Implications of climate change for the distribution of the water opossum (Chironectes minimus): habitat loss and conservation opportunities

Abstract

Climate change is expected to impact the geographic distribution of marsupial species in the near future and this impact is likely to be accentuated for the more specialist species. The water opossum (Chironectes minimus) is the only semiaquatic marsupial in the world and is considered naturally rare throughout its geographical range. In the present study, we use ecological niche modeling (ENM) to predict the potential impacts of climate change on the geographic distribution of water opossum throughout Neotropical Region at the end of twenty-first century. We assess the vulnerability of this species by calculating its biotic velocity and identifying potential areas for the conservation of the water opossum based on the changes in climatically stable areas over time. These areas were also compared with the availability of remnant forest in the future. The area of potential distribution of the water opossum is projected to decrease 22% in the future. Water opossum populations will be more vulnerable to climate change in central Brazil, toward the southern extreme, and in some regions of the Amazon biome. In the future, C. minimus may be unable to colonize some areas in southern South America and in Mexico. Climatically stable areas are found in Central America, northwestern and coastal areas in northern South America, and southeastern Brazil, however, most of these areas will not have remnant forest in the future. Climatically stable areas with remnant forest areas are an opportunity for the development of effective long-term conservation measures for C. minimus.

Introduction

Climate change is currently one of the main threats to biodiversity (Araújo and Rahbek 2006). In the case of Brazilian marsupials, the potential effects of climate change will likely include extensive loss of suitable climatic conditions by 2050 (Loyola et al. 2012). The impacts of the loss of suitable climatic conditions may range from shifts in the species distribution to increase in extinction risk due to limitation in dispersion abilities (Parmesan 2006). It is important to note, however, that different species tend to respond idiosyncratically to climate change (Parmesan 2006; Moritz et al. 2008), with specialist species typically having a reduced ability to track changes in their habitat, being therefore more prone to extinction in comparison with more generalist species (Warren et al. 2001; Clavel et al. 2011). Given this, empirical estimates of the potential impacts of climate change on environmentally restricted species will be imperative for the development of effective conservation strategies in the context of both ongoing and expected environmental changes.

The water opossum, Chironectes minimus (Zimmermann 1780), is a habitat specialist and the only semiaquatic marsupial species in the world. This species is widely distributed in the Neotropical region, occurring from southern Mexico to northern Argentina. At a local scale, the water opossum selects broad stretches of rivers with clear and fast-running waters, and with a high density of trees, which indicates that the abundance of this species is related to specific habitat variables linked to well-conserved landscapes (Fernandez et al. 2015; Prietto-Torres and Penilla-Buitrago 2017). Additionally, this species is seldom captured using traditional trapping procedures and is considered naturally rare throughout its geographic distribution (Bressiani and Graipel 2008; Fernandez et al. 2015), thus making it difficult to be studied. Prieto-Torres and Pinilla-Buitrago (2017) concluded that the areas suitable for C. minimus have been reduced drastically in recent years, driven primarily by habitat loss, whose negative impacts will likely be exacerbated by the ongoing climate change. Thus, it could be expected that climate change will cause shifts and loss of geographical range for this species in the future.

In the context of rapid environmental change, the identification and protection of potential refugia are fundamental for long-term conservation planning (Groves et al. 2012; Keppel and Wardell-Johnson 2012). Refugia can be defined as environmentally suitable areas for species persistence through time resulting from relative climate stability of such areas in spite of climate change (Ashcroft et al. 2010; McDonald-Spicer et al. 2019). The approach of identifying refugia has been adopted in several studies of spatial prioritization seeking to protect species from climate change (e.g., Jones et al. 2016). These climatically stable areas could be useful for complementing or expanding existing protected areas that are predicted to become less effective for species conservation in the future (Graham et al. 2019). In particular, the identification of appropriate refugia within the current geographic distribution of the species is suitable as it would minimize the need for species to overcome potential barriers to dispersal, especially where natural landscapes have been fragmented extensively (Ashcroft 2010; Terribile et al. 2012; Keppel et al. 2015).

