Instituto de Pesquisas Jardim Botânico do Rio de Janeiro Escola Nacional de Botânica Tropical Programa de Pós-graduação em Botânica
Tese de Doutorado
Conservação da diversidade arbórea no Estado do Rio de Janeiro: uma abordagem filogenética
Pablo Viany Prieto
Rio de Janeiro 2017
I
Instituto de Pesquisas Jardim Botânico do Rio de Janeiro Escola Nacional de Botânica Tropical Programa de Pós-graduação em Botânica
Tese de Doutorado
Conservação da diversidade arbórea no Estado do Rio de Janeiro: uma abordagem filogenética
Pablo Viany Prieto
Tese apresentada ao Programa de Pós- Graduação em Botânica, Escola Nacional de Botânica Tropical, do Instituto de Pesquisas Jardim Botânico do Rio de Janeiro, como parte dos requisitos necessários para a obtenção do título de Doutor em Botânica.
Orientadora: Marinez Ferreira de Siqueira
Rio de Janeiro 2017
II
Conservação da diversidade arbórea no Estado do Rio de Janeiro: uma abordagem filogenética
Pablo Viany Prieto
Tese submetida ao Programa de Pós-Graduação em Botânica da Escola Nacional de Botânica Tropical, Instituto de Pesquisas Jardim Botânico do Rio de Janeiro - JBRJ, como parte dos requisitos necessários para a obtenção do grau de Mestre (Doutor).
Aprovada por:
Profa. Dra. Marinez Ferreira de Siqueira (Orientadora) ______
Prof. Dr. Fabio Rúbio Scarano ______
Prof. Dr. Bruno Henrique Pimentel Rosado ______
Prof. Dr. Renato Crouzeilles ______
Prof. Dr. Alexandre Quinet ______
Prof. Dra. Eline de Matos Martins (suplente) ______
Prof. Dr. Richieri Sartori (suplente) ______
em 31/05/2017
Rio de Janeiro 2017
III
Prieto, Pablo Viany. P948c Conservação da diversidade arbórea no Estado do Rio de Janeiro: uma abordagem filogenética / Pablo Viany Prieto. – Rio de Janeiro, 2017. xxii, 83 f. : il. ; 28 cm.
Tese (doutorado) – Instituto de Pesquisas Jardim Botânico do Rio de Janeiro / Escola Nacional de Botânica Tropical, 2017.
Orientadora: Marinez Ferreira de Siqueira.
Bibliografia.
1. Mata Atlântica. 2. Diversidade filogenética. 3.Conservação de espécies. 4. Rio de Janeiro (Estado). I. Título. II. Escola Nacional de Botânica Tropical.
CDD 577.35098153
IV Resumo
Os impactos do homem sobre a Terra atingiram tamanha dimensão que todos os ecossistemas encontram-se modificados em maior ou menor grau pela ação humana. Devido a isso, estamos presenciando uma onda de extinções de espécies por todo o planeta, o que traz a necessidade de se planejar adequadamente as ações de conservação. Embora a Mata Atlântica seja considerada uma prioridade global para conservação, faltam estudos que empreguem a abordagem de representação para fazer o planejamento de conservação dentro do bioma. Além disso, o alto grau de desmatamento e degradação da Mata Atlâtica torna necessário entender a influência de distúrbios sobre a sua biodiversidade. Ao longo desta tese, eu utilizei ferramentas de análise da estrutura filogenética de comunidades para tentar responder a algumas questões que são relevantes para a conservação da diversidade de árvores nativas da Mata Atlântica no Estado do Rio de Janeiro. No primeiro capítulo, eu verifiquei que florestas secundárias que se desenvolveram em áreas utilizadas como pastagens durante pelo menos 20 anos, e particularmente aquelas atingidas por um incêndio durante a sucessão, são dominadas pelas Asteraceae Moquiniastrum polymorphum (camará). Essa espécie pertence a uma linhagem recentemente evoluída de árvores e arbustos típica dos solos pobres do Cerrado. Eu concluí o predomínio de G. polymorphum nas áreas perturbadas deve-se à interação do fogo com a baixa fertilidade do solo (decorrente de décadas de uso dessas áreas como pastagens), à semelhança do que ocorre no Cerrado. O predomínio dessa linhagem recentemente evoluída nas áreas de floresta secundária faz com que essas comunidades apresentem uma idade média das famílias – tanto ponderada pela abundância de indivíduos como pela área basal de árvores – significativamente inferior à floresta ‘madura’, onde são encontradas linhagens bem mais antigas e tipicamente florestais.
Por fim, concluí que as florestas secundárias estabelecidas em áreas usadas por décadas para o pastejo têm um potencial limitado para a conservação da diversidade filogenética de árvores da Mata
Atlântica. No segundo capítulo, eu calculei a beta diversidade filogenética das comunidades de
árvores de 110 localidades distribuídas por todo o território do Rio de Janeiro. Através da combinação
V de métodos de análise multivariada e modelagem de distribuição eu pude predizer a composição filogenética de localidades não-amostradas no estado. Cada uma das principais fitofisionomias apresenta uma combinação característica de linhagens de angiospermas, sendo as restingas e as florestas estacionais mais associadas à presença da maior parte das Rosids, Ericales, Caryophyllales e Santalales. Já nas florestas pluviais e sobretudo nas florestas nebulares, foi verificada uma maior importância de linhagens como Magnoliids, Monocotiledôneas, Lamiids, Campanulids e
Melastomataceae. O modelo do primeiro eixo de ordenação apresenta a maior correlação com um mapa de vegetação remanescente, indicando que as restingas e florestas estacionais, assim como as linhagens associadas a elas, são as mais afetadas pela perda de habitat. Esses tipos de vegetação e as linhagens associadas a eles são considerados prioritários para conservação da Mata Atlântica no estado do Rio de Janeiro.
Palavras-chave: Mata Atlântica; Rio de Janeiro; beta diversidade filogenética; distúrbios; desmatamento.
VI
Abstract
Human impacts on Earth have reached such an extreme level that all ecosystems in the globe have been modified by human action to a certain degree. For this reason, we are witnessing a wave of species extinctions all around the planet, which brings the need to carefully plan conservation actions.
Although the Brazilian Atlantic forest is regarded as a global conservation priority, there is a lack of studies that employ the representation approach to carry out conservation planning within the biome.
Furthermore, the high degree of habitat loss and degradation make it necessary to understand the effect of disturbances on the Atlantic forest biodiversity. In this thesis I have employed analytical tools of phylogenetic community structure to answer some questions that are relevant to the conservation of native trees from the Atlantic forest of Rio de Janeiro state. In the first chapter, I found that secondary forests growing in areas that were used as pastures for at least 20 years, and particularly forests affect by fire during succession, are dominated by the Asteraceae Moquiniastrum polymorphum. This species belongs to a recently evolved lineage of shrubs and trees that is typical of savannas (Cerrado) growing on nutrient-poor soils. I concluded that the dominance of M. polymorphum in the most disturbed forests is due to an interaction between fire and low soil fertility, in a similar fashion as occurs in the Cerrado. As a consequence of the dominance of this late-diverging lineage in the secondary forests, these communities present a mean family age – both weighted by tree abundance and basal area – that is significantly lower than that of old-growth forests, where much older, typical forest-dwelling lineages are found. Finally, I conclude that Atlantic secondary forests growing in areas that were used as pastures for decades have a limited potential to conserve the phylogenetic diversity of Atlantic forest trees. In the second chapter, I calculated the phylogenetic beta diversity of tree communities from 110 sites spread all over the Rio de Janeiro state. By combining multivariate analysis and distribution modelling, I could predict the phylogenetic composition of unsampled sites within the state. Each of the main vegetation physiognomies is
VII characterized by a distinct set of angiosperm tree lineages, with seasonal forests an restingas being more associated to most Rosids, Ericales, Caryophyllales and Santalales. In rain forests, and even more in cloud forests, I found a higher importance of lineages such as Magnoliids, Monocots, Lamiids,
Campanulids and Melastomataceae.The model of the first ordination axis had the highest correlation with a map of remnant vegetation, indicating that restingas and seasonal forests, as well as its associated lineages, are much more affected by habitat loss than rain forests and cloud forests. So, restingas, seasonal forests and their associated lineages must be prioritized for conserving tree phylogenetic diversity in the Atlantic forest of Rio de Janeiro state.
Keywords: Atlantic forest; Rio de Janeiro; phylogenetic beta diversity; disturbance; deforestation.
VIII
Dedicatória
Dedico esta tese carinhosamente à memória de Elza Veiga e Miguel Yalom
IX Agradecimentos
Escrever uma tese de doutorado não é uma tarefa nada fácil. Para minha sorte eu pude contar com a ajuda e o apoio de muita gente, e se não fosse por isso, eu sinceramente não sei se teria êxito nessa empreitada. Gostaria então de expressar minha profunda gratidão a todas essas pessoas:
À minha orientadora Marinez Siqueira. Sinceramente, me faltam palavras para dizer o quanto eu sou grato por tudo o que ela fez por mim durante esses mais de quatro anos. Agradeço pela confiança depositada no meu trabalho, pelo respeito com que sempre me tratou, pela compreensão diante das minhas dificuldades e por todos os ensinamentos que me foram passados.
Ao meu amigo e incansável colaborador Guilherme Seger, sem dúvida um dos caras mais aguerridos que eu conheço, por ter botado a mão na massa junto comigo, sempre compartilhando generosamente seu conhecimento de Ecologia e análise de dados. Sua colaboração foi absolutamente imprescindível para que esta tese pudesse chegar ao nível de qualidade que chegou.
A todos os demais colaboradores que tanto me ajudaram nos dois capítulos da tese: Andrea Sánchez-
Tapia, Jerônimo Sansevero, João Marcelo Braga, Pablo Rodrigues, Ary de Oliveira-Filho e Felipe
Sodré. Agradeço em especial ao João Marcelo, por todo o apoio e ajuda ao longo desses anos.
Aos membros da banca, que gentilmente se dispuseram a ler e avaliar minha tese: Alexandre Quinet,
Bruno Rosado, Eline Martins, Fabio Scarano, Renato Crouzeilles e Richieri Sartori. Agradeço em especial ao Bruno, que também avaliou uma versão preliminar para a disciplina de Seminários II e fez a avaliação pré-tese em tempo recorde.
À CAPES pela bolsa concedida no período de março de 2013 a dezembro de 2015.
Ao Aníbal Carvalho e à Claudia Barros, coordenadores do PPG durante esse período, pela cordialidade e por sempre terem feito o melhor pelos alunos.
À Hevelise Peregrino, secretária do PPG, pela cordialidade e enorme disposição em ajudar.
A todos os funcionários da ENBT e da DIPEQ, pela agradável convivência e pelo apoio.
A todos os amigos e colegas da ENBT e da DIPEQ pela convivência cordial, pelo apoio e pelos
X momentos de descontração e risadas. Agradeço em especial ao Marcus Felippe, ao Elton John e ao
Leandro Cardoso, meus parceiros de coleta em Macaé de Cima, e ao Daniel Maurenza e ao Luiz
Santos.
Aos meus queridos amigos de longa data, em especial ao João Eduardo Mesquita (Fusca) e ao
Marcelo Adnet. A ajuda de vocês no momento em que eu mais precisava foi absolutamente fundamental.
À minha namorada Thais Souza, por ter me dado a paz e a tranquilidade que eu precisava para escrever esta tese, e por pacientemente escutar intermináveis explicações sobre ecologia, botânica, filogenia, árvores, conservação e etc.
À toda minha família, em especial aos meus pais Betina e Fernando.
A TODOS VOCÊS, MUITO OBRIGADO!!!!!!!!!!!!!!!!
XI
Sumário
Introdução geral …………………………………………………………………….1
Capítulo 1 - Secondary succession and fire disturbance promote dominance of a late- diverging tree lineage in a lowland Atlantic forest in Southeastern Brazil………...... 20
Capítulo 2 - Tree phylogenetic assembly and habitat loss in the Atlantic forest of Rio de Janeiro State – implications for the conservation of Angiosperm phylogenetic diversity…………………………………….………………………………...……...55
Considerações finais...... ……………………………………………………………82
XII Introdução Geral
1.1. A Crise da Biodiversidade e a Biologia da Conservação
Os impactos do homem sobre a Terra atingiram tamanha dimensão que todos os ecossistemas encontram-se modificados em maior ou menor grau pela ação humana (Vitousek et al. 1997). Devido a isso, estamos presenciando uma onda de extinções de espécies por todo o planeta, sendo quase todas causadas direta ou indiretamente pelo homem (Pimm e Raven 2000). Embora muitas espécies sejam ameaçadas pelas mudanças climáticas que já estão ocorrendo (Thomas et al. 2004), a perda e degradação de habitats ainda constituem a principal causa direta da erosão da biodiversidade
(Vitousek et al. 1997, Brooks et al. 2002, Dirzo e Raven 2003, Newton et al. 2015). Estimativas recentes indicam que a taxa de extinção atual é 1000 vezes maior do que seria esperado se o impacto humano não existisse; esse número, no entanto, certamente subestima a taxa real de extinção devido
à existência de muitas espécies ainda desconhecidas para a Ciência (Pimm et al. 2014). Como exemplo da enorme discrepância entre o que se conhece e o que não se conhece, podemos citar o fato de que já foram registradas 4.962 espécies de árvores em toda a Amazônia, porém estima-se que haja
16.000 espécies na região (ter Steege et al. 2013). Tanto de um ponto de vista ético quanto de uma visão utilitarista da biodiversidade, é urgente que essa extinção em massa seja freada ou ao menos minimizada (Primack e Rodrigues 2001). Para tanto, é necessário que se planeje adequadamente as ações de conservação, de forma que os recursos humanos e financeiros, ambos bastante limitados, sejam alocados da forma mais eficiente possível, maximizando a conservação da biodiversidade.
