3.1. Evolutionary Hotspots
The average divergence landscape encompassed 110,089 km
2 after clipping to the extent with three or more species overlapping, representing 73% of the study area. Data were lacking in the most northern and western portions of the study region (
Figure 2A). The most divergent areas (categorized as greater than 1.5 standard deviations above the mean) encompassed 4,864 km
2 or 4.4% of the analyzed area. We expected highest areas of divergence across habitat transition zones and our results generally concur with this, as hotspots generally ring the ecoregion. We identified 10 locations with highest levels of genetic divergence (
Table 2;
Figure 3 labeled regions A-J). These hotspots varied in the number and composition of contributing individual species (
Table 2). Concordance was greatest in the Colorado River hotspot, with 10 species showing high divergence in this region, while the Ivanpah Valley and Virgin Mountains hotspots reflect high divergence in only one species each,
G. agassizii and
A. punctatus, respectively. However, the Ivanpah hotspot was also a region of high gene diversity in several other species examined. While relatively few species had high sequence divergence or diversity in the Virgin Mountains, this region has been previously identified as a zone of secondary contact and hybridization in amphibians [
37], a group that is only represented by one species in our dataset. Across all species, variation among datasets was generally highest in the central portion of the study region. (
Figure 2A inset).
Table 2.
Identified divergence and diversity hotspots and individual species contributing to each hotspot. Species codes refer to the first two letters of the genus and species name (full names provided in the table footer). Geographic and geological factors that may have contributed to high levels of genetic divergence and diversity within each region are also listed.
Table 2.
Identified divergence and diversity hotspots and individual species contributing to each hotspot. Species codes refer to the first two letters of the genus and species name (full names provided in the table footer). Geographic and geological factors that may have contributed to high levels of genetic divergence and diversity within each region are also listed.
Map Code | Place Name | Divergence | Sequence Diversity | Gene Diversity | Possible Historical Isolating Factors |
---|
A | Dunmovin - Coso Junction | PLGI, XEMO | XEMO | PLGI, XAVI | Transition from Mojave to Owens Valley |
B | Sierra -Tehachapi Transition | PLGI, THBO, XAVI | PELO, GOAG, XEMO | CHOC, PLGI, XAVI, XEMO | Transition from Mojave to large mountains in the west |
C | Antelope Valley - Mojave Desert Transition | PELO, PLGI, THBO, XEMO | XEMO | PELO, PLGI, THBO, XAVI, XEMO | Transition from western grasslands to eastern scrublands |
D | Ord Mountains - Lucerne Valley | CHPE, PELO, SCMA, THBO, XAVI | PLGI, XAVI | PLGI, XAVI | Historic barrier formed by Mojave River |
E | Indio Hills - Little San Bernardino Mountains | DIDO, HOTH, LITR, PELO, PLGI, THBO, XAVI | HOTH, LITR, PELO, SCMA, XAVI | CHPE, HOTH, LITR, OVCA, PELO, PLGI | Transition from low Sonoran/Colorado desert (Coachella Valley) into high desert of Little San Bernardino Mountains. |
F | Pluvial Lakes (Bristol/Cadiz/Danby) | HOTH, OVCA, SCMA, THBO, UMSC, XEMO | HOSE, OVCA, SCMA, UMSC | ANPU, CHOC, CHPE, OVCA, UMSC, XAVI | Historic barrier across low elevation lakes, Mojave/Sonoran Transition |
G | Colorado River Mountains (Mojave/Black Mountains) | ANPU, CHOC, CRBI, DIDO, HOSE, HOTH, LITR, OVCA, PLGI, SCMA | CHPE | ANPU, CHPE, GOAG | Barrier across river and/or mountains on eastern side of river |
H | Sacramento-Detrital Valley | DIDO, HOSE | CHPE, HOSE | CHPE, XAVI | Low valley transition between Mojave and Sonoran desert |
I | Ivanpah Valley | GOAG | | CHOC, GOAG, OVCA, XAVI | Historic barrier across low elevation lakes |
J | Virgin Mountains | ANPU | ANPU, GOAG | | Barrier between Virgin Valley and Shivwits Plateau |
Figure 2.
