The impacts of climate change on the habitat distribution of the vulnerable Patagonian-Fueguian species Ctenomys magellanicus (Rodentia, Ctenomyidae)

Lazo-Cancino, Daniela; Rivera, Reinaldo; Paulsen-Cortez, Katheryne; González-Berríos, Nicolás; Rodríguez-Gutiérrez, Rodrigo; Rodríguez‐Serrano, Enrique

doi:10.1016/j.jaridenv.2019.104016

Cited by 21 publications

(10 citation statements)

References 34 publications

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“…The continued naturalization and spread of IAPs creates a major concern on how climate change will influence the distribution of these species as climate change is anticipated to modify the dynamics and ecological niches of many species both locally and globally (Lazo-Cancino et al 2020). As a result, this can even be more detrimental to the ecosystem's provision of services with the impacts severely affecting both biodiversity and hydrological systems (Otieno, Nahrung, and Steinbauer 2019).…”

Section: Discussionmentioning

confidence: 99%

Modeling the geographic spread and proliferation of invasive alien plants (IAPs) into new ecosystems using multi-source data and multiple predictive models in the Heuningnes catchment, South Africa

Mtengwana

Dube

Mudereri

et al. 2021

GIScience & Remote Sensing

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The geographic spread and proliferation of Invasive Alien Plants (IAPs) into new ecosystems requires accurate, constant, and frequent monitoring particularly under the changing climate to ensure the integrity and resilience of affected as well as vulnerable ecosystems. This study thus aimed to understand the distribution and shifts of IAPs and the factors influencing such distribution at the catchment scale to minimize their risks and impacts through effective management. Three machine learning Species Distribution Modeling (SDM) techniques, namely, Random Forest (RF), Maximum Entropy (MaxEnt), Boosted Regression Trees (BRT) and their respective ensemble model were used to predict the potential distribution of IAPs within the catchment. The current and future bioclimatic variables, environmental and Sentinel-2 Multispectral Instrument satellite data were used to fit the models to predict areas at risk of IAPs invasions in the Heuningnes catchment, South Africa. The present and two future climatic scenarios from the Community Climate System Model (CCSM4) were considered in modeling the potential distribution of these species. The two future scenarios represented the minimum and maximum atmospheric carbon Representative Concentration Pathways (RCP) 2.6 and 8.5 for 2050 (average for 2041-2060). The results show that IAPs are predicted to expand under the influence of climate change in the catchment. Concurrently, riparian zones, bare areas, and the native vegetation which is rich in biodiversity will greatly be affected. The mean diurnal range (Bio2), warmest quarter maximum temperature (Bio5), and the warmest quarter precipitation (Bio18) were the most important bioclimatic variables in modeling the spatial distribution of IAPs in the catchment. Comparatively, all the models were successful in predicting the potential distribution of IAPs for all the scenarios. The BRT, MaxEnt, and RF predicted the spatial distribution of IAPs with an Area Under Curve (AUC) of 0.89, 0.92, and 0.94, respectively. The study highlighted the importance of multi-source data and multiple predictive models in predicting the current and potential future IAP distribution. The results from this study provide baseline information for effective land management, planning, and continuous monitoring of the further spread of IAPs within the Heuningnes catchment.

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Section: Discussionmentioning

confidence: 99%

Modeling the geographic spread and proliferation of invasive alien plants (IAPs) into new ecosystems using multi-source data and multiple predictive models in the Heuningnes catchment, South Africa

Mtengwana

Dube

Mudereri

et al. 2021

GIScience & Remote Sensing

View full text Add to dashboard Cite

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“…Furthermore, our current predicted distribution range visually shows a large extent of overlap with the current predicted range published by Dianat et al [23], who used Maxent and occurrences from GBIF and the published literature to hindcast the distribution range of the Persian jird and assess its evolutionary history. A good approach to obtain a less biased occurrence dataset would have been to obtain occurrences from species surveys in the field, as has for instance been done by Lazo-Cancino et al [66] who assessed the impact of climate change on an endemic rodent in Patagonia. In contrast to our findings that the Persian jird, favoring shrublands, grasslands and rocky areas in semi-arid regions, may benefit from climate change, they found that the Magellanic tuco-tuco (Ctenomys magellanicus), favoring dry grasslands as well, is likely to be negatively affected by climate change.…”

Section: Discussionmentioning

confidence: 99%

Predicted Future Benefits for an Endemic Rodent in the Irano-Turanian Region

Meeussen

Hof

2021

Climate

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Climate change is expected to have an impact on the geographical distribution ranges of species. Endemic species and those with a restricted geographic range may be especially vulnerable. The Persian jird (Meriones persicus) is an endemic rodent inhabiting the mountainous areas of the Irano-Turanian region, where future desertification may form a threat to the species. In this study, the species distribution modelling algorithm MaxEnt was used to assess the impact of future climate change on the geographic distribution range of the Persian jird. Predictions were made under two Representative Concentration Pathways and five different climate models for the years 2050 and 2070. It was found that both bioclimatic variables and land use variables were important in determining potential suitability of the region for the species to occur. In most cases, the future predictions showed an expansion of the geographic range of the Persian jird which indicates that the species is not under immediate threat. There are however uncertainties with regards to its current range. Predictions may therefore be an over or underestimation of the total suitable area. Further research is thus needed to confirm the current geographic range of the Persian jird to be able to improve assessments of the impact of future climate change.

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“…Throughout the last century, and especially over the last few decades, there have been global alterations leading to a warmer climate 7 with widespread effects on biological systems [8][9][10] . This recent climate change has already caused expansions, reductions, or shifts in the distribution of many species [11][12][13][14] . In particular, climate shifts are modifying the margins of species distributions over short periods of time, a process that is more marked in vagile species such as birds 15,16 .…”

Section: Darío Chamorro * Raimundo Real and Antonio-román Muñozmentioning

confidence: 99%

Fuzzy sets allow gaging the extent and rate of species range shift due to climate change

Chamorro

Real

Muñoz

2020

Sci Rep

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The recent modification of species distribution ranges in response to a warmer climate has constituted a major and generalized biogeographic change. The main driver of the shift in distribution is the disequilibrium of the species ranges with their climatic favourability. Most species distribution modelling approaches assume equilibrium of the distribution with the environment, which hinders their applicability to the analysis of this change. Using fuzzy set theory we assessed the response to climate change of a historically African species, the Atlas Long-legged Buzzard. With this approach we were able to quantify that the Buzzard’s distribution is in a latitudinal disequilibrium of the species distribution with the current climate of 4 km, which is driving the species range northwards at a speed of around 1.3 km/year, i.e., it takes 3 years for the species to occupy new climatically favourable areas. This speed is expected to decelerate to 0.5 km/year in 2060–2080.

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The impacts of climate change on the habitat distribution of the vulnerable Patagonian-Fueguian species Ctenomys magellanicus (Rodentia, Ctenomyidae)

Cited by 21 publications

References 34 publications

Modeling the geographic spread and proliferation of invasive alien plants (IAPs) into new ecosystems using multi-source data and multiple predictive models in the Heuningnes catchment, South Africa

Modeling the geographic spread and proliferation of invasive alien plants (IAPs) into new ecosystems using multi-source data and multiple predictive models in the Heuningnes catchment, South Africa

Predicted Future Benefits for an Endemic Rodent in the Irano-Turanian Region

Fuzzy sets allow gaging the extent and rate of species range shift due to climate change

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