O planejamento da conservação da biodiversidade é frequentemente baseado no mapeamento da riqueza e endemismo de espécies (Margules e Pressey 2000, Whitaker et al. 2005, Hortal et al. 20015).
Na escala global, Myers et al. (2000) identificaram os chamados hotspots da biodiversidade, regiões que detêm uma altíssima riqueza de espécies endêmicas de plantas e vertebrados terrestres mas também encontram-se extremamente ameaçadas pela perda de habitat. O Brasil possui dois dos seus
1 biomas incluídos nessa lista de prioridades globais, a Mata Atlântica e o Cerrado (Myers et al. 2000).
Essa abordagem também vem sendo desenvolvida em escala de maior detalhe (i.e. regional), nas quais a maioria das ações de conservação é, na prática, realizada. Wernek et al. (2011) mapearam a ocorrência de 3.345 espécies de angiospermas endêmicas da Mata Atlântica, e verificaram que a variação na riqueza de espécies é fortemente influenciada pelo esforço de coleta, que está concentrado em algumas poucas localidades onde existem importantes centros de pesquisa botânica
(o ‘efeito museu’). Mesmo reconhecendo essa limitação dos dados, Wernek et al. (2011) apontaram como importantes centros de endemismo o litoral sul da Bahia, a região central do Espírito Santo, a
Serra dos Órgãos (RJ) e a região litorânea da Serra do Mar nos estados de São Paulo e Paraná.
Murray-Smith et al. (2009) realizaram uma modelagem preditiva da distribuição geográfica de espécies de árvore do gênero Myrcia (Myrtaceae) ocorrentes na Mata Atlântica, com o intuito de identificar centros de riqueza e endemismo de espécies de árvores dentro do bioma. Os autores mostraram que a riqueza de espécies de Myrcia é um bom indicativo da riqueza total de árvores, e identificaram centros de endemismo que coincidem com aqueles apontados por Wernek et al. (2011).
Já Martini et al. (2007) utilizaram a metodologia de inventário florestal desenvolvida e amplamente aplicada por Alwin Gentry em florestas neotropicais (e.g. Peixoto e Gentry 1990, Gentry 1995), para comparar a riqueza de espécies arbóreas do Parque Estadual da Serra do Conduru, no sul da Bahia, com diversas outras localidades de florestas tropicais onde a mesma metodologia de amostragem foi utilizada. Esses autores concluíram que as florestas da Serra do Conduru estão entre as mais ricas em espécie de árvores do mundo, abrigando um número de espécies notavelmente maior que outros sítios de Mata Atlântica onde a mesma metodologia de amostragem foi realizada (Martini et al. 2007). Um outro exemplo interessante é o trabalho de Harris et al. (2005), que procuraram distinguir os remanescentes florestais que abrigam o maior número de espécies de aves endêmicas e ameaçadas de extinção da Mata Atlântica. A identificação do fragmento florestal mais importante para a conservação dessas aves, a Reserva Biológica União (RJ), culminou com a implantação de um
2 corredor florestal ligando essa Unidade de Conservação à floresta contínua da Serra do Mar fluminense (Jenkins et al. 2010). Nesse caso, o reconhecimento de uma área altamente prioritária para a conservação de aves endêmicas da Mata Atlântica levou a uma ação concreta em escala local, favorecendo a sobrevivência dessas espécies endêmicas e ameaçadas.
Uma abordagem alternativa à dos ‘hotspots’ (i.e. mapeamento da riqueza e endemismo de espécies) para o planejamento de conservação em larga escala é baseada no conceito de complementariedade, e busca identificar áreas que constituam amostras representativas dos diversos ecossistemas encontrados dentro de uma região ou continente (Vane-Wright 1991, Olson e Dinerstein 1998,
Whittaker et al. 2005). A partir desse princípio, Udvardy (1975) procurou delimitar as principais regiões biogeográficas do planeta, e dentro de cada região foram reconhecidas diversas províncias biogeográficas, que supostamente constituem as ‘unidades da natureza’ a serem conservadas
(Whitaker et al. 2005). Dinerstein et al. (1995), por sua vez, realizaram uma avaliação do status de conservação de 191 ecorregiões terrestres da América Latina e Caribe, utilizando uma adaptação das categorias da IUCN para classificar o grau de ameaça de cada ecorregião. Nesse contexto, uma ecorregião foi definida como um conjunto geograficamente distinto de comunidades naturais que compartilham a mesma dinâmica ecológica e a grande maioria de suas espécies, apresentam condições ambientais semelhantes e interagem ecologicamente de forma crítica para a sua persistência no longo prazo (Dinerstein et al. 1995). Através da aplicação de uma série de critérios para avaliar a singularidade (distinctiveness) e o grau de ameaça, os autores identificaram um conjunto de 55 ecorregiões que foram altamente prioritárias para a conservação da biodiversidade nessa escala continental, incluindo todos os principais biomas brasileiros. Enquanto o Cerrado, a
Caatinga e o Pantanal foram considerados cada um sendo uma única ecorrregião, a Amazônia e a
Mata Atlântica foram subdivididas em várias ecorregiões. Da Mata Atlântica foram incluídas nessa lista de prioridades de conservação as florestas pluviais costeiras, as florestas semidecíduas do interior, as florestas com Araucária e as restingas, ou seja, todas as principais formações vegetacionais do
3 bioma. Critérios semelhantes foram empregados na escala global, permitindo a identificação de 238 ecorregiões terrestres, marinhas e de água doce que são altamente prioritárias para a conservação da biodiversidade da Terra (‘The global 200’; Olson e Dinerstein 1998, 2002). Essa lista das ‘200 globais’ inclui toda a Mata Atlântica, o Cerrado, o Pantanal e algumas regiões da Amazônia, como o sudoeste amazônico e a região do rio Negro-Juruá. Dessa forma, os resultados da abordagem de representação adotada por Dinerstein et al. (1995) em escala continental e por Oslo e Dinerstein (1998, 2002) em escala global vão de encontro à abordagem dos ‘hotspots’ proposta por Myers et al. (2000) ao apontar a Mata Atlântica como sendo uma altíssima prioridade para conservação, seguida pelo Cerrado.
Dentro da Mata Atlântica, no entanto, faltam estudos que apliquem o princípio da representação para identificar áreas prioritárias para conservação. Uma das formas de identificar locais que se complementam em termos de representação da diversidade biológica consiste em calcular a beta diversidade ou dissimilaridade da composição de espécies entre áreas (Dinerstein 1995, Whitaker et al. 2005). Vários estudos investigaram a beta diversidade de árvores da Mata Atlântica e a influência de fatores climáticos sobre a variação da composição de espécies (e.g., Oliveira-Filho e Fontes 2000), porém não em um contexto de planejamento de conservação (e.g., Bergamin et al. 2017). Tal aplicação seria de grande relevância, considerando que a Mata Atlântica constitui uma prioridade global para a conservação da biodiversidade.
1.2. A abordagem filogenética em estudos ecológicos e na conservação
O uso de hipóteses filogenéticas em estudos ecológicos vem sendo cada vez mais frequente, e tem possibilitado avanços expressivos em diversas áreas da Ecologia (Webb et al. 2002; Cavender-Bares et al. 2009; Vamosi et al. 2009). A lógica por trás dessa abordagem é simples. Há 150 anos atrás,
Darwin (1859) já havia percebido que espécies proximamente aparentadas tendem a exibir caracteristicas ecológicas semelhantes:
“Como as espécies de um mesmo gênero apresentam usualmente, embora de modo
4 algum invariavelmente, alguma similaridade nos hábitos e constituição, e sempre na
estrutura, a luta será geralmente mais severa entre espécies do mesmo gênero,
quando essas vêm a competir entre si, do que entre espécies de gêneros diferentes.”
É importante observar a ressalva feita por Darwin: “embora de modo algum invariavelmente”. Ou seja, embora exista uma clara tendência de alta similaridade ecológica entre espécies proximamente aparentadas, existem exceções a essa tendência, e portanto o grau de parentesco não pode ser utilizado como um indicativo da semelhança ecológica entre espécies (e.g. Swenson 2013, Gerhold et al. 2015).
De um ponto de vista estatístico, a importância de considerar as relações filogenéticas em estudos ecológicos reside no fato de que as espécies apresentam diferentes graus de parentesco entre si, e portanto não podem ser consideradas como observações independentes a priori (Felsenstein 1985).
Se as espécies de um mesmo gênero, por exemplo, são consideradas observações independentes em uma análise, a probabilidade de incutir no erro tipo I pode aumentar consideravelmente. No caso de várias dessas espécies co-ocorrerem em um determinado local, uma tentativa de correlacionar os atributos ecológicos das espécies com variáveis do ambiente pode gerar um resultado significativo simplesmente porque essas espécies são proximamente aparentadas e apresentam atributos filogeneticamente conservados. Assim, inicialmente os ecólogos procuraram controlar o efeito da filogenia em suas investigações, utlizando, por exemplo, contrastes filogeneticamente independentes
(e.g. Ackerly 2000), para que padrões puramente ecológicos pudessem ser detectados (Turner 2001).
Entretanto, desde o trabalho de Webb et al. (2002), ecólogos perceberam que a filogenia poderia ajudar a compreender a estrutura e a dinâmica de comunidades biológicas, assim como padrões de distribuição geográfica e de interações entre espécies (Donoghue 2008, Cavender-Bares et al. 2009).
A ideia básica por trás dessa abordagem é simples: a importância dos fatores que determinam a estrutura de uma comunidade pode ser inferida medindo-se (1) o grau de agrupamento ou dispersão filogenética das espécies que compõem a comunidade em relação a um pool regional de espécies; e
5 (2) o grau de conservação ou convergência filogenética dos atributos ecológicos dessas espécies
(Webb et al. 2002). Se, por exemplo, os atributos ecológicos que determinam a preferência de habitat dentre as espécies de uma dada região são filogeneticamente conservados, e as comunidades dessa região são compostas por espécies proximamente aparentadas, então a filtragem ambiental pode ser considerada um importante fator determinante da estrutura dessas comunidades (Kraft et al. 2007,
Cavender-Bares et al. 2009). Nesse caso, a correlação entre as variáveis ambientais e os atributos ecológicos das espécies é mediada pela filogenia, indicando conservação filogenética de nicho (Pillar e Duarte 2010). Outros fatores ecológicos importantes que podem influenciar a estrutura filogenética das comunidades incluem a competição (Webb et al. 2002), a herbivoria (Cavender-Bares et al. 2009), a facilitação (Valiente-Banuet et al. 2006) e diversos tipos de distúrbios (Verdú e Pausas 2007,
Dinnage 2009, Brunbjerg et al. 2012, Ding et al. 2012). Sob uma perspectiva conservacionista, é importante compreender o quanto a degradação de habitats decorrente da ação antrópica pode comprometer a diversidade filogenética das comunidades biológicas (e.g. Helmus et al. 2010). Se as espécies de uma região apresentam conservação filogenética dos atributos que determinam o grau de tolerância a um determinado tipo de distúrbio, as comunidades mais atingidas por esse distúrbio deverão ser compostas por um sub-conjunto de espécies proximamente relacionadas (Ding et al.
2012). Se o distúrbio for generalizado na região, poderá haver a extinção de linhagens mais sensíveis
à perturbação, levando a uma perda de diversidade filogenética (Wiens et al. 2010). Assim, compreender de que forma as diferentes linhagens presentes em uma dada região respondem a distúrbios antrópicos é essencial para determinar qual nível de modificação da paisagem seria tolerável, de forma a permitir a conservação do pool regional de linhagens.
A estrutura filogenética de uma comunidade e também os padrões de conservação/convergência de atributos ecológicos são fortemente dependente das escalas em que a análise é realizada (Cavender-
Bares et al. 2006, Swenson et al. 2006, Emerson e Gillespie 2008). Isso ocorre devido à ação de diversos processos ecológicos, evolutivos, biogeográficos e históricos em diferentes escalas de
6 espaço e tempo (Webb et al. 2002, Wiens e Donoghue 2004, Emerson e Gillespie 2008, Ricklefs
2008, Swenson et al. 2012). Na escala global, Crisp et al. (2009) verificaram uma forte conservação filogenética de bioma em linhagens de plantas. Essa conservação de biomas possivelmente está relacionada ao gradiente latitudinal de riqueza de espécies, uma vez que a maior parte das linhagens de plantas surgiu em um ambiente tropical porém não foi capaz de se adaptar ao clima mais frio de latitudes mais elevadas (Wies e Donoghue 2004, Donoghue 2008). Em escalas regionais, há evidências de que o nicho climático de espécies de plantas também é filogeneticamente conservado
(Prinzing et al. 2001, Giehl e Jarenkow 2012). Esse padrão de conservação do nicho climático é observado mesmo em regiões relativamente pequenas, onde os gradients ambientais não são tão drásticos (Hardy et al. 2012). Na escala local, Swenson et al. (2012) não encontraram um sinal filogenético nos atributos ecológicos de espécies arbóreas co-ocorrentes, tanto em florestas tropicais como temperadas. Staggemeier et al. (2010), por sua vez, encontraram um sinal filogenético nos padrões fenológicos de espécies de Myrtaceae em uma área de Mata Atlântica no litoral de São Paulo.