(A): Average sequence divergence for 17 animal species; (B): Average sequence diversity for 14 animal species; (C): Average gene diversity for 13 animal species. The insets in each figure show the coefficient of variation among individual species layers included in each average.
Figure 2.
(A): Average sequence divergence for 17 animal species; (B): Average sequence diversity for 14 animal species; (C): Average gene diversity for 13 animal species. The insets in each figure show the coefficient of variation among individual species layers included in each average.
Sequence diversity (π) was averaged across 14 species (
A. punctatus, C. occipitalis, C. penicillatus, G. agassizii, H. selenopoides, H. theologus, L. trivirgata, O. canadensis, P. longimembris, P. gilberti, S. magister, U. scoparia, X. vigilis, and X. mohavensis). The remaining three species in our dataset (
C. bicinctores, D. dorsalis, and
T. bottae) were excluded from diversity analyses because only single individuals were sampled at disparate locations that could not be combined. The average sequence diversity landscape covered 87,982 km
2 when clipped to include three or more species (
Figure 2B). High sequence diversity hotspots encompassed 6,724 km
2, or approximately 7.6% of the area. Sequence diversity hotspots were mainly concentrated along the western and southern boundaries of the Mojave Ecoregion and overlapped with regions of high divergence (
Table 2,
Figure 3). Individual species showed the greatest concordance at the Ord Mountain -Lucerne Valley hotspot with 5 species showing high sequence diversity (
Table 2). Variation among species was generally greatest in the northeast portion of the study region, with patches throughout the central and southwest Mojave Desert (
Figure 2B inset).
Gene diversity (heterozygosity) was averaged across 13 species (
A. punctatus, C. occipitalis, C. penicillatus, G. agassizii, H. selenopoides, H. theologus, L. trivirgata, O. canadensis, P. longimembris, P. gilberti, S. magister, U. scoparia, X. vigilis, and X. mohavensis).
Sceloporus magister was excluded because most sampling locations contained less than three individuals. The gene diversity average genetic landscape covered 71,468 km
2 when clipped to the extent of three or more species and showed some geographical concordance with sequence divergence and diversity (
Figure 2C). Highest diversity was concentrated along the western and southern ecoregional transition zones (
Table 2,
Figure 3). In addition, high average gene diversity was evident in the central Mojave near the Ivanpah Valley (
Figure 4). The Indio Hills and Pluvial lakes hotspots represented the most species, with six species contributing to each (
Table 2). Variation among datasets was generally greatest in the north central and northeastern Mojave Desert (
Figure 2C inset).
Figure 3.
Ten regional hotspots of sequence divergence, sequence diversity and gene diversity with relation to land conservation status in the Mojave Desert. Hotspots are A (Dunmovin–Coso Junction), B (Sierra–Tehachapi Transition Zone), C (Antelope Valley–Mojave Desert Transition), D (Ord Mountain–Lucerne Valley), E (Indio Hills–Little San Bernardino Mountains), F (Pluvial Lakes), G (Colorado River), H (Sacramento–Detrital Valley), I (Ivanpah Valley), and J (Virgin Mountains).
Figure 3.
Ten regional hotspots of sequence divergence, sequence diversity and gene diversity with relation to land conservation status in the Mojave Desert. Hotspots are A (Dunmovin–Coso Junction), B (Sierra–Tehachapi Transition Zone), C (Antelope Valley–Mojave Desert Transition), D (Ord Mountain–Lucerne Valley), E (Indio Hills–Little San Bernardino Mountains), F (Pluvial Lakes), G (Colorado River), H (Sacramento–Detrital Valley), I (Ivanpah Valley), and J (Virgin Mountains).
