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Abstract

Background and Research Aims

Climate change, habitat loss, and fragmentation are the major threats to biodiversity. Montane amphibians are particularly sensitive to these threats. We address the vulnerability of the amphibian community in Colombia using a Climate Change Vulnerability Assessment (CCVA) and prioritize amphibian species at risk of extinction and in need of conservation actions.

Methods

We completed two independent spatial analyses to assess species vulnerability in the Sierra Nevada de Santa Marta (SNSM), Colombia. First, we calculated the Area of Habitat and the percent of the Area of Habitat under protected area coverage for 19 species. We then examined the breadth of climatic space occupied by 16 species and how this space is predicted to shift under climate scenarios (RCP scenarios 4.5 and 8.5) for 12 General Circulation Models for 2050. We combined these two analyses with trait data related to adaptive capacity, obtained from previous research, to create a combined (correlative-trait) CCVA.

Results

Our analysis reveals a large reduction in available climatic space under both RCP scenarios by 2050. Our CCVA identified eight high priority species, including three Atelopus species and five within the Serranobatrachus/Tachiramantis complex, with extreme reductions in available climate space under RCP 8.5. The SNSM endemic and range restricted species are at elevated risk of extinction under climate change scenarios, with many moving into a high-risk category of extinction under the RCP 8.5. Given its isolation, the endemic species of the Sierra Nevada de Santa Marta (SNSM) are threatened by changing climates.

Implications for Conservation

The information provided in this manuscript used a vulnerability assessment to develop regional strategies for climate change adaptation and conservation. When possible, climate vulnerability must be incorporated into future adaptation and priority planning for the conservation of endemic, threatened montane amphibians, preferably via local management plans.

Keywords

amphibians climate change vulnerability assessment neotropics modeling threatened species

Introduction

Globally, over one-fifth of vertebrate species are threatened with extinction (Hoffmann et al., 2010; Howard et al., 2020). Climate change, habitat loss or fragmentation, pollution, and species exploitation all play a significant role in biodiversity loss (Bellard et al., 2012; Lacher & Roach, 2018; Parmesan et al., 2011; Urban, 2015). Montane species may be detrimentally impacted by climate change due to strong altitudinal gradients in community composition, restricted ranges, and isolation (Anderson, 2013; Bax & Francesconi, 2019; Elsen & Tingley, 2015; Huey, 1978; La Sorte & Jetz, 2010) resulting in loss of habitat and species assemblage homogenization (Jantz et al., 2015; Menéndez-Guerrero et al., 2019; Nowakowski et al., 2018) and reduction in adaptive divergence along steep elevational gradients (Bachmann et al., 2020).

In 2016, the International Union for Conservation of Nature (IUCN) Climate Change Specialist Group produced the Climate Change Vulnerability Assessment (CCVA) guidelines; a useful conservation application to understand the threats and subsequent vulnerability to extinction risk that species will experience under various climate change scenarios and information to prioritize conservation action (IUCN Species Survival Commission, 2016; Pacifici et al., 2015; Foden & Young, 2016).Vulnerability is defined as the net effects of species sensitivity (S; intrinsic factors such as genetic diversity and dispersal capability) and exposure (E; extrinsic factors i.e. habitat loss, disease, invasive species) minus adaptive capacity (AC; the ability of a species to cope with or adjust to a given change and includes both behavioral and ecological plasticity and evolutionary adaptation); expressed as S+E – AC (Foden et al., 2019; IPCC, 2014; Thurman et al., 2020).

Climate change vulnerability assessments have been conducted for frogs, reptiles, birds, and mammals across different geographic regions (Böhm et al., 2016; Gardali et al., 2012; Hagger et al., 2013; von May et al., 2019). Mountain-dwelling ectotherms like amphibians, in particular those with low dispersal ability, are especially threatened by warming that results in the upward shift in temperature, forcing species to shift their ranges up slope to progressively smaller landscapes (Enrique-Urzdai et al., 2019; Ghalambor et al., 2006; Raxworthy et al., 2008), known as the “escalator to extinction (Urban, 2018)”.

In order to assess species vulnerability to climate change, researchers employ a number of methods (Elith et al., 2010; Harris et al., 2014; Peterson et al., 2015). There are four common methodological approaches to vulnerability assessments: correlative, mechanistic, trait-based, and combined approaches (Foden et al., 2019; IUCN Species Survival Commission, 2016). Correlative models are frequently used in CCVAs because there is more widespread availability of data on associations of species occurrence with environmental information (Foden & Young, 2016). Mechanistic modeling approaches reduce uncertainty but are limited because physiological data can be difficult to obtain for many species (Peterson et al., 2015). Trait-based assessments can be useful tools for prioritizing conservation action, but again, trait data are not widely available for all species (Böhm et al., 2016). Combined approaches use one or more of the aforementioned modeling techniques to assess vulnerability. The spatial scale at which data are collected is of critical importance to reducing model and predictive uncertainty (Austin & Van Niel, 2011; Trivedi et al., 2008). Rare and dispersal-limited species, such as amphibians, pose a challenge to CCVAs given the lack of data and verifiable modeling techniques, which have not been refined for small range species with minimal locality data (Platts et al., 2014). Yet, rare and local species assessments are important for conservation efforts and directly feed back into conservation action plans.

Amphibians are the world’s most threatened vertebrate class, with 41% of species threatened with extinction (IUCN, 2023; Stuart et al, 2004). Limited dispersal, small range sizes, and life history strategies often make amphibians more susceptible to climate change impacts (Agudelo-Hz et al., 2019; Bernal & Lynch, 2008; Cheza et al., 2020; Prieto-Torres et al., 2020). Increasing temperatures in the tropics have been associated with an increased risk of amphibians to chytrid fungus (Pounds et al., 2006; Wake & Verenberg, 2008) ). Over 3,300 species of amphibians have predominantly montane distributions (Rahbek et al., 2019), where these species are threatened with habitat loss, climate change, pollution, and disease (Lips et al., 2008; Scheele et al., 2019; Whitfield et al., 2016).

