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Abstract Context Understanding how organismal attributes influence sensitivity to environmental perturbations is a central theme in ecology and conservation. Certain traits, such as body size, habitat use, dietary preference and reproductive output are considered important determinants of animal species' responses to the impacts of ecological disturbances. However, the general relationships between functional traits and post-disturbance responses by animals are not fully understood. AimsOur primary aim was to use a meta-analysis to evaluate the influence of species traits on variation in population abundances of squamate reptiles (i.e. lizards and snakes). MethodsWe extracted data from 107 original published studies, from which 1027 mean effect sizes of post-disturbance responses by 298 species were estimated. We examined short-term responses only (i.e. within 3 years since the most recent disturbance). A comprehensive range of disturbances was examined, such as habitat destruction, fragmentation, fire, and exotic-species invasions. We used Bayesian linear mixed-effect modelling (BLMM), utilising the Markov-chain Monte Carlo algorithm (MCMC) for the meta-regression. Specifically, we tested the influence of eight species traits (body size, diet, temporal activity pattern, sociality, reproductive mode, clutch size, habitat selection, and mean body temperature), along with disturbance type, in explaining variation in species-specific abundance responses of squamate reptiles post-disturbance. Key resultsPost-disturbance abundance responses of squamate species were significantly influenced by two parameters, namely, mean body temperature and clutch size. In general, significant positive responses post-disturbance were observed for species with higher mean body temperatures and a greater clutch size. The type of disturbance had no detectable influence on squamate abundances. The influence of random effects (heterogeneity among studies and species, and broad taxonomic identity) accounted for more of the model variation than did the fixed effects (species traits and disturbance type). ConclusionsCertain species traits exerted some influence on the sensitivities of lizards and snakes to ecological disturbances, although the influence of random effects was very strong. Our findings are likely to be a result of the complexity and idiosyncratic nature of natural abundance patterns among animal species, in addition to the potential confounding effect of methodological differences among studies. ImplicationsThe present study is the first major quantitative synthesis of how species traits influence population-level responses of squamate reptiles to ecological disturbances. The findings can be used to guide conservation efforts and ecological management, such as by prioritising the efforts of mitigation on species that reproduce more slowly, and those with lower body temperatures.

Feral cats (Felis catus) have a wide global distribution and cause significant damage to native fauna. Reducing their impacts requires an understanding of how they use habitat and which parts of the landscape should be the focus of management. We reviewed 27 experimental and observational studies conducted around the world over the last 35 years that aimed to examine habitat use by feral and unowned cats. Our aims were to: (1) summarise the current body of literature on habitat use by feral and unowned cats in the context of applicable ecological theory (i.e. habitat selection, foraging theory); (2) develop testable hypotheses to help fill important knowledge gaps in the current body of knowledge on this topic; and (3) build a conceptual framework that will guide the activities of researchers and managers in reducing feral cat impacts. We found that feral cats exploit a diverse range of habitats including arid deserts, shrublands and grasslands, fragmented agricultural landscapes, urban areas, glacial valleys, equatorial to sub-Antarctic islands and a range of forest and woodland types. Factors invoked to explain habitat use by cats included prey availability, predation/competition, shelter availability and human resource subsidies, but the strength of evidence used to support these assertions was low, with most studies being observational or correlative. We therefore provide a list of key directions that will assist conservation managers and researchers in better understanding and ameliorating the impact of feral cats at a scale appropriate for useful management and research. Future studies will benefit from employing an experimental approach and collecting data on the relative abundance and activity of prey and other predators. This might include landscape-scale experiments where the densities of predators, prey or competitors are manipulated and then the response in cat habitat use is measured. Effective management of feral cat populations could target high-use areas, such as linear features and structurally complex habitat. Since our review shows often-divergent outcomes in the use of the same habitat components and vegetation types worldwide, local knowledge and active monitoring of management actions is essential when deciding on control programs.

