Abstract
Our main objectives were to verify the effect of climate change on distribution of frogs of the family Ceratophryidae and if the legal protection areas in South America will be effective or ineffective in ensuring the preservation of the toads this family in coming decades. The results showed that in the last 140,000 years, species of the family Ceratophryidae expanded and contracted their distribution areas, which naturally reflected the climate and vegetation changes in the Quaternary of South America. The maps of projections showed that changes in temperature determined the area of habitat suitability of 63.7% of the species of ceratophrids both during the last interglacial period and nowadays, and it seems that this will also be the case for the next 62 years. Given the current concerns about future extinctions in the tropics, it is prudent to examine, with special attention, the effects of climate fluctuations on the diversity and distribution of species, because the current estimates of reduction in biodiversity caused by habitat destruction and emission of greenhouse gases are comparable to estimated reductions during glacial intervals.
Introduction
The distribution of a species is, virtually, the geographical area where it is found, or where there is some probability of it being found [1, 2]. A comprehensive definition suggests the distribution of a species as maying be its habitat. This concept is often loosely applied or even confused with the one defining ecological niche because of the close relationship between niche and habitat [3]. The word niche does not suggest a place, but an idea. Niche is regards the limits placed on organisms by environmental conditions. Thus, didactically speaking, a habitat can provide many different niches, where different organisms live, while a niche refers to manner how they live in areas they inhabit [4–6].
Having knowledge of the distribution and the niche of a species is important because such information is critical in ecological research and, without a doubt, for effective methods for biological conservation. Ignorance of the distribution of a species prevents us from knowing their history or what resources it uses, or how variations in birth rate, mortality and migration affect certain populations. It also prevents us from knowing the action and the effect of intra- and interspecific interactions on it, and of the environment as well.
Although known for nearly three hundred years, our knowledge and comprehension about the geographical distribution of species of the family Ceratophryidae leaves much to be desired [7, 8]. What we know about them is restricted to sparse information on their feeding habits, reproduction and development of a few species [9–14]. Such lack of knowledge is directly due in part to their cryptic fossorial habits [8, 15, 16], making it difficult to study adequately the ecological role they play.
For decades the biome was indicated as the determinant in the distribution of some species of ceratophrids [8], suggesting a historical dependence and co-evolutionary with the environments in which they are found, making its geographical distribution restricted to certain areas. If this is true, urgent preservation measures need to be taken by creating more parks and reserves. Such measures are appropriate because according to the IUCN data, destruction of habitat by agriculture, livestock, pollution, deforestation, international animal trafficking and human occupation are important factors in the decline of the Ceratophryidae throughout South America [17].
Although desirable, knowing the exact distribution of a species is impractical and unrealistic. Timed collections, while effective, are lengthy and burdensome, especially in times of ecological crisis where environmental habitats are at serious risk of disappearing in relatively short time. Therefore, the use and application of ecological niche modeling (ENMs) are justifiable, especially because of their ability to generate habitat suitability areas hypotheses based on the probable relationship between certain environmental variables and the occurrence sites of species studied [18] in a short time compared to conducting timed collections.
Despite the data accumulated over years, the distribution of species of the Ceratophryidae is still debatable. Available distribution information is almost always scarce and with gaps for some species [19, 20], indicating that more collection effort would be needed to fill the gaps and thus make it possible to generate better data in modeling studies.
Based on the geographical distribution of ceratophrids currently available, we verified if the protected areas in South America were effective at holding the distribution of the territory of this amphibian species, especially because the anthropic impact in its environmental. Furthermore, we sought to know the habitat suitability area of family representatives and how and why this area changed across the time. We also seek evidences about the effect of global warming on species distribution in the coming decades and what can be done to mitigate or perhaps avoid any possible reduction in the area of distribution of these animals in the near future.
Materials and methods
All information on the distribution of the species studied was obtained from specimens preserved in scientific collections (presence data). The data came from, in this case, the following sources: information of specimens examined contained on labels and/or records of museum collections, as well as scientific articles (S1 and S2 Tables). For specimens that did not have precise site or geographic coordinates in their records, that information was obtained from the city and/or district near the collection site, up to 10 km. This was make to accommodate spatial inaccuracies in the species occurrences, without causing profound distortions on the data of geographic distribution, since the species studied here are of restricted vagility. Such information was found through the GEOlocate web application [21].
The maps of potential distribution of past, present and future of species of the family Ceratophryidae (S1–S11 Figs) were generated through the DIVA-GIS software—Bioclim [22] and MaxEnt [23], performing it run for each species separately. The MaxEnt use both pseudo absence and presence data randomly sampled from the calibration area and the Bioclim is an envelope-mode method that depict sites that are located within the geographical space potentially occupied by a species [24, 25].
We chose to use the DIVA-GIS and MaxEnt software because they are at the same time simpler and precise for the particularities the species studied here (restricted dispersal properties and niche known, although limited available data), without sacrificing your graphical output nor consistence of the predictions, especially MaxEnt [24, 26], compared to other available software when in specific circumstances [27], principally for species with low vagility and dispersion capacity restricted, as amphibians are when compared to others vertebrates species such several types birds and mammals.
In our study the climatic data of the past, present and future are continuous variables that are part of GIS layers obtained from the WorldClim portal [28]. They were derived from the monthly temperature and rainfall values in order to generate more biologically meaningful variables. In our study, the bioclimatic variables represent annual trends (e.g., mean annual temperature, annual precipitation) seasonality (e.g., annual range in temperature and precipitation) and extreme or limiting environmental factors (e.g., temperature of the coldest and warmest month, and precipitation of the wet and dry quarters).
The layers representing current climates are in a resolution of 2.5 arc-minutes (~4.5 km2 at the equator), which contained bioclimatic data from the 1950s to the present. To predict the distribution of species of Ceratophryidae in future climates, we used climate models with a resolution of 30 arc-seconds (0.93 x 0.93 = 0.86 km2 at the equator) of the Canadian Centre for Climate Modelling and Analysis–CCCMA (CGCM4/CMIP5). Emission scenarios used were A2 and B2 [29, 30]. This was done to predict the distributions in reasonably optimistic (B2) and/or pessimistic (A2) scenarios of global climate change according to the Intergovernmental Panel on Climate Change—IPCC [31, 32].
The distribution study of the species of Ceratophryidae in paleoclimatic conditions was conducted in the GIS layers of the Last interglacial (~ 120 000–140 000 BP) and the Last glacial maximum (~ 21 000 years BP). The first layer is in a resolution of 30 arc-seconds [33], the other at 2.5 arc-minutes. The latter was generated by the Paleoclimate Modelling Intercomparison Project Phase II (PMIP2). The original data was made available by CMIP5, being downscaled and calibrated (bias corrected) using WorldClim 1.4 as baseline 'current' climate. We performed this analysis in attempt to verify how the area of habitat suitability of ceratophrids probably changed (shifted, widened or decreased) over time. This information is of great importance for large-scale conservation plans, since it is predictive of key regions where species are likely to suffer the effects of habitat destruction [34]. See supporting information to more details (S1 File).