The complex climatic and geological history of the Mojave Desert likely contributed to the formation of evolutionary hotspot regions detected. Hotspots are clustered in locations along the western and southern regions of the Mojave Desert, where past inundation, uplift, and the cyclical formation of riverine and lacustrine systems may have isolated lineages [
50]. These areas may represent secondary contact zones or “suture zones” for previously isolated lineages across multiple species [
83,
84]. Regions of high gene diversity and heterozygosity may also reflect large effective population sizes [
7,
8,
9,
85] or refugia [
10]. In addition to historical isolating events, current environmental conditions may contribute to diversity and divergence hotspots in regions with steep environmental gradients (e.g., steep ecotones between mountains and basins).
This study focused on patterns of genetic variation that are presumed to be selectively neutral. Clearly, the ultimate measure of evolutionary potential is genetic variation underlying traits that will be under selection in the future. Although higher intrapopulation genetic diversity measured at neutral loci can be associated with higher fitness and lower extinction rates [
14,
86], correlations between neutral and adaptive variation are not always strong [
87,
88]. However, inferences of adaptive potential are strengthened when the genetic hotspots overlap spatially with zones of lineage recontact and/or steep environmental gradients. Hybridization between previously isolated and divergent lineages or populations can create novel gene combinations that can facilitate speciation and adaptive evolution in some cases [
11,
89,
90,
91,
92,
93]. Adaptive variation is also often concentrated across ecological transitions [
94,
95,
96]. Although not included in this study, previous genetic and morphological analysis of the
Neotoma lepida group revealed zones of lineage recontact and hybridization between coastal and desert morphological groups in Kelso Valley (near hotspot B) and in Morongo Valley (hotspot E) [
97]. Likewise, in the Mojave Desert annual
Linanthus parrayae, dimorphism in flower color occurs in local populations found within hotspot D near Lucerne Valley and Victorville, and along the base of the San Gabriel Mountains near Palmdale [
98]. Flowers are white throughout the majority of the species range, but blue flowers occur with variable frequencies in these mixed populations. Color dimorphism seems to be maintained by temporally variable selection associated with annual rainfall patterns and differential water use [
99,
100]. The adaptive potential stored in ecotonal evolutionary hotspots is likely to become increasingly important as climatic conditions change in the future, and environmental gradients intensify, weaken or shift spatially [
22,
101,
102]. Other studies have also highlighted regions of the Mojave. Our broader analysis encompassing both the Mojave and Sonoran Deserts and including a subset of the species considered here also highlighted hotspots of high neutral diversity and divergence near Ord Mountain—Lucerne Valley, along the Mojave/Sonoran ecotone and across the Colorado River (corresponding to hotspots D, E, F and G in
Figure 3) [
20]. Finally, in an independent analysis focusing on California plants, Kraft
et al. [
5] recognized the Mojave as an important region of evolutionary potential in California, as it contains some of the youngest neoendemic vascular plants.
Because our genetic landscapes are interpolations from point data, the resulting patterns are highly dependent on the number and dispersion of collection locations across the landscape. When individual species datasets vary in sampling location and density (as with those compiled for this study), undoubtedly, uncertainty in the spatial location of hotspots is introduced. With this in mind, we caution against using the resulting hotspots maps for pinpointing exact locations for conservation purposes, rather we feel their utility is greatest for more broadly identifying regions of evolutionary potential within the ecoregion.
3.2. Protection and Vulnerability of Hotspots
All three averaged genetic landscapes had slightly more total area categorized as “At-Risk” than “Protected”, although mean scores for both categories did not vary substantially (
Table 3). For divergence and diversity hotspots, a greater percentage were considered “At-Risk”
versus “Protected” (divergence hotspots: 55% “At-Risk”, 40% “Protected”; sequence diversity hotspots: 53% “At-Risk”, 39% “Protected”; gene diversity hotspots: 63% “At-Risk”, 29% “Protected”;
Table 3). Six identified hotspots were located primarily outside of protected lands, including hotspot A (Dunmovin–Coso Junction), B (Sierra–Tehachapi Transition Zone), C (Antelope Valley–Mojave Desert Transition), D (Ord Mountain–Lucerne Valley), F (Pluvial Lakes), and H (Sacramento and Detrital Valleys,
Figure 3).