In the tropics, species experience smaller seasonal variation and have narrow physiological tolerances, specific thermal niches, and small population sizes (Deutsch et al., 2008; Janzen, 1967). Most amphibians prefer cool, damp, and stable microclimates (Semlitsch, 2003) and small shifts in microhabitat or microclimate conditions can impact physiology, population dynamics, and habitat use (Rivera-Ordonez et al., 2019). Rare and endemic species, with contracted ranges and limited dispersal, can be particularly difficult to assess given mismatches between data collection and resolution and modeling techniques, yet locally endemic species are some of the most vulnerable to habitat loss and climate change due to their relative rarity and restricted ranges (Lowrey et al., 2016; Mayani-Parás et al., 2019).

Colombia has the second highest amphibian diversity in the world (83 described species) of which 415 (47%) are endemic and 299 (34%) are threatened with extinction (IUCN, 2023; Acosta Galvis, 2023). The Colombian Andes are an amphibian diversity hotspot and encompass a number of key conservation areas (Bernal & Lynch, 2008; Etter et al., 2006; Navas, 2003, 2006). The Sierra Nevada de Santa Marta (SNSM) is an insular range, isolated from the Andean chain, and is an important hotspot of global amphibian endemism with 17 endemics, including 10 threatened species (IUCN, 2023).

Hypotheses and Predictions

Our objective was to assess amphibian vulnerability to climate change in the SNSM. Previous studies in the region demonstrated that climate change would lead to shifts and contractions in amphibian ranges and an increase in unsuitable land within these new ranges (Forero-Medina et al., 2011). It is important to identify direct and indirect threats and provide strategies to reduce extinction risk, particularly for species that present the above characteristics, threats, and challenges in data availability. In order to provide guidance for regional amphibian conservation, we evaluated aspects of the adaptive capacity of amphibians to climate change by screening a suite of traits related to life history, distribution, movement, and abiotic niche (Thurman et al., 2020). We then conducted an independent evaluation of the current breadth in climate space for all species to gain insights on possible distributional limits. Finally, we modeled the shift in climate space for these species in two climate change scenarios under multiple General Circulation Models (GCMs).

The CCVA is not conceived to generate new ecological data, rather to assess future extinction risk where climate is assumed to be the principal driver. We hypothesized that the application of a mix of trait data and climate modeling would reveal a number of vulnerabilities in the community to the shifting climate. Other climate models for the tropical Andes indicate a hotter and drier future climate between 1,000 and 3,000 m a.s.l. (Urrutia & Vuille, 2009), and we hypothesize the same will be found in the SNSM; thus endemic, aquatic breeders at mid to high elevations would be more vulnerable to climate impacts as suitability of breeding sites would likely decrease through altered precipitation patterns and elevated temperatures. We also hypothesized that mid to high elevation forest dependent species will see suitable climate space shifting higher in elevation, potentially outpacing the ability of these species to disperse at the same rate. Finally, we hypothesize that low elevation and widespread species are likely to benefit from a projected warmer and drier climate and maintain or expand their range in the future.

Methods

Study Site

The SNSM is one of the world’s tallest coastal mountain ranges, rising from sea level to 5,775 m asl in 42 km. The region is categorized by high levels of elevational zonation and biodiversity. Le Saout et al. 2013 ranked the SNSM the most irreplaceable site on Earth, based on the mountain’s isolation and high levels of amphibian endemism. The SNSM is also a UNESCO Biosphere Reserve, a National Park (Sierra Nevada de Santa Marta National Park and Tayrona National Park), an Important Bird Area, an Alliance for Zero Extinction Site, and a Key Biodiversity Area (González-Maya et al., 2011).

The geographic isolation of the SNSM, exacerbated by intense gradients in topography, had historically shielded it from extremely high levels of development; however, there has been increasing expansion of agricultural and tourism development in the region since the cessation of years of civil conflict in Colombia (Rocca & Zielinski, 2002; Salazar et al., 2018). Land above 2,500 m is protected as a National Park and Indigenous territories. Below 2,500 m the majority of land is privately owned (agriculture, tourism, nature reserves). Small-scale agriculture from four Indigenous cultures (Kogui, Arhuaco, Wiwa, and Kankuamo) and a thriving campesino (farmer) population impact habitat suitability for amphibians (Roach et al. 2020). Deforestation through small-scale agricultural enterprises has reduced connectivity in the region (Granados-Peña et al., 2014). Recent improvements to infrastructure have increased development and tourism also leading to the degradation of intact habitat. Resource extraction, agricultural intensification, and climate change are the biggest threats to amphibian species in the region (Aide & Cavelier, 1994; Roach et al., 2020).

Amphibian Occurrence Data

We used species occurrence data from GBIF (doi: 10.15468/dl.ihs3es, doi: 10.15468/dl.hcqkns) to supplement the records collected from our visual encounter surveys and generate a minimum of five observations for most of our species (Proosdij et al., 2016). All GBIF data were filtered and refined. We removed duplicate localities, those with georeferencing uncertainty above 1 km, samples outside of a species’ known elevation range, and samples with taxonomic uncertainty. Given that most of our species are endemics with small, restricted ranges, we opted to not filter occurrence records further as that would leave too few records for further analysis. This left us with 2,495 occurrence points for the CCVA.

An additional 154 recent field observations were added to the GBIF data by the first author from visual encounter surveys (Heyer et al., 1994; Roach et al., 2020) on the north-western slope of the SNSM, in the department of Magdalena (S1 Figure) between September 2017 and July 2018 as part of a larger study on the distribution of amphibians in the SNSM (details of this methodology and maps of the study sites can be found in Roach et al., 2020). Survey sites were composed of both public and private lands, including the Sierra Nevada National Park and the San Lorenzo Biological Field Station. All data were obtained with permission from the Corporación Autónoma Nacional de Magdalena and the Universidad de Magdalena (14-000034461-DCP-2500) and approved by IACUC Animal Use Protocol 2017-0134 “Assessing the distribution, vulnerability, and conservation of threatened amphibians to land use and climate impacts in Colombia” at Texas A&M University. The total number of occurrence data points used in the climate vulnerability assessment was 2,649. The final curated data set is available at Dryad (https://datadryad.org) as "Sierra Nevada de Santa Marta frog locality data" at (doi:10.5061/dryad.tdz08kq1d).