Dessa forma, o grau de conservação filogenética de nicho parece depender tanto da escala espacial e taxonômica da análise como também do atributos (ou atributos) ecológico(s) em questão.
Antes mesmo dos ecólogos começarem a incluir hipóteses filogenéticas em suas pesquisas, biólogos da conservação já se preocupavam em entender de que forma a informação filogenética poderia ser utilizada para auxiliar o direcionamento dos esforços de conservação (Vane-Wright et al. 1991, Faith
1992, Nee e May 1997). Alguns exemplos dessa aplicação incluem o cálculo da singularidade evolutiva (evolutionary distinctiveness) de espécies ameaçadas de extinção (Crozier 1997) e o mapeamento da diversidade filogenética em diferentes escalas espaciais para identificação de
‘hotspots’ de história evolutiva (Faith 1992, Faith et al. 2004). A ideia principal por trás dessa abordagem é a de que nós devemos salvar o máximo possível de história evolutiva dos organismos face à alarmante onda de extinções decorrente da ação humana. Embora haja controvérsias acerca de algumas justificativas para o uso da filogenia em conservação (Winter et al. 2013), não há dúvidas de
7 que a diversidade filogenética é um importante componente da biodiversidade a ser conservado. A grande questão é como a informação filogenética é utilizada, e o quanto essa abordagem consegue ser mais informativa em comparação à abordagem tradicional baseada em espécies (i.e. sem considerar as relações de parentesco das espécies). Uma possível abordagem consiste em calcular a beta diversidade filogenética para verificar o grau de diferenciação entre comunidades (e.g. Graham e Fine 2008, Morlon et al. 2011, Swenson et al. 2012), dentro de uma perspectiva de representação da diversidade de ecossistemas (ver Whitaker et al. 2005). A beta diversidade filogenética pode expressar a variação espacial na biodiversidade melhor do que a beta diversidade de espécies (Hardy et al. 2012, Duarte et al. 2014, Rosauer et al. 2014), sendo portanto uma ferramenta promissora para o planejamento de conservação.
1.3. A importância da conservação de espécies arbóreas tropicais
Florestas tropicais constituem os ecossistemas de maior biodiversidade do planeta, e provém uma série de serviços ambientais essenciais para a humanidade (Millenniun Ecosystem Assessment 2005,
Brandon 2014). Grande parte da riqueza de plantas (Gentry e Dodson 1987) e a maior parte dos serviços ecossistêmicos providos pela florestas tropicais devem-se às árvores (Brandon 2014), que constituem o principal componente estrutural desses ecossistemas. Árvores de florestas tropicais também fornecem abrigo, suporte físico e/ou recursos alimentares para uma infinidade de outros organismos, incluindo plantas epífitas, lianas, animais frugívoros, herbívoros, predadores de sementes, polinizadores, entre outros (Turner 2001, Novotny et al. 2006). Há evidências crescentes de que ecossistemas mais biodiversos apresentam maiores taxas de serviços ecossistêmicos, e que a perda de biodiversidade pode levar à diminuição desses serviços, comprometendo a qualidade de vida das populações humanas (Díaz et al. 2006, Cardinale et al. 2012). Dessa forma, a conservação da diversidade arbórea em florestas tropicais pode ser fundamental para a manutenção de grande parte dos serviços ecossistêmicos desempenhados por essas florestas (Brandon 2014), assim como para a
8 conservação de muitos outros organismos que compõem esses ecossistemas (e.g., Novotny et al.
2006). Embora a diversidade funcional seja considerada o principal componente da biodiversidade a afetar o funcionamento dos ecossistemas (Díaz e Cabido 2001), alguns estudos indicam que a diversidade filogenética pode ser também um importante preditor de funções ecossistêmicas (Flynn et al. 2011, Srivastava et al. 2012). Essa capacidade preditiva, no entanto, depende do grau de conservação filogenética dos atributos funcionais das espécies em questão (Winter et al. 2013); ou seja, se os atributos funcionais não são filogeneticamente conservados, a diversidade filogenética não pode ser utilizada para predizer a diversidade functional (Swenson et al. 2012). Ainda assim, essa possível relação entre a diversidade filogenética e o funcionamento dos ecossistemas pode ser mais um importante argumento a favor do uso da informação filogenética no planejamento de conservação
(Rolland et al. 2012).
1.4. A Mata Atlântica no Estado do Rio de Janeiro
O Estado do Rio de Janeiro é considerado um dos principais centros de endemismo de plantas da
Mata Atlântica (Murray-Smith et al. 2008). Ainda que esse padrão seja fortemente influenciado pela variação espacial no esforço de coleta (Werneck et al. 2009), não há dúvidas de que o Rio de Janeiro apresenta uma altíssima biodiversidade tanto de plantas quanto de outros grupos (e.g., aves), sendo por isso considerado estratégico para a conservação (Bergallo et al. 2009, Jenkins et al. 2011). Apesar de apresentar uma área que corresponde a menos de 5% da área total da Mata Atlântica, o estado do
Rio de Janeiro abriga uma proporção expressiva da riqueza de angiospermas do bioma. Segundo dados disponíveis na Flora do Brasil (Flora do Brasil 2020 em construção; acesso em 7 de maio de
2017), de 15.010 espécies de angiospermas nativas do bioma Mata Atlântica, 7.404 espécies (49%) são encontradas no estado Rio de Janeiro, e de 3.316 espécies de árvores nativas do bioma, 1.853
(56%) ocorrem no estado. Essa elevada riqueza de plantas em uma área geograficamente tão restrita pode ser atribuída em grande parte à expressiva diversidade de habitats existente no estado (Costa et
9 al. 2009). Dentre as várias fisionomias vegetacionais encontradas no Rio de Janeiro, as principais são a floresta estacional semidecidual e a floresta ombrófila densa, que correspondem a 47% e 41% da
área do estado, respectivamente (Figura 1). Em menor extensão também são encontradas formações pioneiras (manguezais e restingas), a floresta ombrófila mista (i.e., com a presença da conífera
Araucaria angustifolia) e a savanna estépica (Costa et al. 2009), também chamada de floresta caducifólia ou mata seca. Até mesmo um pequeno enclave de Cerrado pode (ou podia) ser encontrada no vale do rio Paraíba do Sul, próximo à divisa com São Paulo (Fidalgo et al. 2009). Essas fisionomias de vegetação diferem marcadamente em relação ao grau de perda e fragmentação de habitat. Enquanto a floresta estacional semidecidual encontra-se reduzida a 10% da área original no estado, e 48% dessa
área remanescente encontram-se em fragmentos de no máximo 100 hectares, a floresta ombrófila densa ainda apresenta 34,8% da sua cobertura original, e 89% dessa cobertura remanescente estão contidos em fragmentos maiores que 100 hectares (Fidalgo et al. 2009). A grande diversidade de habitats existente no estado do Rio de Janeiro e a maneira fortemente enviesada como a vegetação remanescente está distribuída entre os diferentes tipos vegetacionais representa uma desafio do ponto de vista da conservação, principalmente se considerarmos a abordagem que busca conservar amostras representativas dos diferentes ecossistemas existentes no estado. Além da perda de habitat, a vegetação está sujeita a uma série de distúrbios de origem antrópica que podem comprometer a integridade biótica dos remanescentes. Dentre esses distúrbios destaca-se o fogo, que representa um importante fator de degradação dos ecossistemas no estado do Rio de Janeiro (Tanizaki-Fonseca e
Bohrer 2009). Levando em conta que o fogo não exerceu uma pressão seletiva significativa durante a evolução da biota das florestas pluviais tropicais (Cochrane 2003), a alta incidência de incêndios sobre os remanescentes de Mata Atlântica pode comprometer significativamente a conservação da biodiversidade no estado do Rio de Janeiro.
Esse projeto se propõe a contribuir para a conservação da diversidade de angiospermas arbóreas e
10 arbustivas no Estado do Rio de Janeiro. O objetivo principal é identificar áreas, tipos de vegetação e linhagens de árvores que são prioritárias para a conservação da diversidade filogenética de angiospermas arbóreas e arbustivas de Mata Atlântica ocorrentes no Estado do Rio de Janeiro, considerando: (1) As respostas das linhagens a distúrbios na escala local, tendo como caso de estudo a Reserva Biológica de Poço das Antas; e (2) A distribuição das linhagens em relação à distribuição espacial dos remanescentes florestais na escala do estado. No capítulo 1, eu investiguei a estrutura filogenética das comunidades de árvores de florestas secundárias estabelecidas em antigas pastagens dentro da Reserva Biológica de Poço das Antas, e o efeito do fogo sobre a essas comunidades. No capítulo 2, eu realizei uma modelagem preditiva da diversidade filogenética alfa e beta de comunidades de árvores de todo o estado do Rio, e correlacionei os modelos com um mapa de vegetação remanescente, com o intuito de identificar os tipos de vegetação e as respectivas linhagens associadas que são prioritários para a conservação. Dessa forma, a tese aborda os efeitos da perda e degradação de habitats tanto na escala local (i.e. a ReBio de Poço das Antas) quanto na escala regional
(i.e. o estado do Rio de Janeiro). Espera-se, assim, fornecer subsídios que ajudem no direcionamento de ações que visem à conservação da diversidade de árvores da Mata Atlântica no estado do Rio de
Janeiro.
Referências bilbiográficas
Ackerly, D.D. 2000. Taxon sampling, correlated evolution, and independent contrasts. Evolution 54:
1480-1492.
Bergallo, H.G., Uzêda, M.C., Fidalgo, E.C., Alves, M.A.S., Rocha, C.F.D., Van Sluys, M., Costa,
T.C.C., Costa, M.B., Santos, M.A., Cozzolino, A.C.R. e Alencar, R.S. 2009. Conservação da
biodiversidade da Mata Atlântica no Estado do Rio de Janeiro: uma nova abordagem. In:
Bergallo et al. (orgs). Estratégias e ações para a conservação da biodiversidade no Estado do
Rio de Janeiro. Rio de Janeiro: Instituto Biomas. p.23-32.
11 Brandon, K. 2014. Ecosystems services from tropical forests: review of current services. CGD
Working Paper 380. Washington, DC: Center for Global Development.
Brooks, T.M., Mittermeier, R.A., Mittermeier, C.G., Fonseca, G.A.B., Rylands, A.B., Konstant, W.R.,
Flick, P., Pilgrim, J., Oldfield, S., Magin, G. e Hilton-Taylor, C. 2002. Habitat loss and
extinction in the hotspots of biodiversity. Conservation Biology 16: 909-923.
Brum, F.T., Kindel, A., Hartz, S.M. e Duarte, L.S. 2012. Spatial and phylogenetic structure drive
frugivory in Tyrannidae birds across the range of Brazilian Araucaria forests. Oikos 121:
899-906.
Brunbjerg K.A., Borchsenius F., Eiserhardt W.L., Ejrnæs R., Svenning J.-C. 2012. Disturbance drives
phylogenetic community structure in coastal dune vegetation. Journal of Vegetation Science
23:1082–1094.
Cavender-Bares J., Keen A., Miles B. 2006 Phylogenetic structure of Floridian plant communities
depends on taxonomic and spatial scales. Ecology 87:S109–S122.
Cavender-Bares, J., Kozak, K.H., Fine, P.V.A. e Kembel, S.W. 2009. The merging of community
ecology and phylogenetic biology. Ecology Letters 12: 693-715.
Cardinale, B.J., Duffy, J.E., Gonzalez, A., Hooper, D.U., Perrings, C., Venail, P., Narwani, A., Mace,
G.M., Tilman, D., Wardle, D.A., Kinzig, A.P., Daily, G.C., Loreau, M., Grace, J.B.,
Larigauderie, A., Srivastava, D.S. e Naeem, S. 2012. Biodiversity loss and its impacts on
humanity. Nature 486: 59-67.
Crisp M.D., Arroyo M.T.K., Cook, L.G., Gandolfo M.A., Jordan G.J., McGlone M.S., Weston P.H.,
Westoby M., Wilf P. e Linder H.P. 2009. Phylogenetic biome conservatism on a global scale.
Nature 458:754–756.
Cochrane M.A. 2003. Fire science for rainforests. Nature 421:913–919.
Costa, T.C.C., Fidalgo, E.C.C., Santos, R.F., Rocha, J.V., Metzgre, J.P., Vicens, R.S., Tanizaki-
Fonseca, K. e Bohrer, C.B.A. 2009. Diversidade de paisagens no estado do Rio de Janeiro.
12 In: Bergallo et al. (orgs). Estratégias e ações para a conservação da biodiversidade no Estado
do Rio de Janeiro. Rio de Janeiro: Instituto Biomas. p.101-110.
Crozier, R.H. 1997. Preserving the information content of species: genetic diversity, phylogeny, and
conservation worth. Annual Review of Ecology and Systematics 28: 243-268.
Darwin, C. 1859. The origin of species.
Dean, W. 1996. A ferro e fogo: a história e a devastação da Mata Atlântica brasileira. Companhia das
Letras – São Paulo – 484pp.
Díaz, S. e Cabido, M. 2001. Vive la différence: plant functional diversity matters to ecosystem
processes. Trends in Ecology and Evolution 16: 646-655.
Díaz, S., Fargione, J., Chapin III, F.S. e Tilman, D. 2006. Biodiversity loss threatens human well-
being. PLoS Biology 4: 1300-1305.
Dinerstein, E., Olson, D.M., Graham, D.J., Webster, A.L., Pimm, S.A., Bookbinder, M.A. e Ledec,
G. 1995. A conservation assessment of the terrestrial Ecoregions of Latin America and The
Caribbean. The World Bank, Washington, D.C.
