Mudança climática pode alterar relações simbióticas entre microrganismos e árvores

24 de maio de 2019

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Elton Alisson  |  Agência FAPESP – No solo das florestas, algumas espécies de fungos e de bactérias se associam a raízes de árvores para crescerem juntas, de modo a obterem benefícios mútuos. Os microrganismos auxiliam as plantas a absorver água e nutrientes do solo, a sequestrar carbono e a resistir aos efeitos das mudanças climáticas. Em troca, recebem carboidratos essenciais para seu desenvolvimento, produzidos pelas plantas durante a fotossíntese.

Uma colaboração de mais de 200 cientistas de diversos países, incluindo 13 de diferentes regiões do Brasil, mapeou a distribuição global dessas associações entre organismos de espécies diferentes (simbioses), fundamentais para o funcionamento dos ecossistemas florestais. Com base nesse mapeamento foi possível identificar fatores que determinam onde diferentes tipos de simbioses podem surgir e estimar os impactos das mudanças climáticas nessas relações simbióticas e, consequentemente, no crescimento das árvores nas florestas.

Mapeamento feito por consórcio internacional revela como estão distribuídas no globo essas associações entre espécies fundamentais para os ecossistemas florestais. Estudo foi destaque na capa da Nature

Se as emissões de dióxido de carbono (CO2) continuarem inalteradas até 2070, pode ocorrer uma redução de 10% nas espécies de árvores que se associam a um tipo de fungo encontrado principalmente em regiões mais frias do planeta, estimaram os pesquisadores.

O trabalho, destacado na capa da revista Nature, contou com a participação de Carlos Joly e de Simone Aparecida Vieira, ambos professores da Universidade Estadual de Campinas (Unicamp) e membros da coordenação do Programa de Pesquisas em Caracterização, Conservação, Restauração e Uso Sustentável da Biodiversidade (BIOTA-FAPESP).

“Já se sabia que a associação entre microrganismos e raízes é fundamental para alguns grupos de árvores conseguirem se estabelecer em regiões em que o solo é muito pobre e os nutrientes são liberados lentamente pela decomposição de matéria orgânica. O mapeamento permite entender como essas relações estão distribuídas no planeta e os fatores que as definem”, disse Vieira à Agência FAPESP.

Os pesquisadores se concentraram em mapear três dos tipos mais comuns de simbioses: fungos micorrízicos arbusculares, fungos ectomicorrízicos e bactérias fixadoras de nitrogênios. Cada uma dessas interações engloba milhares de espécies de fungos ou bactérias, que formam parcerias únicas com diferentes espécies de árvores.

Há 30 anos, o botânico inglês David Read, professor da University of Sheffield, da Inglaterra, e pioneiro nas pesquisas sobre simbioses, desenhou mapas de lugares no mundo onde achava que poderiam ser encontrados diferentes fungos simbióticos, com base nos nutrientes que exploram para permitir o crescimento das plantas.

Os fungos ectomicorrízicos, por exemplo, obtêm nitrogênio para as árvores diretamente de matéria orgânica, como folhas em decomposição. Por isso, Read propôs que esses microrganismos seriam mais bem-sucedidos em florestas com climas sazonais, mais frios e secos, onde a decomposição em razão da temperatura e umidade é mais lenta e a serrapilheira – camada de restos de plantas – é abundante.

Os fungos micorrízicos arbusculares, por sua vez, seriam dominantes nas florestas tropicais, nas quais o crescimento das árvores é limitado pelo fósforo do solo e nos quais os climas sazonais quentes e úmidos aumentam a decomposição.

Mais recentemente, um estudo feito por outro grupo de pesquisadores estimou que as bactérias fixadoras de nitrogênio seriam mais abundantes em biomas áridos, com solos alcalinos e altas temperaturas máximas.

Essas hipóteses puderam ser testadas, agora, com a coleta de dados de um grande número de árvores, em diversas partes do planeta, reunidos pela Global Forest Biodiversity Initiative (GFBI) – um consórcio internacional de cientistas florestais.

O consórcio é integrado, além de Joly e Vieira, por Pedro Henrique Santin Brancalion e Ricardo Gomes César, ambos da Universidade de São Paulo (USP), Gabriel Dalla Colletta, da Unicamp, Daniel Piotto, da Universidade Federal do Sul da Bahia (UFSB), André Luis de Gasper, da Universidade Regional de Blumenau (FURB), Jorcely Barroso e Marcos Silveira, da Universidade Federal do Acre (UFAC), Iêda Amaral e Maria Teresa Piedade, do Instituto Nacional de Pesquisas da Amazônia (Inpa), Beatriz Schwantes Marimon, da Universidade do Estado de Mato Grosso (Unemat), e Alexandre Fadigas de Souza, da Universidade Federal do Rio Grande do Norte (UFRN).

Nos últimos anos, os pesquisadores ligados ao GFBI fizeram inventários de mais de 1,1 milhão de parcelas permanentes de florestas, que abrangem 28 mil espécies de árvores, de mais de 70 países, situadas em todos os continentes, à exceção da Antártida.

Os inventários reúnem informações, como a composição do solo, a topografia, a temperatura e a evolução do carbono fixado nessas parcelas permanentes de florestas ao longo de grandes períodos de tempo.

“As parcelas inventariadas por pesquisadores ligados ao BIOTA-FAPESP estão situadas na Mata Atlântica e incluem regiões do litoral norte do Estado de São Paulo, como Caraguatatuba, Picinguaba, Cunha e Santa Virgínia, e Carlos Botelho e Ilha do Cardoso, no litoral sul”, disse Joly. “Também inventariamos um conjunto expressivo de parcelas na Amazônia por meio de projetos em colaboração com outros grupos."

A partir desse conjunto de inventários, os pesquisadores conseguiram estimar a localização de 31 milhões de árvores espalhadas pelo mundo, assim como os fungos ou as bactérias simbióticos associadas a elas. Por meio de um programa de computador (algoritmo), foi possível determinar como diferentes variáveis relacionadas ao clima, química do solo, vegetação e topografia influenciam a prevalência de cada simbiose.

Os resultados das análises sugeriram que variáveis climáticas associadas à decomposição da matéria orgânica, como a temperatura e a umidade, são os principais fatores que influenciam as simbioses de fungos micorrízicos arbusculares e ectomicorrízicos. Já as simbioses de bactérias fixadoras de nitrogênio são provavelmente limitadas pela temperatura e acidez do solo.

“Qualquer mudança que possa ocorrer no clima no hemisfério norte pode deslocar os fungos ectomicorrízicos para outras regiões e ocorrer a perda ou uma diminuição muito grande da densidade dessas relações simbióticas”, disse Vieira.

“Isso pode afetar a ciclagem de nutrientes e, principalmente, a fixação de carbono, que depende dessa associação simbiótica para que a vegetação das florestas possa absorver nutrientes pouco disponíveis ou que não estão na forma de que necessitam”, afirmou.

Efeito das mudanças climáticas

A fim de estimar a vulnerabilidade dos padrões globais de simbiose às mudanças climáticas, os pesquisadores usaram o mapeamento para prever como poderiam mudar até 2070, se as emissões de dióxido de carbono continuarem inalteradas.

As projeções indicaram uma redução de 10% dos fungos ectomicorrízicos e, consequentemente, da abundância de árvores associadas a esses fungos – que correspondem a 60% das árvores.

Os pesquisadores alertam que essa perda poderia levar a mais CO2 na atmosfera, porque esses fungos tendem a aumentar a quantidade de carbono armazenado no solo.

“O CO2 limita a fotossíntese e, em princípio, seu aumento na atmosfera pode ter efeito fertilizante. As espécies de plantas que crescem mais rápido talvez consigam aproveitar melhor esse aumento da disponibilidade de CO2 na atmosfera do que aquelas que crescem mais lentamente. Dessa forma, poderíamos ter uma seleção de espécies. Mas ainda não há resposta para essa pergunta”, disse Joly.

Outra pergunta que os pesquisadores têm buscado responder é qual seria o impacto da interação do aumento da disponibilidade de CO2 na atmosfera com a elevação da temperatura do planeta no desenvolvimento das plantas. Com o aumento da temperatura as plantas terão que gastar mais recursos com a respiração, que aumentará mais do que a taxa de fotossíntese. O saldo desse balanço no crescimento da vegetação ainda não está claro, afirmam os pesquisadores.

“Essas questões, que dizem respeito às florestas tropicais, ainda estão em aberto. O monitoramento contínuo de parcelas permanentes de florestas vai nos ajudar a respondê-las”, disse Joly.

O artigo Climatic controls of decomposition drive the global biogeography of forest-tree symbioses (DOI: 10.1038/s41586-019-1128-0), de B. S. Steidinger, T. W. Crowther, J. Liang, M. E. Van Nuland, G. D. A. Werner, P. B. Reich, G. Nabuurs, S. de-Miguel, M. Zhou, N. Picard, B. Herault, X. Zhao, C. Zhang, D. Routh, GFBI consortium e K. G. Peay, pode ser lido na revista Nature em www.nature.com/articles/s41586-019-1128-0.