Climate Change Vulnerability Assessment Outline

We employed the metrics of adaptive capacity (Thurman et al., 2020) and environmental filtering (Ocampo-Peñuela et al., 2016) along with evaluations of available habitat Brooks et al., 2019) and estimation of protected area coverage (UNEP-WCMC & IUCN, 2022) followed by hypervolume-based models of current and future climate space (Blonder et al., 2014) to conduct the vulnerability assessments for each species. Our procedure closely follows the published recommendations for conducting CCVAs (Foden et al., 2013, 2019; IUCN Species Survival Commission, 2016; Thurman et al., 2020) and we outline all procedures below.

Amphibian Trait Data

The assessment of adaptive capacity is an essential component of a CCVA. The goal is to select attributes from a number of broad categories: life history, demography, distribution, movement, evolutionary potential, ecological role, abiotic niche (Foden et al., 2013; Thurman et al., 2020). Not all categories need to be represented, but as broad a representation as possible is recommended (Thurman et al., 2020). Some of these categories are continuous variables, and others are either ordinal or binary. When the data availability for continuous variables is inconsistent, there is the option to rank species on a high-medium-low ordinal scale. It is ideal to have species-specific, experimental, or mechanistic data to assess adaptive capacity, but these data are lacking for most species of amphibians globally, and for nearly all species in the SNSM. We selected the following trait variables to consider in our species level assessments: reproductive mode, mating system, extent of occurrence, geographic rarity, habitat specialization, dispersal distance, site fidelity, population size, climate niche breadth (Amphibia Web, 2023; Mendoza-Henao et al., 2019; Stuart et al., 2008). Not all attributes were available for all species and were used on a species-specific basis while others were used for the entire amphibian community and are described below. We used the recent taxonomic revision of Arroyo et al. (2022) to update the taxonomy of former Pristimantis. The scarcity of trait data for many species reinforces that value for continued natural history research on these and all species.

Statistical Methods: Area of Habitat and Protected Status

We used the IUCN Red List Extent of Occurrence (EOO) polygons (EOO maps accessed from https://www.iucnredlist.org/ in 2017), to calculate Area of Habitat (AOH, km²), defined as the “habitat available to a species, that is, habitat within its range” (Brooks et al., 2019). Extent of Occurrence polygons are minimum convex polygons that represent the dispersion of risk for species to threats and are not range maps (IUCN, 2012). They are often the only available spatial data for species on the Red List, especially when there are too few data points to calculate Area of Occupancy (AOO), the closest equivalent of range in IUCN terminology (IUCN, 2012). None of the 19 species in the study had AOO estimates, common for rare endemics. We included two of our three non-endemic species in our AOH analysis: Leptodactylus savagei and Lithobates vaillanti, both of which have largely Central American distributions, but with disjunct populations in the SNSM which were included in our analysis. These non-endemic species are classified as Least Concern on the IUCN Red List and though not priority candidates for a vulnerability assessment were included to compare their response to the models to the endemics. We did not include records from the Boana boans group, which is broadly distributed throughout the Amazon Basin and the northern Pacific and Caribbean coasts of South America. There is some taxonomic confusion in records on which Boana species (Lynch & Suárez-Mayorga, 2001) occurs at which localities in the SNSM and we were unsure of the reliability of the GBIF data given this confusion.

Following the published methodology (Brooks et al., 2019), AOH was derived for our selected 18 of 19 species. We filtered EOO polygons for all study species according to the published elevation range and land cover classifications taken from the most recent IUCN Red List Assessments for each species (S1 Table). We used elevation data from the Shuttle Radar Topography Mission digital elevation model version 4.1 (Jarvis et al., 2017) at a resolution of 250 m and land cover data from the 2018 European Space Agency Climate Change Initiative Land Cover product at a resolution of 300 m. Both raster layers were resampled to ∼ 1 km resolution before being used to filter the species polygons. The resulting polygons representing AOH for each species were validated using the point data previously described and obtained from the Global Biodiversity Information Facility ("Sierra Nevada de Santa Marta frog locality data" at (doi: 10.5061/dryad.tdz08kq1d) following Brooks et al. (2019). The resultant AOH maps represent an estimate of the present-day occurrence of all species based upon all available data, and results in an Area of Habitat (AOH) much smaller than the published EOO values often used in ecological and biogeographic research. Additionally, for each species, we calculated percent coverage of protected areas for all AOH estimates using the most recent shape files from www.protectedplanet.net available through the World Database on Protected Areas (Explore the World’s Protected Areas, 2022) of the IUCN World Commission on Protected Areas. This approach has been used to generate estimates of percent of potential range under some level of protection (Warudkar et al., 2022).

Climate Space Analysis

The assessment of the vulnerability of species to climate change is now a critical part of IUCN Red List Assessments, and studies range from coarse-scale global analyses (Foden et al., 2013; Pacifici et al., 2017), to species interactions (Gómez-Ruiz & Lacher, 2019) and detailed species-specific assessments (Vicenzi et al., 2017). There are multiple available modeling approaches, and species distribution models are most widely used, but they present limitations when assessing the risk for rare, range-restricted endemics with few presence data points due to model overfitting or a lack of data to model (Breiner et al., 2015). Using techniques that provide a coarser view of a species’ relationship with environmental space, such as niche ordinations or calculating hypervolume overlap, can provide useful information in these scenarios (Broennimann et al., 2012; Di Cola et al., 2016; Guisan et al., 2014; Jezkova, 2020). These techniques determine the density and shape of the climate space of a species within the given environmental space using methods such as kernel density estimation or support vector machines. Importantly, this analysis allows for a comparison to be made between species, different populations of species, and species at different time points by calculating the overlaps in climate space.