Abstract Context Feral cats, Felis catus, have caused the decline and extinction of many species worldwide, particularly on islands and in Australia where native species are generally naïve to the threat of this introduced predator. Effectively reducing cat populations to protect wildlife is challenging because cats have a cryptic nature, high reproductive rate and strong reinvasion ability. Aims We experimentally tested the response of feral cats and their native prey to an Eradicat® poison baiting program at a conservation reserve. Methods Baits were distributed by hand along roads and tracks every 50 m (~10 baits km−2). We used camera traps to monitor the response of cats to baiting using a repeated before–after, control–impact design over 6 years. We also measured introduced rabbit, Oryctolagus cuniculus, activity by using sand pads and small mammal and reptile captures by using pitfall trapping. Key results Dynamic occupancy modelling showed only modest effects of baiting on cats in 2 of 6 years, with occupancy in the baited area decreasing from 54% to 19% in 2014 (–35%) and from 89% to 63% in 2017 (–26%). Baiting effectiveness was not related to antecedent rainfall or prey availability. Bait availability was reduced by non-target interference; 73% of 41 monitored baits were removed by non-target species. We found no evidence for persistent changes in small mammal or reptile capture rates in the baited area relative to the unbaited area over the life of the project. Conclusions Relatively low baiting density and non-target interference with baits are likely to have reduced baiting efficacy. Further testing and refinement of ground baiting is needed, including trialling higher baiting densities and/or frequencies. Implications We highlight key areas for future research that should benefit feral cat management not only in Australia, but also on the many islands worldwide where cats threaten native wildlife.

Abstract
ContextFeral domestic cats (Felis catus) have contributed to substantial loss of Australian wildlife, particularly small- and medium-sized terrestrial mammals. However, mitigating cat impacts remains challenging. Understanding the factors that facilitate coexistence between native prey and their alien predators could aid better pest management and conservation actions.
AimsWe estimated feral cat density, examined the impact of habitat cover on long-nosed potoroos (Potorous tridactylus tridactylus), and assessed the spatial and temporal interactions between cats and potoroos in the 'Bluegums' area of French Island, south-eastern Australia.
Materials and methodsWe operated 31 camera stations across Bluegums for 99 consecutive nights in each of winter 2018 and summer 2018/19. We used a spatially explicit capture–recapture model to estimate cat density, and two-species single-season occupancy models to assess spatial co-occurrence of cats and potoroos. We assessed the influence of vegetation cover and cat activity on potoroo activity by using a dynamic occupancy model. We also used image timestamps to describe and compare the temporal activities of the two species.
Key resultsBluegums had a density of 0.77 cats per km2 across both seasons, although this is a conservative estimate because of the presence of unidentified cats. Cats and long-nosed potoroos were detected at 94% and 77% of camera stations, respectively. Long-nosed potoroo detectability was higher in denser vegetation and this pattern was stronger at sites with high cat activity. Cats and potoroos overlapped in their temporal activity, but their peak activity times differed.
Conclusions Feral cat density at Bluegums, French Island, is higher than has been reported for mainland Australian sites, but generally lower than in other islands. Long-nosed potoroos were positively associated with cats, potentially indicating cats tracking potoroos as prey or other prey species that co-occur with potoroos. Temporal activity of each species differed, and potoroos sought more complex habitat, highlighting possible mechanisms potoroos may use to reduce their predation risk when co-occurring with cats.
ImplicationsOur study highlighted how predator and prey spatial and temporal interactions, and habitat cover and complexity (ecological refuges), may influence the ability for native prey to coexist with invasive predators. We encourage more consideration and investigation of these factors, with the aim of facilitating more native species to persist with invasive predators or be reintroduced outside of predator-free sanctuaries, exclosures and island safe havens.

The Australian Government's 5‐year Threatened Species Strategy contains four priority action areas and associated targets. Here, we argue that the well‐publicized target to cull 2 million feral cats has a weak scientific basis because: (1) reliable estimates of Australia's cat population size did not exist when the target was set; (2) it is extremely difficult to measure progress (numbers of cats killed) in an accurate, reliable way; and, most importantly, (3) the cull target is not explicitly linked to direct conservation outcomes (e.g., measured increases in threatened species populations). These limitations mean that the cull target fails to meet what would be considered best practice for pest management. The focus on killing cats runs the risk of distracting attention away from other threats to biodiversity, most prominent of which is widespread, ongoing habitat loss, which has been largely overlooked in the Threatened Species Strategy. The culling target is a highly visible symbol of a broader campaign around feral cat research and management in Australia, rather than a direct indicator of conservation action and success. We are concerned that progress toward the 2 million target could be misinterpreted as progress toward conserving threatened species, when the link between the two is not clear.