Mapped USRED project footprints encompassed approximately 3,547 km
2 across the study region, while transmission corridors occupied approximately 14,483 km
2. The area of overlap of average divergence and diversity landscapes with USRED project footprints ranged from 2,563 to 3,209 km
2 and overlap with transmission corridors ranged from 8,503 to 10,733 km
2 (
Table 3). USRED footprints overlapped with 3–7% of the area designated as divergence or diversity hotspots, but this rose to 10–17% with the inclusion of transmission corridors (
Table 3). Certain hotspot regions overlapped more than others. Hotspots B (Sierra–Tehachapi Transition Zone), D (Ord Mountain–Lucerne Valley), F (Pluvial Lakes) and G (Colorado River) showed the most overlap with project footprints, while Hotspots C (Antelope Valley–Mojave Transition) and I (Ivanpah Valley), showed the most overlap with transmission corridors. In total, 6 of the 10 identified divergence and diversity hotspot regions have the potential to be impacted by energy and infrastructure development (
Figure 4).
Figure 4.
Ten regional hotspots of sequence divergence, sequence diversity and gene diversity overlaid with existing and pending utility scale renewable energy development (USRED) project site footprints and energy corridors. Impervious surfaces represent existing urban development.
Figure 4.
Ten regional hotspots of sequence divergence, sequence diversity and gene diversity overlaid with existing and pending utility scale renewable energy development (USRED) project site footprints and energy corridors. Impervious surfaces represent existing urban development.
Table 3.
Overlap between divergence and diversity landscapes, land status, proposed utility scale renewable energy development (USRED), and transmission corridors.
Table 3.
Overlap between divergence and diversity landscapes, land status, proposed utility scale renewable energy development (USRED), and transmission corridors.
Layer | Divergence | | | Sequence Diversity | | | Gene Diversity | | |
---|
| Area (km2) | Mean Score | Score Range | % Hotspot Area | Area (km2) | Mean Score | Score Range | % Hotspot Area | Area (km2) | Mean Score | Score Range | % Hotspot Area |
---|
Total Layer | 110,089 | 0.42 | 0.08–0.72 | 5% | 87,982 | 0.25 | 0.02–0.75 | 7% | 71,468 | 0.6 | 0.08–0.91 | 4% |
“Protected” Lands | 47,428 | 0.42 | 0.19–0.69 | 40% | 37,775 | 0.25 | 0.02–0.58 | 39% | 32,363 | 0.59 | 0.08–0.91 | 29% |
“Uncertain” Lands | 8,275 | 0.39 | 0.10–0.64 | 5% | 5,213 | 0.24 | 0.05–0.75 | 8% | 3,388 | 0.56 | 0.13–0.87 | 8% |
“At-Risk” Lands | 54,188 | 0.42 | 0.08–0.72 | 55% | 44,881 | 0.25 | 0.02–0.66 | 53% | 35,709 | 0.61 | 0.10–0.91 | 63% |
USRED Footprint | 3,209 | 0.44 | 0.08–0.67 | 4% | 2,906 | 0.24 | 0.05–0.65 | 3% | 2,563 | 0.58 | 0.27–0.91 | 7% |
Transmission Footprint | 10,733 | 0.43 | 0.09–0.66 | 10% | 9,863 | 0.24 | 0.03–0.67 | 8% | 8,503 | 0.6 | 0.18–0.91 | 12% |
USRED + Transmission | 12,554 | 0.43 | 0.08–0.67 | 13% | 11,477 | 0.24 | 0.03–0.67 | 10% | 9,970 | 0.6 | 0.18–0.91 | 17% |
Because evolutionary hotspots tend to occur in ecological transition zones, they may not necessarily be included in national and state parks, or other protected lands aimed at preserving exemplars of ecoregions and geomorphic provinces. We found that greater than half of the total area identified as divergence and diversity hotspots fell outside of designated protected lands. While less than 10% of the total area identified as diversity and divergence hotspots overlapped with current and pending USRED project sites, four hotspots showed substantial spatial overlap. When transmission corridors were included, overlap with hotspots increased up to 17%. Mapped energy corridors have high overlap with two additional hotspots in our study area. Given the potential impact of USRED in these areas, these six evolutionary hotspots may deserve further investigation, both in terms of habitat use and fine scale genetic structure across these regions, and in terms of specific impacts of USRED on wildlife populations in these regions.