To assess current and future climate space of species within the SNSM, we used hypervolumes (Blonder at al., 2014) to quantify a coarse measure of species’ overlap with climatic space in the SNSM. We further determined how this overlap shifts under two climate scenarios. We used our species occurrence data from GBIF and the visual encounter surveys as described in the section on amphibian occurrence data. Only species with at least five occurrence points were used in the modeling. We defined our geographic extent for analyses as the entire range of the SNSM, which would encompass all available habitats from sea level to 5,775 m with a one-degree buffer around the SNSM to include potential low elevation, non-montane climates.

At this stage, the endemic species Atelopus nahumae and Serranobatrachus carmelitae did not have sufficient occurrence data to include in the analysis, and we had excluded the broadly distributed Boana records for reasons discussed earlier, leaving 16 species for the CCVA. We used the hypervolume package (version 2.0.12) in R version 4.0.2 (R Core Team, 2020) to quantify the percentage of climatic space within our geographic extent occupied by our 16 focal species (Blonder at al., 2014; R: The R Project for Statistical Computing, 2022). The hypervolume package enables the computation of an n-dimensional hypervolume for a series of points (Blonder et al., 2014). Using the hypervolume function, we constructed hypervolumes using kernel density estimation and a bandwidth estimated using the function's internal cross validation procedure, as opposed to choosing a value or using the Silverman or plug-in estimator. This particular method cannot take into account adaptation by the species to new niches, but this is unlikely to affect our study given our interest in the near future of 2050. However, due to our small sample sizes, this methodology provides the opportunity to determine where these species exist in climate space and see how the areas where they exist may shift in multiple climate change scenarios.

To define climate space for this study, we considered the 19 bioclimatic variables from WorldClim version 1.4 (Hijmans et al., 2005l; S2 Table). Version 1.4 is better suited for our analysis than Version 2.1 as it projects at a spatial resolution of 30 arc seconds (∼ 1 km) rather than 2.4 arc minutes (∼ 5 km) and thus is superior for modeling in topographically variable montane systems (Bobrowski et al.2021). This does have a small cost of setting current climate for the period 1960 – 1990; however, given the temporal heterogeneity of the date of collection of GBIF records (Di Marco et al. 2021) and the smaller number of recently collected occurrence records we feel this is not an issue. WorldClim 1.4 does allow for climate projections under Representative Concentration Pathways (RCPs) 4.5 and 8.5 and subsequent comparison to other species projections (Cerasoli et al., 2022). In order to construct the hypervolumes of current estimates of species’ climate space breadth with limited occurrence data, these climate variables were reduced using a principal component analysis (PCA). To determine the current climate space breadth of each species, we used a PCA of the WorldClim version 1.4 data cropped to our study extent. The first two axes of this PCA, representing 64.54% and 13.30% of variation, respectively, were selected for further use with hypervolume construction. We present these results as Current Climate Space (CCS), calculated as a percentage of total climate space of the SNSM. For determining climate space in 2050, we considered two RCPs – 4.5 and 8.5 – chosen to represent medium- and high-risk scenarios for the time period considered (Harris et al., 2014). From these RCPs, we selected 12 GCMs, (S3 Table) available for both RCPs; these are described in detail in the Fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change (Pachauri & Meyers, 2014). Considering these 12 GCMs and their respective projections for our climate variables of interest provides a more comprehensive view of the climate uncertainty in this region for this 30-year time period (Beaumont et al., 2008). To evaluate potential climate space breadth for each species in 2050, we bound the values from the WorldClim version 1.4 data and one of the GCMs to use in a PCA, resulting in 24 PCAs (12 GCMs and 2 RCPs). Since we wished to assess the difference between the current and future climate hypervolumes, by calculating the PCA on the current and future climate together, we allow for comparisons to be made among separate hypervolumes summarizing the current climate space, future climate space, and climate space on a species by species basis as they are all created using values from the same PCA (Barros et al. 2016).

We evaluated the climate change impact for each species, through the following process (Figure 1). We used the hypervolume set function to compute the overlap between the species and available climate space in the present (current climate space) defined by the SNSM hypervolume. This represents the current “climate realized niche” of each species, which is unlikely to shift much between the present and 2050 due to the short time span for evolutionary adaptation. For 2050 comparisons, we made 24 hypervolumes of the SNSM using the PCAs of each of the 24 GCM-RCP combinations. Species overlap with climate space in 2050 was quantified as described above, resulting in 24 overlap scores per species for a total of 360 hypervolume comparisons. We calculated the mean and standard deviation of the overlap percentage for each species in 2050. These mean values are expressed at the percent of current climate space under the two RCP scenarios, defined as CS 4.5 (Climate Space for 4.5) and CS 8.5 (Climate Space for 8.5; Table 1, S4 Table).

Figure 1.

Flow chart of the hypervolume process. Hypervolume used for estimating current (CCS) and future climate space (CS 4.5 and CS 8.5) overlap.

Table 1.

Area-based and trait-based variables used in the regional climate change vulnerability assessment (CCVA) of amphibians in the Sierra Nevada de Santa Marta.