To discriminate the individual percentage contribution of the model (regularized training gain), we applied the Jackknife test to the model in all environmental layers and also generated predictive contribution tables for the variables (S12–S22 Figs). These tables were constructed because the particular predictive power was easily checked for each distribution variable of the species studied [35].
The performance of each estimated model was generated by the "area under curve" (AUC). In this case, AUC values equal or close to 1 indicate excellent accuracy. Values equal to or less than 0.5 are predictive results that are not as good as those obtained randomly [36]. Some studies suggest that the application of ROC AUC is essentially a very reliable measure of accuracy when compared to other estimators [37, 38].
To avoid ambiguity and a wide range of settings [1], we decided to apply the term areapause to spatial limits (outlines) of the suitable area of the species. The proposal of this new term, inspired in the astronomical term heliopause, suggests that the distribution is stopped because of some ecological pressure and because the species is no longer able to adjust to certain areas of the geographical space. Areapause is a virtual term to the most outer border of the distribution (varying according of method and descriptors). Different factors can determine the spatial limit of the distribution of a species. In our study, it was shown by potential distribution, indicted by abiotic factors, here designed through of climatic variables—Grinnellian niche [39, 40].
The rasters containing the models of the potential distribution areas of ceratophrids have also been overlapping to polygons of geographical areas which delimited environmental preservation/conservation areas in South America [41]. This was done to determine how the effective distribution of these frogs was or wasn’t inside in areas protected by law, facilitating in this way, future categorization of the conservation status [42].
Results
The niche ecological models produced for eleven species of ceratophrids—across subsets of environmental variables of the past, present and future—resulted in a total of 55 predictions (more 33 maps of ecological reserves, whose areas were geometrically extracted of the input features). In the ‘distributions’ generated, the area potentially occupied by species (during some moments in history) showed some interesting variations throughout in time and of the geographical space.
Our models demonstrated that the horned frogs C. joazeirensis; C. ornata and C. stolzmanni had their smallest recorded areas of habitat suitability during the last inter-glacial, and that their areas varied very little during the climate changes that occurred during that period as compared to the other species of the Ceratophyidae, which demonstrated accentuated contractions or expansions of their areas of habitat suitability projected (Fig 1).
Fig 1. The dynamics of the retraction and expansion of the areas of habitat suitability (km2) of Ceratophryidae species during the last 140,000 years.
Our results also demonstrated that during the last glacial maximum there was a significant increase in the areas of habitat suitability of almost all of the species we studied, except for C. stolzmanni, Chacophrys pierotti, L. laevis, and L. llanensis (whose probability of presence seems larger under more warmer climate), which, despite the low sampling, can be associated for variations in temperature and regime of rains, modulate by South America Monsoon System during this period, which changed the structuration of biomes, mainly in central region of South America, in approximately 18,000 years ago, especially in the Chaco, which coincided with the greatest extensions of the polar ice caps [43].
Curiously, all of the models predicted expansions of the areas occupied by those horned frog species (with the exception of C. stolzmanni) within ecological reserve areas in approaching decades (Fig 2). Those models likewise suggest that the expansions of those species will occur in response to the gradual intensification and expansion of semi-arid environments (and alteration in regime of rains) in South America until 2080 (Fig 3).
Fig 2. Probable retraction and expansion dynamics of the areas of habitat suitability (km2) of Ceratophryidae species within existing legally protected areas until the year 2080, as compared to their current distributions (total and inside protected areas).
Data obtained from two projections of CO2 emissions (A2a and B2a).
Fig 3. Projected vegetation map of South America in 2080 elaborated through the sum of polygons of the areas of habitat suitability.
Data obtained from models generated for Ceratophryidae species based on two projections of CO2 emissions (A2a and B2a).
Different from the other Ceratophryidae species, C. crawelli and C. calcarata are expected to demonstrate hyper-expansions of their areas of habitat suitability in the next 62 years that will greatly exceed their present distributions–extending even further than they did during the last glacial maximum. That predicted hyper-expansion is explained in our model by variations in minimum temperatures during the coldest and driest months.
Discussion
First, we must point out something important about our results. The data are treated here in a superficial time plan, that is, in a relatively short period of time. This means that comparisons between the effects of climate change in South America since the Last interglacial and up to the year 2080 are not as absurd or disparate as they may seem, because the species treated here are the link between these two historical moments and can be easily inserted into the current diversity and biogeography as in the Quaternary without major problems [44, 45]. Thus, we can say that the ceratophrids first expanding and then contracting their distribution area in the last 140 000 years, which will naturally occur in the coming decades according to predictions of our models.
The Earth's climate, consequently its biosphere, has undergone profound changes due to the Pleistocene glaciations that occurred over the last few thousand years. Given the current concerns about future extinctions in the tropics, it is prudent to examine with special attention the effects of climate fluctuations on the diversity and distribution of species, both in the past and especially in the future, because the decrease in current estimates of biodiversity, caused by habitat destruction and emission of greenhouse gases, are comparable to estimated reductions during glacial intervals [45]. Therefore, this would justify making a parallel between the likely effects of current climate change on biodiversity with those that occurred during the Quaternary without running the risk of making erroneous observations and arriving at false conclusions.
The distribution of organisms is a multidimensional and multivariate event, and therefore, the relationship between climate and species distribution is not always direct [46]. In addition to climatic factors, interaction processes and resource utilization (Eltonian niche–scenopoetic dimensions) also contribute in determining the limits (areapauses) of the distribution of species [47–49]. Because it is not so simple to discriminate these components, much caution is necessary in the use of projections to indicate a land mass as an effective occupation area of a particular species, either in the past or in the present [50]. Otherwise, there is a risk of making mistakes in interpreting the results. Having secured this, our models showed fluctuations in precipitation affecting the area of habitat suitability of almost all species of ceratophrids during the Last interglacial, remaining an important variable, less in present day, and it seems that it will also be in the coming decades. In contrast, we found that temperature had effected on these toads regarding ‘occupation area’ during the Last glacial maximum, where we found a greater territorial expansion compared to today and the Last interglacial.
In the case of species of ceratophrids, the way these amphibians reacted to climate changes during the last 140 000 years was something very curious in spite of microhabitats where they usually live [10, 12, 51]. We observed that representatives of the genera Chacophrys and Lepidobatarchus (except L. asper) had higher area of habitat suitability during the Last interglacial unlike species of Ceratophrys—with wider area of habitat suitability during the Last glacial maximum. This suggests that ceratophrids, even though they share many traits, did not respond equally to climate fluctuations, and some species were much more sensitive to the oscillatory effects of temperature (e.g., C. calcarata; C. cranwelli; C. ornata; Chacophrys; L. asper and L. laevis) while others to precipitation (e.g., C. aurita; C. cornuta; C. joazeirensis; C. stolzmanni and L. llanensis). Note that it is difficult to make any conclusions about why such conditions affect the species in this way. To further investigate the prospects of ceratophrids under climate change, would be required do physiological studies to investigate the species’ tolerance in different ecological conditions.