In the present study, we use ecological niche modeling (ENM) to predict the potential geographical distribution of C. minimus in the Neotropical region and evaluate the long-term effects of climate change on this distribution. Based on the specific climatic and environmental requirements of this species (Prieto-Torres and Pinilla-Buitrago 2017, see also Loyola et al. 2012 and Ribeiro et al. 2016), we expected that the water opossum will lose areas of climatic suitability on the future. We assess the vulnerability of the species by calculating the biotic velocity, which is a measure of the velocity at which a species must migrate to keep pace with habitat displacement (Ordonez and Williams 2013; Carroll et al. 2015; Hamann et al. 2015). We also identify potential areas for C. minimus conservation based on the distribution of climatically suitable areas over time (Terribile et al. 2012), taking also into account the availability of native forest vegetation in the future.

Materials and methods

Species distribution data and ecological Niche Models (ENMs)

We searched for geographical records of C. minimus in the SISBIO database (ICMBIO 2016), GBIF database (GBIF 2017) and in the scientific literature (Ardente et al. 2013; Brandão et al. 2014; Gonçalves et al. 2018). A total of 255 occurrences were compiled, recorded between 1912 and 2014. We built Ecological Niche Models (ENMs) using six methods in R software (v. 3.4.3, R Core Team 2017) (Franklin 2010): BIOCLIM using “bioclim” function, Gower Distance (GD) using “domain” function, Mahalanobis Distance (MD) using “mahal” function, Maximum Entropy (MaxEnt) using “maxent” function, these of “dismo” package (Hijmans et al. 2017), Support Vector Machine (SVM) using “ksvm” function of “kernlab” package (Karatzoglou et al. 2004), and Generalized Linear Modelling (GLM) using “glm” function.

The ENMs were calibrated using the preindustrial climate scenario and projected to the future scenario represented by mean conditions between 2080 and 100 for the Representative Concentration Pathway 8.5 (RCP8.5). This scenario is characterized by very high anthropogenic greenhouse gas emissions at the end of the century in the absence of actions to mitigate climate change and reduce or stabilize greenhouse gases emissions (Moss et al. 2010). We chose this scenario to evaluate the opportunities for long term persistence of the species in face of the worst climatic conditions. We obtained climate data from three Atmosphere–Ocean General Circulation Models, or AOGCMs (CCSM, GISS and MIROC), available in the ecoClimate database (www.ecoclimate.org; Lima-Ribeiro et al. 2015), for a grid of cells of the whole Neotropical region with a resolution of 0.5° (~ 55 × 55 km). The protocol for statistical downscaling of climate data in the ecoClimate database uses corresponding baseline climate from each AOGCM to reconstitute climatic values and obtain downscaled layers for past and future climates of each AOGCM (Lima-Ribeiro et al. 2015). Consequently, the original differences in AOGCM are maintained through ENM predictions, thus allowing analyzing uncertainties in ENM future predictions (see below). We opt to use preindustrial data to represent current climatic conditions to calibrate ENM because the RCP scenarios (in our case, the RCP8.5) provide estimates of radiative forcing for future relative to preindustrial conditions (Taylor et al. 2012). Also, all AOGCMs available in ecoClimate has its respective preindustrial baseline (Lima-Ribeiro et al. 2015). Thus, we considered it more appropriate to use preindustrial data to evaluate long-term variation in climate.

For niche modeling, we selected five bioclimatic variables known to influence the occurrence of didelphid marsupial species (Loyola et al. 2012; Ribeiro et al. 2016; Prietto-Torres and Pinilla-Buitrago 2017), and specifically being of ecological importance to the water opossum: annual mean temperature, temperature seasonality, temperature annual range, annual precipitation, precipitation seasonality. We check for collinearity among bioclimatic variables through a variance inflation factor analysis (VIF) and a correlation analysis, using “cor” function of “stats” package and “vif” function of “car” package (Fox and Weisberg 2019), respectively. We found that temperature seasonality and temperature annual range have high correlation (Supplementary Material, Table S1), and VIF values of 11.1 and 9.5, respectively. VIF values higher than 10 indicates collinearity (Dormann et al. 2012), and although temperature seasonality had a VIF higher than this, we opt to maintain both variables in the models because they represent temperature variation of watercourses throughout the year, which is very important for the ecology of semi-aquatic species (see Prieto-Torres and Pinilla-Buitrago 2017). Also, temperature annual range can determine the maximum temperature this species can support, also directly influencing the watercourses’ temperature and the water level.