SPECIES	AOH (km²)	CCS	CS 4.5	CS 8.5	PA % Coverage	Endemic	Foot Webbing	Dev	Land Cover	Vulnerability Assessment
Atelopus carrikeri **	360.3	1.51	0.36	0.28	97.7	Yes	Very extensive	ND	Ecotone, Paramo	High
Atelopus laetissimus **	24.3	5.33	0.34	0.08	87.07	Yes	Very extensive	ND	Ecotone, Forest, Pasture	High
Atelopus nahumae **	182.3	NA	NA	NA	89.26	Yes	Very extensive	ND	Forest	High
Bolitoglossa savagei	1,705.2	5.46	0.22	0.05	53.03	Yes	Extensive	DD	Ecotone, Forest	Medium-High
Colostethus ruthveni	2,782.4	9.01	0.4	0.17	16.73	Yes	Reduced feet only	ND	Ecotone, Forest, Coffee	Low-Medium
Cryptobatrachus boulengeri *	5,253.7	9.54	0.39	0.19	13.94	Yes	Absent	DD	Ecotone, Forest	Medium
Geobatrachus walker **	467.7	6.45	0.39	0.1	61.9	Yes	Absent	DD	Ecotone, Forest	Medium
Ikakogi tayrona *	3,028.0	30.82	0.66	0.38	26.35	Yes	Absent	ND	Ecotone, Forest	Medium
Leptodactylus savagei	199,864.0	35.57	1.15	1.2	37.73	No	Absent	ND	Coffee	Low
Lithobates vaillanti	379,236.3	60.43	0.89	0.96	37.47	No	Very extensive	ND	Ecotone	Low
Serranobatrachus carmelitae **	8.4	NA	NA	NA	5	Yes	Absent	DD	Forest	High
Serranobatrachus cristinae **	191.4	5.49	0.35	0.09	53.93	Yes	Absent	DD	Forest, Pasture	High
Serranobatrachus delicatus **	10.9	3.37	0.31	0.06	0	Yes	Absent	DD	Ecotone, Forest, Pasture	High
Serranobatrachus insignitus	277.0	2.19	0.34	0.07	64.72	Yes	Absent	DD	Forest	High
Serranobatrachus megalops	1,138.2	7.3	0.37	0.09	37.24	Yes	Absent	DD	Ecotone, Pasture	Medium – High
Serranobatrachus ruthveni **	301.4	4.9	0.34	0.07	61.75	Yes	Absent	DD	Pasture, Paramo	High
Serranobatrachus sanctaemartae	2,762.3	9.4	0.38	0.11	34.91	Yes	Absent	DD	Ecotone, Forest	Medium – High
Tachiramantis tayrona	1,842.1	14.02	0.48	0.15	47.11	Yes	Absent	DD	Pasture	Medium – High

AOH = Area of Habitat (km²); CCS = Current Climate Space, thepercent of current climate space that the species occupies relative to all available climate space in the SNSM; CS 4.5 = projected climate envelope under RCP 4.5 as a percent of Current Climate Space; CS 8.5 = projected climate envelope under RCP 8.5 as a percent of Current Climate Space; PA% = percent protected area coverage in the AOH; Dev = direct (DD) or non-direct development (ND); Land Cover Types indicate the likely degree of habitat specificity; Vulnerability Assessments indicate our quantitative (S4 Table) and qualitative evaluation of the species vulnerability to climate change between now and 2050 based upon the available spatial and trait-based data.

***

Current IUCN Red List Threatened category: =VU, =EN.

Given the lack of data availability above 3,000 m, and the fact that this elevational range falls outside the limits for 14 of our focal species, our modeling approach does not allow us to make predictions above 3,000. The elevational transition from upper montane rain forest to sub-páramo also begins at 3,000 m, representing a major change in vegetation structure (Peyre et al., 2018).

Vulnerability Ranking

We organized the data we generated into a flowchart to illustrate the process of developing our CCVA for amphibians in the SNSM (Figure 2). We compiled information on variables that represented exposure, sensitivity, and adaptive capacity of species to climate change. Exposure variables included current and future climate space and protected area coverage (World Database of Protected Areas: https://www.protectedplanet.net/). Sensitivity variables included land cover use from Roach et al. (2020) and available trait data (Amphibia Web, 2023; Mendoza-Henao et al., 2019; Stuart et al., 2008) which included feet webbing (indicator for flowing water dependency), reproductive development modes (plasticity in habitat use) and endemism (dispersal capability). To assess adaptive capacity (AC) we used species’ land cover usage (Roach et al., 2020) trait data, and information provided by previous studies on abundance, thermal tolerance, and epidemiology (Navas et al., 2013; Roach et al., 2020; Rueda Solano et al., 2016a, 2016b).

Figure 2.

Process for conducting the Climate Change Vulnerability Assessment on the target amphibian species on the Sierra Nevada de Santa Marta.

Rankings of criteria used in the vulnerability assessment from low to high, either qualitatively or ordinal, are recommended in conducting a CCVA for a complex of species because all the variables included vary in data quality and ranks avoid prioritizations made with unrealistic precision (Thurman et al., 2020). To compare the climate space breadth of each species within the SNSM under each climate scenario (current, 2050 RCP 4.5, 2050 RCP 8.5), we used the overlap of the species and SNSM hypervolumes as described above. We categorized future climate niche space from low (occupying below 20% of the current climate space breadth for that species) to high (occupying above 80% of the current climate space breadth). Protected areas were ranked by the percentage of total coverage per species for comparisons among species 1 = 75 – 100%; 2 = 50 – 75; 3 = 25 – 50; 4 = 10 – 25; 5 = < 10.

To rank the AOH of our species, we used the range of the area of distribution sizes (IUCN Red List) for all amphibian species from Colombia with distribution polygons available. We calculated the distribution area for each species that overlapped Colombia (setting the maximum distribution area allowed to the area of Colombia to reduce outliers caused by widespread species). We then determined the quintile cutoff thresholds considering all of these values to rank our species from 5 (small AOH comparable in size to the lowest 20% of Colombian amphibian distributions) to 1 (large AOH comparable in size to the top 20% of Colombian amphibian distributions). Land cover data were ranked from 1 – 3; 1 = agriculture habitat; 2 = mixed habitat use (natural and agricultural), and 3 = habitat specialists that only used natural habitat (forest or páramo – a high elevation natural grassland habitat). We ranked trait data as a 1 – 3 for feet webbing (higher score of 3 for complete dependency on water); 1 or 2 for reproductive development modes (1 = direct developer; 2 = non-direct developer); and 1 (non-endemic) or 2 for endemic species. Trait and spatial data collected relevant to adaptive capacity of species were evaluated amongst co-authors when identifying species of low – high risk. If species were able to use mixed types of land cover (natural and anthropogenic), we believed them to be more adaptable to environmental degradation.

We quantitatively ranked species based on the aforementioned information. We then discussed each species ranking individually amongst co-authors, taking into account expert opinion, adaptive capacity, and anecdotal evidence (e.g. importance of high flow streams for some species that was noted in the field but not specified in the data collection). Each species was given a ranking from low – high vulnerability (Table 1) and a justification for their subsequent ranking (S5 Table).