The Quaternary was characterized by fairly rapid climate fluctuations, where it affect the distribution of faunas and floras, extinguished many species (mainly mammals and birds) and gave rise to many others in less than a million years [46, 52–54]. For ceratophrids, it is possible that they were already well adapted when they survived the changes of the Quaternary, responding to them with few extinctions and following the dynamics of biomes with which they remained associated and seemingly dependent on for millennia [8, 44, 55]. Like other species, the way these frogs responded to climate change in the last thousands of years defined and still influences their current distributions [8, 56].
Quaternary deposits of South America indicate climate fluctuations to wetter conditions interspersed with drier climates in large areas [56, 57]. This oscillation was responsible for the processes of formation of new types of soil and topography, expanding and retracting forested areas or savanna steppe areas as sculpted microhabitats and new landscapes [56, 58]. The faunas and floras that negatively responded to this dynamics became extinct or relegated to a few scattered refuges [50, 59–61]. In the latter case, we can locate almost all ceratophrids that in response to Quaternary climatic fluctuations increased their area of habitat suitability (probably the effective occupation area) in the glacial phase, something very well represented in our projections. During the Last glacial maximum, the temperature was milder and the dry areas much larger. In contrast, during the wet stages (interglacial), we observed shrinkage of the distribution areas of these species of frogs, which indicates a higher relation of these amphibians to the steppe grasslands than rainforests.
Many transformations occurred in the paleovegetation of South America during glacial periods to interglacial and vice versa, with faunas and floras receding and expanding their ranges over time as a result of global climate change. For the Ceratophryidae, this was no different and necessarily such cycles (retraction and expansion) can will happen again, with possible worsening because of the result of human activity in this century, an at a much shorter period of time than that observed during the Quaternary, something that will be greatly detrimental to the survival of ceratophrids and that also can cause extinction of others species, an event comparable only those that have already occurred during the Permo-Triassic and Cretaceous-Tertiary [62–65].
While we can look at the past and imagine detailed scenarios, it is difficult to predict how ceratophrids, and also many other amphibians [66], will react to environmental change and the gradual increase in temperature as a result of current climate change—probably aggravated by humans. During the glacial phase, the temperature was milder compared to interglacial periods and in these two stages, there was no environmental degradation on a scale as fast, deep and broad as currently observed. This, by itself, unlike today, already provided a good chance of survival to many animal and plant species. Thus, based on this perspective, it may be that the possible expansion of distribution areas proposed by our models is false positive indicators of the future of ceratophrids instead of representing truly optimistic scenarios for them. On this account, it may be that those new areas cannot be colonized by these amphibians. For example, while a cougar can walk kilometers after kilometers, and thus access to new areas, the same is not valid for most toads. In this case, we recommend that the projections be viewed with caution and not as empirical evidence in treating the future of these animals because of the possible overestimated probabilities in PM(g) in the BAM diagram [40].
Given the exponentially growth of the human population and its increasing demands for resources, environmental preservation/conservation areas have recently been understood and designed as a safeguard of wildlife areas and nature strongholds for future generations [67]. There are many reasons that led to the development of the concept of legally protected areas, as well as the justifications to convince governments of the importance of preservation/conservation areas [68, 69]. No doubt, environmental preservation/conservation areas must ensure the protection of species and ecosystems, so that they can still exist in the medium and long term [70]. However, will such areas be effective in protecting these species?
In the particular case of ceratophrids, according to our results, by the year 2080, most of the distribution area of 50% of these frog species will be still included in environmental preservation/conservation areas, which means that half of them will not be vulnerable in the next 65 years. However, this situation becomes alarming when considering habitat destruction coupled with the lack of legal support of protected areas, and in this case, it is very possible that four species will be almost extinct by the turn of this century: C. aurita, C. ornata and C. stolzmanni (see data of the IUCN). If there is a possibility of this happening to ceratophrids, animals that are well adapted to water stress (because of climate changes over the past 140 000 years), the chances of other species of the global amphibiofauna of becoming extinct or extremely vulnerable are much higher. Recent studies showed that the world herpetofauna will endure large losses by 2080 due to global climate change, disease and defaunation caused by humans [65, 71–74].
Much of the optimism of our future projections for ceratophrids are, at best, unlikely scenarios, especially when considering the rapid pace of degradation of habitats and the lack of effectiveness of environmental preservation/conservation areas in the long term [75]. This leads us to conclude that although we may consider a likely limit to the future expansion of distribution for these amphibians, our results suggest a broad expansion of dry climates in South America in the XXII century and hence retraction of forested environments, similar to what occurred during the Pleistocene [56, 57, 76], differing only by a larger decline in diversity, and not only of ceratophrids, around the turn of the century [65].
Other studies have also indicated losses in diversity, especially when it remains confined to specific areas, mainly due to effects of habitat fragmentation and climate change [75, 77–79]. Thus, the effectiveness and functionality of long-term environmental preservation/conservation areas is something very questionable, and that was also what we found out from our results. For example, only in relation to C. aurita, environmental preservation/conservation areas currently comprise 48.24% of the total distribution of this species, and official data indicate that the Atlantic Forest is under an accelerated rate of destruction [80], including within its own ecological reserves, because of illegal deforestation [81, 82]. This suggests the possibility that by the second half of the twenty-first century all endemic species of the Atlantic Forest (and those that there are distributed) are in serious risk [79, 83, 84], including C. aurita. With this in mind, one of the challenges will be to know with relative certainty, what would be the appropriate minimum distribution size to provide viability, in this case Ceratophryidae populations, and ensure the future of their species. This question can only be answered by studies in population dynamics.
When developing public policies for the demarcation of environmental reserve areas, the last thing that is contemplated is if the geographical space is appropriate or not for the viability of populations of species, whether animal or plant. This is a subject that does not arouse much interest or popular mobilization, so the areas are generally designed with regard to tourism potential and fitted to private property areas and/or land of economic interest [85]. Moreover, with a serious aggravating future, environmental reserves may give way with changes in economic interests and also increased demands for resources. This will aggravate even further the problem of the conservation of species and generate a serious impasse; therefore, to be viable, the environmental preservation/conservation areas will need to be adjusted as the spatial distribution of biodiversity changes in the near future [86]. This will be necessary if we want these reserves to be functional by offering guarantees of future existence of the species they harbor and consequently also for future generations of humans. But how will this be possible with the massive and continuous destruction of habitats?
For a long time, both philosophers and eminent scientists have been concerned about climate change, many of them even claiming that there seems to be an optimistic future for biodiversity as a whole, including ourselves [87, 88]. Furthermore, the current political and economic reality imposes difficult barriers to overcome [89, 90]. To meet the growing human and livestock demands, it has been necessary to destroy wilderness areas and expand or create new spaces for agriculture in recent centuries. If this scenario continues, and it looks that way, any measure that promises to ensure spatial plasticity to environmental protection areas (albeit restricted) will be more like hope.