As no absence data are available for C. minimus, we selected pseudo-absences randomly across the whole Neotropical region. The database of occurrence and pseudo-absence records was divided randomly into a sample for training (75% of the data) and a sample for the testing of the ENMs (25% of the data), with this procedure being repeated 20 times. The model predictions were evaluated according to the area under the curve (AUC). The initial models (6 methods × 3 GCMs × 20 repetitions) with AUC values of over 0.7 (66 models with AUC values > = 0.7) (see Manel et al. 2001; Regos et al. 2019) were combined in an ensemble approach to generate climatic suitability and potential distribution maps for current and future scenarios. The models we standardized using “decostand” function of “vegan” package (Oksanen et al. 2017).

We used a hierarchical Analysis of Variance (hierarchical ANOVA) to quantify and map the modeling uncertainties using climatic suitability as the response variable, and the time scale (current or future), the methods (BIOCLIM, DF, DM, Maxent, SVM e GLM), and the AOGCM (CCSM, GISS and MIROC) as predictor variables. The variance in the predictions among the methods were computed within each AOGCM, which were designed hierarchically within each time setting (current and future). The mean squares of the methods and the AOGCMs express the methodological uncertainties, whereas the variance among the predictions over time indicates the climatic effect on the species distribution, which are a proxy for the effects of climate change (Terribile et al. 2012). These analyses were done using the “summary.aov” function from “stats” package of R software (v. 3.4.3, R Core Team 2017).

Biotic velocity

We used biotic velocity metrics to assess the vulnerability of C. minimus to climate change. Biotic velocity is a distance-based parameter that can be estimated from the ENM predictions by dividing the distance of migration (from one spatial unit to another) by time, e.g., from the present to the end of the 21st Century (Carroll et al. 2015; Hamann et al. 2015). Biotic velocity can be implemented and interpreted in either direction, that is, as either a forward or a backward velocity, by considering the suitability of the cells in the present and in the future. Thus, forward velocity is the distance between a cell that is currently suitable but unsuitable in the future to the nearest cell that will be suitable in 2080–2100. A given cell that is suitable in the present and future has distance equal to zero. In ecological terms, the forward velocity is the minimum distance that an individual must migrate to maintain suitable climatic conditions. This parameter thus reflects the risk of local extinctions or the relative difficulty that a current population will face from the deterioration of its present habitat over time and is used to evaluate the conservation status of the species (Carroll et al. 2015). By contrast, the backward velocity is the distance of future climate cells projected back to analogous current climate cells, indicating the minimum distance of predicted future conditions that a species would have to migrate to colonize the climatically suitable areas (Carroll et al. 2015; Hamann et al. 2015).

Based on climatic suitability obtained from ENMs, we calculated the forward velocity as the distance between each climatically suitable cell in the present that would become unsuitable in the future. For the backward velocity, we calculated the minimum distance between every area added, that is, each cell that is unsuitable at the present time, but will become suitable in the future. Finally, we calculated the median distance for all cells that were lost and added, to obtain the forward and backward velocities. These analyses were done using R software (v. 3.4.3, R Core Team 2017).