Results

Area of Habitat and Protected Area Coverage

Filtering range polygons by elevation and habitat characteristics more accurately quantifies areas suitable for species but reduces the Extent of Occurrence (EOO; Figure 3). Reduction in suitable area of AOH (due to filtering by elevation and habitat limits), ranged from a minimum of 41% to a maximum of 97% of the EOO, with an average reduction in area by 71%. Many species had significant decreases in available habitat when AOH was calculated (S2 Figure). Ranges for Atelopus laetissimus, Atelopus nahumae, and Serranobatrachus carmelitae were reduced to less than 10% of their original EOO.

Figure 3.

Maps of EOO and AOH for the Amphibian Species. Maps showing the difference in species richness observed using A) IUCN Red List ranges (EOO) and B) Area of Habitat (AOH) polygons filtered for elevation range and available habitat, while C) an anomaly map shows where the change in species richness occurs. Contour lines delimit elevational ranges every 1,500 m.

The presentation of the spatial data as an AOH rather than EOO also gives a more ecologically realistic representation of current protected area coverage. Coverage values for the three Atelopus species range from the high 80 to high 90 percent of the AOH. This is encouraging, but the AOH values for all three species are quite small. Some of the smallest AOH values and lowest percent protected area coverage are found among the Serranobatrachus species, in particular S. carmelitae and S. delicatus, Colostethus ruthveni also has very low percent protected area coverage but this species tolerates disturbance and agriculture and is quite abundant and wide ranging.

Climate Space Analysis

Sixteen of the amphibian species had at least five records to enable the construction of hypervolumes. These species varied in how much and what parts of climate space they occupied (Table 1). The total amount of current climate space available for species ranged from 1.51% (Atelopus carrikeri) to 60.43% (Lithobates vaillanti) with an average of 13.17% (S4 Table). The largest amount of overlap among the community in climate space occurred at mid-range values of PC1 and mid to high values of PC2 (Figure 4). PC1 is typically negatively associated with temperature and positively associated with precipitation, whereas high positive PC2 scores are associated with higher isothermality and lower precipitation in the driest month and quarter (S2 Table; Figure 4). The cluster of points moving up the curve to the top of the graph (Figure 4) represents the elevational gradient from high on the right to low at the top and the cluster on the far negative side of PC1 represents the lowland habitats. With the exception of the lowland species Leptodactylus savagei and Lithobates vaillanti, the environmental space occupied by most species is relegated to mid-elevation bands between 1,500 m and 3,000 m (Figure 3).

Figure 4.

Results of the Hypervolume Analysis. A) represents current species overlap based on AOH polygons. Below are the differences in B) RCP 4.5 and C) RCP 8.5 climate change scenarios, regarding species overlap and anomaly maps of change in predicted species richness for each RCP scenario (2050 species change). Blue shading in Figures B and C represent the Current Climate Space (CCS) and the orange shading represents the climate space under RCP 4.5 (B) and RCP 8.5 (C). White circles in these panels represent current climate centroids for our amphibian study species. High elevation species are associated with lower values of PC2 and lower elevation species are found closer to the top of the panel. To the far left, are species associated with warmer, drier climates (e.g. Leptodactylus savagei and Lithobates vaillanti). The shifts of PC1 to more negative values under both 4.5 and 8.5 represent a hotter, drier climate.

The two climate scenarios examined (RCPs 4.5 and 8.5) show different results (Figure 4). Both scenarios show a decrease in climate space occupied for most species, however the changes are extremely pronounced in RCP 8.5 (Table 1). This is due to available environmental space decreasing at the extremes, notably in the areas of higher precipitation and cooler temperatures as well as a tendency for higher isothermality found in more negative values of PC2. Overall, the shift in new climate space (orange areas) is left on PC1 relative to the current climate space (blue areas) indicating a trend to a warmer, drier climate (Figure 4). Typically overlaps in climate space for RCP 8.5 are much smaller than the overlaps found from comparisons with an RCP of 4.5. Means and standard deviation of climate space decrease from 4.5 to 8.5 for each species except for Leptodactylus savagei and Lithobates vaillanti, lowland species which gain elevation (Table 1).

Vulnerability Assessment

We ranked species from low to high vulnerability (Table 1). The majority of species have low AC as they are endemic, dispersal limited, and often occur in few locations across one to two land cover types. Additionally, the majority of species have a small AOH and occupy low climate envelopes for both RCP scenarios, and therefore trended toward moderate-high vulnerability. All but two species lose over 60 percent of their climate space in RCP 8.5 and 12 species lose 80 percent. Most high-risk species occur above 1,500 m in elevation. All three Atelopus species were ranked “high”. The Serranobatrachus/Tachiramantis (S/T) species complex is of particular concern. All eight Serranobatrachus/Tachiramantis (S/T) species ranked medium-high to high on the vulnerability assessment. All S/T species are endemic, have small AOHs, have relatively low current climate space availability, and low protected area coverage. Under RCP 4.5, S/T species all maintain a third or more of their current climate space, and potentially tolerate some disturbance. However, under RCP 8.5 this entire clade becomes highly vulnerable to climate change. The only species that ranked low on the CCVA were the two non-endemic species (Lithobates vaillanti, and Leptodactylus savagei). One endemic species ranked low-medium (Colostethus ruthveni) largely based on their capability to persist in disturbed habitats and their relatively high levels of abundance (Roach et al., 2020). Species justifications for vulnerability rankings, including their associated threats, are detailed in (S5 Table).

Our results show a loss of low to mid elevation (0 – 2,500 m) habitat suitability where many species are currently living close to their upper thermal limits. The northwestern section of the SNSM is currently characterized by high precipitation. Both RCP models predict decreased precipitation impacting species in this northwestern elevational gradient representing a significant threat to amphibian habitat. Our models for 2050 show new climate space that does not currently exist in the SNSM for high elevation species like A. carrikeri in regions above 3,000 m.