Context Invasive predators are major drivers of global biodiversity loss. Red foxes (Vulpes vulpes) and feral cats (Felis catus) have contributed to the decline and extinction of many native species in Australia. The deployment of poison baits to control fox populations is a widespread conservation tool, but the effects of baiting intensity, rainfall and prey abundance on baiting effectiveness remain poorly understood. Aims We aimed to understand what influences the association between fox baiting intensity, red fox activity and feral cat activity, to provide inferences about what might affect the effectiveness of fox baiting in reducing fox activity. Methods We used generalised linear models to assess how fox and cat activity changes in relation to fox baiting intensity, rainfall, native prey availability and distance to agricultural land over a 6-year period (2006–13) in the forest ecosystems of the Upper Warren region of south-western Australia. Key results We found that fox activity was negatively associated with rainfall in the previous 12 months and positively associated with prey abundance and fox baiting intensity. We also found an interaction between fox baiting and prey abundance, with fox activity increasing with prey activity in areas of low and moderate baiting intensity, but remaining constant in areas of high baiting intensity. Feral cat activity was positively associated with prey abundance and fox baiting intensity. We found no clear relationship between fox and cat activity. Conclusions The drivers of the association between fox baiting and fox activity are unclear because intense fox baiting was targeted at areas of known high fox abundance. However, our results indicate that intense fox baiting may be effective at decoupling the positive association between fox activity and prey abundance. Our results also suggest a positive association between fox baiting intensity and feral cat activity, thus supporting the case for integrated fox and cat management. Implications We caution interpretation of our results, but note that management of invasive predators could be improved by adjusting the intensity of management in response to changes in environmental conditions and local context (e.g. strategically conducting intense predator management where prey abundance is highest). Improved understanding of these associations requires a monitoring program with sufficient replication and statistical power to detect any treatment effects.

Context
Provision of key habitat resources is essential for effectively managing species that have specific ecological requirements and occur in production landscapes. Threatened black cockatoos in the jarrah (Eucalyptus marginata) forest of Western Australia have a wide range, so their conservation requires support from all land tenures, not just reserves. Mining in the jarrah forest temporarily removes cockatoo feeding habitat, so it is important to understand how cockatoos exploit revegetated areas for food resources.

Aims
We aimed to determine whether there were successional patterns in cockatoo feeding activity in revegetation aged from 4 to 23 years at three mine sites in the jarrah forest in south-western Australia.

Methods
We surveyed 232 plots in revegetation to document (1) structural and floristic variation in vegetation across mine sites and revegetation ages, (2) differences in cockatoo feeding activity across mine sites and revegetation ages on the basis of feeding residues and (3) any edge effect reflecting preferential use of vegetation at the interior or exterior of mine pits. We also documented the frequency of occurrence of cockatoo food plants and feeding residues in 480 plots in unmined forest to compare with revegetated areas.

Key results
Marri (Corymbia calophylla) and jarrah were commonly consumed in unmined forest and Banksia and Hakea species were also fed on to a lesser extent. Revegetated mine pits provided food within 4 years and continued to do so up until the oldest plots studied (23 years). The relative importance of food plants shifted from proteaceous species in young revegetation to myrtaceous species in intermediate to older revegetation. However, extent of feeding on myrtaceous species in older revegetation did not equate to feeding rates in unmined forest, with lower frequencies recorded in revegetation.

Conclusions
Black cockatoos fed in revegetation at all three mine sites, despite variations in vegetation age, structure and floristics. Feeding on proteaceous and myrtaceous food plants occurred within 4 and 7 years of revegetation being established, respectively, indicating that some food resources are restored quickly after mining disturbance of the jarrah forest.

Implications
Our results emphasise the importance of monitoring fauna recolonisation over appropriate time scales, to understand how successional processes in revegetation influence fauna population persistence in production landscapes.