Refugia

To define the areas that will be climatically stable through the time, we converted the ensemble maps of present and future into binary distribution maps using the fifth percentile of the Lowest Presence Threshold (LPT, Pearson et al. 2007) using “quantile” function from “raster” package (Hijmans 2017) of R software (v. 3.4.3, R Core Team 2017). A given cell was thus considered to be climatically stable only if the species was predicted to occur in there during both periods analyzed, that is, in the present and in the future. We used the binary maps to quantify the magnitude of the range dynamic (retraction or expansion) that the species would experience between the current and future scenarios. Finally, we use a native forest vegetation model (primary and secondary forest) for the year of 2080 for the pessimistic scenario RCP8.5 (Hurtt et al. 2020) to check whether there will be forest habitat for water opossum in the future scenario within the region of climatically stable areas. For this, we upscaled the vegetation data from 0.25° of resolution to 0.5 × 0.5°, compatible with climatic data, and generated a binary raster of vegetation using a threshold of 0.3, (i.e., a cell was considered suitable if there will be at least 30% of vegetation in 2080). We choose this threshold value based on Estavillo et al. (2013), which suggested this amount of vegetation as the minimum necessary to promote increase in the abundance of forest specialist small mammals. Thus, we overlapped both binary raster (climatically stable areas and vegetation) to identify suitable areas for the species in the future. Upscale of vegetation data was done using “aggregation” function from “raster” package, (Hijmans 2017) of R software (v. 3.4.3, R Core Team 2017).

Results

Climatic change and range shifts

When combined, the ENMs predicted a potentially ample distribution for C. minimus in the present (Fig. 1a), with a total range of ≈ 11,991,100 km2 (3964 cells, Supplementary Material Fig. S1a; Fig. 2a) and high suitability values throughout much of the Neotropical region (Fig. 1a and 2b). However, substantial changes in this pattern were observed in the future scenario (2080–2100), with the potential distribution of the water opossum being predicted to contract primarily in marginal areas, leaving a potential distribution gap between the central Amazon and more arid areas, such as the Cerrado biome (Fig. 1b). The ENM prediction suggests a reduction of 22% in the range size in the future in relation to the present, being ≈ 9,395,650 km2 (3106 cells, Supplementary Material Fig S1b; Fig. 2a), with a decrease in the suitability values for these areas (Fig. 1b and 2b).

Fig. 1
figure1

Present (a) and future—2020–2100 (b) climatic suitability for Chironectes minimus derived from the ensemble of ecological niche models

Fig. 2
figure2

Magnitude of the range shift (a) and suitability values (b) predicted by the ENMs for Chironectes minimus for the current and future

The hierarchical ANOVA (Table 1) indicated a considerable degree of methodological uncertainty (AOGCM and methods, Supplementary Material Fig. S2), but with low uncertainty in the predictions over time. The spatial distribution of the uncertainties also varied among the different modeling components (Supplementary Material Fig S2a and b).

Table 1 Hierarchical ANOVA for the effects of niche modeling methods (Bioclim, Gower distance, Mahalanobis distance, MaxEnt, SVM, and GLM) nested within each climatic model—AOGCM (CCSM, GISS, MIROC), and these nested within time (present and future), in the suitability variation

Biotic velocity

The analyses indicated that water opossum populations will be exposed most to unsuitable climate change (high forward velocity values) in central Brazil (Fig. 3a), in the southern extreme of its distribution, and also in some parts of the Amazon biome. According to backward velocity, some areas in southern South America (northern Argentina and southern Brazil) and Mexico (Yucatan Peninsula) are predicted to be suitable areas that will be difficult for the species to colonize in the future (Fig. 3b).

Fig. 3
figure3

Forward (a) and backward (b) biotic velocity for Chironectes minimus represented by the distance (in km) between suitable cells in the present and future

Refugia areas

The map of climatic stability revealed areas that are expected to remain suitable for C. minimus in the future, in particular in Central America, northwestern South America, and coastal areas of northern and southeastern Brazil, with total range of ≈ 8,391,350 km2 (2774 cells, Fig. 4a). The distribution of these climatically stable areas does not coincide with the methodological uncertainties of the predictions of the ENMs, which reinforces the importance of these areas for long-term conservation planning. However, after overlapping the map of stable areas with the raster of native forest remnants, a loss of 48.3% of climatically stable areas was observed (i.e., stable areas without native vegetation expected for 2080). Most of this lost will occur in northern and southern of Brazil and southwest of South America. Climatically stable areas with native vegetation in the future will be located in south of Mexico, portions along Central America and northwestern South America (Fig. 4b).