While we have evaluated the spatial overlap between hotspot regions and planned renewable development, we do not have data on the extent to which these developments will directly impact individuals and populations in these locations. Perhaps of greatest importance to maintaining the functionality of evolutionary hotspots is mitigating the potential reduction of population size and connectivity due to habitat loss and fragmentation within and surrounding development footprints. Habitat disturbance within USRED project footprints may vary depending on the number and size of wind turbines or solar arrays placed at a site, vegetation clearing, access roads, fencing, and other project requirements [
103]. Many of the mapped USRED projects currently slated for development within hotspot regions will generate wind energy. The documented effects of large scale wind energy farms on wildlife are varied. Research has largely focused on direct mortality of birds and bats from collisions [
103,
104], with impacts varying by life history and ecology of species [
105,
106], wind turbine type [
106], and other specific site characteristics (e.g., region, layout design of the site, topology, weather, and lighting [
107]). Direct effects on ground dwelling animals are largely unknown. Behavioral changes due to turbine noise have been documented in ground squirrel populations [
108], but no differences were noted in individual growth rates and mortality in a population of desert tortoises on a wind farm when compared to other locations [
109]. The effects of solar development projects on wildlife have not been well documented in the scientific literature [but see 80,110], and will likely vary extensively with the type of system and specific site management practices, although it should be noted that sites developed in the Mojave appear to have high levels of impact (e.g., blading with removal of all topsoil and vegetation, fencing,
etc.). Associated USRED infrastructure including transmission corridors and road networks can affect connectivity [
111,
112], and may have a greater impact on connectivity in the Mojave than production sites themselves. Transmission corridors and surrounding right-of-ways throughout the Mojave Desert could encompass up to four times as much area as project footprints alone. In addition these crisscross through both protected and unprotected lands, further fragmenting the Mojave Desert. Over the long term, fragmentation and isolation may lead to loss of genetic diversity and increased divergence among sites, however this may take many generations to be measurable [
113,
114]. While transmission corridors and associated road networks may represent barriers to movement for some species, they may be permeable or even facilitate movement for others [
115,
116,
117]. Variable disturbance characteristics can influence permeability (e.g., corridor width, grading, vegetation removal, paving, lighting, fencing, culverts, berms and traffic volume (reviewed in [
103,
112,
118]). Transmission corridors and roads may also act as conduits for exotic and invasive species [
119,
120]. For example, power lines, roads and other linear right-of-ways provide nesting and perching sites for predatory birds, including the common raven,
Corvus corax [
121,
122,
123]. Large raven populations subsidized by human development in the Mojave Desert and elsewhere pose a threat to juvenile desert tortoises and other sensitive prey species [
124]. Increased perch availability in xeric habitats has been studied elsewhere and shown to have a negative impact on certain prey species of lizards [
125].
Future survey and genetic research efforts may better resolve patterns of genetic diversity in the Mojave Desert, and refine our assessment of evolutionary hotspots. Our initial work was opportunistic, relying mainly on previously conducted population genetic and phylogeographic studies. Increasing genetic sampling of additional species representing different ecotypes or species guilds, and gathering genomic data representative of both functional and selectively neutral diversity could provide greater resolution of population-level patterns across the landscape, and determine whether the hotspots identified here are indicative of a wider range of species, and how well these reflect patterns of adaptive genetic diversity. The lack of coverage in the northern Mojave represents a significant data gap. Because hotspots tend to occur at ecotones, the northern transition between the Mojave and Great Basin may also retain high genetic diversity. This region may be particularly important if climate change results in northward range shifts for some species [
126,
127]. Finally, focused surveys aimed at determining population status, fine-scale habitat suitability, and movement corridors within identified hotspot regions could further assess the potential site-specific impacts of USRED and other development to wildlife populations in these regions.