Abstract ContextRecent global concern over invertebrate declines has drawn attention to the causes and consequences of this loss of biodiversity. Feral cats, Felis catus, pose a major threat to many vertebrate species in Australia, but their effect on invertebrates has not previously been assessed. AimsThe objectives of our study were to (1) assess the frequency of occurrence (FOO) of invertebrates in feral cat diets across Australia and the environmental and geographic factors associated with this variation, (2) estimate the number of invertebrates consumed by feral cats annually and the spatial variation of this consumption, and (3) interpret the conservation implications of these results. MethodsFrom 87 Australian cat-diet studies, we modelled the factors associated with variation in invertebrate FOO in feral cat-diet samples. We used these modelled relationships to predict the number of invertebrates consumed by feral cats in largely natural and highly modified environments. Key resultsIn largely natural environments, the mean invertebrate FOO in feral cat dietary samples was 39% (95% CI: 31–43.5%), with Orthoptera being the most frequently recorded order, at 30.3% (95% CI: 21.2–38.3%). The highest invertebrate FOO occurred in lower-rainfall areas with a lower mean annual temperature, and in areas of greater tree cover. Mean annual invertebrate consumption by feral cats in largely natural environments was estimated to be 769 million individuals (95% CI: 422–1763 million) and in modified environments (with mean FOO of 27.8%) 317 million invertebrates year−1, giving a total estimate of 1086 million invertebrates year−1 consumed by feral cats across the continent. ConclusionsThe number of invertebrates consumed by feral cats in Australia is greater than estimates for vertebrate taxa, although the biomass (and, hence, importance for cat diet) of invertebrates taken would be appreciably less. The impact of predation by cats on invertebrates is difficult to assess because of the lack of invertebrate population and distribution estimates, but cats may pose a threat to some large-bodied narrowly restricted invertebrate species. ImplicationsFurther empirical studies of local and continental invertebrate diversity, distribution and population trends are required to adequately contextualise the conservation threat posed by feral cats to invertebrates across Australia.

Context Invasive species are a major cause of biodiversity loss across much of the world, and a key threat to Australia's diverse reptile fauna. There has been no previous comprehensive analysis of the potential impact of the introduced European red fox, Vulpes vulpes, on Australian reptiles. Aims We seek to provide an inventory of all Australian reptile species known to be consumed by the fox, and identify characteristics of squamate species associated with such predation. We also compare these tallies and characteristics with reptile species known to be consumed by the domestic cat, Felis catus, to examine whether predation by these two introduced species is compounded (i.e. affecting much the same set of species) or complementary (affecting different groups of species). Methods We collated records of Australian reptiles consumed by foxes in Australia, with most records deriving from fox dietary studies (tallying >35 000 samples). We modelled presence or absence of fox predation records against a set of biological and other traits, and population trends, for squamate species. Key results In total, 108 reptile species (~11% of Australia's terrestrial reptile fauna) have been recorded as consumed by foxes, fewer than that reported for cats (263 species). Eighty-six species have been reported to be eaten by both predators. More Australian turtle species have been reported as consumed by foxes than by cats, including many that suffer high levels of predation on egg clutches. Twenty threatened reptile species have been reported as consumed by foxes, and 15 by cats. Squamate species consumed by foxes are more likely to be undergoing population decline than those not known to be consumed by foxes. The likelihood of predation by foxes increased with squamate species' adult body mass, in contrast to the relationship for predation by cats, which peaked at ~217 g. Foxes, but not cats, were also less likely to consume venomous snakes. Conclusions The two introduced, and now widespread, predators have both compounding and complementary impacts on the Australian reptile fauna. Implications Enhanced and integrated management of the two introduced predators is likely to provide substantial conservation benefits to much of the Australian reptile fauna.

