750 25,018 25,768 13 61 74 1,434 3,334 4,768
PDD 649 22,265 22,914 16 81 97 1,516 3,443 4,959
NCD 942 30,427 31,369 12 60 72 1,384 3,131 4,515
NDD 909 29,207 30,116 16 78 94 1,391 3,107 4,498
H.M. Penteado
City and Environment Interactions 19 (2023) 100106
7
increases were not signicantly different between compact and
dispersed development (greenways, parks and network scenarios), but
produced population increases that were signicantly different
(greenway and park scenarios). While GCD had an increase signicantly
higher than GDD, PDD resulted in a larger increase than PCD, indicating
that compact and dispersed development patterns played a small role in
determining differences within spatial concepts. All scenarios present
more habitat and larger populations than ca. 2010, but all have lower
population densities.
Discussion
This study demonstrates the use of two assessment methods to
analyse the trade-offs between adopting three open space spatial con-
cepts and two urban development patterns in scenarios of urban
expansion. The amount of habitats was measured by calculating the
amount and quality of open spaces that sustain populations of wildlife
species. While other studies have adopted connectivity measurements to
assess the effects of urbanization [63,62,68,64], here, the actual ability
of the landscape represented in each scenario to sustain viable pop-
ulations was calculated by linking each scenario to the amount of in-
dividuals they are able to sustain.
Results showed that the amount and quality of habitats, urban
development patterns, and the processes considered (species dispersal
and migration) were inuential in determining scenario differences, and
that results were, at times, counterintuitive. Some discrepancies
appeared in the results where scenarios with less habitat area than ca.
2010 presented larger populations ca. 2060. In such cases, it is likely
that the spatial conguration of open space and not habitat quantity and
quality alone, was important in determining populations. In some cases,
the second assessment corroborated the rst (larger the amount of
habitats, larger the population); in others, they disagree.
Red-legged frog
Network scenarios presented the best combination of protection of
breeding and dispersal habitats for the RLF. Modest increases of habitat
area produced large increases of population. Park scenarios showed
comparable habitat area, but presented small losses of habitat area
compared to ca. 2010. Population increased in the PCD scenario despite
its decrease of habitat area, which indicates that compact development
may have played an important role in determining the increased pop-
ulation while its dispersed development counterpart presented a small
decrease of population relative to ca. 2010. The NCD scenario also
presented some advantage over NDD, also indicating that there may be
an inuence of compact patterns of urbanization over dispersed devel-
opment. It is important to notice that, not only compact development
scenarios consumed less land than dispersed development scenarios
(Table 2), but development areas were contiguous (Fig. 5c), allowing a
less fragmented open space armature as sprawl was contained. Scenarios
with no open space spatial concepts (CD and DD) presented comparable
habitat loss, but population had a smaller decrease in the compact
development scenario. Comparing across open space patterns, compact
development performed better than dispersed development except for
the greenway scenarios’ total population. However, the difference was
not statistically relevant.
Western meadowlark
No open space and greenway scenarios presented relatively small
total habitat area (between 11 and 16 ha – Table 1), but the numbers
indicated that those landscapes could sustain small populations of WML.
Table 4
Results from rst and second assessments. Habitats stands for High-Quality Habitats; Population includes the total populations (sum of breeding individuals and
oaters); I/ha stands for number of individuals per hectare of habitat. Shaded cells indicate the highest results.
Red-legged frog Western meadowlark Douglas squirrel
Habitats (ha) Population I/ha Habitats (ha) Population I/ha Habitats (ha) Population
2010 597 22,994 38.5 112 84 0.7 85 3,755
CD 519 22,084 42.5 11 0 0 195 4,923
DD 504 20,327 40.3 11 0 0 189 4,628
GCD 601 22,699 37.8 12 0 0 194 4,998
GDD 593 22,812 38.5 16 0 0 194 4,840
PCD 553 25,768 46.6 101 74 0.7 186 4,768
PDD 552 22,914 41.5 90 97 1.1 187 4,959
NCD 673 31,369 46.6 140 72 0.5 164 4,515
NDD 675 30,116 44.6 134 94 0.7 163 4,498
Fig. 5. Red-legged frog suitability maps: a) ca. 2010: one large and several small wetlands (breeding habitats) appear near some possible migratory habitats (other
habitats); b) DD: some wetlands were developed and less migratory habitats are available; c) NCD: a network of migratory habitats appear near the original large and
new wetlands.
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City and Environment Interactions 19 (2023) 100106
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However, these scenarios (Fig. 6b) presented a large number of small
habitats. The dispersal model showed that the habitat area was not
sufcient to overcome fragmentation in those scenarios (Table 2).