Discussion

Previous CCVAs have yielded useful results to set spatially-explicit conservation priorities (Böhm et al., 2016; Gardali et al., 2012; von May et al., 2019). Our results demonstrate large decreases in available climatic space for the majority of our study species from RCP 4.5 to 8.5. It will be crucial to keep projected warming scenarios to RCP 4.5 levels in order to manage species vulnerability to climate change; under RCP 8.5 the situation becomes dire for the endemic species. The dire consequences of climate change for all ectotherms has previously been reported (Deutsch et al. 2008). Across Latin America, the impacts of climate change on montane amphibian species paint a glum narrative (Agudelo-Hz et al., 2019; McCain & Colwell, 2011; Menéndez-Guerrero et al., 2019). Eight of our focal species were ranked high and four ranked medium-high on our vulnerability assessment, yet current conservation action in the region is primarily aimed at Atelopus species. Atelopus are the most threatened amphibian genus in the world (Granda-Rodríguez et al., 2020; IUCN, 2023). Unlike Atelopus populations in Central America, Atelopus species in the SNSM have not been heavily affected by Chytridiomycosis (Flechas et al., 2017; Lips et al., 2004; Rueda Solano et al., 2016b; Whitfield et al., 2016). The biggest threats to Atelopus in the SNSM is habitat loss or degradation and climate change. Prior amphibian research in the SNSM has been focused on Atelopus life-history and population dynamics, including thermal ecology and epidemiology (Granda-Rodríguez et al., 2020; Navas et al., 2013; Rueda Solano et al., 2016a, 2016b). Previous literature supports findings that some species, like Atelopus carrikeri, may be resilient to changing temperatures, which would increase their adaptive capacity (Rueda Solano et al., 2016a). Yet, many of our focal species are dispersal limited and they may not be able to disperse to new habitats regardless of climate availability, which ultimately reduces their AC. Further detailed natural history information on Atelopus populations, distributions, and dispersal ability, coupled with more detailed mechanistic analyses on thermal tolerances of species (e.g. Rueda Solano et al., 2016a) will be useful to improve predictions of extinction risk.

We calculated the percent protected area coverage for the current AOH values, which gives some indication of the conservation value of protected areas per species. We did not project AOH into the future, only climate space, and the trend is consistently hotter and dryer. This might force species to disperse to higher elevation to compensate, potentially moving out of protected areas (Hannah, 2008). There is a real need to gather additional species specific thermal and ecophysiological data to model range shifts of the species most indicated as at risk to allow for the design of corridors and expanded protected areas in the SNSM.

A recent study found that climate change sensitivity was highest for amphibians (Etard & Newbold 2023). Other studies have noted that small-bodied direct-developers (such as Serranobatrachus/Tachiramantis species) may potentially be more susceptible to thermal stressors than other species (von May et al., 2019). Studies from other Andean countries have shown a reduction in Pristimantis habitat (a related and ecological similar genus to Serranobatrachus/Tachiramantis) under RCP 4.5 and 8.5 climate scenarios (Cheza et al., 2020), while others have found that direct developers may even be more susceptible to Chytridiomycosis (Mesquita et al., 2017). Some S/T species tolerate disturbance in habitat (Arroyo et al. 2022; S1 Table), moderately impacted under RCP 4.5, therefore it is critical to reduce climate-related threats since this will likely be a main driver for extinction of S/T species in the region. S/T species remain among the most understudied genera in the SNSM and increased monitoring effort of populations is greatly needed.

Serranobatrachus/Tachiramantis species are an important but overlooked priority in the SNSM and it will require data collection on abundance, distribution, taxonomy, and threats to accurately assess the vulnerability of the S/T species complex. There is a lack of published information on their thermal tolerance and dispersal ability and these are urgent data gaps to fill. Currently, amphibian conservation action in the region includes data collection on known Atelopus populations and searches for new populations (Granda-Rodríguez et al., 2020) as well as education and engagement programs with local Indigenous and campesino (rural farming) communities. Future studies on amphibian adaptive capacity will improve the predictions of at risk species (Bever et al., 2016) for the SNSM.

A recent modeling exercise using both paleo-reconstructions and future projections presents evidence that climate impacts on anuran communities primarily act on the extremes of their body size distribution, selectively filtering out both larger and smaller bodied species (Feijó et al., 2023). Smaller bodied species, like Serranobatrachus/Tachiramantis, tend to have smaller clutch sizes and low dispersal ability contributing to the risk under climate change. This study in addition projects that future climate impacts in anurans will be most severe in tropical regions.

In the SNSM, there has been an expansion of high impact land use practices and development that have intensified habitat loss, including agriculture, mining, excessive loss of water quality and flow, and tourism (Duran-Izqueirdo & Olivero-Verbel, 2021). The possibility of local land users growing crops in previously undisturbed forested habitat due to altered temperature and precipitation levels may reduce amphibian habitat and population sizes (Etter et al., 2006; Laurance et al., 2014). Future availability of water and the protection of watersheds as microhabitats is of critical importance to safeguard amphibian habitat (Cortes-Gómez et al., 2013; Earl & Semlitsch, 2015; Nowakowski et al., 2017). Current agricultural practices often dump wastewater directly into streams and microcuenas (small watersheds), potentially increasing contaminant loads that may disrupt amphibian reproduction cycles (Boone et al., 2007). The predicted decrease in precipitation levels from the climate models will likely result in reduced streamflow, exacerbating stream flow deficits and posing additional threats to amphibian reproduction. Water-dependent breeders like Atelopus species are particularly vulnerable to reduction of water quality and volume and losses of breeding sites. Management and manipulation of water is a tool that has been successful in amphibian conservation, especially as drought frequency increases (Mathwin et al., 2020). Water scarcity is a critical consequence of changing climates and addressing freshwater quality and availability has significance for biodiversity and human well-being (Mwenge Kahinda et al., 2019).