Reconstrução de crânios em 3D esclarece evolução de macacos do Novo Mundo

23 de maio de 2019

Peter Moon  |  Agência FAPESP – Crânios de duas espécies de primatas já extintas – Caipora bambuiorum e Cartelles coimbrafilhoi – foram examinados por tomografia computadorizada e reconstruídos em imagens tridimensionais por um grupo que reúne cientistas de diversos países. Foram usados no trabalho fósseis encontrados há quase 30 anos no fundo de uma gruta da Caatinga, no norte da Bahia.

Análise de fósseis de duas espécies extintas, com uso de tomografia computadorizada, indica adaptações evolutivas e relações com os atuais bugios, macacos-aranha e monos-carvoeiros (imagem: André Menezes Strauss) 

 

As imagens foram comparadas com as de outros 14 primatas do Novo Mundo ainda viventes, o que permitiu descobrir adaptações e inferir relações até então desconhecidas daquelas duas espécies extintas com os macacos que atualmente habitam as matas das Américas do Sul e Central, além do Caribe.

“Pela primeira vez, foi conduzido um estudo da morfologia endocraniana [formato do interior de um crânio, considerado um reflexo direto da forma externa do cérebro] de platirrinos fósseis, os primatas do Novo Mundo”, disse André Menezes Strauss, professor do Museu de Arqueologia e Etnologia (MAE) e pesquisador colaborador do Laboratório de Arqueologia e Antropologia Ambiental e Evolutiva (LAAAE) do Instituto de Biociências (IB) da Universidade de São Paulo (USP).

Os resultados da pesquisa, apoiada pela FAPESP, foram divulgados em artigo publicado no American Journal of Physical Anthropology. 

O trabalho descreve a variação na forma do crânio e do endocrânio de 14 espécies de bugios (gênero Alouatta), macacos-aranha (Ateles), monos-carvoeiros (Brachyteles) e macacos-barrigudos (Lagothrix), além dos outros dois táxons extintos, Cartelles e Caipora. Das cerca de 350 espécies de primatas viventes em todo o mundo, os platirrinos formam o maior contingente, com pouco mais de 200 espécies.

O artigo é resultado de uma pesquisa liderada pelo antropólogo argentino Ivan Perez, do Museu de La Plata, da qual participou Cástor Cartelle (que dá nome à espécie Cartelles coimbrafilhoi), da Pontifícia Universidade Católica de Minas Gerais (PUC-MG), além de pesquisadores da USP, da Universidade Estadual de Campinas (Unicamp) e de instituições da Alemanha, Bélgica, Estados Unidos e França.

Além da FAPESP, apoiaram a investigação o Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), o Fondo para la Investigación Científica y Tecnológica (FonCyT) e o Consejo Nacional de Investigaciones Científicas y Técnicas (Conicet). 

Os fósseis de Cartelles e Caipora estão depositados no Museu de História Natural da PUC-MG, em Belo Horizonte. Os 14 crânios de platirrinos viventes saíram das coleções do Museu de La Plata, do Museu Nacional (Rio de Janeiro), do Museu Argentino de Ciências Naturais (Buenos Aires) e do Museu Nacional de História Natural (Washington).

“Os 16 espécimes foram digitalizados usando um scanner médico de tomografia computadorizada. Um modelo virtual tridimensional do endocrânio foi gerado para cada amostra e os modelos de superfície 3D dos crânios foram extraídos dos dados tomográficos”, explicou Strauss à Agência FAPESP.

Como os espécimes fósseis (Cartelles e Caipora) apresentam alguns danos, particularmente na região dos arcos zigomáticos – que formam a proeminência da bochecha, parte da parede lateral e assoalho da órbita e partes das fossas temporal e infratemporal –, duas estratégias foram adotadas para poder analisá-los.

Segundo Strauss, no caso de Caipora, o arco zigomático direito está ausente, mas o lado esquerdo está intacto. “Assim, no modelo 3D, refletimos o lado não danificado, aproveitando a simetria bilateral, para o lado danificado. Dessa forma, obtivemos um espécime completo, virtualmente reparado”, disse.

“No caso de Cartelles, dado que ambos os lados estão ausentes, recorremos a um método de imputação para estimar a posição das partes em falta”, disse.

Perez digitalizou 26 marcos anatômicos e 373 marcos secundários ao longo das curvas e superfícies de cada endocrânio, bem como 64 referências anatômicas e 196 marcos secundários em cada crânio.

“Esses dados serviram de base a análises multivariadas para a comparação de todos os 16 espécimes nas suas mais variadas características, buscando similaridades e diferenças que indicassem padrões morfológicos [portanto, padrões adaptativos] entre todos eles”, disse Strauss.

Em outras palavras, uma vez que entre os espécimes viventes de macacos atelídeos – os maiores primatas do Novo Mundo, que hoje congrega bugios, monos-carvoeiros, macacos-aranha e macacos-barrigudos – havia crânios de bugios, de macacos-aranha, de monos-carvoeiros e de macacos-barrigudos, a comparação dos dados de todos esses com os de Cartelles e de Caipora serviu para indicar a qual ou quais daqueles gêneros da família dos atelídeos os dois fósseis seriam mais assemelhados e, portanto, mais aparentados.

Crânios em 3D

Strauss conta que os dados de Caipora se agruparam claramente próximos aos dados de macacos-aranha, monos-carvoeiros e macacos-barrigudos, que são em seu conjunto distanciados dos dados dos bugios.

Ou seja, os bugios possuem um ancestral comum com os outros gêneros de atelídeos e com Caipora, que é mais antigo do que o ancestral comum de macacos-aranha, monos-carvoeiros e macacos-barrigudos.

“Agora, quando se analisa a posição de Caipora unicamente com relação aos macacos-aranha, monos-carvoeiros e macacos-barrigudos, verifica-se que o fóssil se posiciona claramente próximo aos monos-carvoeiros”, disse Strauss.

“A hipótese inicial feita por Cástor Cartelle há 20 anos de que Caipora seria semelhante a um macaco-aranha gigante não se verifica, pois os nossos dados indicam que esse macaco extinto se assemelharia, na verdade, muito mais a um mono-carvoeiro ‘gigante’”, disse Strauss.

No caso do fóssil de Cartelles, os resultados das análises multivariadas revelaram surpresas. Em primeiro lugar, os dados não se agruparam claramente a nenhum dos quatro gêneros viventes de atelídeos, mas se posicionaram consistentemente preenchendo o espaço morfológico, antes vazio, que separa os bugios de macacos-aranha, monos-carvoeiros e macacos-barrigudos.

“Em relação às espécies fósseis, mostramos que a espécie Caipora bambuiorum se posiciona dentro da faixa observada de variação entre os monos-carvoeiros. Já Cartelles coimbrafilhoi ocupa uma região de formato endocranial que não se sobrepõe com a faixa de variação observada em nenhum dos atelídeos viventes. Dos quatro gêneros, Cartelles está mais próximo dos bugios [Alouatta] no que diz respeito ao espaço do interior do crânio [endocrânio], porém mais próximo dos macacos-barrigudos [Lagothrix] no que diz respeito ao formato de seu crânio”, disse Strauss.

“Verificamos que, quando removido o fator tamanho, Cartelles era um primata com características intermediárias entre bugios, de um lado, e macacos-aranha, monos-carvoeiros e macacos-barrigudos, de outro”, disse Strauss.

“Nossos resultados sugerem que dentro do clado atelídeo, a extinção de Caipora bambuiorum e de Cartelles coimbrafilhoi levou a uma perda de significativa variação biológica que não poderia ser antecipada sem a descoberta desses fósseis”, concluíram os autores no artigo.

Peter Lund e Cástor Cartelle

Toda a linhagem dos primatas do Novo Mundo, espalhados desde o norte da Argentina até o México e o Caribe, descende de um único bando de fundadores, formado por pequenos macacos africanos que, há cerca de 45 milhões de anos, teriam feito a travessia do antigo Atlântico Sul (que tinha um terço da extensão atual) em balsas formadas por vegetação flutuante.

A pesquisa de macacos fósseis nas Américas começou no Brasil há 183 anos, quando o naturalista dinamarquês Peter Wilhelm Lund, em 1836, descobriu em uma caverna da região de Lagoa Santa (MG) os restos de um primata de dimensões muito maiores do que todos os platirrinos viventes.

Àquele macaco extinto há mais de 10 mil anos Lund deu o nome de Protopithecus brasiliensis, o “macaco ancestral brasileiro”, um parente próximo – porém com o dobro do tamanho – do mono-carvoeiro, o maior platirrino vivente.

Desde então, foram sendo achados fósseis (quase sempre dentes isolados e fragmentos de mandíbulas, porém pouquíssimos crânios) de platirrinos muito mais antigos, extintos há milhões ou dezenas de milhões de anos, na Patagônia argentina, no alto da cordilheira chilena, no altiplano boliviano, na selva amazônica peruana e em diversas ilhas caribenhas.