Dinnage, R. 2009. Disturbance alters the phylogenetic composition and structure of plant
communities in an old field system. PLoS ONE 4:e7071
Ding Y., Zang, R., Letcher, S.G., Liu, S. e He, F. 2012. Disturbance regime changes the trait
distribution, phylogenetic structure and community assembly of tropical rain forests. Oikos
121:1263–1270.
Donoghue, M.J. 2008. A phylogenetic perspective on the distributoin of plant diversity. Proceedings
of the National Academy of Sciences 105: 11549-11555.
Emmerson, B.C. e Gillespie, R.G. 2008. Phylogenetic analysis of community assembly and structure
over space and time. Trends in Ecology and Evolution 23: 619-630
Faith, D.P. 1992. Conservation evaluation and phylogenetic diversity. Biological Conservation 61:
1-10.
13 Faith, D.P, Reid, C.A.M. e Hunter, J. 2004. Integrating phylogenetic diversity, complementarity, and
endemism for conservation assessment. Conservation Biology 18: 255-261.
Felsenstein, J. 1985. Phylogenies and the comparative method. The American Naturalist 125: 1-15.
Fidalgo, E.C.C., Uzêda, M.C., Bergallo, H.G., Costa, T.C.C. e Abreu, M.B. 2009. Distribuição dos
remanescentes vegetais no estado do Rio de Janeiro. In: Bergallo et al. (orgs). Estratégias e
ações para a conservação da biodiversidade no Estado do Rio de Janeiro. Rio de Janeiro:
Instituto Biomas. p.91-99.
Flynn, D.F.B., Mirotchnick, N., Jain, M., Palmer, M.I. e Naeem, S. 2011. Functional and phylogenetic
diversity as predictors of biodiversity-ecosystem function relationships. Ecology 92: 1573-
1581.
Flora do Brasil 2020 em construção. Jardim Botânico do Rio de Janeiro. Disponível em: <
http://floradobrasil.jbrj.gov.br/ >. Acesso em: 7 de Maio de 2017.
Gentry, A.H. 1995. Patterns of diversity and floristic composition in neotropical montane forests. In
Churchill, S.P., Balslev, H., Forero, E. e Luteyn, J.L. (eds.). Biodiversity and conservation
of neotropical montane forests. The New York Botanical Garden. Pp. 103-126.
Gentry, A.H. e Dodson, C. 1987. Contribution of nontrees to species richnessa of a tropical rain forest.
Biotropica 19: 149-156.
Gerhold, P., Cahill Jr, J.F., Winter, M., Bartish, I.V., e Prinzing, A. 2015. Phylogenetic patterns are
not proxies of community assembly mechanisms (they are far better). Functional Ecology
29:600-615.
Giehl, E.L. e Jarenkow, J.A. 2012. Niche conservatism and the differences in species richness at the
transition of tropical and subtropical climates in South America. Ecography 35: 933-943.
Graham, C.H. e Fine, P.V.A. 2008. Phylogenetic beta diversity: linking ecological and evolutionary
processes across space in time. Ecology Letters 11: 1265-1277.
Hardy, O.J., Couteron, P., Munoz, F., Ramesh, B.R. e Pélissier, R. 2012. Phylogenetic turnover in
14 tropical tree communities: impact of environmental filtering, biogeography and mesoclimatic
niche conservatism. Global Ecology and Biogeography 21: 1007-1016.
Harris, G.M., Jenkins, C.N. e Pimm, S.L. 2005. Refining biodiversity conservation priorities.
Conservation Biology 19: 1957-1968.
Helmus, M.R., Keller, W., Paterson, M.J., Yan, N.D., Cannon, C.H. e Rusak, J.A. 2010. Communities
contain closely related species during ecosystem disturbance. Ecology Letters 13: 162-174.
Hortal, J., Bello, F., Diniz-Filho, J.A.F., Lewinsohn, T.M., Lobo, J.M. e Ladle, R.J. 2015. Seven
shortfalls that beset large-scale knowledge of biodiversity. Annual review of Ecology,
Evolution and Systematics 46: 523-549.
Jenkins, C.N., Pimm, S.L. e Alves, M.A.S. 2011. How conservation GIS leads to Rio de Janeiro,
Brazil. Natureza & Conservação 9: 152-159.
Kraft, N.J.B., Cornwell, W.K., Webb, C.O. e Ackerly, D.D. 2007. Trait evolution, community
assembly, and the phylogenetic structure of ecological communities. The American
Naturalist 170: 271-283.
Margules, C.R. e Pressey, R.L. 2000. Systematic conservation planning. Nature 405: 243-253.
Martini, A.M., Fiaschi, P., Amorim, A.M. e Paixão, J.L. 2007. A hot-point within a hot-spot: a high
diversity site in Brazil’s Atlantic forest. Biodiversity and Conservation 16: 3111-3128.
Millennium Ecosystem Assessment. 2005. Ecosystems and human well-being: current state and
trends. Island Press, Washington, DC, USA.
Morlon, H., Scwilk, D.W., Bryant, J.A., Marquet, P.A., Rebelo, A.G., Tauss, C., Bohannan, B.J.M. e
Green, J. 2011. Spatial patterns of phylogenetic diversity. Ecology Letters 14: 141-149.
Murray-Smith, C., Brummitt, N.A., Oliveira-Filho, A.T., Bachman, S., Moat, J., Lughadha, E.M.L.
e Lucas, E.J. 2008. Plant diversity hotspots in the Atlantic coastal forests of Brazil.
Conservation Biology 23: 151-163.
Myers, N., Mittermeier, R. A., Mittermeier, C. G., Fonseca, G. A. B. & Kent, J. 2000. Biodiversity
15 hotsposts for conservation priorities. Nature 403: 853-858.
Nee, S. e May, R.M. 1997. Extinction and the loss of evolutionary history. Science 278: 692-694.
Novotny, V., Drozd, P., Miller, S.E., Kulfan, M., Janda, M., Basset, Y. e Weiblen, G.D. 2006. Why
are there so many species of herbivorous insects in tropical rainforests. Science 313: 1115-
1118.
Oliveira-Filho, A.T. & Fontes, M.A.L. 2000. Patterns of floristic differentiation among Atlantic
forests in southeastern Brazil and the influence of climate. Biotropica 32: 793-810.
Peixoto, A.L. e Gentry, A.H. 1990. 1990. Diversidade e composição florística da mata de tabuleiro
na Reserva Florestal de Linhares (Espírito Santo, Brasil). Revista Brasileira de Botânica
13:19-25.
Pillar, V.P. e Duarte, L.S. 2010. A framework for metacommunity analysis of phylogenetic structure.
Ecology Letters 13: 587-596.
Pimm, S.L., Jenkins, C.N., Abell, R., Brooks, T.M., Gittleman, J.L., Joppa, L.N., Raven, P.H.,
Roberts, C.M. e Sexton, J.O. 2014. The biodiversity of species and their rates of extinction,
distribution and protection. Science 344: 1246752.
Pimm, S.L. e Raven, P. 2000. Extinction by numbers. Nature 403: 843-845.
Primack, R.B. e Rodrigues, E. 2001. Biologia da Conservação. Londrina. 328 pp.
Prinzing, A. 2001. The niche of higher plants: evidence for phylogenetic conservatism. Proceedings
of the Royal Society of London B 268: 2383-2389.
Fundação SOS Mata Atlântica e Instituto Nacional de Pesquisas Espaciais-INPE. 2011. Atlas dos
remanescentes florestais da Mata Atlântica período 2008-2010. São Paulo. 122 pp.
Ricklefs, R.E. 2008. Disintegration of the ecological community. American Naturalist 172: 741-750.
Rolland, J., Cadotte, M.W., Davies, J., Devictor, V., Lavergne, S., Mouquet, N., Pavoine, S.,
Rodrigues, A., Thuiller, W., Turcati, L., Winter, M., Zupan, L., Jabot, F. & Morlon, H. 2012
Using phylogenies in conservation: new perspectives. Biology Letters 8: 692-694.
16 Rosauer, D.F., Ferrier, S., Williams, K.J., Manion, G., Keogh, J.S. e Laffan, S.W. 2014. Phylogenetic
generalised dissimilarity modelling: a new approach to analysing and predicting spatial
turnover in the phylogenetic composition of communities. Ecography 37: 21-32.
Srivastava, D., Cadotte, M.W., MacDonald, A.A.M., Maroshia, R.G. e Mirotchnick, N. 2012.
Phylogenetic diversity and the functioning of ecosystems. Ecology Letters 15: 637-648.
Staggemeier, V.G., Diniz-Filho, J.A.F. e Morellato, L.P.C. 2010. The shared influence of phylogeny
and ecology on the reproductive patterns of Myrteae (Myrtaceae). Journal of Ecology 98:
1409-1421.
Swenson, N.G. 2013. The assembly of tropical tree communities - the advances and shortcomings of
phylogenetic and functional trait analyses. Ecography 36:264-276.
Swenson, N.G., Enquist, B.J., Pither, J., Thompson, J. e Zimmerman, J.K. 2006. The problem and
promise of scale dependency in community phylogenetics. Ecology 87: 2418-2424.
Swenson, N.G., Erickson, D.L., Mi, X., Bourg, N.A., Forero-Montana, J., Ge, X., Howe, R., Lake,
J.K., Liu, X., Ma, K. et al. 2012. Phylogenetic and functional alpha and beta diversity in
temerate and tropical tree communities. Ecology 93: S112-S125.
Tanizaki-Fonseca, K. e Bohrer, C.B.A. 2009. O fogo como fator de degradação de ecossistemas de
Mata Atlântica no Estado do Rio de Janeiro. In: Bergallo et al. (orgs). Estratégias e ações
para a conservação da biodiversidade no Estado do Rio de Janeiro. Rio de Janeiro: Instituto
Biomas. p. 81-90. ter Steege H, Pitman NCA, Sabatier D, Baraloto C, Salomão RP, Guevara JE, Phillips OL, Castilho
CV, Magnusson WE, Molino JF, et al. 2013. Hyperdominance in the Amazonian tree flora.
Science 342:1243092.
Thomas, C.D., Cameron, A., Green, R.E., Bakkenes, M., Beaumont, L.J., Collingham, Y.C., Erasmus,
B.F.N., Siqueira, M.F., Grainger, A., Hannah, L., Hughes, L., Huntley, B., van Jaarsveld, A.,
Midgley, G.F., Miles, L., Ortega-Huerta, M.A., Peterson, A.T., Phillips, O.L. e Williams, S.E.
17 2004. Extinction risk from climate change. Nature 427: 145-148.
Turner, I.M. 2001. The ecology of trees in the tropical rain forest. Cambridge University Press.
Valiente-Banuet A, Rumebe AV, Verdú M, Callaway RM. 2006. Modern Quaternary lineages
promote diversity through facilitation of ancient Tertiary lineages. Proceedings of the
National Academy of Sciences USA 103:16812–16817.
Vane-Wright, R.I., Humphries, C.J. e Williams, P.H. 1991. What to protect? – Systematics and the
agony of choice. Biological Conservation 55: 235-254.
Verdú M, Pausas JG. 2007. Fire drives phylogenetic clustering in Mediterranean Basin woody plant
communities. Journal of Ecology 95:1316–1323.
Vitousek, P.M., Mooney, H.A., Lubchenco, J. e Melillo, J.M. 1997. Human domination of Earth’s
ecosystems. Science 277: 494-499.
Webb, C.O., Ackerly, D.D., McPeek, M.A. e Donoghue, M.J. 2002. Phylogenies and community
ecology. Annual Reveiew of Ecology, Evolution and Systematics 33: 475-505.
Webb, C.O., Ackerly, D.D. e Kembel, S.W. 2008. Phylocom: software for the analysis of
phylogenetic community structure and trait evolution. Bioinformatics 24: 2098-2100.
Wernek, M. S., Sobral, M.E.G., Rocha, C.T.V., Landau, E.C. e Stehmann, J.R. 2011. Distribution
and endemism of angiosperms in the Atlantic forest. Natureza & Conservação 9: 188-193.
Whitaker, R.J., Araújo, M.B., Jepson, P., Ladle, R.J., Watson, J.E.M. e Willis, K.J. 2005.
Conservation biogeography: assessment and prospect. Diversity and Distributions 11: 3-23.
Wiens J.J., Ackerly D.D., Allen A.P., Anacker B.L., Buckley L.B., Cornell H.V., Damschen E.I.,
Davies T.J., Grytnes J.-A., Harrison S.P., Hawkins B.A., Holt R.D., McCain C.M. e Stephens
P.R. 2010. Niche conservatism as an emerging principle in ecology and evolutionary biology.
Ecology Letters 13:1310–1324.
Wiens, J.J., Donoghue, M.J. 2004. Historical biogeography, ecology and species richness. Trends in
Ecology and Evolution 19: 639-644.
18 Winter, M., Devictor, V. e Schweiger, O. 2013. Phylogenetic diversity and nature conservation:
where are we? Trends in Ecology and Evolution 28: 199-204.
Figura 1. Mapa do Estado do Rio de Janeiro.