Patches were signicantly small and apart.
Habitat area increased in the NCD scenario, but the IBM showed a
decreased population. Conversely, habitat area decreased in the PDD,
but the population increased, indicating the effect of a combination of
patch size with spatial conguration. PCD and NCD had decreased
populations of WML, while dispersed development scenarios presented
increased populations. Park and network scenarios presented at least
one large grassland patch (approximately 30 ha – Fig. 6c).
The consistent difference between development patterns raises
questions, for this particular species, regarding the assertion that
compact development patterns result in useful habitat [4,18].
The ca. 2010 landscape and the scenarios that supported viable
populations presented different habitat congurations. The ca. 2010
landscape presented scattered but relatively large habitat patches
(Fig. 6a). For the WML, it is likely that the combination of the amount
and quality of habitats and their arrangement in the ca. 2010 landscape
determined the indicated population, as well as the presence of large
patches in the park and network scenarios.
Despite the evidence that suggests that variations in habitat area and
quality have bigger effects than variation in spatial arrangements of
habitats [38], the results conrm the importance of clusters of small
habitat patches for the conservation of WML [69].
Douglas squirrel
All scenarios presented more habitats for DSQ than ca. 2010
(Fig. 7a). Population projections proportionally followed habitat gain,
but at much smaller rates. Greenway scenarios, built mainly upon
forested riparian corridors, had the best results in both assessments,
what indicates the importance of corridors for this species’ dispersal
(Fig. 7b). CD and DD scenarios also performed well, mainly because
minimal conservation assumptions included protection of riparian cor-
ridors, allowing vegetation succession in those areas. Network scenarios
(Fig. 7c) showed the smallest amount of habitats and individuals,
probably because those scenarios have a more balanced distribution of
habitats among the three species. This species demonstrated less sensi-
tivity to differences between compact and dispersed development
patterns.
Effects of open space spatial concepts
Park system (patches)
Patches are major structural components of landscapes [34]. Within
an urban fabric, because of fragmentation, patches, as remnants of
habitats [29], may represent the most viable form of open space. Mul-
tiple types of patches, with varying sizes and functions, were simulated
in this study, including, for example, urban parks, conservation areas,
and urban farms. Wetland patches played important roles in sustaining
RLF breeding individuals; WML adopted patches of grasslands and oak
savanna; DSQ succeeded in all scenarios, perhaps partly because this
species disperses over comparatively short distances (<0.15 km) and
have small territories (<0.6 ha).
While it has been argued that habitat size is the most important
variable for conservation [38], small patches also play important roles in
conserving biodiversity [66,44]. For at least one of the species studied,
size mattered. The WML was successful in scenarios with the largest
amount of habitats (PCD, PDD, NCD, and NDD). Park scenarios pre-
sented the largest patches, while smaller but more numerous patches
permeated network scenarios (Fig. 8, PCD and NCD).
Greenways (corridors)
Greenways are critical for addressing biodiversity conservation in
urban areas [49,2,16], and effective in overcoming fragmentation
[19,21]. This study used greenways to implement corridors. Greenway
and network scenarios promoted an expansion of protected corridors
along streams. In the modelled ca. 2060 landscapes, the 60 m-wide
vegetated corridors provided pathways for RLF migrations and dispersal
of DSQ. Although greenway scenarios were not successful for the WML,
an increase in forested areas may benet forest birds (Marzluff and
Ewing 2001). The diversity of urban greenspaces provided by greenways
could support diverse types of birds [17], yet the lack of grasslands does
not help species such as the WML. Increased riparian vegetation that
supports RLFs and DSQs may also benet other species.
Networks
While patches are important to achieve conservation goals [3],
amount and quality of habitats [38] or connectivity [45] for population
viability in urban areas, it has been argued that networks are better than
other congurations in achieving conservation goals [51,7,10].
Networks developed in this study aimed at creating mosaics of
habitats (Fig. 8, NCD) to sustain the selected species and allow the ow
of individuals [65]. They merge characteristics from both patch and
corridor spatial concepts, achieving the best combined results: large
amounts and diversity of habitats that produced the necessary condi-
tions for the three species.
Effects of urban pattern
In compact development scenarios, urbanization happened close to
existing transportation corridors; open space policies limited the
expansion of development over open space. Urbanization developed on
Fig. 6. Western meadowlark suitability maps: a) ca. 2010: some patches of breeding habitats (grasslands) appear in the north-western corner ca. 2010; b) GCD: a
few, small, isolated patches are present; c) PDD: a large patch appears in the central, southern portion.