Apesar das mais de 30 espécies de platirrinos extintas descritas, Protopithecus nunca perdeu seu posto de gigante, muito maior que todos os demais.

Existem apenas duas exceções. Em 1992, foram encontrados em uma câmara recuada no interior da Toca da Boa Vista (BA), a maior caverna brasileira, os esqueletos quase completos de dois outros platirrinos gigantes, que viveram no final da Idade do Gelo, portanto há mais de 10 mil anos.

Ambos os fósseis foram estudados na PUC-MG por Cartelle, que descreveu um dos indivíduos como um macaco-aranha gigante de uma nova espécie, Caipora bambuiorum. 

No caso do segundo indivíduo, Cartelle identificou-o como sendo membro da espécie Protopithecus descrita por Lund.

Caipora e Protopithecus pertenciam à família dos atelídeos. O maior de todos é o mono-carvoeiro, que chega a 15 quilos, seguido pelos bugios, com no máximo 10 quilos. Caipora e Protopithecus, no entanto, eram 60% maiores. Em vida, deveriam superar os 25 quilos. Ou seja, tinham o tamanho de um babuíno africano.

Em 2013, graças ao trabalho de antropólogos norte-americanos, veio a se saber que aquele indivíduo achado na Toca da Boa Vista e identificado originalmente como Protopithecus pertencia, na verdade, a uma nova espécie: Cartelles coimbrafilhoi, nome que homenageia Cartelle.

Os pesquisadores identificaram Cartelles como aparentado dos bugios (gênero Alouatta), e não mais do mono-carvoeiro (Brachyteles), como havia sido proposto por Cartelle.

Agora, em 2019, o emprego de novas técnicas de investigação científica forneceu uma nova interpretação para os fósseis de Caipora e, especialmente, de Cartelles.

A construção de um modelo tridimensional do crânio de Cartelles permitiu concluir que o animal tinha adaptações morfológicas cranianas diferentes de qualquer outro primata do Novo Mundo, vivente ou extinto.

“Hoje, graças ao uso da tomografia computadorizada, Cartelles pode contar com uma nova análise, com novas conclusões. Nem tanto bugio nem tanto mono-carvoeiro, acredita-se agora que Cartelles, aquele macaco gigante do Pleistoceno encontrado na Bahia, possuía características cranianas únicas, que não são mais encontradas em nenhum outro primata do Novo Mundo”, disse Strauss.

O Protopithecus descrito por Lund não fez parte do estudo de Aristide, Strauss e colegas pela ausência de um crânio que pudesse ser tomografado. Os fósseis já encontrados apresentam elevado grau de fragmentação.

O artigo Cranial and endocranial diversity in extant and fossil atelids (Platyrrhini: Atelidae): A geometric morphometric study (doi: 10.1002/ajpa.23837), de Leandro Aristide, André Strauss, Lauren B. Halenar-Price, Emmanuel Gilissen, Francisco W. Cruz, Castor Cartelle, Alfred L. Rosenberger, Ricardo T. Lopes, Sergio F. dos Reis e S. Ivan Perez, está publicado em https://onlinelibrary.wiley.com/doi/full/10.1002/ajpa.23837.

Paleobotanist Scott Wing stands in wintry Wyoming badlands, where alligators swam 56 million years ago.

IRA BLOCK

A 500-million-year survey of Earth's climate reveals dire warning for humanity

Uma pesquisa de 500 milhões de anos do clima da Terra revela um aviso terrível para a humanidade

By Paul VoosenMay. 22, 2019 , 2:25 PM

When it opens next month, the revamped fossil hall of the Smithsonian Institution's National Museum of Natural History in Washington, D.C., will be more than a vault of dinosaur bones. It will show how Earth's climate has shifted over the eons, driving radical changes in life, and how, in the modern age, one form of life—humans—is, in turn, transforming the climate.

To tell that story, Scott Wing and Brian Huber, a paleobotanist and paleontologist, respectively, at the museum, wanted to chart swings in Earth's average surface temperature over the past 500 million years or so. The two researchers also thought a temperature curve could counter climate contrarians' claim that global warming is no concern because Earth was much hotter millions of years ago. Wing and Huber wanted to show the reality of ancient temperature extremes—and how rapid shifts between them have led to mass extinctions. Abrupt climate changes, Wing says, "have catastrophic side effects that are really hard to adapt to."

But actually making the chart was unexpectedly challenging—and triggered a major effort to reconstruct the record. Although far from complete, the research is already showing that some ancient climates were even more extreme than was thought.

Ancient glaciations are easy enough to trace, as are hothouse periods when palms grew near the poles. But otherwise little is certain, especially early in the Phanerozoic, which spans the past 541 million years. Paleoclimate scientists study their own slices of time and use their own specialized temperature proxies—leaf shape, say, or growth bands in fossilized corals—which often conflict. "We don't talk to each other all that much," says Dana Royer, a paleoclimatologist at Wesleyan University in Middletown, Connecticut. So at a meeting last year, Wing and Huber assembled a loose-knit collaboration, dubbed Phantastic, dedicated to putting together a rigorous record. "Most people came away quite inspired to do something about this," says Dan Lunt, a paleoclimate modeler at the University of Bristol in the United Kingdom.

The value of a deep-time temperature curve extends beyond the exhibit. Similar curves exist for atmospheric carbon dioxide (CO₂). Combine the two and you can see how much warming CO₂ caused in the past, says Jessica Tierney, a paleoclimatologist at the University of Arizona in Tucson. Because the latest climate models seem to forecast more warming than earlier ones, "using paleoclimate to constrain the models is becoming much more important," she says. "We feel we have to step up."

Fever line

A preliminary global temperature curve shows that marine life diversified in extreme heat (1) before land-based plants absorbed carbon dioxide (CO₂) and polar ice caps formed (2). Volcanoes and erosion swung CO₂ levels up and down (3), but mammals evolved in a warm period (4). Now, humans are rapidly warming the climate again (5).

500 Millions of years ago 10˚ 15.5˚ 21.1˚ 26.7˚ 32.2˚C 50˚ 60˚ 70˚ 80˚ 90˚F 450 400 350 300 250 200 150 100 50 Today World without polar caps World with polar caps 2 3 5 4

SMITHSONIAN INSTITUTION NATIONAL MUSEUM OF NATURAL HISTORY, ADAPTED BY N. DESAI/SCIENCE

But ancient global temperatures are elusive because they varied with location and season, and because the gauges drop away as you move deeper in time: Tree rings go back only thousands of years and ice cores only a million years or so. Still, oxygen isotopes in tiny fossilized shells on the ocean floor give a fairly reliable longer-term record. Because water molecules with lighter oxygen variants evaporate faster and end up locked in ice sheets, the ratio of light to heavy isotopes in the fossils indicates the volume of global ice, a rough guide to temperatures.

However, ocean floor older than 100 million years or so is scarce, devoured by the constant churn of plate tectonics. To go deeper in time, Ethan Grossman, a geochemist at Texas A&M University in College Station, looks for marine fossils found on land—mostly teeth and extinct bivalves called brachiopods. They tend to be from the shallow, isolated seas that formed inside ancient supercontinents. To glean temperatures from those fossils, scientists have to assume those seas had a balance of oxygen isotopes similar to the ocean today.

Este "problema da água" tem décadas. Mas cientistas em Phantastic estão atacando-o com um segundo termômetro, baseado em uma nova técnica, chamada isótopos aglomerados, que mede a abundância de dois ou mais isótopos raros. Usando espectrômetros de massa sensíveis, eles analisam as cascas fósseis de moléculas de carbonato que contêm um isótopo pesado de oxigênio ligado a um carbono pesado, que se forma mais frequentemente a temperaturas mais baixas. Os resultados serão enganosos se o fóssil tiver sido exposto ao calor e à pressão durante o seu enterro, mas os pesquisadores aprenderam como identificar espécimes alterados. "Nós nos mudamos para o lugar onde podemos aplicá-lo", diz Kristin Bergmann, geobióloga do Instituto de Tecnologia de Massachusetts, em Cambridge, que está usando isótopos agregados para preparar um registro de temperatura dos últimos bilhões de anos.

In collaboration with Gregory Henkes, a geochemist at the State University of New York in Stony Brook, and others, Grossman has gone through his samples, tossing out those that show signs of alteration, and analyzed their clumped isotopes. The results match his existing oxygen-isotope measures, and they tell a startling story, he and Henkes reported last year in Earth & Planetary Science Letters. Some 450 million years ago, ocean waters averaged 35°C to 40°C, more than 20°C warmer than today. Yet marine life thrived, even diversified. "It's unsettling for the biologists, these warm temperatures we're proposing," Grossman says. "These are extreme for modern organisms."

To turn such data into a global temperature curve, researchers need to fill gaps in geography and time. One Phantastic collaborator, Christopher Scotese, a geologist at Northwestern University in Evanston, Illinois, has come up with a simple way to spread limited data into a global picture. He uses the presence of polar ice caps to indicate whether the world had a steep temperature differential between the equator and its poles.