19
Capítulo 1
Secondary succession and fire disturbance promote dominance of a late-diverging tree lineage in a lowland Atlantic forest in
Southeastern Brazil*
*manuscrito revisado a ser submetido ao periódico Plant Ecology & Diversity
20 Secondary succession and fire disturbance promote dominance of a late-diverging tree lineage in a lowland Neotropical forest
Pablo Viany Prietoa*
Email: [email protected] – Phone number: +55 21 98462-5600
Guilherme Dubal Santos Segerb
Email: [email protected] – Phone number: +55 51 8224-3033
Andrea Sánchez-Tapiaa
Email: [email protected] – Phone number: +55 21 3875-6201
Jerônimo Boelsums Barreto Sanseveroa,c
Email: [email protected] – Phone number: +55 21 3875-6218
João Marcelo Alvarenga Bragaa
Email: [email protected] – Phone number: +55 21 3204-2139
Pablo José Francisco Pena Rodriguesa
Email: [email protected] – Phone number: +55 21 3204-2123
a Instituto de Pesquisas Jardim Botânico do Rio de Janeiro, Pacheco Leão 915, Rio de Janeiro,
RJ, 22460-030, Brazil b Programa de Pós-Graduação em Biologia de Fungos, Algas e Plantas, Laboratório de
Sistemática Vegetal, Universidade Federal de Santa Catarina, CP 476, Florianópolis, SC,
88040-900, Brazil c Departamento de Ciências Ambientais - DCA, Instituto de Florestas - IF, Universidade Federal
Rural do Rio de Janeiro - UFRRJ, BR 465 Km 07, Seropédica, RJ, 23890-000, Brazil
*Corresponding author
21
Notes on contributors
Pablo Viany Prieto is a plant ecologist. His research interests include community ecology, plant conservation and restoration ecology.
Guilherme Dubal dos Santos Seger is a plant ecologist. His research interests include plant phenology and the phylogenetic and functional structure of plant communities.
Andrea Sánchez-Tapia is a quantitative ecologist. Her research interests include invasion biology, fire ecology and the functional and phylogenetic structure of plant communities.
Jerônimo Boelsums Barreto Sansevero is a plant ecologist. His research interests include forest succession, restoration ecology and functional ecology of tree communities.
João Marcelo Alvarenga Braga is a plant taxonomist. His research interests include the taxonomy of families Marantaceae and Balanophoraceae, and floristic surveys in the Atlantic forest.
Pablo José Francisco Pena Rodrigues is an ecologist. His research interests include general aspects of forest ecology, mainly related to anthropogenic impacts on vegetation.
22 Secondary succession and fire disturbance promote dominance of a late-diverging tree lineage in a lowland Neotropical forest
Abstract
Background: Variations among woody plants in the response to disturbances such as fire may be explained by lineage age.
Aims: We tested whether lowland tropical tree lineages colonizing secondary forests are more late- diverging than clades from old-growth forests, and whether tree phylogenetic beta diversity from old- growth to secondary forests is higher in burned than non-burned secondary forests.
Methods: We sampled tree communities in old-growth forests and in secondary forests with distinct disturbance histories (burned and unburned). We calculated mean family age in each plot, and tested for differences among forest types using ANOVA. A phylogenetic fuzzy-weighting procedure was employed to generate a matrix describing the abundance of tree clades per plot, which was then analysed using a principal coordinate analysis.
Results: Most clades found in old-growth forests are underrepresented in secondary stands, which23 have been densely colonized by a species from a young lineage that is not found in old-growth forests.
Phylogenetic beta diversity was found to be higher between unburned secondary forests and old- growth forests than between burned secondary forests and old-growth forests.
Conclusions: The capacity of Neotropical trees to colonize secondary forests and persist after fire disturbance may depend on the timing of origin of distinct lineages.
Key words: Atlantic forest, phylogenetic structure, community assembly, fire ecology, land use.
23 INTRODUCTION
Plant lineages may differ strongly in their ability to cope with various types of disturbances they are subjected to, including natural events such as wildfires, landslides and hurricanes, and anthropogenic events such as logging and plowing. Because tolerance to disturbance varies widely among plant clades, disturbance stands as an important driver of phylogenetic structure in plant communities as distinct as Mediterranean woody vegetation (Verdú and Pausas 2007), old fields
(Dinnage 2009), coastal sand dunes (Brunbjerg et al. 2012) and tropical rain forests (Ding et al. 2012).
In all these studies, the authors found that more disturbed communities are composed of a non-random subset of closely-related species, suggesting that tolerance to disturbance is phylogenetically conserved. An important cue to understand the relationship between disturbance and plant phylogenetic structure comes from fire-prone Mediterranean woody vegetation, where between- species variation in trait syndromes related to establishment after fire disturbance is explained by the age of plant lineages (Verdú 2000), with more recent lineages that originated during the Quaternary showing a higher capacity of establishing after a fire than more ancient species of Tertiary origin
(Valiente-Banuet et al. 2006). In this case, differences in ecological traits between lineages of contrasting ages reflect the environmental conditions under which each lineage arose: young
Quaternary lineages, which emerged under a drier (Mediterranean) climate, are better able to colonize disturbed areas than older lineages emerged under a more umid, tropical climate in the Tertiary
(Verdú 2000, Verdú et al. 2003). Under phylogenetic conservatism of ecological traits, lineages emerged at different points in time and under contrasting environmental conditions will track distinct contemporary habitats (Ackerly 2003). The relationship between lineage age and tolerance to disturbance may be a more general pattern, because there has been a global-scale contraction of closed-canopy forests and an expansion of more open, fire-prone vegetation from the Eocene to the
Miocene (Bond and Midgley 2012). So, ancient forest lineages that kept their ecological traits over time are predicted not to establish successfully in the ‘novel’, open habitats of fire-prone grasslands
24 and savannas; instead, they are expected to track the closed-canopy environment that resembles their old habitat of origin.
Natural regeneration in tropical forest sites altered by human activities is complex, and forest recovery and patterns are difficult to predict (Brown and Lugo 1990; Guariguata and Ostertag 2001;
Norden et al. 2015). Factors such as past land use (e.g., the conversion of forests into pastures and agriculture), introduction of invasive species, and disturbances (e.g., fire, grazing) exert a strong influence on the rate of recovery and the trajectory of forest succession (Mesquita et al. 2001; Colón and Lugo 2006; Scervino and Torezan, 2015). Fire in tropical forests may increase tree mortality and lead to changes in species composition, community structure, and ecosystem functioning (Cochrane and Laurance 2002; Barlow and Peres 2008; Oliveras et al. 2014). Ultimately, past disturbances may exert a filtering effect that selects for species with a narrow range of ecological traits, strong influencing tree community structure in regenerating tropical forests (Jakovac et al. 2016).
Considering the widespread conservatism of ecological traits among Neotropical forest tree lineages
(Souza et al. 2016), we can hypothesize that tree communities subjected to contrasting disturbance histories will show a distinct phylogenetic composition (see Wiens et al. 2010, Ding et al. 2012).
Furthermore, because lineage age may explain the response to disturbance (Verdu 2000, Valiente-
Banuet et al. 2006), we can expect that tropical tree clades colonizing more disturbed sites have evolved more recently than those occurring in undisturbed forests. This may represent an important advance in understanding drivers of species and phylogenetic beta diversity during tropical succession, increasing our predictive power about vegetation responses to human disturbance.
In this paper, we tested whether tropical tree communities are phylogenetically structured along a gradient of disturbance history in a lowland Atlantic forest. More specifically, we tested the following hypotheses: (1) Tree lineages colonizing secondary forests are younger than clades present in old-growth forests; and (2) Tree phylogenetic beta diversity from old-growth to secondary forests is higher in burned than non-burned secondary forests. To perform this test we sampled tree
25 communities in old-growth forests, unburned secondary forests and secondary forests that were burned during the course of succession in a lowland Atlantic forest in southeastern Brazil. To test the first hypothesis we extracted estimates on family ages from the literature to calculate mean family age in each sampled community, and tested for differences among distinct forest types using
ANOVAs. To test the second hypothesis we used data from an updated published angiosperm phylogeny to construct a phylogenetic hypothesis encompassing all sampled species. Then we performed an ordination with the phylogeny-weighted community data, and tested for differences in phylogenetic structure among communities using null models and ANOVAs. We discuss how our findings relate to the understanding of Neotropical forest succession and to the conservation of
Atlantic forest tree phylogenetic diversity.
METHODS
The study was conducted at Poço das Antas Biological Reserve (Poço das Antas) (22º32’17’’S,
42º16’50’’W), in Rio de Janeiro State, southeastern Brazil. The reserve covers 5160 ha. Mean annual temperature is 25.5 ºC and mean annual rainfall is 1900 mm, with a moderate dry season from June to August. The topography is formed by small round hills, with a maximum height of 200 m, and alluvial plains (Lima et al. 2006). Ultisols with high aluminum content and low phosphorus availability are predominant (Moraes et al. 2008). The vegetation is composed of remnants of lowland
Atlantic Rain Forest (sensu Oliveira-Filho and Fontes 2000). Around 50% of Poço das Antas’ area is covered by old-growth forests, and the remaining area is covered by secondary forests and pastures of exotic grasses (Melinis minutiflora P. Beauv., Megathyrsus maximus (Jacq.) B.K.S. and Urochloa mutica (Forssk.) T.Q. Nguyen.) (Lima et al. 2006). Pastures also constitute the predominant type of land-use in the landscape surrounding the Reserve (Rocha et al. 2009). Fire is frequently used to renovate pastures and clean land (Tanizaki-Fonseca and Bohrer 2009), and occasionally gets out of control and spreads into the Reserve. There is no register of natural fires. The tree flora in this lowland
26 region is comprised exclusively of Angiosperm species (Oliveira-Filho and Fontes 2000, Carvalho et al. 2008).
We sampled tree communities in a total of nine sites distributed across three distinct forest types, with three sites representing each forest type: old-growth forest, burned secondary forest and unburned secondary forest. We determined past land-use and disturbance history of each site by examining aerial photographs and satellite images, and by conducting interviews with the staff of the
Poço das Antas Biological Reserve. One old-growth site and three unburned secondary forest sites are located in a large fragment of 2727 ha, while two old-growth forest sites and three burned secondary forest sites are located in a medium-sized fragment of 263 ha. The two fragments are separated by pastures, being at a distance of 200 m from each other at their closest point. Secondary forest sites are clumped in the landscape, while old-growth sites are more dispersed (mean distance in m ± SD: BU, 298±129; UN, 734±537; OG, 3597±2893). Before secondary growth took place, fields were used as pastures for at least 20 yr until 1974, when the Reserve was created and the cattle removed. This allowed the establishment of woody vegetation in these areas, which had a homogeneous, low forest physiognomy by 1988. In 1990 a large fire event burned 1200 ha inside the
Reserve, and reached some of the areas that were undergoing succession for 16 yr. All above ground biomass was burned in the sites sampled. As we used data collected in 2010, all secondary forests had an age of 36 yr since abandonment and burned areas regenerated for 20 yr after fire disturbance.
All these secondary forest sites were subjected to the same past land use, and differ only due to the incidence/absence of fire. Hereafter we refer to all unburned secondary forests as UN and burned secondary forests as BU. An aerial photograph taken in 1956 shows that old-growth sites (hereafter
OG) already had a tall forest physiognomy by that time, and they suffered no anthropogenic disturbance since then. All sampled sites are at least 100 m apart from each other.
In each site a 30 m x 60 m permanent plot was placed. All plots are located on mid slopes to avoid confounding effects from topography. Plots were divided into subplots of 10 m x 10 m, and six
27 subplots were selected by stratified random sampling. For this, each plot was divided into three sections of 20 m x 30 m, and within each section two subplots were randomly assigned for sampling.
We pooled all data from the subplots to have a sample size of nine plots, making a total sampling area of 600 m2 in each plot and 1.800 m2 in each forest type. Total area sampled was 0.54 ha. We measured and identified all trees with a diameter at breast height ≥ 5 cm. Nomenclature for families follows the Angiosperm Phylogeny Group (APG IV 2016).
To test whether secondary forests are colonized by tree lineages younger than those found in old-growth forests we calculated mean family age, abundance-weighted mean family age (Qian 2014) and basal area-weighted mean family age using family age estimates provided by Magallón et al.
(2015). We used age estimates generated using the uncorrelated lognormal (UCLN) Bayesian method.
For each species and each individual tree we attributed the age estimate of the family it belongs to.
To calculate mean family age, we summed the family ages of all species of each plot, and this value was divided by the total number of species in the plot. To calculate abundance-weighted family age, we summed up the family ages of all individuals of each plot, and this value was divided by the total number of individuals in the plot. Finally, to calculate community mean family age weighted by basal area, we multiplied the total basal area of each species in the plot by the age of its botanical family.
Then we summed the resulting values of all species of each plot, and this sum was divided by the total basal area of the plot. We tested for differences among different forest types using one-way
ANOVA followed by Tukey's HSD test.
To test whether phylogenetic beta diversity from old-growth to secondary forests is higher in secondary forests that were burned than non-burned, we calculated principal coordinates of phylogenetic structure (Duarte 2011). The analysis consists of various steps which are described in detail as follows. First, we constructed a phylogenetic tree based on the hypothesis proposed by
Magallón et al. (2015), with resolution at family level. Branch lengths within families were adjusted through the BLADJ algorithm of Phylocom 4.2 software (Webb et al. 2008). Then we generated the
28 phylogenetic tree using the Phylomatic 2 module of Phylocom 4.2 software (Webb and Donoghue
2005) and calculated the pairwise phylogenetic distance matrix (Dp; in millions of years) among all sampled species. Next, we employed the phylogenetic fuzzy-weighting method developed by Pillar and Duarte (2010), which combines the phylogenetic information contained in Dp and a matrix of communities described by species relative abundances, to generate a matrix P expressing the abundance of different lineages within samples (Duarte et al. 2014). The matrix P was subjected to a principal coordinates analysis (PCoA) using square-root of Bray-Curtis dissimilarities between plots.
