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Intraspecific morphological and genetic variation of common species predicts ranges of
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threatened ones
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Electronic Supplementary Material
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(a) Inclusion of cost into the prioritizations
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Land value is typically an extremely important factor in the establishment of areas to conserve
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biodiversity. Indeed, historically, conservation areas have often been decreed in inexpensive land
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that was considered unsuitable for development such as areas that are steep or otherwise
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physically inaccessible [1,2]. Furthermore, since there is significant spatial variation in land cost
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at the global scale and the national scale [3,4], when cost is incorporated into the prioritization of
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conservation areas, the portfolio of selected sites can differ significantly from prioritizations that
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fail to account for cost. To address this, we repeated the analysis incorporating land cost to assess
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whether sites prioritized to include genetic and morphological variation of common species and
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minimize land cost would include more habitat for threatened and endemic species than sites
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selected to minimize land cost and include environmental parameters or occurrences of bird and
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amphibian species.
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Since there is no database of land values for Ecuador, we modeled land value as an
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increasing function of proximity to roads and infrastructure and a decreasing function of site
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steepness [5,6]. Our land cost model was defined as follows:
Sets
𝑖∈𝐼
10 × 10 km sites
Data
1
𝑡𝑖
topographic diversity of site 𝑖
𝑟𝑖
number of transformed pixels in 𝑖
𝑑𝑖
distance from 𝑖 to the closest road
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A site’s topographic diversity is defined as the surface area divided by the planimetric area [5].
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Steep, physically-inaccessible sites have high topographic diversity and flat sites that are suitable
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for development have low topographic diversity. We calculated topographic diversity by
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obtaining a digital elevation model for the study region [7] and then calculating the surface area
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of each site using 3D Analyst Tools in ArcGIS 10. We assumed that flatter sites are more
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desirable and expensive than steep sites. The number of “transformed” pixels per site is an
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estimate of the amount of infrastructure and anthropogenic activity at a site. Transformed pixels
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include artificial surfaces such as urban areas and farmland and were obtained from a satellite-
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derived land cover map [8]. We assumed that transformed, urbanized land was more valuable
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than land lacking infrastructure. Major roads were obtained from a GIS database [9]. Our model
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makes the assumption that sites close to the road network are more valuable than remote sites
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distant from roads. To model the idea that flat, developed sites located near the road network are
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more expensive that steep, undeveloped sites distant from roads, we defined site cost as:
𝑐𝑖 =
2 1 𝑟𝑖
𝑡𝑖
𝑑𝑖
+ (𝑚𝑎𝑥 − (𝑚𝑎𝑥 + 𝑚𝑎𝑥 ))
3 3 𝑖∈𝐼 𝑟𝑖
𝑡
𝑑
𝑖∈𝐼 𝑖
𝑖∈𝐼 𝑖
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Distance from roads is measured in units of meters whereas topographic diversity is in units of
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m3 and the number of transformed pixels is dimensionless. So that each term would contribute
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equally to the site cost, we normalized the terms by dividing by the maximum value in the study
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region such that road distance, transformed pixels, and topographic diversity each have a
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maximum value of one. The above cost definition also rescales the sum of road distance,
2
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transformed pixels, and topographic diversity cost such that flat, developed land close to roads
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has a cost of one and steep, undeveloped land far from roads has a cost of zero.
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Next, we prioritized sites to meet two criteria: (i) include 17% of the land containing genetic and
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morphological traits of common species and (ii) minimize land cost as defined above. Sites were
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selected using the “Multi-criteria minimum area problem” option in the ConsNet 2.0 software
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package [10]. We also prioritized sites to include environmental parameters and occurrences of
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amphibian and bird species while minimizing site cost. Results indicate that when cost is
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included in the analysis, genetic and morphological traits of seven common species remain the
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best surrogate for threatened and endemic species (figure S3). To begin, in figure S3, the line
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representing genetic and morphological traits is above and to the left of the line that represents
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sites selected at random for almost all data points. This means that intraspecific variation almost
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always performs significantly better than random with respect to the representation of threatened
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and endemic species. Furthermore, genetic and morphological traits perform better than
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environmental parameters or occurrences of amphibian and bird species when land value is
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included in the prioritization. In figure S3, the lines representing species occurrences and
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environmental parameters are below and to the right of the line that represents randomly selected
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sites for more than half of the data points, indicating that bird and amphibian occurrences and
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environmental data perform no better than random in the majority of cases. Finally, the line that
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depicts genetic and morphological traits is always above and to the left of the lines representing
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species occurrences and environmental variables, which means that areas prioritized based on
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genetic and morphological data include more habitat for threatened and endemic species than
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sites prioritized based on occurrences of amphibians and birds or environmental data when the
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prioritization accounts for land cost.
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Table captions
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Table S1. Spatial resolution of the planning units for the selection of conservation areas,
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generalized dissimilarity models (GDMs) of genetic and morphological diversity, and
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species distribution models (SDMs) for threatened and endemic species. At all spatial
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resolutions, the analysis utilized square cells.
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Table S2. Spatial congruence of conservation areas selected to include genetic and
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morphological traits of common species and threatened and endemic species. The spatial
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configurations of sites prioritized to include intraspecific variation were compared to
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configurations of areas prioritized based on threatened and endemic species using a Cramer-von
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Mises test [11,12]. The null hypothesis is that there is significant overlap in the spatial
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configurations of the selected areas. In each case, we failed to reject the null hypothesis,
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suggesting that areas priorized based on genetic and morphological variation are similar in
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spatial extent to land selected based on threatened and endemic species.
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Table S3. Environmental classes used in the surrogacy analysis.
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Table S1.