Other collaborators are using the sparse data to calibrate computer simulations of the ancient climate, the way weather models use satellite data as a reality check. Lunt and Paul Valdes, also at Bristol, are ground-truthing a suite of several hundred paleoclimate simulations. They've been able to extrapolate temperatures across the planet for broad stretches of the Phanerozoic.

Although Wing and Huber are pleased with the work they've seeded, they also ran out of time. The temperature curve they're presenting at the museum opening is a beta, Wing says. "It's sort of jamming together different kinds of observations, different kinds of models, different kinds of procedures, and probably different assumptions." The plan is to replace it once the Phantastic team's efforts reach maturity. But even the draft version should open eyes, Grossman says. "This kind of work gives people a sense of how easy it is to tip into a warm period. Because the world has been warm."

Posted in:

• Climate

doi:10.1126/science.aay1323

Synchrotron x-ray scans of a 3-million-year-old mouse fossil reveal a chemical trace of the pigment pheomelanin (bright yellow here).

University of Manchester

Este rato de 3 milhões de anos apenas deu aos cientistas a chave para decodificar antigos pigmentos vermelhos

By Gretchen VogelMay. 21, 2019 , 5:00 AM

Descobrir as cores dos animais fossilizados costumava ser uma adivinhação completa - mesmo nas raras descobertas contendo pedaços de penas, escamas ou pelos, os matizes originais em tais tecidos moles costumam ter desaparecido há muito tempo. Agora, pela primeira vez, os pesquisadores conseguiram identificar a assinatura química do pigmento que dá cor vermelha aos cabelos no fóssil de um rato antigo - usando uma nova técnica que deixa intactos os espécimes fósseis preciosos.

“The mouse fossil, it looks nice. It’s a beautiful specimen. But then you scan it, and it’s this eureka moment,” says Roy Wogelius, a geochemist at the University of Manchester in the United Kingdom, who with his colleagues developed the technique.

Using a variety of techniques, scientists have been able to gather hints about the colors of fossils including dinosaur feathers and dinosaur eggs. A decade ago, scientists used high-energy synchrotron x-rays to identify the key chemical signatures of a pigment called eumelanin, which colors skin, hair, and other tissues black, brown, and gray. But its sister pigment called pheomelanin, which gives skin and hair a pink or red hue, has been tougher to nail down.

Parte do problema, diz Wogelius, era que relativamente pouco se sabia sobre a química do pigmento nos tecidos modernos. Em trabalhos publicados em 2016, ele e seus colegas analisaram cuidadosamente os diferentes traços de metais em pigmentos de penas modernas e descobriram que, enquanto a eumelanina contém cobre, a feomelanina contém enxofre e zinco. Eles se perguntaram se traçar esses metais poderia permitir que eles também encontrassem sinais do pigmento avermelhado nos fósseis.

The mouse Apodemus atavus lived 3 million years ago in what is now central Germany.

University of Manchester

Para testar a ideia, os cientistas analisaram dois fósseis excepcionais - com tecidos moles e cabelos ainda visíveis - de um rato extinto chamado Apodemus atavus que viveu há 3 milhões de anos no que hoje é a Alemanha. Os parentes próximos das espécies atualmente vivos, como o camundongo europeu, têm pelos avermelhados, então os pesquisadores pensaram que o rato fóssil poderia ter coloração semelhante. Com certeza, quando examinaram os fósseis de ratos, encontraram a característica sobreposição de enxofre e zinco em regiões onde o cabelo era visível no fóssil. Eles relatam sua descoberta hoje em Nature Communications.

Now that scientists know what to look for, Wogelius says, he’s confident the pheomelanin signature will be detectable in much older fossils. The new data support the team’s previous claim of evidence for pheomelanin in a 30-million-year-old fossil tadpole. “I’m certain we can go back 30 million years, and probably even longer than that.”

The technique is “a very elegant method for analyzing the whole fossil in a nondestructive way,” says Jasmina Weimann, a molecular paleobiologist at Yale University. “It’s very cool.”

Other chemical analysis methods require researchers to take tiny samples from fossils. Not only does that damage part of the fossil, it also means the full picture is still guesswork. “If you took a square-millimeter sample of zebra skin, you might be able to tell if the sample was black or white, but you wouldn’t understand what a zebra looks like,” Wogelius says.

Weimann hopes similar techniques might allow researchers to identify not only pigments, but also other chemical signatures, for example of proteins specific to certain tissues.

Posted in:

• Plants & Animals

doi:10.1126/science.aay1066

Early fungi from the Proterozoic era in Arctic Canada

• Corentin C. Loron,
• Camille François,
• Robert H. Rainbird,
• Elizabeth C. Turner,
• Stephan Borensztajn &
• Emmanuelle J. Javaux 

Nature (2019) | Download Citation

Abstract

Os fungos são componentes cruciais dos ecossistemas modernos. Eles podem ter tido um papel importante na colonização de terras por eucariotos e na aparência e sucesso de plantas terrestres e metazoários1,2,3.

No entanto, os fósseis que podem ser inequivocamente identificados como fungos estão ausentes do registro fóssil até o meio da era Paleozóica4,5. Aqui mostramos, usando análises morfológicas, ultraestruturais e espectroscópicas, que microfósseis multicelulares de paredes orgânicas preservados em xisto da Formação da Baía de Gramíneas (Shaler Supergroup, Arctic Canada), que datam de aproximadamente 1.010 a 890 milhões de anos atrás, têm uma afinidade fúngica.
Esses microfósseis são mais de meio bilhão de anos mais antigos do que as ocorrências não-ambíguas de fungos relatadas anteriormente, uma data que é consistente com os dados dos relógios moleculares para o surgimento desse clado6,7. Ao estender o registro fóssil dos fungos, essa descoberta também afasta a data mínima para o surgimento do grupo de coroas eucarióticas Opisthokonta, que compreende metazoários, fungos e seus parentes protistas.^8,9.

One million species to go extinct — a decades-old headline

Richard J. Ladle

PDF version

 

Faz menos de 20 anos desde a última vez que acordamos com as manchetes proclamando que 1 milhão de espécies serão extintas (ver R. J. Ladle et al. Nature 428, 799; 2004).

Manchetes quase idênticas estão sendo geradas em todo o mundo com a publicação do resumo do relatório de avaliação global da Plataforma Intergovernamental de Políticas Científicas sobre Biodiversidade e Serviços Ecossistêmicos (IPBES). Apesar de muitos conservacionistas ficarem contentes com a publicidade, ela corre o risco de prejudicar os achados mais detalhados deste importante relatório quando for publicado ainda este ano.

Em ambos os casos, a figura da extinção é uma extrapolação baseada na riqueza de espécies prevista e não documentada. Tais manchetes são alvos fáceis para o lobby antiambientalista e assim poderiam minar a credibilidade e legitimidade do relatório e da ciência da conservação em geral.

The doom and gloom of the report summary is intended to mobilize conservation action (see N. Knowlton Nature 544, 271; 2017). But the more often such claims are made, the more likely they are to be met with apathy. What we need is a more nuanced use of extinction rhetoric, one that aligns scientific evidence of documented and predicted extinctions with cultural frames, institutional frameworks and organizational interests.

Nature 569, 487 (2019)

doi: 10.1038/d41586-019-01618-4

The shells of pond snails normally spiral in a clockwise direction (right). But knocking out a gene called Lsdia1 creates snails whose shells spiral anticlockwise (left). Credit: Hiromi Takahashi/Kuroda Lab

Developmental biology

14 May 2019

The gene that explains why some snails are ‘lefties’

CRISPR helps to pinpoint DNA involved in establishing an embryo’s body plan.

A maioria dos caracóis possui uma concha que espirala para fora do centro no sentido horário. Mas alguns caracóis "esquerdistas" têm conchas que se enrolam no caminho oposto, e agora os cientistas sabem por quê.

Masanori Abe e Reiko Kuroda, agora na Universidade Chubu em Kasugai, Japão, usaram a técnica de edição de genes CRISPR-Cas9 no caramujo Lymnaea stagnalis para nocautear um gene chamado Lsdia1 Isso codifica uma proteína que ajuda a governar a estrutura interna de uma célula.
A equipe descobriu que caramujos que não tinham este gene tiveram descendentes com as raras conchas no sentido anti-horário, sugerindo que Lsdia1 é a chave para determinar a "lateralidade" das criaturas. Estes caracóis passaram o gene mutado e tipo de concha a gerações subsequentes; aqueles com cópias funcionais do gene tinham conchas que enrolavam o caminho normal. O gene influenciou o padrão de divisão celular do estágio em que os embriões de caracol se dividiram de uma célula em duas.

Research on genes such as Lsdia1 could shed light on a rare human condition called situs inversus, in which the positions of the organs in the body are reversed, the authors say.