Challenges to Data Collection and Analysis

Most global models are on a scale that is too coarse to discern microhabitat features that are important to amphibian distribution and habitat use (Mendenhall et al., 2014). Using a variety of data sources and an assortment of analytical methods allowed us to build a more robust analysis of climate vulnerability in a region where reliable spatial data are scarce. Restricted data availability limits our ability to model species distributions at a fine scale across strong environmental gradients. Methods like hypervolume provide a coarser scale solution in the absence of abundant data. When working with endemic, difficult to find species, opportunistic methods like these can generate a starting point for future research that can collect additional data points at a finer spatial scale. The only local climate data station is on a western-facing slope at 2,500 m, at the San Lorenzo Biological Station. No local climate data stations exist above 2,500 m (on a mountain which reaches 5,775 m asl). Lack of fine-scale climate data from high elevation habitats makes it difficult to build reliable local climate models. Until we are able to reduce uncertainty, associated with lack of data for local climate models, we must continue to rely on global-scale models and data sets like WorldClim.

Our analyses estimate the vulnerability of species in the SNSM to climate-change driven extinction risk, however multiple additional factors will also potentially mitigate or exacerbate this risk. Coffee is the most important agricultural enterprise in the region and both the presence of plantations and the agricultural practices on the plantations increase risk (Roach et al. 2021). This same study highlights the social and economic pressures that coffee agriculturists deal with; these pressures can force both expansion of land under coffee cultivation and the shift to potentially more environmentally impactful practices than shade coffee. There are pine plantations in parts of the SNSM at a site we sampled near San Lorenzo which show reduced richness of soil invertebrates (Camero R. et al., 1999) and appear to be inhospitable to most amphibian species (pers. obs., Rueda-Solano, 2016b) though at present these are restricted in scope. Many small, highly suitable microhabitats persist in the SNSM that are highly favorable for a number of species (e.g. the Quebrada San Lorenzo) and need to be given the highest priority for protection. There could also be other microclimates within the SNSM that would facilitate survival through dispersal and adaptation, and this is where more field data would be indispensable. There has been growing attention provided to Nature-Based Solutions to mitigating the impact of climate change on biodiversity, but we need to avoid solutions that focus on things like carbon capture through afforestation by non-natives which would just compound biodiversity loss (Seddon et al., 2020). A key component of assessment of risk is the use of estimates of adaptive capacity (Thurman et al., 2020) based upon trait categories. Most of these, however, lack field or experimental data, which is why risk is only assigned within broad categories (low, medium, high; Foden et al., 2019). We clearly need much more data on mechanistic models of ecophysiology, osmotic balance, thermal biology, and dispersal ability to accurately assess adaptive capacity, however time and resources to complete these studies across the entire community of amphibians in the SNSM are limited, especially given the potential severity of climate impacts over the next few decades. Nevertheless, assessment of the risk of extinction to amphibian species worldwide will be improved by studies focused on integrative biology and the relative impacts of multiple ecological, social, and economic factors (Leudtke et al., 2023). Our results do highlight those species most vulnerable, and these should be of the highest priority for targeted research. More locally collected, fine resolution field data are needed in the region.

The majority of amphibian occurrence records in the SNSM come from the northwestern portion of the mountain range (near the city of Santa Marta). Other regions of the mountain, especially in the departments of Guajira and Cesar, remain largely understudied. The southern and eastern portion are not well explored and much of the land is Indigenous territory. Researchers are not allowed to enter these regions without proper permits, which can take years to acquire. Difficult road accessibility, increasing conflict over land use, illicit activities, government corruption, and permitting issues remain barriers toward data collection and enforcement of conservation action.

Implications for Conservation

Prior applications of the IUCN Red List to assess extinction risk have not conducted climate change vulnerability assessments. Following the guidelines presented in the literature (Blonder et al., 2014; Brooks et al., 2019; Foden et al., 2013; Thurman et al., 2020) we present a CCVA of the largely endemic and threatened amphibian species of a biogeographically unique region, the SNSM. These results will inform conservation planning and prioritization by providing guidelines for adaptation, protected area management, and the design of future protected landscapes.

Home to 85% of vertebrate species, mountains represent critical biodiverse regions that are susceptible to the compounded threats from land use and climate impacts (Elsen & Tingley, 2015; Newbold et al., 2015; Peters et al., 2019; Rahbek et al., 2019) increasing the threat of species extinction risk (Williams & Newbold, 2019). Slowing the impact of climate change will require collaborative conservation action. We must work across academic institutions, NGO’s, government agencies, and private landowners to share information, data, and resources to improve and reduce model uncertainty (Lacher et al., 2012). This type of collaborative action can improve data sharing, model predictions, and technologies that increase mitigation and improve adaptation schemes.

A recent example of local collaboration that led to a conservation success is the story of the “lost” amphibian species Atelopus arsyecue. After three years of collaboration with the Arhuaco Indigenous Sogrome community, local NGO, Fundación Atelopus, was able to photograph the toad for the first time since the early 1990’s (Mongabay, 2019). This is an example of how local collaboration and expertise combining biological and local ecological knowledge (Petriello & Stronza, 2020; Thorton & Scheer, 2012) and building community trust can lead toward the acquisition of new knowledge of an elusive species. Collaborative conservation initiatives with local schools, campesinos, and Indigenous groups increase equitable conservation solutions. Climate mitigation and adaptation targets must be inclusive and take place through a transparent and holistic understanding of shared conservation goals.

Supplemental Material

Supplemental Material - Assessing the Vulnerability of Endemic Colombian Amphibian Species to Climate Change in an Isolated Montane Ecosystem

Supplemental Material for Assessing the Vulnerability of Endemic Colombian Amphibian Species to Climate Change in an Isolated Montane Ecosystem by Nicolette S. Roach, Adrian A. Castellanos, Thomas E. Lacher in Tropical Conservation Science

Footnotes

Acknowledgements

Thank you to Dr. Kyle Barrett and Dr. Michelle Lawing, and the anonymous reviewers for their helpful commentary to improve this manuscript. We would like to thank research assistants Jeferson Villalba and Jose Pérez González for their time and dedication collecting field data.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Research was made possible by the funding from the Mohamed bin Zayed Species Conservation Fund (162514343; 1804788), Fulbright Colombia, ReWild, Chicago Herpetological Society, and Phoenix Zoo.

ORCID iD

Nicolette S. Roach

Supplemental Material

Supplemental material for this article is available online.

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