Motivation: The BioTIME database contains raw data on species identities and abundances in ecological assemblages through time. These data enable users to calculate temporal trends in biodiversity within and amongst assemblages using a broad range of metrics. BioTIME is being developed as a community-led open-source database of biodiversity time series. Our goal is to accelerate and facilitate quantitative analysis of temporal patterns of biodiversity in the Anthropocene. Main types of variables included: The database contains 8,777,413 species abundance records, from assemblages consistently sampled for a minimum of 2 years, which need not necessarily be consecutive. In addition, the database contains metadata relating to sampling methodology and contextual information about each record. Spatial location and grain: BioTIME is a global database of 547,161 unique sampling locations spanning the marine, freshwater and terrestrial realms. Grain size varies across datasets from 0.0000000158 km(2) (158 cm(2)) to 100 km(2) (1,000,000,000,000 cm(2)). Time period and grainBio: TIME records span from 1874 to 2016. The minimal temporal grain across all datasets in BioTIME is a year. Major taxa and level of measurement: BioTIME includes data from 44,440 species across the plant and animal kingdoms, ranging from plants, plankton and terrestrial invertebrates to small and large vertebrates. ; European Research Council; EU [AdG-250189, PoC-727440, ERC-SyG-2013-610028]; Natural Environmental Research Council [NE/L002531/1]; National Science Foundation [DEB-1237733, DEB-1456729, 9714103, 0632263, 0856516, 1432277, DEB 9705814, BSR-8811902, DEB 9411973, DEB 0080538, DEB 0218039, DEB 0620910, DEB 0963447, DEB-1546686, DEB-129764]; National Science Foundation (LTER) [DEB-1235828, DEB-1440297, DBI-0620409, DEB-9910514, DEB-1237517, OCE-0417412, OCE-1026851, OCE-1236905, OCE-1637396, DEB 1440409, DEB-0832652, DEB-0936498, DEB-0620652, DEB-1234162, DEB-0823293, OCE-9982105, OCE-0620276, OCE-1232779]; Fundacao para a Ciencia e Tecnologia [POPH/FSE SFRH/BD/90469/2012, SFRH/BD/84030/2012, PTDC/BIA-BIC/111184/2009]; Ciencia sem Fronteiras/CAPES [1091/13-1]; Instituto Milenio de Oceanografia [IC120019]; ARC Centre of Excellence [CE0561432]; NSERC Canada; CONICYT/FONDECYT [1160026, ICM PO5-002, 11110351, 1151094, 1070808, 1130511]; RSF [14-50-00029]; Gordon and Betty Moore Foundation [GBMF4563]; Catalan Government; Marie Curie Individual Fellowship [QLK5-CT2002-51518, MERG-CT-2004-022065]; CNPq [306170/2015-9, 475434/2010-2, 403809/2012-6, 561897/2010, 306595-2014-1]; FAPESP (Sao Paulo Research Foundation) [2015/10714-6, 2015/06743-0, 2008/10049-9, 2013/50714-0, 1999/09635-0 e 2013/50718-5]; EU CLIMOOR [ENV4-CT97-0694]; VULCAN [EVK2-CT2000-00094]; DFG [120/10-2]; Polar Continental Shelf Program; CENPES - PETROBRAS; FAPERJ [E-26/110.114/ 2013]; German Academic Exchange Service; New Zealand Department of Conservation; Wellcome Trust [105621/Z/14/Z]; Smithsonian Atherton Seidell Fund; Botanic Gardens and Parks Authority; Research Council of Norway; Conselleria de Innovacio, Hisenda i Economia; Yukon Government Herschel Island-Qikiqtaruk Territorial Park; UK Natural Environment Research Council ShrubTundra Grant [NE/M016323/1]; IPY; Memorial University; ArcticNet; Netherlands Organization for Scientific Research in the Tropics NWO [W84-194]; Ciencias sem Fronteiras and Coordenacao de Pessoal de Nivel Superior (CAPES, Brazil) [1091/13-1]; U.S. Fish and Wildlife Service/State Wildlife federal grant [T-15]; Australian Research Council Centre of Excellence for Coral Reef Studies [CE140100020]; Australian Research Council Future Fellowship [FT110100609]; University of Lodz; NSF DEB [1353139]; Catalan Government fellowships (DURSI) [1998FI-00596, 2001BEAI200208]; MECD Post-doctoral fellowship [EX2002-0022]; FONDECYT [1141037]; FONDAP [15150003]; [SFRH/BD/80488/2011]; [PD/BD/52597/2014]; [REN2000-0278/CCI]; [REN2001-003/GLO]; [CGL2016-79835-P]; [AGAUR SGR-2014453]; [SGR-2017-1005]; [FCT - SFRH / BPD / 82259 / 2011]; [OCE 95-21184]; [OCE-0099226]; [OCE 03-5234]; [OCE-0623874]; [OCE-1031061]; [OCE-1336206]; [DEB-1354563]; [OPP-1440435] ; 12 month embargo; published online: 24 July 2018 ; This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.