The resulting principal coordinates of phylogenetic structure (PCPS; Duarte 2011) describe orthogonal phylogenetic gradients in the data set. The PCPS with the highest eigenvalues describes phylogenetic gradients related to wide phylogenetic clades, represented by deep nodes in the tree, while PCPS with lower eigenvalues are related to shallow nodes representing finer taxonomic scales
(e.g. families and genera; Duarte et al. 2012). This procedure was carried out using the PCPS package
(Debastiani and Duarte 2014) in the R Statistical Environment. We applied the function PCPS.sig to test for the significance of the relationship between the PCPSs and the environmental gradient (i.e. the distinct forest types) using generalized linear models (GLMs; see Duarte et al. 2016). The function uses two null models, one that shuffles the plots across the forest types (site shuffle) and one that shuffles the species across the tips of the phylogenetic tree (taxa shuffle). The first null model tests whether variation in phylogenetic composition among plots is driven by the environmental gradient, while the second null model tests whether the association between the environmental gradient and the PCPSs is driven either by the phylogenetic position of species or merely by species taxonomic composition. Because secondary forest plots are clumped in the Reserve landscape, we tested for spatial autocorrelation by calculating the principal coordinates of neighborhood matrices (PCNM;
Borcard et al. 1992) and identifying the best-fitting model for each ordination axis. We tested for all possible combinations of PCNM and forest types as predictors in the model of each PCPS. The best- fitting model selection was based on Akaike’s Information Criterion (AIC; Burnham and Anderson
29 2002). If the best-fitting model included any PCNM, the PCPS.sig was calculated including the
PCNM as a predictor in the model. We also tested for differences among forest types in their ordination scores in the two first PCPSs by means of one-way ANOVAs, followed by Tukey's HSD test.
RESULTS
We sampled 916 individuals from 126 tree species and 38 families encompassing all major angiosperm tree lineages. Species richness is unevenly distributed across main angiosperm clades, with most species belonging to rosids (69 species), followed by magnoliids (25) and asterids (24).
The remaining species belong to monocots (palms; three species), Caryophyllales (three species),
Proteales and Santalales (one species each). See Appendix for the complete species list and species abundance in distinct forest types. All major angiosperm clades are represented in unburned and burned secondary forests, although most of them with a low abundance (Figure 1). Family richness is higher in old-growth forests (32), followed by unburned (19) and burned secondary forests (12).
The distribution of tree abundance among plant families in secondary forests is strongly skewed in comparison to old-growth forests, especially in burned areas (Figure 1). Such pattern is due to the strong dominance of the asterid Moquiniastrum polymorphum (Less.) G. Sancho (Asteraceae; former
Gochnatia polymorpha) in burned sites and both M. polymorphum and Miconia cinnamomifolia (DC.)
Naudin (Melastomataceae, rosids) in unburned sites.
Abundance- and basal area-weighted mean family ages per plot are strongly correlated
(Pearson’s correlation = 0.99, P < 0.000001). Both differ significantly between distinct forest types, with mean values increasing from the more disturbed to the less disturbed forests (ANOVA; abundance-weighted mean family age: F(2,6) = 198.9, P < 0.00001; basal area-weighted mean family
2 age: F(2,6) = 50.24, P < 0.001; Figure 2). The abundance-weighted model presents the best fit (R adj =
2 0.98 vs. R adj = 0.92). Pairwise comparisons show that all forest types differ from each other (Tukey’s
30 HSD; abundance-weighted model: OG-BU, P < 0.00001; OG-UN, P < 0.0001; BU-UN, P < 0.01; basal area-weighted model: P < 0.001, P < 0.01 and P < 0.05, respectively). On the other hand, mean family age (i.e. unweighted) did not differ between forest types (P = 0.087). Tree density does not differ between forest types (ANOVA, P = 0.38), while basal area differs (ANOVA; F(2,6) = 60.1, P <
0.001). Pairwise comparisons indicate that basal area is higher in OG than both BU and UN, but BU and UN do not differ from each other (Tukey HSD; OG-BU: P < 0.001; OG-UN: P < 00.1; BU-UN:
P = 0.6).
The two first principal coordinates of phylogenetic structure (PCPS) accounted for 54% of the variation in phylogeny-weighted species relative abundance among plots (Fig. 3), with most variation
(34%) contained in the first axis. This axis describes a gradient in the abundance of major angiosperm clades in the phylogenetic structure of distinct forest types, with an increasing importance of asterids and rosids and a decreasing importance of magnoliids and palms from the less to the more disturbed tree communities (Figure 3). The site shuffle null model was significant for the two first axes (P =
0.005 and P = 0.009 for PCPS1 and PCPS2, respectively). On the other hand, the taxa shuffle null model was not significant for the two first PCPSs (P > 0.3 in both cases), indicating a taxonomic structuring of communities along the environmental gradient that is independent of phylogenetic relationships among species. For the first PCPS, the best-fitting model included as predictors both the
2 forest types and the third PCNM (R adj = 0.96; F(3,5) = 61.09, P < 0.001). So, forest types are important predictors of community phylogenetic structure along the first PCPS, yet some variation is accounted for by a spatial autocorrelation between plots. The best-fitting model of the second PCPS included
2 only the forest types as predictors (R adj = 0.77; F(2,6) = 14.35, P < 0.01), indicating an absence of spatial autocorrelation. Ordination scores differed between forest types in both ordination axes
(ANOVA; PCPS1: F(2,6) = 31.79, P < 0.001; PCPS 2: F(2,6) = 14.35, P < 0.01). In the first axis, scores of old-growth forest sites differed significantly from those of both BU and UN, but BU and UN did not differ from each other (Tukey HSD; OG-BU: P < 0.001; OG-UN: P < 0.01; BU-UN: P = 0.23).
31 In the second axis, scores of both burned and old-growth plots differed significantly from those of unburned sites (Tukey HSD; OG-BU: P = 0.29; OG-UN: P < 0.05; BU-UN: P < 0.01), with the latter being more associated with Myrtales (Fig. 3). So, phylogenetic beta diversity was higher between OG and UN because these forest types differed significantly along two PCPS, while OG and BU differed only along the first PCPS.
DISCUSSION
Tree communities in the lowland secondary forests at Poço das Antas Reserve show a phylogenetic structure distinct from nearby old-growth forests. Most tree clades found in old-growth forests are under-represented in secondary forest stands, which have been densely colonized by a tree species from a young lineage that is not found in old-growth forests. Thus, after 36 years of abandonment the distribution of tree abundance among angiosperm clades in secondary forests is still strongly biased. Contrary to our expectation, the higher phylogenetic beta diversity was found to be between unburned secondary forests and old-growth forests rather than between burned secondary forests and old-growth forests.
We found that mean family age increases significantly from the more to the less disturbed communities, suggesting that tolerance of tropical trees to disturbance depends on the timing of origin of distinct lineages. Such dependence of tolerance to disturbance on lineage age may reflect the contrasting environments in which distinct clades arose, as is the case of Mediterranean woody plants
(Ackerly 2003). Modern tropical rain forests seem to have originated during the mid-Cretaceous, when there was an explosive radiation of many typical rain forest-dwelling clades that constitute a substantial portion of angiosperm species richness in this vegetation worldwide (Davies et al. 2005).
Likewise, extant palm lineages began to diversify by the same time in a tropical rain forest environment (Couvreur et al. 2011). Rainforest biotas evolved under negligible fire pressure, and as a general rule are ill-adapted to fire disturbance (Cochrane 2003; e.g. Hoffmann et al. 2003). The
32 flora of savannas, on the other hand, evolved much later in an open environment where fire has played a major role as a selective pressure. For instance, a time-calibrated phylogeny indicates that the genus
Moquiniastrum diversified in the late Miocene, between 2.3 and 13.4 Myr (Funk et al. 2014). This period was characterized by a global-scale expansion of fire-prone grasslands in the tropical regions
(Bond and Midgley 2012), including the rapid diversification of fire-adapted, endemic species in the
Brazilian Cerrado (Simon et al. 2009). Thus, it seems that Moquiniastrum constitutes a recently- evolved clade whose diversification is directly linked to the spread of fire disturbed, grass-dominated ecosystems in South America during the late Miocene (Funk et al. 2014). This genus is comprised of wind-dispersed, sclerophyllous shrubs (or rarely trees) which inhabit grasslands and savannas on nutrient-poor and rocky soils (Sancho 2000). Soil fertility is known to act synergistically with fire to determine plant community structure in fire-prone ecosystems: where soil fertility is low, vegetation is less likely to attain a closed canopy that shades the understory and inhibits fire; so, low-fertility soils tend to select for fire-adapted species and lineages (Kellman 1984, Ojeda et al. 2010, Silva et al.
2013, Dantas et al 2015). In tropical forests, intense past land-use leads to decreased soil quality, which strongly determines tree community assembly in regenerating forests (Jakovac et al. 2016).
Therefore, our results suggest that in the lowland Atlantic forest at Poço das Antas, both fire disturbance and low soil fertility in old pastures acts as strong environmental filters for virtually all tree lineages from old-growth forests, which is consistent with strong biome conservatism among vascular plants (e.g. Crisp et al. 2009). This created an opportunity for colonization by a young lineage which arose amid fire-prone, nutrient-poor savannas and grasslands and does not establish in closed-canopy rain forests.
An important question that arises is whether our results apply to other Neotropical forests recovering from disturbance. Letcher et al. (2012) investigated patterns of tree phylogenetic change along chronosequences of lowland forests in Costa Rica, Mexico and Brazilian Amazon. Although there was substantial variation among sites, one common trend could be detected: the preference
33 among magnoliid lineages for old-growth forests. A similar pattern was found in a subtropical grassland-forest vegetation mosaic in southern Brazil (Duarte 2011). Tree families from this large clade – mainly Lauraceae, Annonaceae and Myristicaceae – are among the oldest angiosperm tree lineages, with age estimates ranging from 85 to 105 Myr (Magallón et al. 2015). Sapotaceae (Asterids) seems to be another old family (94 Myr; Magallón et al. 2015) associated with old-growth forests both in our dataset (Figure 1), elsewhere in the Atlantic forest (Oliveira et al. 2004) and other lowland
Neotropical forests (Letcher et al. 2015). Euphorbiaceae, the most abundant tree family in old-growth forests at Poço das Antas (26% of all individuals; see Appendix), ages 74 Myr (Magallón et al. 2015).
This plant family also contributes disproportionally to tree abundance in the Amazonian flora: 14
Euphorbiaceae species - out of 143 tree species from the family occurring in the Amazon - belong to the small group of 227 hyperdominant species which together account for 50 % of total tree abundance in the region (ter Steege et al. 2013). On the other hand, younger families that seem to occur preferentially in regenerating and/or disturbed forests both in our study area and elsewhere in the Neotropics include Asteraceae (Tabarelli et al. 1999) and Anacardiaceae (Letcher et al. 2015), whose age estimates are 49 and 51 Myr, respectively (Magallón et al. 2015). It is important to highlight that we do not mean that all tree families associated with old-growth forests are old and all families associated with disturbed/secondary forests are young, as there certainly are exceptions on both sides. For instance, Neotropical rain forests also include very recent tree radiations, such as species from genus Inga (Richardson et al. 2001). Melastomataceae, a family strongly associated with
Neotropical secondary forests (Letcher et al. 2012, 2015), has an age of 73 Myr (Magallón et al. 2015).
Tree and shrub species from this family are highly dependent on canopy gaps to establish in
Neotropical rain forests (Ellison et al. 1993, Silveira et al. 2013); so, they seem to successfully track the more open, gap-like environment of early secondary forests (see Guariguata & Ostertag 2001).
Nevertheless, our results are consistent with the notion that the age of a given habitat is related to the maximum age of lineages found within it (see Gerhold et al 2015): fire-prone, long-lasting pastures
34 are ‘novel habitats’ to which ancient rainforest tree lineages are not adapted. Thus, we suggest that the use of tree mean family age as a proxy for disturbance intensity and forest recovery in lowland
Neotropical forests is a promising direction for future investigations.
Our results indicate that, at the scale of angiosperms, tree species colonizing secondary forests constitute a random subset of lineages found in the local pool. So, if we remove the large effect of M. polymorphum on the phylogenetic structure and mean family age of tree communities in secondary forests, how different from old-growth forests would they be? If secondary forests are phylogenetically similar to old-growth forests when we remove the effect of this one species, then our conclusion that disturbance favours younger clades may not hold. Nevertheless, this result does not rule out the existence of phylogenetic patterns at distinct taxonomic scales (e.g. Cavender-Bares et al. 2006, Letcher et al. 2012). Malpighiales, for instance, seems to be phylogenetically structured among forest types: while some families occur in secondary forests, the clade formed by
Chrysobalanaceae, Erythroxylaceae, Euphorbiaceae and Phyllantaceae was found only in old-growth forests. Although the PCPS method may be able to detect phylogenetic patterns at distinct taxonomic scales (Duarte et al. 2012), the existence of strong differences between forest types in the abundance of major angiosperm lineages may obscure patterns at smaller taxonomic scales. However, these small-scale patterns may depend on well-resolved phylogenies to be detected (e.g. Kress et al. 2009,
Molina-Venegas and Roquet 2014, Muscarella et al. 2014). So, coupling analyses at distinct taxonomic scales with well-resolved, sequence-based phylogenies may be necessary to detect more subtle differences among communities in their phylogenetic structure. We also must be cautious in interpreting our results because BU and UN differ both in terms of disturbance type (i.e. presence/absence of fire) and time since disturbance (36 yr vs 20 yr). Because our results indicate that forest succession is occurring very slowly in these old pastures, we argue that differences between
BU and UN are more likely to be due to fire disturbance than due to contrasting times since disturbance.