Preventive measures need to be urgently developed and implemented so that they can minimize this impasse. However, this is not possible without a radical measure, for example, changing the way we see environmental preservation/conservation areas: from inert objects to dynamic ones, change on the current politico-economic model, making the people aware of the use of natural resources, and restructuring of the urban mechanism from dysfunctional to sustainable [91–93].
The survival of the human species will require a new social model that is based on cooperativity, the responsible and equitable distribution of resources, as well as an education based on the real needs of human society and other species. This will force us to think differently, to reshape our interpersonals relations and to see nature, not as a thing which we preyed upon for centuries, but as a part of ourselves. Only then can we ensure a future not only for ceratophrids but also for all other species and ecosystems.
Supporting information
(DOCX)
Last interglacial (A); Last glacial maximum (B) and Current (C). (A): 12,163 km2; (B): 34,958 km2 and (C): 11,301 km2. Training data: AUC = 0.985 (A); AUC = 0.986 (B) and AUC = 0.988 (C). Test data: AUC = 0.985 (A); AUC = 0.973 (B) and AUC = 0.986.
(TIF)
Last interglacial (A); Last glacial maximum (B) and Current (C). (A): 7,287 km2; (B): 27,623 km2 and (C): 7,298 km2. Training data: AUC = 0.996 (A); AUC = 0.991 (B) and AUC = 0.997 (C). Test data: AUC = 1:00 (A); AUC = 0.710 (B) and AUC = 0.997.
(TIF)
Last interglacial (A); Last glacial maximum (B) and Current (C). (A): 59,979 km2; (B): 166,127 km2 and (C): 76,329 km2. Training data: AUC = 0.962 (A); AUC = 0.936 (B) and AUC = 0.956 (C). Test data: AUC = 0.892 (A); AUC = 0.919 (B) and AUC = 0.929.
(TIF)
Last interglacial (A); Last glacial maximum (B) and Current (C). (A): 67,880 km2; (B): 82,321 km2 and (C): 69,362 km2. Training data: AUC = 0.966 (A); AUC = 0.950 (B) and AUC = 0.956 (C). Test data: AUC = 0.930 (A); AUC = 0.942 (B) and AUC = 0.942 (C).
(TIF)
Last interglacial (A); Last glacial maximum (B) and Current (C). (A): 14,574 km2; (B): 62,883 km2 and (C): 33,162 km2. Distribution areas shown in the most western parts of the continent are unlikely and represent analysis artifacts resulting from Grinnellian niche concept. Training data: AUC = 0.989 (A); AUC = 0.968 (B) and AUC = 0.984 (C). Test data: AUC = 0.995 (A); AUC = 0.976 (B) and AUC = 0.984 (C).
(TIF)
Last interglacial (A); Last glacial maximum (B) and Current (C). (A): 22,657 km2; (B): 54,701 km2 and (C): 25,563 km2. Distribution areas indicated in the extreme south of the continent may be due to analysis artifacts resulting from Grinnellian niche concept. Training data: AUC = 0.994 (A); AUC = 0.982 (B) and AUC = 0.991 (C). Test data: AUC = 0.991 (A); AUC = 0.988 (B) and AUC = 0.984 (C).
(TIF)
Last interglacial (A); Last glacial maximum (B) and Current (C). (A): 746 km2; (B): 4,729 km2 and (C): 595 km2. Distribution areas indicated in the northern part of the continent are unlikely and represent analysis artifacts resulting from Grinnellian niche concept. Training data: AUC = 1.000 (A); AUC = 0.999 (B) and AUC = 1.000 (C). Test data: AUC = 1.000 (A); AUC = 0.987 (B) and AUC = 0.996 (C).
(TIF)
Last interglacial (A); Last glacial maximum (B) and Current (C). (A): 68,824 km2; (B): 43,109 km2 and (C): 58,920 km2. Distribution areas indicated in the extreme west of the continent are unlikely and represent analysis artifacts resulting from the Grinnellian niche concept. Training data: AUC = 0.989 (A); AUC = 0.991 (B) and AUC = 0.971 (C). Test data: AUC = 0.940 (A); AUC = 0.917 (B) and AUC = 0.995.
(TIF)
Last interglacial (A); Last glacial maximum (B) and Current (C). (A): 37,905 km2; (B): 31,409 km2 and (C): 31,822 km2. Training data: AUC = 0.992 (A); AUC = 0.991 (B) and AUC = 0.994 (C). Test data: AUC = 0.982 (A); AUC = 0.994 (B) and AUC = 0.940 (C).
(TIF)
Last interglacial (A); Last glacial maximum (B) and Current (C). (A): 59,958 km2; (B): 74,262 km2 and (C): 55 569 km2. Training data: AUC = 0.979 (A); AUC = 0.980 (B) and AUC = 0.979 (C). Test data: AUC = 0.962 (A); AUC = 0.970 (B) and AUC = 0.954 (C).
(TIF)
Last interglacial (A); Last glacial maximum (B) and Current (C). (A): 31,170 km2; (B): 29 288 km2 and (C): 24,105 km2. Distribution areas indicated in the western part of the continent are unlikely and represent analysis artifacts resulting from the Grinnellian niche concept. Training data: AUC = 0.994 (A); AUC = 0.989 (B) and AUC = 0.996 (C). Test data: AUC = 0.985 (A); AUC = 0.996 (B) and AUC = 1.000 (C).
(TIF)
(TIF)
(TIF)
(TIF)
(TIF)
(TIF)
(TIF)
(TIF)
(TIF)
(TIF)
(TIF)
(TIF)
(XLSX)
(XLSX)
Acknowledgments
We thank the following professors/researchers whose assistance was essential in conducting this study: Abraão Ribeiro Barbosa, at the time, lecturer, Universidade Estadual da Paraíba; Ednilza Maranhão, Universidade Federal Rural de Pernambuco; Míriam Guarnieri, Universidade Federal de Pernambuco; Ronald Heyer, Smithsonian Institution; Felgueiras Napoli, Museu de Zoologia da Universidade Federal da Bahia; Ana Lúcia Prudente, Fabrício Sarmento and Marinus Hoogmoed, Museu Paraense Emílio Goeldi; Santiago Ron, Museo de Zoología/Centro de Biodiversidad y Ambiente/Escuela de Biología Universidad del Ecuador; Federico Kacoliris, Museu de La Plata; Juan Fernicola, Museu Argentino de Ciências Naturais Bernardino Rivadavia; Enrique La Marca, Laboratório de Biogeografia da Universidade de Los Andes; Diego Cisneros-Heredia, Universidad San Francisco de Quito; Manuel Morales de Mite, Pontificia Universidad Catolica del Ecuador; Marissa Fabrezi, Universidad Nacional de Salta; Maria Luiza Beçak and Radenka Batistic, Instituto Butantan; Flora Juncá, da Universidade Estadual de Feira de Santana; Ana Paula Zampieri, Universidade de São Paulo; Renato Faria, Universidade Federal de Sergipe; Célio Haddad, Universidade Estadual Paulista Júlio de Mesquita Filho/Instituto de Biociências de Rio Claro; Ariadna Sabbag and Renato Neves Feio, Museu de Zoologia da Universidade Federal de Viçosa; Diego Santana, Universidade Federal de Mato Grosso do Sul; Carolina Mello, Museu de Zoologia da Universidade de São Paulo; Hussam Zaher, Museu de Zoologia da Universidade de São Paulo; José Perez Pombal Jr, Departamento de Vertebrados do Museu Nacional do Rio de Janeiro. We are also grateful to the anonymous referees for their critical review that allowed us to improve the article. The Drs. A. Leyva and Gentil Alves Pereira Filho helped with English translation and editing of the manuscript.