Planning unit
Selection of
conservation areas and
surrogacy analysis
Scale (km)
10
No. of planning units
639
GDM
1
9378
GDM predicts the distribution of environmentallyassociated genetic and morphological variation across
the landscape. The environmental variables were
available at the 1 km scale [13].
SDM
1
9378
Environmental variables used to construct the species
distribution models were available at the 1 km resolution
[14].
150
10
Rationale
The correlation between surrogates and threatened
species is highest at this scale [11].
151
Table S2.
Target for genetic and
morphological traits (%)
10
10
10
17
17
17
Target for threatened & endemic
species (%)
17
34
50
17
34
50
Cramer-von Mises
statistic
1.557
2.336
2.899
2.103
2.624
3.273
152
11
p
0.81
1
1
0.5
1
1
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Table S3.
Environmental variable(s)
Annual mean temperature, total annual
precipitation
Aspect
Elevation
Maximum temperature of the hottest
quarter of the year, minimum temperature
of the coldest quarter
Slope
Reference
[15]
Data Processing*
Divided into 10 equal interval classes
Calculated from elevation**
[7]
[15]
Divided into nine classes of 40° each
Divided into 10 equal interval classes
Divided into four equal interval classes
Calculated from elevation**
Soil type
[16]
Divided into five classes based on standard
deviations
Utilized soil associations types in the FAO
world soil map
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*Processing of environmental variables follows published protocols [11,17].
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**Aspect and slope were calculated from elevation using Spatial Analyst Tools in ArcGIS 10.
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Figure captions
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Figure S1. Workflow for converting genetic and morphological variation into a set of
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prioritized areas.
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Figure S2. Bar heights represent the number of threatened and endangered species per 100
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km2 site when sites were prioritized based on: (a) genetic and morphological variation of
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seven common species, (b) environmental features, and (c) species occurrences. In each
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panel, the vertical axis is richness of threatened and endemic species. Sites prioritized based on
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genetic and morphological diversity of common species contain more threatened and endemic
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species per site than sites prioritized based on environmental features or occurrences of birds and
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amphibians. The mean number of threatened and endangered species in the entire set of the
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selected sites is also highest when we prioritized areas based on intraspecific genetic and
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morphological variation (figure 2 of the main text). Bars are normalized by the mean richness of
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threatened and endemic species in each panel.
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Figure S3. Effectiveness of genetic and morphological surrogates for threatened and
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endemic species when land cost is included in the prioritizations.
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Figure S4. Sites selected to include genetic and morphological traits are effective surrogates
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for threatened and endemic species when we used lower percentage targets for the former
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and higher percentage targets for the latter than in the main text. (A) The targets for the
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selection of sites: 50% for threatened and endemic species and 10% for genetic and
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morphological traits. We first prioritized areas to include 50% of the land containing threatened
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and endemic species using a complementarity-based algorithm [18]. Next, we selected sites to
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include 10% of the land containing each one of the genetic and morphological traits of the
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common species. We used a target of 50% for threatened and endemic species because the 17%
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target used in the main text may be too low in some conservation planning contexts; for example,
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conservation plans for critically endangered species may attempt to conserve at least 50% of
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extant habitat [19,20]. We used a 10% target for genetic and morphological traits because the
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17% target may be too high for widespread components of biodiversity, and 10% has seen
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widespread use in conservation planning exercises [11,21-23]. For example, Illoldi-Rangel et al.
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[20] used a 50% target for endemic species and a 10% target for non-endemics. We then
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calculated the percentage of threatened and endemic species that had 50% of their habitat
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included in sites selected to include 10% of the occurrences of the genetic and morphological
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traits of common species. Finally, we calculated the percentage of threatened and endemic
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species that had 50% of their habitat included in sites selected at random. Results indicate that
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genetic and morphological traits of common species are effective surrogates for threatened and
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endemic species insofar as sites selected to include the former contain significantly more
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threatened and endemic species than sites selected at random. For example, on the “genetic and
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morphological traits” curve in panel (A), the point with the x-coordinate 5% and the y-coordinate
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15% has the following interpretation. If land comprising 5% of the study region is selected to
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include intraspecific variation, then such land includes 15% of the threatened and endemic
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species. (B) Targets: 34% for threatened and endemic species and 10% for the genetic and
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morphological traits of common species. The target of 34% was utilized for threatened and
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endemic species because it is twice as large as the 17% target used in the main text. We selected
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sites to include 10% of the genetic and morphological traits for the reasons listed above. The
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“genetic and morphological traits” curve is similar to panel (A) but the y-coordinates of the
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points are higher because the target for the threatened and endemic species is lower than in (A).
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Since the target is lower, the target is satisfied for a higher percentage of the threatened and
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endemic species than in (A). In both panels, the range of the x-axis is zero to ten because the
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target for the genetic and morphological traits was 10%. Sites selected to include 10% of the
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occurrences of the genetic and morphological traits comprise approximately 10% of the total
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area of the study region.
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Figure S5. Effectiveness of genetic and morphological surrogates for threatened and
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endemic species. This figure is the same as figure three of the main text except that in the latter
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the target was 17% for all surrogates whereas here the target is 10%. The black line with white
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circles represents the percentage of threatened and endemic species that is found in areas
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designed to include unique intraspecific morphologic and genetic traits of common species. The
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solid black line shows the percentage of threatened and endemic species in random areas. The
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black line with white squares depicts areas selected to include occurrences of birds and
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amphibians. The gray line represents environmental surrogates. Since the black line with white
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circles is to the left of the other lines, areas designed to include intraspecific variation of
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common species protect the highest percentage of threatened and endemic species.
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CBD=Convention on Biological Diversity.
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Figure S1.
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Figure S2.
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Figure S3
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228
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Figure S4
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Figure S5
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20