Development (2019)

• Developmental biology

Temporal evidence shows Australopithecus sediba is unlikely to be the ancestor of Homo

1. Andrew Du* and
2. Zeresenay Alemseged

See all authors and affiliations

Science Advances  08 May 2019:
Vol. 5, no. 5, eaav9038
DOI: 10.1126/sciadv.aav9038

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Abstract

Entender o surgimento do gênero Homo é um problema premente no estudo das origens humanas. O Australopithecus sediba foi recentemente proposto como a espécie ancestral do Homo, embora postergando o mais antigo Homo em 800.000 anos. Aqui, usamos modelos de probabilidade para demonstrar que a observação do horizonte fóssil de um ancestral que é pelo menos 800.000 anos mais jovem do que o horizonte dos descendentes é improvável (cerca de 0,09% em média). Corroboramos esses resultados buscando na literatura e descobrindo que, dentro de pares de supostas espécies descendentes de ancestrais hominídeos, em apenas um caso, o primeiro fóssil descoberto no antepassado datava do descendente, e a diferença de idade entre esses fósseis era muito menor. do que a diferença observada entre A. sediba e Homo mais antigo. Juntos, esses resultados sugerem que é altamente improvável que A. sediba seja ancestral do Homo, e a espécie ancestral candidata mais viável continua sendo Australopithecus afarensis.

INTRODUCTION

Understanding the origin of the genus Homo is one of paleoanthropology’s most enduring questions. A key element in resolving this question is determining which species may have been ancestral to our genus. Because Australopithecus sediba has recently been proposed as a candidate ancestral species (1–3), it is essential that we critically evaluate this claim. Fossil specimens from A. sediba are currently only known from Malapa, South Africa, which is dated to 1.977 million years (Ma) ago (2). These fossils postdate by 800,000 years (0.8 Ma) the only known specimen from the oldest, and currently unnamed, species of Homo (hereafter, “earliest Homo”), which is dated to 2.8 to 2.75 Ma ago at Ledi-Geraru, Ethiopia (4, 5). Most recently, the argument for A. sediba being ancestral to Homo was continued by Robinson et al. (6), who discussed how a fossil horizon from an ancestral species could be much younger than a horizon from the descendant and claimed, “On temporal grounds alone one cannot dismiss the possibility that A. sediba could be ancestral to the genus Homo” (p. 1).

Two conditions must both be met for A. sediba to be ancestral to Homo and for the recovery of an A. sediba fossil horizon that is much younger than an earliest Homo horizon (barring severe postdepositional stratigraphic mixing or errors in taxonomic assignment or dating): (i) Because an ancestor’s fossil horizon can only postdate a descendant’s if there is some overlap in the species’ temporal ranges (Fig. 1A), the descendant must have speciated from the ancestor via budding cladogenesis (Fig. 1B). 

For our study, we assume that Homo cladogenetically budded from A. sediba because, otherwise, this analysis would be unnecessary, and the argument for A. sediba being ancestral to Homo would be illogical (because the A. sediba fossil horizon postdates the earliest Homo horizon). (ii) Given the large amount of time separating the fossil horizons of A. sediba and earliest Homo, there must have been substantial overlap between the two species’ temporal ranges, such that the end of the A. sediba range is able to postdate the beginning of the earliest Homo range by at least 0.8 Ma (Fig. 2). If range overlap is less than 0.8 Ma, then the A. sediba fossil horizon cannot be 0.8 Ma younger than the earliest Homo horizon (assuming A. sediba was ancestral to Homo) (Figs. 1A and 2). As range overlap increases, so does the probability of sampling the end and beginning of the A. sediba and earliest Homo ranges, respectively, such that their horizons are at least 0.8 Ma apart (Fig. 2A). This second condition forms the theoretical basis for our probability model.

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Fig. 1 Conditions where an ancestor’s fossil horizon can be younger than the descendant’s.

 

For both figures, “A” represents the ancestral species, and “D” represents the descendant species. (A) When there is no overlap between the temporal ranges of an ancestor and a descendant, an ancestor’s fossil horizon can never be younger than the descendant’s. If ranges partially overlap (gray), then an ancestor’s fossil horizon can postdate the descendant’s (fossil horizons are represented by white circles). The maximum age difference between a younger horizon from an ancestor and an older horizon from a descendant is ultimately constrained by the amount of range overlap, such that the age difference can never be greater than the amount of overlap. (B) Three different ways a descendant can speciate from an ancestor. Budding cladogenesis is the only speciation mode that produces ancestors and descendants with overlapping temporal ranges and is therefore the only mode where an ancestor’s fossil horizon can postdate the descendant’s. “D1” and “D2” represent two sister lineages, which are both descendants of “A.” (B) is modified after Fig. 1 in (25).

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Fig. 2 Schematic used to derive the model for quantifying the probability that an ancestor’s fossil horizon postdates the descendant’s by at least 0.8 Ma.

For both figures, “A” represents the ancestral species, and “D” represents the descendant species. (A). The probability of sampling an ancestor’s fossil horizon that is at least 0.8 Ma younger than the descendant’s is ultimately a function of the amount of overlap between both species’ temporal ranges relative to the age difference of interest (which here is 0.8 Ma). When range overlap is less than 0.8 Ma, the ancestor’s horizon cannot postdate the descendant’s by 0.8 Ma (represented by the Xs in the leftmost example). In the middle example, there is enough range overlap where 0.8 Ma separates the end and beginning of the ancestor’s and descendant’s ranges, respectively (black), and each species’ fossil horizon must be sampled from these black regions. 

As overlap increases (rightmost example), so does the size of the black regions and the probability of sampling an ancestor’s fossil horizon that is at least 0.8 Ma younger than the descendant’s horizon. The rightmost example is used to illustrate the three variables from our probability model (Eq. 5c): T_d represents the age difference of interest (i.e., 0.8 Ma), T_o represents the amount of range overlap, and T_R represents the duration of the entire temporal range (i.e., 0.97 Ma). (B) Focusing on the black regions, a descendant’s fossil horizon (white circles) can sample some time near the species’ age of origination (leftmost example), which means that the ancestor’s horizon can be sampled anywhere in its own black region and still be at least 0.8 Ma younger than the descendant horizon (white-striped region). If the descendant’s horizon is found in the middle of the black region (middle example), the ancestor’s horizon must sample the younger half of its own black region. If the descendant horizon samples the end of its black region (rightmost example), the ancestor’s horizon must sample the end of its temporal range. The rightmost example is used to illustrate the X_A and X_D variables (Eq. 3), each of which represents the distance from the beginning of the black region to the temporal location of the fossil horizon in the ancestor’s and descendant’s range, respectively. For the ancestor’s horizon to postdate the descendant’s by at least 0.8 Ma, X_A must be greater than X_D, and two iterations of this are shown.

While Robinson et al. (6) are correct that it is possible for an ancestor’s fossil horizon to be much younger than the descendant’s, a more informative question would be, “How likely is this chronological pattern?” We build upon previous work concerning the evolutionary relationships of A. sediba (1–3, 6) and construct a probability model, which serves as a null hypothesis test, to evaluate whether A. sediba is ancestral to Homo. 

We assume that (i) A. sediba and earliest Homo each had temporal ranges of 0.97 Ma (6), (ii) the probability of recovering fossils throughout each species’ range is uniform through time (7, 8), and (iii) the probability of sampling an A. sediba fossil horizon does not affect the probability of sampling an earliest Homo fossil horizon, i.e., these are independent events (see Materials and Methods). From these assumptions, we quantify the probability of finding one fossil horizon from A. sediba that is at least 0.8 Ma younger than one horizon from earliest Homo (i.e., the observed data), assuming A. sediba is ancestral to Homo (i.e., the null hypothesis). 

The computed probabilities are equivalent to P values, and if they are exceptionally low, this would suggest that A. sediba is unlikely to be the ancestor of Homo (i.e., the null hypothesis is falsified). We calculate multiple P values as a function of the overlap between the two species’ true temporal ranges, which is currently unknown. We analyze temporal evidence only (6) and do not consider morphological data concerning the evolutionary relationship between A. sediba and Homo (1, 9–11). We also analyze the historical record of hominin discovery and calculate the geological age difference between initial fossil discoveries in purported ancestor and descendant species. The aim here is to corroborate our theoretical probability results and to empirically assess how likely it is for an ancestor’s fossil horizon to postdate a descendant’s by at least 0.8 Ma.

RESULTS

The probability of finding an ancestor’s fossil horizon that is at least 0.8 Ma younger than the descendant’s is, by definition, zero when temporal range overlap is less than or equal to 0.8 Ma (Figs. 2A and 3 and Eq. 5c). This probability monotonically increases with range overlap when overlap is greater than 0.8 Ma (Fig. 3 and Eq. 5c) for reasons discussed above (Fig. 2A). However, even when the two species’ ranges completely overlap, which is impossible for ancestor-descendant species and is only presented as a theoretical upper bound, the computed P value is only 0.016 (Fig. 3 and Eq. 5c). If we treat all possible values of range overlap as equally likely, the mean P value over all overlap values is 0.0009 (Eq. 6c). We have confirmed our probability model results with simulations (fig. S1 and data file S5).

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Fig. 3 Probability of finding an ancestor’s fossil horizon that is at least 0.8 Ma younger than the descendant’s fossil horizon (P value).