Data Availability
All relevant data are within the paper and its Supporting Information files.
Funding Statement
This work was supported by Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) and Programa de Desenvolvimento Científico e Tecnológico Regional da Paraíba. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
References
- 1.Gaston KJ, Fuller RA. The Sizes of Species' Geographic Ranges. Journal of Applied Ecology. 2009;46:1–9. [Google Scholar]
- 2.Soberón J, Nakamura M. Niches and Distributional Areas: Concepts, methods, and assumptions. PNAS. 2014;106(2):19644–50. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Pulliam HR. On The Relationship Between Niche and Distribution. Ecology Letters. 2000;3:349–61. [Google Scholar]
- 4.Elton C. The Ecology of Animals 1a ed New York: John Wiley & Sons Inc; 1933. [Google Scholar]
- 5.Hutchinson GE. Concluding Remark. Cold Spring Harbor Symposia on Quantitative Biology. 1957;22(2):415–27. [Google Scholar]
- 6.Holt RD. On the Evolutionary Ecology of Species' Ranges. Evolutionary Ecology Research. 2003;5:159–78. [Google Scholar]
- 7.Lynch JD. Relationships of the Frogs of the Genus Ceratophrys (Leptodactylidae) and Their Bearing on Hypotheses of Pleistocene Forest Refugia in South America and Punctuated Equilibria. Systematic Zoology. 1982;31(2):166–79. [Google Scholar]
- 8.Mercadal IT. Ceratophrys joazeirensis sp. n. (Ceratophryidae, Anura) del noreste de Brasil. Amphibia-Reptilia. 1986;7:313–34. [Google Scholar]
- 9.Cei JMR, Virgilio G. Telmatobinos de las lagunas basalticas de Neuquen (Anura, Leptodactylidae). Physis. 1968;Tomo XXVII(75):265–84. [Google Scholar]
- 10.Duellman WE, Trueb L. Biology of Amphibians 2a ed Baltimore and London: The Johns Hopkins University Press; 1994. 1–670 p. [Google Scholar]
- 11.Zimmerman BL, Simberloff D. An Historical Interpretation of Habitat Use by Frogs in a Central Amazonian Forest. Journal of Biogeography. 1996;23, No.1:27–46. [Google Scholar]
- 12.Ortiz DA, Almeida-Reinoso D, Coloma LA. Notes on Husbandry, Reproduction and Development in the Pacific Horned frog Ceratophrys stolzmanni (Anura: Ceratophryidae), with Comments on its Amplexus. International Zoo Yearbook. 2013;47:151–62. [Google Scholar]
- 13.Jorge JdS, Sales RFD, Kokubum MNdC, Freire EMX. On the Natural History of the Caatinga Horned Frog, Ceratophrys joazeirensis (Anura: Ceratophryidae), a Poorly Known Species of Northeastern Brazil. Phyllomedusa. 2015;14(2):147–56. [Google Scholar]
- 14.Schalk CM, Fitzgerald LA. Ontogenetic Shifts in Ambush-site Selection of a Sit-and-wait Predator, the Chacoan Horned Frog (Ceratophrys cranwelli). Canadian Journal of Zoology. 2015;93(6):461–7. [Google Scholar]
- 15.Pueta M, Perotti MG. Feeding Habits of Juvenile Chacophrys pierottii (Ceratophryidae-Ceratophryinae) From Northwestern Córdoba Province, Argentina. Herpetological Conservation and Biology. 2013;8(2):376–84. [Google Scholar]
- 16.Faivovich J, Nicoli L, Blotto BL, Pereyra MO, Baldo D, Barrionuevo JS, et al. Big, Bad, and Beautiful: Phylogenetic Relationships of the Horned Frogs (Anura: Ceratophryidae). South American Journal of Herpetology. 2014;9(3):207–27. [Google Scholar]
- 17.IUCN. IUCN Red List of Threatened Species 2013 [cited 2013 15/05/2013]. Version 2012.2.:[Available from: http://www.iucnredlist.org/details/57112/0.
- 18.Diniz-Filho JA, Araújo MB. Macroecologia e Mudanças Climáticas In: Carvalho CJBA, Botelho Eduardo Andrade, editor. Biogeografia da América do Sul Padrões & Processos. 1a ed São Paulo: Roca; 2011. p. 151–61. [Google Scholar]
- 19.InfoNatura. Animals and Ecosystems of Latin America Arlington, Virginia (USA): NatureServe; 2007 [cited 2013 15/05/2013]. Version 5.0:[Available from: http://www.natureserve.org/infonatura.
- 20.Frost DR. Amphibian Species of the World: an Online Reference New York: American Museum of Natural History; 2015. [cited 2015 13/01/2015]. Version 6.0 [Available from: http://research.amnh.org/vz/herpetology/amphibia/. [Google Scholar]
- 21.Rios NE, Bart HL Jr, Abibou D. GEOLocate Web Application—A Platform for Georeferencing Natural History Collections Data Belle Chasse, LA Tulane: University Biodiversity Research Institute; 2013. [cited 2013 September 10]. Available from: http://www.museum.tulane.edu/geolocate/default.html. [Google Scholar]
- 22.Hijmans RJ, Guarino L, Jarvis A, O'Brien R, Mathur P, Bussink C, et al. DIVA-Gis Version 7.5. Bioversity International, the International Potato Center, the International Rice Research Institute, the University of California-Berkeley Museum of Vertebrate Zoology, and others; 2005. p. 11p.
- 23.Phillip SJ, Anderson RP, Schapire RE. Maximum Entropy Modeling of Species Geographic Distributions. Ecological Modelling. 2006;190:231–59. [Google Scholar]
- 24.Giovanelli JGR, de Siqueira MF, Haddad CFB, Alexandrino J. Modeling a Spatially Restricted Distribution in the Neotropics: How the Size of Calibration Area Affects the Performance of Five Presence-only Methods. Ecological Modelling. 2010;221:215–24. [Google Scholar]
- 25.Halvorsen R, Mazzoni S, Bryn A, Bakkestuen V. Opportunities for Improved Distribution Modelling Practice Via a Strict Maximum Likelihood Interpretation of MaxEnt. Ecography. 2014;37(1):1–12. [Google Scholar]
- 26.Hernandez PA, Graham CH, Master LL, Albert DL. The Effect of Sample Size and Species Characteristics on Performance of Different Species Distribution Modeling Methods. Ecography. 2006;29:773–85. [Google Scholar]
- 27.Qiao H, Soberón J, Peterson AT. No Silver Bullets in Correlative Ecological Niche Modelling: insights from testing among many potential algorithms for niche estimation. Methods in Ecology and Evolution. 2015;6(10):1126–36. [Google Scholar]
- 28.Hijmans RJ, Cameron S, Parra J, Jones P, Jarvis A, Richardson K. WorldClim—Global Climate Data Berkeley: Museum of Vertebrate Zoology, University of California; 2005. [cited 2018 May, 26]. Available from: http://www.worldclim.org/about. [Google Scholar]
- 29.Nakičenovič N, Davidson G, Grübler A, Kram T, La Rovere EL, Metz B, et al. A Special Report of IPCC Working Group III—Emissions Scenarios: Intergovernmental Panel on Climate Change; 2000.