Fig. 4
figure4

Refugia areas based on climatically stable areas (a) and after excluding areas without native forest vegetation in the future (b)

Discussion

Effects of climatic change and biotic velocity

Our study indicates a loss of 22% in the suitable area for C. minimus distribution in the future due to climate change. This reduction is similar to the pattern found in previous studies for all Brazilian marsupials (Loyola et al. 2012; Ribeiro et al. 2016), which predicted a considerable reduction in the distribution of the species by 2050, with a further decline by 2080. In addition, we found that the Cerrado biome of central Brazil seems to represent the principal climatic corridor for the dispersal of C. minimus between the southern portion of its current distribution and the Amazon biome (see Fig. S1a in the Supplementary Material). The loss of suitable areas in the central Brazil is thus especially worrying, given that it may result in loss of contact between southeastern (Atlantic Forest) and northwestern (Amazonian) populations.

Given the uncertainties in the predictions, the variance among the AOGCMs and the methods indicated that our modeling approach recovered the climatic dynamics of the species distribution over time (Terribile et al. 2012). As most of the uncertainty is outside the potential distribution of the species, the predicted distribution can be considered reliable for the purposes of long-term conservation planning. This evidence indicates that the effects of climate change on the distribution of the species was well depictured by the ENMs, irrespective of the contrasting predictions derived from the different methods and AOGCMs.

To track suitable areas within the landscape, species need to overcome certain barriers, even in the case of a species with a broad geographic range as C. minimus. The forward biotic velocity represents the level of vulnerability of the species due to climate change (Carroll et al. 2015), and the results of our analysis indicate that the water opossum is threatened in some areas due to the large distances it will need to migrate to reach areas with suitable climatic conditions. Also, the backward distance indicated that some areas (e.g., southern South America) would limit potential dispersal. As the home range of C. minimus has been recorded at between 870 m and 5860 m (Fernandez et al. 2015), their populations may have limited potential for dispersal over large distances, reflecting additional potential threats to its long-term conservation.

Potential conservation areas

In the present study, we applied an ecological modeling approach to predict the long-term effects of climate change on the geographic distribution of the water opossum and addressed possibilities for conservation, following a “forward looking” approach (Hannah et al. 2007). In particular, we found that climate change will divide the climatically stable areas of its distribution into two wide regions, one from Mexico, central America and neighboring areas of northwestern South America, and the other in the eastern and southern coast of Brazil (Supplementary Material Fig S1b). This division can be harmful for water opossum because reduced the possibilities of contact between the populations in these two regions, which can lead to a decrease in populations genetic diversity and increasing the risk of local extinctions (Brito 2009). Also, it is noteworthy that the contraction of the predicted distribution towards southeastern will restrict the species to the Atlantic Forest biome, which is extremely fragmented and poorly protected (Ribeiro et al. 2009).

Overall, our analyses provide a pessimistic prediction for the future of C. minimus, which was expected because we are using a pessimistic scenario (RCP8.5). Even so, from a proactive perspective (Brooks et al. 2006) we are not without opportunities. Further research is recommended, in particular, within the predicted refugia that still have relatively well-preserved native vegetation (e.g., the west and east Amazon basin) and that can guide the development of conservation initiatives for this species, in particular, through the creation of conservation units. Refugia area is also indicated to new studies to reduce knowledge gaps related to the population viability, species’ ecology, potential threats, and colonization capabilities.

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Acknowledgements

This study was developed within the scope of the National Institutes for Sciences and Technology (INCT) Program in Ecology, Evolution and Biodiversity Conservation, supported by MCTIC/CNPq (proc. 465610/2014-5) and FAPEG (proc. 201810267000023). The research of LCT and MSLM is supported by CNPq productivity grants. We thank two anonymous reviewers for their constructive comments.

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Correspondence to Roniel Freitas-Oliveira.

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Freitas-Oliveira, R., Hannibal, W., Lima-Ribeiro, M.S. et al. Implications of climate change for the distribution of the water opossum (Chironectes minimus): habitat loss and conservation opportunities. Mamm Biol (2021). https://doi.org/10.1007/s42991-021-00105-6

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Keywords

  • Climate velocity
  • Ecological niche model
  • Marsupials
  • Neotropical region
  • Specialist species
  • Stable areas