P values are plotted as a function of the overlap between the two species’ true, unknown temporal ranges, each of which is assumed to be 0.97 Ma in duration (6).

Reviewing the paleoanthropology literature, we recorded 28 hypothesized ancestor-descendant species pairs (table S1). There is only one instance where an ancestor’s first-discovered fossil postdated the descendant’s: ancestor Homo erectus sensu lato (Kedung Brubus 1) dated to 0.8 to 0.7 Ma ago (12) and descendant Homo antecessor (ATD6-1) dated to 0.9 to 0.8 Ma ago (13). The age difference between these specimens (i.e., 0.1 Ma) is far less than the age difference observed between A. sediba and earliest Homo (i.e., 0.8 Ma) (Fig. 4). When the mean and SD of the 28 observed age differences are used to generate a normal distribution model (bell curve in Fig. 4), 0.8 Ma falls in the >99.9th percentile, which translates to a P value less than 0.001.

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Fig. 4 Histogram of the geological age differences between first-discovered fossils in purported hominin ancestor-descendant species pairs (n = 28).

Negative age differences represent those species pairs where the ancestor’s first-discovered fossil is older than the descendant’s, and positive age differences indicate the opposite. The black arrow represents the observed age difference between A. sediba (hypothesized ancestor) and earliest Homo at Ledi-Geraru (hypothesized descendant). The bell curve represents a normal distribution model, generated using the sample mean and SD of the 28 observed age differences.

DISCUSSION

We have demonstrated using probability models that the null hypothesis of A. sediba being ancestral to Homo can be falsified. That is, it is very unlikely (about 0.09% on average) to find an A. sediba fossil horizon that is at least 0.8 Ma younger than an earliest Homo horizon, if the former species is actually ancestral to the latter. The prior record of paleoanthropological discoveries also reflects the rarity of cases in which this chronological pattern is observed, further supporting that A. sediba is unlikely to be ancestral to Homo.

We can explore how strongly our assumptions influenced our modeling results. We calculated our P values, assuming the 2.8-Ma-old Ledi-Geraru mandible actually belongs to Homo (5). Some researchers dispute this (14), so we also ran our analyses assuming A.L. 666-1 (2.33 Ma-old)—a specimen widely regarded as Homo—represents the oldest Homo specimen (15). Although a handful of researchers argue that all pre–1.9-Ma-old specimens assigned to Homo are invalidly named or are poorly dated (2, 3), we view this assertion as unlikely [as does Robinson et al. (6)]. By selecting a younger fossil to represent the oldest Homo specimen, we are decreasing the observed age difference between A. sediba and earliest Homo, which should increase the P values overall (Eq. 5c). We also explored whether our choice of 0.97 Ma to represent hominin temporal durations might affect our results because using a longer duration will increase the amount of time associated with a given percentage of range overlap between two species, and this should increase P values as well (Eq. 5c). We therefore reran our analyses assuming hominin temporal durations of 2 Ma, which is at the larger end of estimated mean species durations in African large mammals [all African large mammals: 2.3 Ma (16); eastern African bovids: 1.4 Ma (17); large mammals in the Omo-Turkana Basin, Ethiopia/Kenya: 1.4 Ma (17); Australopithecus anamensis-afarensis: 1.2 Ma (7, 8)]. Results show that calculated P values are still small even when relaxing the age of earliest Homo to 2.33 Ma ago or hominin temporal durations to 2 Ma. For example, P values exceed 0.05 only when range overlap is at least 70%, and the mean and maximum P values over all possible overlap values are only 0.04 and 0.20, respectively (Eqs. 5c and 6c, and fig. S2, A and B). When both assumptions are simultaneously relaxed, P values exceed 0.05 when overlap is at least 50%, and the mean and maximum P values are 0.093 and 0.34, respectively (Eqs. 5c and 6c, and fig. S2C).

For our model, we assumed that the probability of recovering a fossil horizon from each of the A. sediba and earliest Homo temporal ranges is uniform through time. This assumption is a parsimonious one given that only one horizon each has been sampled from A. sediba (1, 2) and earliest Homo (5), and a uniform fossil recovery potential (FRP) (i.e., the probability of finding a fossil horizon) is a good approximation for the one hominin lineage where FRP has been explored, i.e., A. anamensis-afarensis (7, 8). However, we also have to consider the possibility that FRP is not uniform through time in the A. sediba and earliest Homo temporal ranges. Our P values would only be biased downward if FRP is greater in South Africa and eastern Africa during the geological time periods when A. sediba and earliest Homo are found, respectively. This is because if FRP is actually higher toward the end and beginning of the A. sediba and earliest Homo temporal ranges, respectively, then it is more likely that one will recover an A. sediba horizon that is much younger than an earliest Homo horizon, even if the former species is ancestral to the latter. Using the number of hominin fossil horizons—defined as midpoint ages of hominin-bearing members with age duplicates removed (see data file S3) (7, 8)—as a proxy for FRP, we find that FRP is not appreciably higher during the times when A. sediba and earliest Homo are found in their respective geographic regions (fig. S3). There is the possibility that FRP might be slightly higher in South Africa around the time of A. sediba (fig. S3), but even if we double the probability of recovering a fossil horizon in the last 25% of the ancestor’s (i.e., A. sediba) temporal range, the maximum P value is only 0.025 (fig. S4).

Regarding our analysis of the historical record of first-discovered hominin fossils, ancestor-descendant hypotheses might implicitly or explicitly incorporate temporal information, which would potentially render our analysis circular. 

That is, if ancestor-descendant relationships are proposed at least partly based on the fact that the ancestor’s fossil predates the descendant’s, it should be no surprise that ancestors’ fossil horizons rarely postdate descendants’ horizons. However, incorporating temporal data into ancestor-descendant hypotheses does not necessarily mean that the ancestor’s first-discovered fossil must predate the descendant’s first-discovered fossil (fig. S5). For example, a newly discovered fossil from the ancestral species may sample the end of its temporal range, and the rest of the range is revealed only after subsequent sampling. 

A second, more recently found fossil may be proposed as the ancestor’s descendant based on the new fossil postdating the ancestor’s first appearance, but the new descendant fossil can still predate the younger, first-discovered fossil from the ancestor (see fig. S5 for a discussion about the more complicated scenario when the descendant fossil is found first). Regardless of whether the ancestor or descendant was found first, none of the ancestor’s first-discovered fossils ever postdated the descendants by more than 0.8 Ma (i.e., the observed age difference between A. sediba and earliest Homo) in our literature review (Fig. 4 and table S1).

Robinson et al. (6) write, “Until such time as additional data on its temporal range are available for A. sediba, any inferences about the evolutionary relationship between it and Homo should be based primarily on morphological data” (p. 6). More fossils will always strengthen any inference, but we have demonstrated here that even with the scant data relevant to the question at hand (i.e., only one fossil horizon each from A. sediba and earliest Homo), we can still use temporal evidence to rigorously assess the proposed ancestor-descendant relationship between these two species. This is accomplished by modeling the process/question of interest to generate the probability of obtaining the observed pattern (i.e., an ancestor’s fossil horizon that is 0.8 Ma younger than the descendant’s), analogous to a null hypothesis test. Our analyses demonstrate that strong inferences can be made even with an incomplete fossil record, so chronological data and tests should not be so quickly discarded.

The issue of the origin of Homo is one of the thorniest questions in paleoanthropology and one that has led to myriad proposals and, sometimes, speculations (2, 3, 18, 19). Answers to the questions of how, when, and where the earliest representatives of the genus emerged are still in flux, owing especially to the dearth of fossil data from the relevant temporal range (3.0 to 2.5 Ma ago). It is therefore important to use all available lines of evidence when addressing a question as data poor as this one. While fossil remains from the 3.0- to 2.5-Ma-old interval are necessary to reasonably document the morphological patterns surrounding the origin of Homo, probabilistic methods such as the one used here are also critical for assessing the chronological evidence for proposed relationships between Homo and candidate ancestors. Hypothesized ancestor-descendant relationships must satisfy both temporal and morphological criteria (7, 20). We tested the first criterion here, and the second one has been tested elsewhere (11). A. sediba fails both benchmarks, and the most viable ancestral candidate for the genus Homo remains Australopithecus afarensis both on morphological (5) and temporal grounds (7, 8).

MATERIALS AND METHODS

Probability model

We are interested in the probability that an ancestor’s fossil horizon postdates the descendant’s by at least some amount, T_d. Let us denote this probability as P(H_A − H_D > T_d), where H_A and H_D represent the ages of the ancestor’s and descendant’s fossil horizons, respectively. To have an ancestor’s horizon postdate the descendant’s, the fossils must come from the period of temporal range overlap (Fig. 1A). To get an ancestor’s horizon that postdates the descendant’s by at least T_d, the ancestor’s fossil must sample the younger end of the overlap region, and the descendant’s fossil must sample the older end (Fig. 2A); let us designate these respective regions as end_A and end_D (i.e., black regions in Fig. 2A), and the probability of sampling these regions is P(end_A) and P(end_D). Because we assume that the ancestor and descendant species have equal temporal ranges, P(end_A) = P(end_D) (Fig. 2A). Assuming sampling probability is uniform throughout a species’ temporal range, the probability of sampling a fossil horizon from this region is

P(endA)=P(endD)=To−TdTR

(1)where T_o is the amount of range overlap and T_R is the duration of the entire temporal range (Fig. 2A). We assume here that the probability of selecting a fossil horizon from the ancestor’s range is independent from selecting a fossil horizon from the descendant’s range. This is a sensible assumption given that the earliest Homo specimen is from eastern Africa (5), whereas the A. sediba specimens are from South Africa (1). Therefore, the probability of sampling one fossil horizon each from end_A and end_D is P(end_A) × P(end_D) or

P(endA∩endD)=(To−Td)2T2R

(2)where “∩” denotes the intersection, i.e., when two events both occur.