- 30.Govindasamy B, Duffy PB, Coquard J. High-Resolution Simulations of Global Climate, part 2: effects of increased greenhouse cases. Climate Dynamics. 2003;21:391–404. [Google Scholar]
- 31.Watson RT, Albritton DL, Barker T, Bashmakov IA, Canziani O, Christ R, et al. Climate Change 2001: Synthesis Report. 2001 24–29 September 2001. Report No.: VIII.
- 32.Alley RB, Berntsen T, Bindoff NL, Chen Z, Chidthaisong A, Friedlingstein P, et al. A Report of Working Group I of the Intergovernmental Panel on Climate Change—Summary for Policymakers In: Qin D, Manning M, Chen Z, Marquis M, Averyt KB, Tignor M, et al. , editors. Climate Change 2007: The Physical Science Basis. Cambridge, United Kingdom and New York, NY, USA: Cambridge University Press; 2007. p. 18. [Google Scholar]
- 33.Otto-Bliesner B, Marshall SJ, Overpeck JT, Miller GH, Hu A. Simulating Arctic Climate Warmth and Icefield Retreat in the Last Interglaciation. Science. 2006;311:1751 10.1126/science.1120808 [DOI] [PubMed] [Google Scholar]
- 34.Tôrres NM, Vercillo UE. How Can Species Distribution Modeling Tools Support Government Actions? Natureza & Conservação. 2012;10(2):228–30. [Google Scholar]
- 35.Young N, Carter L, Evangelista P. A MaxEnt Model v3.3.3e Tutorial (ArcGis v10) Colorado: Natural Resource Ecology/National Institute of Invasive Species/Colorado State University; 2011. p. 1–30. [Google Scholar]
- 36.Fielding AH, Bell JF. A Review of Methods for the Assessment of Prediction Errors in Conservation Presence/absence Models. Environmental Conservation. 1997;24(1):38–49. [Google Scholar]
- 37.McPherson JM, Jetz W, Rogers DJ. The Effects of Species' Range Sizes on the Accuracy of Distribution Models: ecological phenomenon or statistical artefact? Journal of Applied Ecology. 2004;41:811–23. [Google Scholar]
- 38.Peterson AT, Papes M, Soberón J. Rethinking Receiver Operating Characteristic Analysis Applications in Ecological Niche Modeling. Ecological Modelling. 2008;213:63–72. [Google Scholar]
- 39.Soberón J. Grinnellian and Eltonian Niches and Geographic Distributions of Species. Ecology Letters. 2007. 10:1115–23. 10.1111/j.1461-0248.2007.01107.x [DOI] [PubMed] [Google Scholar]
- 40.Soberón JN, Miguel. Niches and Distributional Areas: concepts, methods, and assumptions. PNAS. 2009;106(2):19644–50. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41.IUCN, UNEP. The World Database on Protected Areas (WDPA) Cambridge, UK: UNEP-WCMC; 2014. [cited 2014 05/01]. Available from: www.protectedplanet.net. [Google Scholar]
- 42.Paglia AP, de Rezende DT, Koch I, Kortz AR, Donatt C. Species Distribution Models (SDM) in Biodiversity Conservation Strategies and Climate Change Ecosystem Based Adaptation. Natureza & Conservação. 2012;10(2):231–4. [Google Scholar]
- 43.Strikis NM, Novello VF. Evolução Hidrológica do Brasil Durante o Pleistoceno Superior e Holoceno In: Carvalho IdS, Garcia MJ, Lana CC, Strohschoen O Jr, editors. Paleontologia: Cenários de Vida—Paleoclimas. 5. 1a ed Rio de Janeiro: Editora Interciência; 2014. p. 343–51. [Google Scholar]
- 44.Maxson LR, Ruibal R. Relationships os Frogs in the Leptodactylidae Subfamily Ceratophryinae. Journal of Herpetology. 1988;22(2):228–31. [Google Scholar]
- 45.Raup DM. Diversity Crises in the Geological Past Biodiversity. 1a ed Washington, D. C: National Academy of Scince and The Smithsonian Institution; 1988. p. 51–7. [Google Scholar]
- 46.Seguio K. As Mudanças Paleoclimáticas Quaternárias e os seus Registros Geologia do Quaternário e Mudanças Ambientais: (Presente + Passado = Futuro?). São Paulo: Paulo's Editora; 1999. p. 51–72. [Google Scholar]
- 47.Horton DR. Dominance and Zoogeography of Southern Continents. Systematic Zoology. 1974;23(3):440–5. [Google Scholar]
- 48.Bigarella JJ, Andrade-Lima, Dárdano;, Riehs PJ. Considerações a Respeito das Mudanças Paleoambientais na Distribuição de Algumas Espécies Vegetais e Animais no Brasil. Anais da Academia Brasileira de Ciências. 1975;47:411–64. [Google Scholar]
- 49.Pearson RG, Dawson TP. Predicting the Impacts of Climate Change on the Distribution of Species: are bioclimate envelope models useful? Global Ecology & Biogeography. 2003;12:361–71. [Google Scholar]
- 50.Bonaccorso E, Koch I, Peterson T. Pleistocene Fragmentation of Amazon Species' Ranges. Diversity and Distributions. 2006;12:157–64. [Google Scholar]
- 51.Peters JA. The Generic Allocation of the frog Ceratophrys stolzmanni Steindachner, with the Description of a New Subspecies from Ecuador. Proceedings of the Biological Society of Washington. 1967;80:115–2. [Google Scholar]
- 52.Wolberg DL. Late Pleistocene Extinction: A Note. American Anthropologist, New Series. 1970;72(1):106–7. [Google Scholar]
- 53.Raup DM. The Role of Extinction in Evolution. Proceedings of the National Academy of Sciences. 1994;91:6758–63. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 54.Bobe R, Behrensmeyer AK. The Expansion of Grassland Ecosystems in Africa in Relation to Mammalian Evolution and the Origin of the Genus Homo Palaeogeography, Palaeoclimatology, Palaeoecology. 2004;207:399–420. [Google Scholar]
- 55.Agnolin FL. Un Nuevo Escuerzo (Anura, Leptodactylidae) del "Ensenadense" (Pleistoceno Inferior-Medio) de la Provincia de Buenos Aires (Argentina), con Notas sobre la Classificación del Género Ceratophrys. Studia Geológica Salmanticensia. 2005;41:45–55. [Google Scholar]
- 56.Ab'Saber AN. Paleoclimas Quaternários e Pré-história da América Tropical I. Revista Brasileira de Biolologia. 1990. a;50(4):805–20. [Google Scholar]
- 57.Ab'Saber AN. Espaços Ocupados pela Expansão dos Climas Secos na América do Sul, por Ocasião dos Períodos Glaciais Quaternários. Paleoclimas. 1977;3:1–19. [Google Scholar]
- 58.Ab'Saber AN. Paleoclimas Quaternários e Pré-história da América Tropical II. Revista Brasileira de Biologia. 1990. b;50(4):821–31. [Google Scholar]
- 59.Vanzolini PE. Paleoclimas e Especiação em Animais da América do Sul Tropical. Estudos Avançados. 1992;6(15):41–65. [Google Scholar]
- 60.Ranzi A. Significado Paleoecológico. Paleoecologia da Amazônia (Megafauna do Pleistoceno) Florianópolis—Santa Catarina: Editora da UFSC; 2000. p. 59–83. [Google Scholar]
- 61.Vanzolini PE, Williams EE. The Vanishing Refuge: a mechanism for ecogeographic speciation. Papéis Avulsos de Zoologia (São Paulo). 2008;34(23):251–5. [Google Scholar]