35 The value of secondary forests for biodiversity conservation is currently a matter of debate
(Chazdon et al. 2009; van Breugel et al. 2013; Arroyo-Rodriguez et al. 2015). Under favorable conditions, secondary forests may exhibit high resilience, providing habitat for many species typical of old-growth forests (Norden et al. 2009). However, our results suggest that lowland Atlantic secondary forests in areas used as pastures for decades perform poorly in conserving the whole range of Atlantic tree clades that occur in old-growth forests. The dominance of M. polymorphum in early- successional forests regenerating on abandoned, fire-prone pastures is observed both at the landscape scale at Poço das Antas Reserve (Lima et al. 2006) and in many other sites in the same region (e.g.
Santana et al. 2004; P.V. Prieto, personal observation). Thus, the pattern we found at the local scale reflects a more widespread pattern of dominance of this young lineage at larger spatial scales under such ecological conditions, i.e., fire-prone, old pastures. Intermediate secondary forests and small, disturbed fragments account for up to 40% of remaining Brazilian Atlantic forest (Ribeiro et al. 2009).
This picture is even worse in the lowlands, where habitat loss and fragmentation are much more severe (Tabarelli et al. 2010). In this scenario, fires are common and widespread, with almost 70 000 fire outbreaks being detected by satellites only in 2014 (INPE, 2015). Such human-modified landscapes in the Atlantic Forest present an impoverished tree assemblage and increased species dominance, which has been described as forest secondarization (Joly et al. 2014; see Santos-Silva et al. 2015). So, it is expected that most forest remnants in this biome show a strongly biased tree phylogenetic composition (e.g. Matos et al. 2016; see Santos et al 2014). Consequently, the conservation of the whole phylogenetic diversity of Atlantic forest trees relies mainly on the maintenance of undisturbed, old-growth forest remnants. This is a critical issue because Atlantic secondary forests may take centuries to attain many floristic and functional attributes that are typical of old-growth forests (Liebsch et al. 2008). Assessing the phylogenetic structure of successional tree communities may help us to understand and predict the recovery of disturbed tropical forests, as well as to identify endangered lineages that depend more on conservation actions.
36
ACKNOWLEDGEMENTS
We thank Mark Leithead and three anonymous reviewers that provided useful suggestions to improve the manuscript; Adilson Pintor and Antonio Tavares for fieldwork support; and the
Instituto Chico Mendes de Conservação da Biodiversidade (ICMBio) for logistical support.
Financial support was provided by the PROBIO II/BIRD/MMA/MCTI/JBRJ and Fundação
Flora/PETROBRAS under grant 6000.0023998.06.02 to Programa Mata Atlântica/P.J.F.P.
Rodrigues. PVP benefited from a grant from the Brazilian Higher Education Office (CAPES-MEC).
REFERENCES
Ackerly DD. 2003. Community assembly, niche conservatism, and adaptive evolution in changing
environments. International Journal of Plant Sciences 164:S165–S184. doi:10.1086/368401
APG IV. 2016. An update of the Angiosperm Phylogeny Group classification for the orders and
families of flowering plants: APG IV. Botanical Journal of the Linnean Society 181:1–20.
doi:10.1111/boj.12385
Arroyo-Rodríguez V, Melo FPL, Martínez-Ramos M, Bongers F, Chazdon RL, Meave JA, Norden
N, Santos BA, Leal IR, Tabarelli M. 2015. Multiple successional pathways in human-modified
tropical landscapes: new insights from forest succession, forest fragmentation and landscape
ecology research. Biological Reviews. doi: 10.1111/brv.12231
Barlow J, Peres CA. 2008. Fire-mediated dieback and compositional cascade in an Amazonian forest.
Philosophical Transactions of the Royal Society B 363:1787–1794.
doi:10.1098/rstb.2007.0013
Bond WJ, Midgley JJ. 2012. Fire and the angiosperm revolutions. International Journal of Plant
Sciences 173:569–583. doi:10.1086/665819
Borcard D, Legendre P, Drapeau P. 1992. Partialling out the spatial component of ecological
37 variation. Ecology 73:1045–1055. doi: 10.2307/1940179
Brown S, Lugo AE. 1990. Tropical secondary forests. Journal of Tropical Ecology 6:1–32.
Brunbjerg KA, Borchsenius F, Eiserhardt WL, Ejrnæs R, Svenning J-C. 2012. Disturbance drives
phylogenetic community structure in coastal dune vegetation. Journal of Vegetation Science
23:1082–1094. doi:10.1111/j.1654-1103.2012.01433.x
Burnham, K. P. and Anderson, D. R. 2002. Model selection and multi-model inference: a practical
information-theoretic model. - Springer-Verlag New York.
Carvalho FA, Nascimento MT, Oliveira-Filho AT. 2008. Composição, riqueza e heterogeneidade da
flora arbórea da bacia do rio São João, RJ, Brasil. Acta Botanica Brasilica 22:929–940.
doi:10.1590/S0102-33062008000400004
Cavender-Bares J, Keen A, Miles B. 2006 Phylogenetic structure of Floridian plant communities
depends on taxonomic and spatial scales. Ecology 87:S109–S122. doi: 10.1890/0012-
9658(2006)87[109:PSOFPC]2.0.CO;2
Chazdon RL, Peres CA, Dent D, Sheil D, Lugo AE, Lamb D, Stork NE, Miller S.E. 2009. The
potential for species conservation in tropical secondary forests. Conservation Biology 23:1406–
1417. doi:10.1111/j.1523-1739.2009.01338.x
Cochrane MA. 2003. Fire science for rainforests. Nature 421:913–919. doi:10.1038/nature01437
Cochrane MA, Laurance WF. 2002. Fire as a large-scale edge effect in Amazonian forests. Journal
of Tropical Ecology 18:311–325. doi:10.1017/S0266467402002237
Colón SM, Lugo AE. 2006. Recovery of a subtropical dry forest after abandonment of different land
uses. Biotropica 38:354–64. doi:10.1111/j.1744-7429.2006.00159.x
Couvreur TLP, Forest F, Baker WJ. 2011. Origin and global diversification patterns of tropical rain
forests: inferences from a complete genus-level phylogeny of palms. BMC Biology 9:44.
doi:10.1186/1741-7007-9-44
Crisp MD, Arroyo MTK, Cook, LG, Gandolfo MA, Jordan GJ, McGlone MS, Weston PH, Westoby
38 M, Wilf P, Linder HP. 2009. Phylogenetic biome conservatism on a global scale. Nature
458:754–756. doi:10.1038/nature07764
Dantas VL, Batalha MA, França H, Pausas JG. 2015. Resource availability shapes fire-filtered
savannas. Journal of Vegetation Science 26:395–403. doi:10.1111/jvs.12247
Davis CC, Webb CO, Wurdack KJ, Jaramillo CA, Donoghue MJ. 2005. Explosive radiation of
Malpighiales supports a mid-Cretaceous origin of modern tropical rain forests. The American
Naturalist 165:E36–E65. doi:10.1086/428296
Debastiani VJ, Duarte LS. 2014. PCPS - an R-package for exploring phylogenetic eigenvectors across
metacommunities. Frontiers in Biogeography 6:144–148.
Dinnage R. 2009. Disturbance alters the phylogenetic composition and structure of plant communities
in an old field system. PLoS ONE 4:e7071. doi:10.1371/journal.pone.0007071
Ding Y, Zang R, Letcher SG, Liu S, He F. 2012. Disturbance regime changes the trait distribution,
phylogenetic structure and community assembly of tropical rain forests. Oikos 121:1263–1270.
doi:10.1111/j.1600-0706.2011.19992.x
Duarte LS. 2011. Phylogenetic habitat filtering influences forest nucleation in grasslands. Oikos
120:208–215. doi: 10.1111/j.1600-0706.2010.18898.x
Duarte LS, Both C, Debastiani VJ, Carlucci MB, Gonçalves LO, Capelatti L, Seger GDS, Bastazini
VAG, Brum FT, Salengue EV, Bernardo-Silva JS. 2014. Climate effects on amphibians
distributions depend on phylogenetic resolution and the biogeographical history of taxa. Global
Ecology and Biogeography 23:213–222. doi:10.1111/geb.12089
Duarte LS, Debastiani VJ, Freitas AVL, Pillar VP. 2016. Dissecting phylogenetic fuzzy weighting:
theory and application in metacommunity phylogenetics. Methods in Ecology and Evolution.
doi:10.1111/2041-210X.12547
Duarte LS, Prieto PV, Pillar VP. 2012. Assessing spatial and environmental drivers of phylogenetic
structure in Brazilian Araucaria forests. Ecography 35:952–960. doi:10.1111/j.1600-
39 0587.2011.07193.x
Ellison AM, Denslow JS, Loiselle B, Brenés D. 1993 Seed and seedling ecology of Neotropical
Melastomataceae. Ecology 74:1733–1749. doi:10.2307/1939932
Funk VA, Sancho G, Roque N, Kelloff CL, Ventosa-Rodríguez I, Diazgranados M, Bonifacino JM,
Chan R. 2014. A phylogeny of the Gochnatieae: Understanding a critically placed tribe in the
Compositae. Taxon 63:859–982. doi:10.12705/634.27
Gerhold P, Cahill Jr JF, Winter M, Bartish IV, Prinzing A. 2015. Phylogenetic patterns are not proxies
of community assembly mechanisms (they are far better). Functional Ecology 29:600-615.
doi:10.1111/1365-2435.12425
Guariguata MR, Ostertag R. 2001. Neotropical secondary forest succession: changes in structural and
functional characteristics. Forest Ecology and Management 148:185–206. doi:10.1016/S0378-
1127(00)00535-1
Hoffmann WA, Orthen B, Nascimento PKV. 2003. Comparative fire ecology of tropical savanna and
forest trees. Functional Ecology 17:720–726. doi:10.1111/j.1365-2435.2003.00796.x
Instituto Nacional de Pesquisas Espaciais [INPE] (2015) Monitoramento de queimadas e incêndios.
Available at http://sigma.cptec.inpe.br/queimadas/
Jakovac CC, Bongers F, Kuyper TW, Mesquita RC, Peña‐Claros M. 2016. Land use as a filter for
species composition in Amazonian secondary forests. Journal of Vegetation Science.
doi:10.1111/jvs.12457
Joly C, Metzger J, Tabarelli M. 2014. Experiences from the Brazilian Atlantic forest: ecological
findings and conservation initiatives. New Phytologist 204:459–473. doi:10.1111/nph.12989
Kellman M. 1984. Synergistic relationship between fire and low soil fertility in Neotropical savannas:
a hypothesis. Biotropica 16:158–160. doi:10.2307/2387850
Kembel SW, Cowan PD, Helmus MR, Cornwell WK, Morlon H, Ackerly DD, Blomberg SP, Webb
CO. 2010. Picante: R tools for integrating phylogenies and ecology. Bioinformatics 26:1463–
40 1464. doi:10.1093/bioinformatics/btq166
Kress WJ, Erickson DL, Jones FA, Swenson NG, Perez R, Sanjur O, Bermingham E. 2009. Plant
DNA barcodes and a community phylogeny of a tropical forest dynamics plot in Panama. Proceedings
of the National Academy of Sciences USA 106:18621–18626. doi:10.1073/pnas.0909820106
Letcher SG, Chazdon RL, Andrade ACS, Bongers F, van Breugel M, Finegan B, Laurance SG,
Mesquita RCG., Martínez-Ramos M., Williamson GB. 2012. Phylogenetic community structure
during succession: Evidence from three Neotropical forest sites. Perspectives in Plant Ecology,
Evolution and Systematics 14:79–87. doi:10.1016/j.ppees.2011.09.005
Letcher SG, Lasky JR, Chazdon RL, Norden N, Wright SJ, Meave JA, Pérez-García EA, Muñoz R,
Romero-Pérez E, Andrade A, et al. 2015. Environmental gradients and the evolution of
successional habitat specialization: a test case with 14 Neotropical forest sites. Journal of
Ecology 103:1276-1290. doi:10.1111/1365-2745.12435
Liebsch D, Marques MCM, Goldenberg R. 2008. How long does the Atlantic Rain Forest take to
recover after a disturbance? Changes in species composition and ecological features during
secondary succession. Biological Conservation 141:1717–1725.
doi:10.1016/j.biocon.2008.04.013
Lima HC, Pessoa SVA, Guedes-Bruni RR, Moraes LFD, Granzotto SV, Iwamoto S, di Ciero J. 2006.
Caracterização fisionômico-florística e mapeamento da vegetação da Reserva Biológica de Poço
das Antas, Silva Jardim, Rio de Janeiro, Brasil. Rodriguésia 57:369–389.
Magallón S, Gómez-Acevedo S, Sánchez-Reyes LL, Hernández-Hernández T. 2015. A
metacalibrated time-tree documents the early rise of flowering plant phylogenetic diversity.