Once end_A and end_D are both sampled, Fig. 2B illustrates the necessary conditions that must occur for the ages of the ancestor’s and descendant’s fossil horizons (i.e., H_A and H_D, respectively) to be separated by at least T_d. Let X_D represent the age difference between the beginning of end_D and H_D (X_A represents the same but for the ancestor) (Fig. 2B). For a given value of X_D, which we will call t, X_A must be greater than X_D, so H_A falls within the white-striped regions in Fig. 2B. The probability of this occurring for all possible values of t (i.e., from zero to infinity) is

P(XA>XD)=⌠⌡t=0∞P(XA>XD|XD=t)P(XD=t)dt

(3a)

Note that this is the law of total probability (21), which states P(A)=∑nP(A|Bn)P(Bn)

, i.e., the probability of event A occurring is equal to the probability of A given event B_n multiplied by the probability of B_n, and all these are summed (or integrated) over all possible instances of B_n in the sample space to get the total probability of A. Because we assume X_A and X_D are independent (i.e., the probability of X_D taking on some value, t, does not affect the value of X_A and whether it is greater than t), the first probability on the right-hand side in Eq. 3a can be simplified, so

P(XA>XD)=⌠⌡t=0∞P(XA>t)P(XD=t)dt

(3b)

Because we assume that FRP is uniform throughout a species’ temporal range, the probability of sampling a fossil can be modeled as a Poisson process, where X_A and X_D are exponentially distributed (22, 23). The first probability in the integral (i.e., P[X_A > t]; Eq. 3b) can be thought of as the probability that H_A is not found within the interval (0, t) (or one minus the probability that H_A is sampled in this interval). Using the exponential cumulative distribution function, this probability is

P(XA>t)=1−(1−e−λt)=e−λt

(3c)

The second probability in the integral (P[X_D = t]; Eq. 3b) can be calculated using the exponential probability density function (i.e., the probability that X_D takes on some value, t), so

P(XD=t)=λe−λt

(3d)

Substituting Eqs. 3c and 3d into Eq. 3b, we get

P(XA>XD)=⌠⌡t=0∞e−λtλe−λtdt

(3e)

Note that because we are only concerned with sampling one fossil horizon each from the ancestor’s and descendant’s range, both of which are of equal duration, the sampling rate, λ, for each species is the same. Solving Eq. 3e

P(XA>XD)=λ⌠⌡t=0∞e−2λtdt=λ⋅−e−2λt2λ∣∣∞t=0=λ(−e−2λ∞2λ+12λ)

(3f)

The exponential term equals zero given that λ is positive, so

P(XA>XD)=λ2λ=12

(3g)

The same logic and result hold if the roles of X_D and X_A are reversed, i.e., if we instead solve P(XD<XA)=∫t=0∞P(XD<XA|XA=t)P(XA=t)dt

. Therefore, the probability of getting H_A and H_D separated by at least T_d given that H_A and H_D come from end_A and end_D, respectively, is one-half, or using probability notation

P(HA−HD>Td|endA∩endD)=12

(4)

Putting all the above equations together using the law of total probability (21)

P(HA−HD>Td)=P(HA−HD>Td|endA∩endD)P(endA∩endD)+P(HA−HD>Td|[endA∩endD]c)P([endA∩endD]c)

(5a)where the superscript “c” denotes the complement, i.e., when an event does not happen. We have already established that end_A and end_D need to both be sampled for an ancestor’s horizon to postdate a descendant’s by at least T_d (Fig. 2A), so P(H_A − H_D > T_d | [end_A ∩ end_D]^c) = 0. Therefore, the second product in Eq. 5a equals zero and can be dropped. We have already solved the two probabilities in the first product of Eq. 5a with Eqs. 4 and 2, so

P(HA−HD>Td)=P(HA−HD>Td|endA∩endD)P(endA∩endD)=12×(To−Td)2T2R=(To−Td)22T2R

(5b)

And because P(H_A − H_D > T_d) must be zero when the age difference of interest (T_d) is greater than the amount of range overlap (T_o) (Figs. 1A and 2A), the final model is

P(HA−HD>Td)={0(To−Td)22T2RTd>ToTd≤To

(5c)

For our main analysis (Fig. 3), T_d = 0.8 Ma, we assume T_R to be 0.97 Ma (6), and we explored multiple values for T_o, which is currently unknown.

Because T_o (i.e., how much the A. sediba and earliest Homo temporal ranges overlap) is currently unknown, we also applied uniform prior probabilities over all possible values of T_o to distill the P value function (Eq. 5c) into its mean value (i.e., the expected value) (24). To get the expected P value, we integrate Eq. 5c with respect to T_o over all possible values of T_o (i.e., from zero to T_R) against the probability density function of our T_o uniform prior, which is defined as 1/T_R between zero and T_R. Therefore, the expected value is

E[P(HA−HD>Td)]=1TR(⌠⌡⎮To=0Td0dTo+⌠⌡⎮To=TdTR(To−Td)22T2RdTo)

(6a)

Note that because P(H_A − H_D > T_d) is a piecewise function (Eq. 5c), we break the integral into the sum of two integrals separated by T_d (i.e., the value that separates the piecewise function in Eq. 5c). The first integral in Eq. 6a equals zero, and pulling out the 1/2T_R² constant in the second integral gives

E[P(HA−HD>Td)]=12T3R⌠⌡⎮To=TdTR(To−Td)2dTo

(6b)

Solving Eq. 6b

E[P(HA−HD>Td)]=12T3R×(To−Td)33∣∣∣TRTo=Td=12T3R[(TR−Td)33−(Td−Td)33]=(TR−Td)36T3R

(6c)which is the expected P value from Eq. 5c, treating all possible values of T_o as equally likely.

Analysis of published fossil ages

We reviewed the literature and recorded the geological ages (lower and upper bracketing ages) and year of discovery of the first fossil found in each species in a hypothesized hominin ancestor–descendant pair [this mirrors the situation in A. sediba and earliest Homo, both of which currently have only one fossil horizon each (2, 5)]. Because we were only interested in by how much the ancestor’s first-discovered fossil postdated the descendant’s first-discovered fossil, we were more inclusive than not in our selection (i.e., the accuracy or widespread acceptance of an ancestor-descendant relationship should have no bearing on the age difference between first-discovered fossils). To calculate the age difference, we subtracted the midpoint age of the ancestor’s first-discovered fossil from the midpoint age of the descendant’s first-discovered fossil, where the midpoint age is defined as (lower bracketing age + upper bracketing age)/2. Negative age differences indicate that the ancestor’s first-discovered fossil is older than the descendant’s, and vice versa, for positive differences.

SUPPLEMENTARY MATERIALS

Supplementary material for this article is available at http://advances.sciencemag.org/cgi/content/full/5/5/eaav9038/DC1

Fig. S1. Confirming our probability model results (Fig. 3) with simulations.

Fig. S2. Same analysis as in Fig. 3 but assuming hominin temporal durations of 2 Ma, A.L. 666-1 (2.33 Ma old) represents the oldest Homo fossil, or both.

Fig. S3. Uniform probability plots for 4- to 1-Ma-old hominin fossil horizons in South Africa and eastern Africa.

Fig. S4. Same analysis as in Fig. 3, but the probability of sampling a fossil horizon (i.e., FRP) from the last 25% of the ancestor’s range is doubled.

Fig. S5. Schematic illustrating how proposing an ancestor-descendant relationship based on temporal evidence does not necessarily constrain the first-discovered fossil in each species to be in the “correct” order (i.e., where the ancestor’s first-discovered fossil predates the descendant’s).

Table S1. Previously proposed ancestor-descendant hominin species pairs (n = 28), and the year discovered and geological ages of the first-discovered specimen in each species.

Data file S1. Hypothesized hominin ancestor–descendant species pairs.

Data file S2. Geological ages for first-discovered specimens of hominin species.

Data file S3. Four- to 1-Ma-old South African and eastern African hominin-bearing members and their geological ages.

Data file S4. Dataset references.

Data file S5. R code for analyses and creating figures.

References (26, 27)

This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial license, which permits use, distribution, and reproduction in any medium, so long as the resultant use is not for commercial advantage and provided the original work is properly cited.