- 62.Thomas JA, Telfer MG, Roy DB, Preston CD, Greenwood JJD, Asher J, et al. Comparative Losses of British Butterflies, Birds, and Plants and the Global Extinction Crisis. Science. 2004;303(5665):1879–81. 10.1126/science.1095046 [DOI] [PubMed] [Google Scholar]
- 63.Kiehl JT, Shields CA. Climate Simulation of the Latest Permian: implications for mass extinction. Geology. 2005;33(9):757–60. [Google Scholar]
- 64.Ward PD, Botha J, Buick R, De Kock MO, Erwin DH, Garrinson GH, et al. Abrupt and Gradual Extinction Among Late Permian Land Vertebrates in the Karoo Basin, South Africa. Science. 2005;307:709–14. 10.1126/science.1107068 [DOI] [PubMed] [Google Scholar]
- 65.Dirzo R, Young HS, Galetti M, Ceballos G, Isaac NJB, Collen B. Defaunation in the Anthropocene. Science. 2014;345:401–6. 10.1126/science.1251817 [DOI] [PubMed] [Google Scholar]
- 66.Skelly DK, Yurewicz KL, Werner EE, Relyea RA. Estimating Decline and Distributional Change in Amphibians. Conservation Biology. 2003;17(3):744–51. [Google Scholar]
- 67.McNeely JA, Miller KR. N ational Parks, Conservation, and Development: The Role of Protected Areas in Sustaining Society 1a ed McNeely JA, Miller KR, editors. Washington, D.C: Smithsonian Institution Press; 1984. 825 p. [Google Scholar]
- 68.McNeely JA. Economics and Biological Diversity: Developing and Using Economic Incentives to Conserve Biological Resources Gland, Switzerland: IUCN; 1988. [Google Scholar]
- 69.Devall B. Conservation of Biodiversity: Opportunities and Challenges. Human Ecology Review. 2006;13(1):60–75. [Google Scholar]
- 70.Primack RB, Rodrigues E. Biologia da Conservação 1a ed Londrina: Editora Planta; 2001. [Google Scholar]
- 71.Blaustein AR, Kiesecker JM. Complexity in Conservation: lessons from the global decline of amphibian populations. Ecology Letters. 2002;5:597–608. [Google Scholar]
- 72.Stuart SN, Chanson JS, Cox NA, Young BE, Rodrigues ASL, Fischman D, et al. Status and Trends of Amphibian Declines and Extinctions Worldwide. Sciencexpress. 2004:1–5. [DOI] [PubMed] [Google Scholar]
- 73.Araújo MB, Thuiller W, Pearson RG. Climate Warming and the Decline of Amphibians and Reptiles in Europe. Journal of Biogeography. 2006;33:1712–28. [Google Scholar]
- 74.Pounds JA, Bustamante MR, Coloma LA, Consuegra JA, Fogden MPL, Foster PN, et al. Widespread Amphibian Extinctions from Epidemic Disease Driven by Global Warming. Nature. 2006;439(12):161–7. [DOI] [PubMed] [Google Scholar]
- 75.Chape S, Harrinson J, Spalding M, Lysenko I. Measuring the Extent and Effectiveness of Protected Areas as an Indicator for Meeting Global Biodiversity Targets. Philosophical Transactions of the Royal Society B. 2005;360:443–55. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 76.Ab'Saber AN. Os Mecanismos da Desintregração das Paisagens Tropicais no Pleistoceno—Efeitos paleoclimáticos do período Würm-Wisconsin no Brasil. Inter-facies escritos e documentos. 1979;No. 4:1–19. [Google Scholar]
- 77.Rodrigues PH, Ferigolo J. Roedores Pleistocênicos da Planície Costeira do Estado do Rio Grende do Sul, Brasil. Revista Brasileira de Paleontologia. 2004;7(2):231–8. [Google Scholar]
- 78.Araújo MB, Alagador D, Cabeza M, Nogués-Bravo D, Thuiller W. Climate Change Threatens European Conservation Areas. Ecology Letters. 2011;14:484–92. 10.1111/j.1461-0248.2011.01610.x [DOI] [PMC free article] [PubMed] [Google Scholar]
- 79.Loyola RD, Lemes P, Brum FT, Provete DB, Duarte LDS. Clade-specific Consequences of Climate Change to Amphibians in Atlantic Forest Protected Areas. Ecography. 2013;36:1–8. [Google Scholar]
- 80.Weigand R Jr, Pires MO, Farias AE, Schaffer WB, Prates AP, Albernaz AL, et al. Áreas Prioritárias para a Conservação, Uso Sustentável e Repartição de Benefícios da Biodiversidade Brasileira Brasília: Ministério do Meio Ambiente, Secretaria de Biodiversidade e Florestas; 2007. [Google Scholar]
- 81.Tabarelli M, Pinto LP, Silva JMC, Hirota MM, Bedê L. Challenges and Opportunities for Biodiversity Conservation in the Brazilian Atlantic Forest. Conservation Biology. 2005;19(3):695–700. [Google Scholar]
- 82.Spracklen BD, Kalamandeen M, Galbraith D, Gloor E, Spracklen DV. A Global Analysis of Deforestation in Moist Tropical Forest Protected Areas. PLoS ONE. 2015;e0143886:1–16. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 83.Loyola RD, Lemes P, Faleiro FV, Trindade-Filho J, Machado RB. Severe Loss of Suitable Climatic Conditions for Marsupial Species in Brazil: Challenges and Opportunities for Conservation. PLoS ONE. 2012;7(9):1–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 84.Lemes P, Loyola RD. Accommodating Species Climate-forced Dispersal and Uncertainties in Spatial Conservation Planning. PloS one. 2013;8(1):e54323 10.1371/journal.pone.0054323 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 85.Eagles PFJ, McCool SF, Haynes CD. Sustainable Tourism in Protected Areas: Guidelines for Planning and Management Phillips A, editor. United Kingdon: IUCN, Gland, Switzerland, and Cambridge, UK, the United Nations Environment Programme and the World Tourism Organization; 2002. 183 p. [Google Scholar]
- 86.Hannah L, Midgley GF, Lovejoy T, Bonds WJ, Bush M, Lovett JC, et al. Conservation of Biodiversity in a Changing Climate. Conservation Biology. 2002;16(1):264–8. [DOI] [PubMed] [Google Scholar]
- 87.Neumann J. Climatic Change as a Topic in the Classical Greek and Roman Literature. Climatic Change. 1985;7:441–54. [Google Scholar]
- 88.Lovelock J. The Earth as a Living Organism In: Wilson EO, editor. Biodiversity. Washington, D.C: National Academy Press; 1988. p. 486–9. [Google Scholar]
- 89.Görg C, Brand U. Global Environmental Politics and Competition Between Nation-states: on the regulation of biological diversity. Review of International Political Economy. 2000;7(3):371–98. [Google Scholar]
- 90.Simon JM. Green Economy: an ecological contradiction or a governance challenge? Annual European Seminar on the Future of the European Union; September 8-9th, 2012; Ventotene. Ventotene: Altiero Spinelli Institute, in collaboration with the James Madison Trust (London); 2012. p. 9. [Google Scholar]
- 91.Czech B, editor Urbanization as a Threat to Biodiversity: Trophic Theory, Economic geography, and Implications for Conservation Land Acquisition. Proceedings of a Symposium at the Society for Conservation Biology 2004 Annual Meeting; 2005; St. Paul, MN: U.S. St. Paul, MN: U.S.: Department of Agriculture, Forest Service, North Central Research Station; 2005.
