As descobertas destacam a necessidade de olhar além de apenas espanãcies raras para melhorar os esforços para conservar a biodiversidade global, dizem os cientistas.
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)
Gannet do Norte. Crédito: Gergana Daskalova, Universidade de Edimburgo
As populações de animais comuns tem a mesma probabilidade de aumentar ou diminuir em número em uma anãpoca de mudança global acelerada, assim como as de espanãcies raras, sugere um estudo.
Um estudo de mais de 2.000 espanãcies revela que as populações de animais em todo o mundo - desde as mais comuns atéas ameaa§adas de extinção - estãosubindo e descendo conforme a mudança global altera os ecossistemas terrestres, maratimos e de águadoce.
As descobertas destacam a necessidade de olhar além de apenas espanãcies raras para melhorar os esforços para conservar a biodiversidade global, dizem os cientistas.
Animais criticamente ameaa§ados - como a tartaruga-de-pente - eram considerados anteriormente em maior risco de declanio do que espanãcies comuns como o veado, mas o estudo encontrou um amplo espectro demudanças no número de animais.
Os resultados do novo estudo sugerem que os números dentro de espanãcies animais muito comuns são, de fato, tão propensos a aumentar ou diminuir quanto os raros.
No entanto, as espanãcies com tamanhos populacionais menores tem maior probabilidade de mudar de ano para ano, potencialmente aumentando seu risco de extinção a longo prazo.
Atérecentemente, os cientistas ainda estavam compilando dados sobre como as populações de animais estavam mudando ao longo do tempo em uma escala global nas diferentes regiaµes do planeta.
Pato Eider. Crédito: Gergana Daskalova, Universidade de Edimburgo
Fazendo uso dos dados recentemente disponaveis, uma equipe de pesquisadores da Universidade de Edimburgo estudou cerca de 10.000 populações de animais registradas no Living Planet Database entre 1970 e 2014 para fornecer uma nova perspectiva sobre a mudança da população animal. Isso inclui registros de mamaferos, ranãpteis, tubaraµes, peixes, pa¡ssaros e anfabios.
A equipe descobriu que 15% de todas as populações diminuaram durante o período, enquanto 18% aumentaram e 67% não mostraram nenhuma mudança significativa.
Os anfabios foram o aºnico grupo em que o tamanho da população diminuiu, enquanto as aves, mamaferos e ranãpteis aumentaram.
O declanio geral dos anfabios os torna uma prioridade para os esforços de conservação , dizem os pesquisadores, uma vez que sua perda pode ter efeitos indiretos nas cadeias alimentares e ecossistemas mais amplos.
O estudo, publicado na revista Nature Communications , foi financiado pelo Natural Environment Research Council e pelo Carnegie Trust.
Papagaio mulga. Crédito: Gergana Daskalova, Universidade de Edimburgo
Gergana Daskalova, da Escola de Geociências da Universidade de Edimburgo, que liderou o estudo, disse: "Muitas vezes presumimos que o declanio no número de animais prevalece em todos os lugares. Mas descobrimos que também hámuitas espanãcies que aumentaram na última metade de um século, como aqueles que se da£o bem em paisagens modificadas pelo homem ou aqueles que são o foco de ações de conservação. "
A Dra. Isla Myers-Smith, também da School of GeoSciences, coautora do estudo, disse: "Somente quando reunimos dados de todo o mundo, podemos comea§ar a realmente entender como asmudanças globais estãoinfluenciando a biodiversidade de nosso planeta. A ideia original para este estudo surgiu de uma classe de graduação do quarto ano na Universidade de Edimburgo. a‰ tão inspirador ver pesquisadores em inicio de carreira lidando com algumas das grandes questões de conservação de nosso tempo usando habilidades avana§adas de ciência de dados. "