REFERENCES AND NOTES

1. ↵
   1. L. R. Berger,
   2. D. J. de Ruiter,
   3. S. E. Churchill,
   4. P. Schmid,
   5. K. J. Carlson,
   6. P. H. G. M. Dirks,
   7. J. M. Kibii

   , Australopithecus sediba: A new species of Homo-like australopith from South Africa. Science 328, 195–204 (2010).

   Abstract/FREE Full TextGoogle Scholar
2. ↵
   1. R. Pickering,
   2. P. H. G. M. Dirks,
   3. Z. Jinnah,
   4. D. J. de Ruiter,
   5. S. E. Churchill,
   6. A. I. R. Herries,
   7. J. D. Woodhead,
   8. J. C. Hellstrom,
   9. L. R. Berger

   , Australopithecus sediba at 1.977 Ma and implications for the origins of the genus Homo. Science 333, 1421–1423 (2011).

   Abstract/FREE Full TextGoogle Scholar
3. ↵
   1. L. Berger

   , Australopithecus sediba and the earliest origins of the genus Homo. J. Anthropol. Sci. 90, 117–131 (2012).

   PubMedGoogle Scholar
4. ↵
   1. E. N. DiMaggio,
   2. C. J. Campisano,
   3. J. Rowan,
   4. G. Dupont-Nivet,
   5. A. L. Deino,
   6. F. Bibi,
   7. M. E. Lewis,
   8. A. Souron,
   9. D. Garello,
   10. L. Werdelin,
   11. K. E. Reed,
   12. J. Ramón Arrowsmith

   , Late Pliocene fossiliferous sedimentary record and the environmental context of early Homo from Afar, Ethiopia. Science 347, 1355–1359 (2015).

   Abstract/FREE Full TextGoogle Scholar
5. ↵
   1. B. Villmoare,
   2. W. H. Kimbel,
   3. C. Seyoum,
   4. C. J. Campisano,
   5. E. N. DiMaggio,
   6. J. Rowan,
   7. D. R. Braun,
   8. J. Ramón Arrowsmith,
   9. K. E. Reed

   , Early Homo at 2.8 Ma from Ledi-Geraru, Afar, Ethiopia. Science 347, 1352–1355 (2015).

   Abstract/FREE Full TextGoogle Scholar
6. ↵
   1. C. Robinson,
   2. T. L. Campbell,
   3. S. Cote,
   4. D. J. de Ruiter

   , Temporal ranges and ancestry in the hominin fossil record: The case of Australopithecus sediba. S. Afr. J. Sci. 114, 7 (2018).

   Google Scholar
7. ↵
   1. A. Du,
   2. J. Rowan,
   3. S. C. Wang,
   4. B. A. Wood,
   5. Z. Alemseged

   , Statistical estimates of hominin origination and extinction dates: a case study examining the Australopithecus anamensis-afarensis lineage. J. Hum. Evol. (in revision).

   Google Scholar
8. ↵
   Z. Alemseged, A. Du, J. Rowan, B. A. Wood, “Estimating the timing of and placing confidence intervals on the origination and extinction of the Australopithecus anamensis-afarensis lineage,” Abstr. 2018 Paleoanthropology Soc. Meet. PaleoAnthropology 2018, A1 (2018).

   Google Scholar
9. ↵
   1. J. D. Irish,
   2. D. Guatelli-Steinberg,
   3. S. S. Legge,
   4. D. J. de Ruiter,
   5. L. R. Berger

   , Dental morphology and the phylogenetic “place” of Australopithecus sediba. Science 340, 1233062 (2013).

   Abstract/FREE Full TextGoogle Scholar
10. 1. M. Dembo,
    2. N. J. Matzke,
    3. A. Ø. Mooers,
    4. M. Collard

    , Bayesian analysis of a morphological supermatrix sheds light on controversial fossil hominin relationships. Proc. Biol. Sci. 282, 20150943 (2015).

    CrossRefPubMedGoogle Scholar
11. ↵
    1. W. H. Kimbel,
    2. Y. Rak

    , Australopithecus sediba and the emergence of Homo: Questionable evidence from the cranium of the juvenile holotype MH 1. J. Hum. Evol. 107, 94–106 (2017).

    Google Scholar
12. ↵
    1. G. D. van den Bergh,
    2. J. de Vos,
    3. P. Y. Sondaar

    , The Late Quaternary palaeogeography of mammal evolution in the Indonesian Archipelago. Palaeogeogr. Palaeoclimatol. Palaeoecol. 171, 385–408 (2001).

    CrossRefWeb of ScienceGoogle Scholar
13. ↵
    1. D. Moreno,
    2. C. Falguères,
    3. A. Pérez-González,
    4. P. Voinchet,
    5. B. Ghaleb,
    6. J. Despriée,
    7. J.-J. Bahain,
    8. R. Sala,
    9. E. Carbonell,
    10. J. M. B. de Castro,
    11. J. L. Arsuaga

    , New radiometric dates on the lowest stratigraphical section (TD1 to TD6) of Gran Dolina site (Atapuerca, Spain). Quat. Geochronol. 30, 535–540 (2015).

    Google Scholar
14. ↵
    1. J. Hawks,
    2. D. J. de Ruiter,
    3. L. R. Berger

    , Comment on “Early Homo at 2.8 Ma from Ledi-Geraru, Afar, Ethiopia”. Science 348, 1326 (2015).

    Abstract/FREE Full TextGoogle Scholar
15. ↵
    1. W. H. Kimbel,
    2. D. C. Johanson,
    3. Y. Rak

    , Systematic assessment of a maxilla of Homo from Hadar, Ethiopia. Am. J. Phys. Anthropol. 103, 235–262 (1997).

    CrossRefPubMedWeb of ScienceGoogle Scholar
16. ↵
    E. Vrba, in Cenozoic Geology of Southern Africa, T. C. Partridge, R. Maud, Eds. (Oxford Univ. Press, 2000), pp. 277–304.

    Google Scholar
17. ↵
    1. F. Bibi,
    2. W. Kiessling

    , Continuous evolutionary change in Plio-Pleistocene mammals of eastern Africa. Proc. Natl. Acad. Sci. 112, 10623–10628 (2015).

    Abstract/FREE Full TextGoogle Scholar
18. ↵
    1. B. Wood,
    2. M. Collard

    , The human genus. Science 284, 65–71 (1999).

    Abstract/FREE Full TextGoogle Scholar
19. ↵
    1. B. Villmoare

    , Early Homo and the role of the genus in paleoanthropology. Am. J. Phys. Anthropol. 165, 72–89 (2018).

    Google Scholar
20. ↵
    1. C. R. C. Paul

    , The recognition of ancestors. Hist. Biol. 6, 239–250 (1992).

    Google Scholar
21. ↵
    W. Mendenhall, R. J. Beaver, B. M. Beaver, Introduction to Probability and Statistics (Brooks/Cole, Cengage Learning, ed. 14/Student edition, 2013).

    Google Scholar
22. ↵
    1. D. Strauss,
    2. P. M. Sadler

    , Classical confidence intervals and Bayesian probability estimates for ends of local taxon ranges. Math. Geol. 21, 411–427 (1989).

    CrossRefGoogle Scholar
23. ↵
    J. F. C. Kingman, Poisson Processes (Oxford Studies in Probability Series, Clarendon Press, 1993).

    Google Scholar
24. ↵
    G. Casella, R. L. Berger, Statistical Inference (Thomson Learning, ed. 2, 2002).

    Google Scholar
25. ↵
    1. M. Foote

    , On the probability of ancestors in the fossil record. Paleobiology 22, 141–151 (1996).

    AbstractGoogle Scholar
26. ↵
    1. B. Wood,
    2. E. K. Boyle

    , Hominin taxic diversity: Fact or fantasy? Am. J. Phys. Anthropol. 159, S37–S78 (2016).

    Google Scholar
27. ↵
    1. J.-J. Hublin,
    2. A. Ben-Ncer,
    3. S. E. Bailey,
    4. S. E. Freidline,
    5. S. Neubauer,
    6. M. M. Skinner,
    7. I. Bergmann,
    8. A. L. Cabec,
    9. S. Benazzi,
    10. K. Harvati,
    11. P. Gunz

    , New fossils from Jebel Irhoud, Morocco and the pan-African origin of Homo sapiens. Nature 546, 289–292 (2017).

    CrossRefPubMedGoogle Scholar

Acknowledgments: For discussions about probability models, we thank A. Gordon (who recommended substantive improvements), M. Foote, and E. Friedlander. We thank S. Wang, M. Foote, and K. Hatala for comments on an earlier version of the manuscript. We also thank The University of Chicago Anthropology Journal Club for their helpful comments on the manuscript. Funding: No funding was received for this project. Author contributions: A.D. and Z.A. designed the research. A.D. and Z.A. collected the data. A.D. created the probability model and analyzed the data. A.D. wrote the paper with contributions from Z.A. Competing interests: The authors declare that they have no competing interests. Data and materials availability: All analyzed datasets and R code can be found in the Supplementary Materials. Additional data related to this paper may be requested from the authors.

• Copyright © 2019 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC).

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