European Research Council and EU, Grant/Award Number: AdG‐250189, PoC‐727440 and ERC‐SyG‐2013‐610028; Natural Environmental Research Council, Grant/Award Number: NE/L002531/1; National Science Foundation, Grant/Award Number: DEB‐1237733, DEB‐1456729, 9714103, 0632263, 0856516, 1432277, DEB‐9705814, BSR‐8811902, DEB 9411973, DEB 0080538, DEB 0218039, DEB 0620910, DEB 0963447, DEB‐1546686, DEB‐129764, OCE 95‐21184, OCE‐ 0099226, OCE 03‐52343, OCE‐0623874, OCE‐1031061, OCE‐1336206 and DEB‐1354563; National Science Foundation (LTER) , Grant/Award Number: DEB‐1235828, DEB‐1440297, DBI‐0620409, DEB‐9910514, DEB‐1237517, OCE‐0417412, OCE‐1026851, OCE‐1236905, OCE‐1637396, DEB 1440409, DEB‐0832652, DEB‐0936498, DEB‐0620652, DEB‐1234162 and DEB‐0823293; Fundação para a Ciência e Tecnologia, Grant/Award Number: POPH/FSE SFRH/BD/90469/2012, SFRH/BD/84030/2012, PTDC/BIA‐BIC/111184/2009; SFRH/BD/80488/2011 and PD/BD/52597/2014; Ciência sem Fronteiras/CAPES, Grant/Award Number: 1091/13‐1; Instituto Milenio de Oceanografía, Grant/Award Number: IC120019; ARC Centre of Excellence, Grant/Award Number: CE0561432; NSERC Canada; CONICYT/FONDECYT, Grant/Award Number: 1160026, ICM PO5‐002, CONICYT/FONDECYT, 11110351, 1151094, 1070808 and 1130511; RSF, Grant/Award Number: 14‐50‐00029; Gordon and Betty Moore Foundation, Grant/Award Number: GBMF4563; Catalan Government; Marie Curie Individual Fellowship, Grant/Award Number: QLK5‐CT2002‐51518 and MERG‐CT‐2004‐022065; CNPq, Grant/Award Number: 306170/2015‐9, 475434/2010‐2, 403809/2012‐6 and 561897/2010; FAPESP (São Paulo Research Foundation), Grant/Award Number: 2015/10714‐6, 2015/06743‐0, 2008/10049‐9, 2013/50714‐0 and 1999/09635‐0 e 2013/50718‐5; EU CLIMOOR, Grant/Award Number: ENV4‐CT97‐0694; VULCAN, Grant/Award Number: EVK2‐CT‐2000‐00094; Spanish, Grant/Award Number: REN2000‐0278/CCI, REN2001‐003/GLO and CGL2016‐79835‐P; Catalan, Grant/Award Number: AGAUR SGR‐2014‐453 and SGR‐2017‐1005; DFG, Grant/Award Number: 120/10‐2; Polar Continental Shelf Program; CENPES – PETROBRAS; FAPERJ, Grant/Award Number: E‐26/110.114/2013; German Academic Exchange Service; sDiv; iDiv; New Zealand Department of Conservation; Wellcome Trust, Grant/Award Number: 105621/Z/14/Z; Smithsonian Atherton Seidell Fund; Botanic Gardens and Parks Authority; Research Council of Norway; Conselleria de Innovació, Hisenda i Economia; Yukon Government Herschel Island‐Qikiqtaruk Territorial Park; UK Natural Environment Research Council ShrubTundra Grant, Grant/Award Number: NE/M016323/1; IPY; Memorial University; ArcticNet. DOI:10.13039/50110000027. Netherlands Organization for Scientific Research in the Tropics NWO, grant W84‐194. Ciências sem Fronteiras and Coordenação de Pessoal de Nível Superior (CAPES, Brazil), Grant/Award Number: 1091/13‐1. National Science foundation (LTER), Award Number: OCE‐9982105, OCE‐0620276, OCE‐1232779. FCT ‐ SFRH / BPD / 82259 / 2011. U.S. Fish and Wildlife Service/State Wildlife federal grant number T‐15. Australian Research Council Centre of Excellence for Coral Reef Studies (CE140100020). Australian Research Council Future Fellowship FT110100609. M.B., A.J., K.P., J.S. received financial support from internal funds of University of Lódź. NSF DEB 1353139. Catalan Government fellowships (DURSI): 1998FI‐00596, 2001BEAI200208, MECD Post‐doctoral fellowship EX2002‐0022. National Science Foundation Award OPP‐1440435. FONDECYT 1141037 and FONDAP 15150003 (IDEAL). CNPq Grant 306595‐2014‐1 ; Peer reviewed ; Publisher PDF