- 92.Singer M. Eco-nomics: Are the Planet-Unfriendly Features of Capitalism Barriers to Sustainability? Sustainability. 2010;2:127–44. [Google Scholar]
- 93.Smith R. Beyond Growth or Beyond Capitalism?. Real-World Ecomist Review. 2010(53):28–42. [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
(DOCX)
Last interglacial (A); Last glacial maximum (B) and Current (C). (A): 12,163 km2; (B): 34,958 km2 and (C): 11,301 km2. Training data: AUC = 0.985 (A); AUC = 0.986 (B) and AUC = 0.988 (C). Test data: AUC = 0.985 (A); AUC = 0.973 (B) and AUC = 0.986.
(TIF)
Last interglacial (A); Last glacial maximum (B) and Current (C). (A): 7,287 km2; (B): 27,623 km2 and (C): 7,298 km2. Training data: AUC = 0.996 (A); AUC = 0.991 (B) and AUC = 0.997 (C). Test data: AUC = 1:00 (A); AUC = 0.710 (B) and AUC = 0.997.
(TIF)
Last interglacial (A); Last glacial maximum (B) and Current (C). (A): 59,979 km2; (B): 166,127 km2 and (C): 76,329 km2. Training data: AUC = 0.962 (A); AUC = 0.936 (B) and AUC = 0.956 (C). Test data: AUC = 0.892 (A); AUC = 0.919 (B) and AUC = 0.929.
(TIF)
Last interglacial (A); Last glacial maximum (B) and Current (C). (A): 67,880 km2; (B): 82,321 km2 and (C): 69,362 km2. Training data: AUC = 0.966 (A); AUC = 0.950 (B) and AUC = 0.956 (C). Test data: AUC = 0.930 (A); AUC = 0.942 (B) and AUC = 0.942 (C).
(TIF)
Last interglacial (A); Last glacial maximum (B) and Current (C). (A): 14,574 km2; (B): 62,883 km2 and (C): 33,162 km2. Distribution areas shown in the most western parts of the continent are unlikely and represent analysis artifacts resulting from Grinnellian niche concept. Training data: AUC = 0.989 (A); AUC = 0.968 (B) and AUC = 0.984 (C). Test data: AUC = 0.995 (A); AUC = 0.976 (B) and AUC = 0.984 (C).
(TIF)
Last interglacial (A); Last glacial maximum (B) and Current (C). (A): 22,657 km2; (B): 54,701 km2 and (C): 25,563 km2. Distribution areas indicated in the extreme south of the continent may be due to analysis artifacts resulting from Grinnellian niche concept. Training data: AUC = 0.994 (A); AUC = 0.982 (B) and AUC = 0.991 (C). Test data: AUC = 0.991 (A); AUC = 0.988 (B) and AUC = 0.984 (C).
(TIF)
Last interglacial (A); Last glacial maximum (B) and Current (C). (A): 746 km2; (B): 4,729 km2 and (C): 595 km2. Distribution areas indicated in the northern part of the continent are unlikely and represent analysis artifacts resulting from Grinnellian niche concept. Training data: AUC = 1.000 (A); AUC = 0.999 (B) and AUC = 1.000 (C). Test data: AUC = 1.000 (A); AUC = 0.987 (B) and AUC = 0.996 (C).
(TIF)
Last interglacial (A); Last glacial maximum (B) and Current (C). (A): 68,824 km2; (B): 43,109 km2 and (C): 58,920 km2. Distribution areas indicated in the extreme west of the continent are unlikely and represent analysis artifacts resulting from the Grinnellian niche concept. Training data: AUC = 0.989 (A); AUC = 0.991 (B) and AUC = 0.971 (C). Test data: AUC = 0.940 (A); AUC = 0.917 (B) and AUC = 0.995.
(TIF)
Last interglacial (A); Last glacial maximum (B) and Current (C). (A): 37,905 km2; (B): 31,409 km2 and (C): 31,822 km2. Training data: AUC = 0.992 (A); AUC = 0.991 (B) and AUC = 0.994 (C). Test data: AUC = 0.982 (A); AUC = 0.994 (B) and AUC = 0.940 (C).
(TIF)
Last interglacial (A); Last glacial maximum (B) and Current (C). (A): 59,958 km2; (B): 74,262 km2 and (C): 55 569 km2. Training data: AUC = 0.979 (A); AUC = 0.980 (B) and AUC = 0.979 (C). Test data: AUC = 0.962 (A); AUC = 0.970 (B) and AUC = 0.954 (C).
(TIF)
Last interglacial (A); Last glacial maximum (B) and Current (C). (A): 31,170 km2; (B): 29 288 km2 and (C): 24,105 km2. Distribution areas indicated in the western part of the continent are unlikely and represent analysis artifacts resulting from the Grinnellian niche concept. Training data: AUC = 0.994 (A); AUC = 0.989 (B) and AUC = 0.996 (C). Test data: AUC = 0.985 (A); AUC = 0.996 (B) and AUC = 1.000 (C).
(TIF)
(TIF)
(TIF)
(TIF)
(TIF)
(TIF)
(TIF)
(TIF)
(TIF)
(TIF)
(TIF)
(TIF)
(XLSX)
(XLSX)
Data Availability Statement
All relevant data are within the paper and its Supporting Information files.