H.M. Penteado
City and Environment Interactions 19 (2023) 100106
9
contiguous areas, as opposed to dispersed development scenarios.
Some of the results obtained from the IBM indicated that dispersed
development caused smaller effects on populations or a larger increase
of populations than compact development. Two aspects may have
inuenced these results. First, the software used for simulating scenarios
– Envision – did not represent new roads connecting new development
zones. Second, dispersed development may actually be more permeable
to some species and support habitats for foraging and dispersal for some
life history strategies. Although compact development produces a
smaller urban footprint, it creates denser urban zones that may act as
barriers to wildlife dispersal and increase disturbance in adjacent
habitats.
The simulated urban expansion resulted, in all scenarios, in the
decrease of farmland area. Compact and dispersed patterns of urbani-
zation played an important role: while farmland remained contiguous in
compact development scenarios, dispersed development consumed and
fragmented agricultural lands. This latter conguration reduces habitat
for and increase disturbance to WML, as well as for grassland birds that
use crops for foraging and breeding in managed crops [52]. Some
agricultural types, like pasture, may be suitable for amphibians [24].
Fig. 7. Douglas squirrel suitability maps: a) ca. 2010; b) GDD: the combination of breeding and dispersal habitats assume a more linear aspect (corridors); c) NDD:
habitats are scattered throughout the area.
Fig. 8. Portions of the study area depicting LULC representations of ca. 2010 and PCD, GCD, and NCD scenarios.
H.M. Penteado
City and Environment Interactions 19 (2023) 100106
10
Conclusion
This study explored two ways of quantifying landscape ecological
outcomes to understand the trade-offs of adopting different landscape
plans based in a combination of open space spatial concepts and urban
patterns. The quantications are the result of habitat proportions and
weightings based on existing and projected landscape patterns, and an
individual dispersal model. The results of comparisons of the two
methods show differences in how habitat proportions change and the
modelled wildlife population sizes. Differences were not consistent
across the three species. This quantitative analysis distinguishes effects
by spatial concept and species to better understand the implications of
using different spatial concepts in decisions concerning sensitive species.
By selecting a suite of target species, spatial concepts to support them
may also indicate consequences for other species with similar life-
history traits [58]. For example, RLFs share habitats with North-
western salamanders, Long-toed salamanders, Pacic chorus frogs,
and Rough-skinned newts [43]. WMLs coexist with other grassland birds
such as Western bluebird, Oregon vesper sparrow, Horned lark, Grass-
hopper sparrow, and Common nighthawk [52]. DSQs share habitats
with Northern ying squirrels and the Townsend chipmunks, and may
benet predators such as Northern spotted owls, goshawks, or weasels
[30].
The alternative future scenarios method helped to visualize a large
number of possible outcomes; the assessments helped to understand the
trade-offs among various open space patterns and compact vs. dispersed
development. These methods also helped to confront accepted theories
and assumptions with quantitative data. For example, the conventional
wisdom is that compact versus dispersed development makes much
difference on wildlife, but results showed variations among the species
studied; landscapes structured by scattered patches and relatively less
cohesive than others (park scenarios) are able to sustain viable pop-
ulations of all species. Lastly, this approach contributes to understanding
how decisions about open space and urban form differently affect spe-
cies with different life history requirements, contributing to scienti-
cally informed planning decisions.
Declaration of Competing Interest
The authors declare the following nancial interests/personal re-
lationships which may be considered as potential competing interests:
Homero Marconi Penteado reports nancial support and travel were
provided by CAPES Foundation. Homero Marconi Penteado reports
nancial support was provided by Universidade Federal do Espírito
Santo. Homero Marconi Penteado reports nancial support was pro-
vided by University of Oregon. Homero Marconi Penteado reports
administrative support was provided by Fulbright Commission.
Data availability
Data will be made available on request.
Acknowledgements
This study derives from a doctoral research funded by the CAPES
Foundation (Ministry of Education of Brazil), and supported by the
Fulbright Program. Additional support came from the University of
Oregon and the Universidade Federal do Espírito Santo. The author
thanks professor David Hulse for his supervision; John Bolte (Oregon
State University) for assistance with Envision modelling; Nathan Schu-
maker (US EPA) for assistance with dispersal modelling; Bart Johnson
with the ecological analysis; Chris Enright and Allan Branscomb for
assistance with GIS mapping and analysis.
Appendix A. Supplementary material
Supplementary data to this article can be found online at https://doi.
org/10.1016/j.cacint.2023.100106.
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H.M. Penteado