New Phytologist 207:437–453. doi:10.1111/nph.13264
Matos FAR, Magnago LFS, Gastauer M, Carreiras JMB, Simonelli M, Meira-Neto JAA, Edwards
DP. 2016. Effects of landscape configuration and composition on phylogenetic diversity of trees
in a highly fragmented tropical forest. Journal of Ecology. doi:10.1111/1365-2745.12661
41 Mesquita RCG, Ickes K, Ganade G, Williamson GB. 2001. Alternative successional pathways in the
Amazon Basin. Journal of Ecology 89:528–537. doi:10.1046/j.1365-2745.2001.00583.x
Molina-Venegas R, Roquet C. 2014. Directional biases in phylogenetic quantification: a
Mediterranean case study. Ecography 37:572–580. doi:10.1111/j.1600-0587.2013.00442.x
Moraes LFD, Campello EFC, Pereira MG, Loss A. 2008. Características do solo na restauração de
áreas degradadas na Reserva Biológica de Poço das Antas, RJ. Ciência Florestal 18:193–206.
Muscarella R, Uriarte M, Erickson DL, Swenson NG, Zimmerman JK, Kress WJ. 2014. A well-
resolved phylogeny of the trees of Puerto Rico based on DNA barcode sequence data. PLoS
ONE 9: e112843. doi: 10.1371/journal.pone.0112843
Norden N, Angarita HA, Bongers F, Martínez-Ramos M, Granzow-de la Cerda I, van Breugel M,
Lebrija-Trejos E, Meave JA, Vandermeer J, Williamson GB, Finegan B, Mesquita R, Chazdon
RL. 2015. Successional dynamics in Neotropical forests are as uncertain as they are predictable.
Proceedings of the National Academy of Sciences USA 112:8013–8018.
doi:10.1073/pnas.1500403112
Norden N, Chazdon RL, Chao A, Jiang Y-H, Vílchez-Alvarado B. 2009. Resilience of tropical rain
forests: tree community reassembly in secondary forests. Ecology Letters 12:385–394.
doi:10.1111/j.1461-0248.2009.01292.x.
Ojeda F, Pausas JG, Verdú M. 2010. Soil shapes community structure through fire. Oecologia
163:729-735. doi:10.1007/s00442-009-1550-3
Oliveira MA, Grillo AS, Tabarelli M. 2004. Forest edge in the Brazilian Atlantic forest: drastic
changes in tree species assemblages. Oryx 38:389–394. doi:10.1017/S0030605304000754
Oliveira-Filho AT, Fontes MAL. 2000. Patterns of floristic differentiation among Atlantic Forests in
southeastern Brazil and the influence of climate. Biotropica 32:793–810. doi:10.1111/j.1744-
7429.2000.tb00619.x
Oliveras I, Malhi Y, Salinas N, Huaman V, Urquiaga-Flores E, Kala-Mamani J, Quintano-
42 Loaiza JA, Cuba-Torres I, Lizarraga-Morales N, Román-Cuesta RM. 2014. Changes in forest
structure and composition after fire in tropical montane cloud forests near the Andean treeline.
Plant Ecology & Diversity 7:329–340. doi:10.1080/17550874.2013.816800
Pillar VD, Duarte LS. 2010. A framework for metacommunity analysis of phylogenetic structure.
Ecology Letters 13:587–596. doi:10.1111/j.1461-0248.2010.01456.x
Qian H. 2014. Contrasting relationships between clade age and temperature along latitudinal versus
elevational gradients for woody angiosperms in forests of South America. Journal of Vegetation
Science 25:1208–1215. doi:10.1111/jvs.12175
R Core Team (2015) R: A language and environment for statistical computing. R Foundation for
Statistical Computing, Vienna, Austria. URL http://www.R-project.org/.
Ribeiro MC, Metzger JP, Martensen AC, Ponzoni FJ, Hirota MM. 2009. The Brazilian Atlantic Forest:
how much is left, and how is the remaining forest distributed? Implications for conservation.
Biological Conservation 142:1141–1153. doi:10.1016/j.biocon.2009.02.021
Richardson JE, Pennington RT, Pennington TD, Hollingsworth PM. 2001. Rapid diversification of a
species-rich genus of Neotropical rain forest trees. Science 293:2242–2245. doi:
10.1126/science.1061421
Rocha CFD, Costa TCC, Teixeira AMG, Cruz CBM, Figueiredo CAA, Bohrer CBA, Volcker CM,
Sá CFC, Chaves LCT, Maciel NC, Villaça RC. 2009. Região turística dos lagos fluminenses.
In: Estratégias e ações para a conservação da biodiversidade no Estado do Rio de Janeiro. Rio
de Janeiro: Instituto Biomas. p. 313-326.
Sancho G. 2000. Revisión y filogenia de la sección Moquiniastrum Cabrera del género Gochnatia
Kunth (Asteraceae, Mutisieae). Fontqueria 54:61–122.
Santana CAA, Lima CCD, Magalhães LMS. 2004. Estrutura horizontal e composição florística de
três fragmentos secundários na cidade do Rio de Janeiro. Acta Scientarum Biological Sciences
26:443-451. doi:10.4025/actascibiolsci.v26i4.1525
43 Santos BA, Tabarelli M, Melo FPL, Camargo JLC, Andrade A, Laurance SG, Laurance WF. 2014.
Phylogenetic impoverishment of Amazonian tree communities in an experimentally fragmented
forest landscape. PLoS ONE 9:e113109. doi:10.1371/journal.pone.0113109
Santos-Silva EE, Withey KD, Almeida WR, Mendes G, Lopes AV, Tabarelli M. 2015. Seedling
assemblages and the alternative successional pathways experienced by Atlantic forest fragments.
Plant Ecology & Diversity 8:483–492. doi:10.1080/17550874.2015.1048486
Scervino RP, Torezan JMD. 2015. Factors affecting the genesis of vegetation patches in
anthropogenic pastures in the Atlantic forest domain in Brazil. Plant Ecology & Diversity
8:475–482. doi:10.1080/17550874.2015.1044582
Silva LCR, Hoffmann WA, Rossatto DR, Haridasan M, Franco AC, Horwath WR. 2013. Can
savannas become forests? A coupled analysis of nutrient stocks and fire thresholds in central
Brazil. Plant and Soil 373:829-842. doi: 10.1007/s11104-013-1822-x
Silveira FAO, Fernandes GW, Lemos-Filho JP. 2013. Seed and seedling ecophysiology of
Neotropical Melastomataceae: implications for conservation and restoration of savannas and
rainforests. Annals of the Missouri Botanical Garden 99:82-99. doi: 10.3417/2011054
Simon MF, Grether R, Queiroz LP, Skema C, Pennington RT, Hughes CE. 2009. Recent assembly
of the Cerrado, a Neotropical diversity hotspot, by in situ evolution of adaptations to fire.
Proceedings of the National Academy of Sciences USA 106:20359–20364.
doi:10.1073/pnas.0903410106
Souza FC, Dexter KG, Phillips OL, Brienen RJW, Chave J, Galbraith DR, Gonzalez GL,
Mendoza AM, Pennington RT, Poorter L, et al. 2016. Evolutionary heritage influences Amazon tree
ecology. Proceedings of the Royal Society B 283: 20161587. doi:10.1098/rspb.2016.1587
Tabarelli M, Aguiar AV, Ribeiro MC, Metzger JP, Peres CA. 2010. Prospects for biodiversity
conservation in the Atlantic forest: Lessons from aging humand-modified landscapes.
Biological Conservation 143:2328–2340. doi:10.1016/j.biocon.2010.02.005
44 Tabarelli M, Mantovani W, Peres CA. 1999. Effects of habitat fragmentation on plant guild structure
in the montane Atlantic forest in southeastern Brazil. Biological Conservation 91:119–127.
doi:10.1016/S0006-3207(99)00085-3
Tanizaki-Fonseca K, Bohrer CBA. 2009. O fogo como fator de degradação de ecossistemas de Mata
Atlântica no Estado do Rio de Janeiro. In: Estratégias e ações para a conservação da
biodiversidade no Estado do Rio de Janeiro. Rio de Janeiro: Instituto Biomas. p. 81-90. ter Steege H, Pitman NCA, Sabatier D, Baraloto C, Salomão RP, Guevara JE, Phillips OL, Castilho
CV, Magnusson WE, Molino JF, et al. 2013. Hyperdominance in the Amazonian tree flora.
Science 342:1243092. doi:10.1126/science.1243092 van Breugel M, Hall JS, Craven D, Bailon M, Hernandez A, Abbene M, van Breugel P. 2013.
Succession of ephemeral secondary forests and their limited role for the conservation of floristic
diversity in a human-modified tropical landscape. PLoS ONE 8: e82433.
doi:10.1371/journal.pone.0082433
Valiente-Banuet A, Rumebe AV, Verdú M, Callaway RM. 2006. Modern Quaternary lineages
promote diversity through facilitation of ancient Tertiary lineages. Proceedings of the National
Academy of Sciences USA 103:16812–16817. doi:10.1073/pnas.0604933103
Verdú M. 2000. Ecological and evolutionary differences between Mediterranean seeders and
resprouters. Journal of Vegetation Science 11:265–268. doi:10.2307/3236806
Verdú M, Dávila P, García-Fayos P, Flores-Hernández N, Valiente-Banuet A. 2003. ‘Convergent’
traits of Mediterranean woody plants belong to pre-mediterranean lineages. Biological Journal
of the Linnean Society 78:415–427. doi:10.1046/j.1095-8312.2003.00160.x
Verdú M, Pausas JG. 2007. Fire drives phylogenetic clustering in Mediterranean Basin woody plant
communities. Journal of Ecology 95:1316–1323. doi:10.1111/j.1365-2745.2007.01300.x
Webb CO, Ackerly DD, Kembel SW. 2008. Phylocom: software for the analysis of phylogenetic
community structure and trait evolution. Bioinformatics 24:2098–2100.
45 doi:10.1093/bioinformatics/btn358
Webb CO, Donoghue MJ. 2005. Phylomatic: Tree assembly for applied phylogenetics. Molecular
Ecology Notes 5:181–183. doi:10.1111/j.1471-8286.2004.00829.x
Wiens JJ, Ackerly DD, Allen AP, Anacker BL, Buckley LB, Cornell HV, Damschen EI, Davies TJ,
Grytnes J-A, Harrison SP, Hawkins BA, Holt RD, McCain CM, Stephens PR. 2010. Niche
conservatism as an emerging principle in ecology and evolutionary biology. Ecology Letters
13:1310–1324. doi:10.1111/j.1461-0248.2010.01515.x
46 Appendix. Abundance of tree species sampled in lowland secondary and old-growth forests at Poço das Antas Biological Reserve, southeastern Brazil. OG, old-growth forests; BU, burned secondary forests; UN, unburned secondary forests. BU UN OG ROSIDS ANACARDIACEAE Astronium graveolens Jacq. 1 Schinus terebinthifolius Raddi 2 1 Tapirira guianensis Aubl. 21 BURSERACEAE Protium widgrenii Engl. 1 CALOPHYLLACEAE Calophyllum brasiliense Cambess. 2 CELASTRACEAE Maytenus samydaeformis Reiss. 1 CHRYSOBALANACEAE Chrysobalanaceae sp. 2 Couepia venosa Prance 1 CLUSIACEAE Garcinia gardneriana (Planch. & Triana) Zappi 1 Tovomitopsis paniculata (Spreng.) Planch. & Triana 1 ERYTHROXYLACEAE Erythroxylum cuspidifolium Mart. 4 EUPHORBIACEAE Actinostemon verticillatus (Klotzsch) Baill. 12 Euphorbiaceae sp. 1 5 Mabea fistulifera Mart. 26 Sagotia racemosa Baill. 4 Senefeldera verticillata (Vell.) Croizat 30 FABACEAE Apuleia leiocarpa (Vogel) J.F.Macbr. 1 Copaifera langsdorffii Desf. 1 Hymenolobium janeirense Kuhlm. 1 Inga laurina (Sw.) Willd. 4 3 Plathymenia reticulata Benth. 1 Poecilanthe falcata (Vell.) Heringer 1 Swartzia apetala Raddi 4 Tachigali pilgeriana (Harms) Oliveira-Filho 2 HYPERICACEAE
47 Vismia martiana Mart. 1 LACISTEMATACEAE Lacistema pubescens Mart. 7 MALVACEAE Eriotheca pentaphylla (Vell.) A.Robyns 1 Pseudobombax grandiflorum (Cav.) A.Robyns 1 MELASTOMATACEAE Miconia albicans (Sw.) Triana 3 Miconia cinnamomifolia (DC.) Naudin 1 67 1 Miconia lepidota Schrank & Mart. ex DC. 1 Miconia prasina (Sw.) DC. 9 Miconia sp.1 1 MELIACEAE Cabralea canjerana (Vell.) Mart. 1 Guarea guidonia (L.) Sleumer 4 Guarea macrophylla Vahl 2 Trichilia martiana C.DC. 1 Trichilia sp. 1 1 MORACEAE Brosimum glaziovii Taub. 2 Brosimum guianense (Aubl.) Huber 1 1 1 Helicostylis tomentosa (Poepp. & Endl.) Rusby 2 Naucleopsis oblongifolia (Kuhlm.) Carauta 3 Pourouma sp. 1 Sorocea guilleminiana Gaudich. 1 MYRTACEAE Calyptranthes lucida Mart. ex DC. 3 Eugenia candolleana DC. 1 Eugenia excelsa O.Berg. 1 Eugenia macahensis O. Berg 1 Eugenia oblongata O.Berg 1 Eugenia pisiformis Cambess. 2 Eugenia subundulata Kiaersk. 2 Eugenia sp. 1 2 Eugenia sp. 2 1 Marlierea sp. 1 2 Myrcia anacardiifolia Gardner 4 Myrcia anceps (Spreng.) O. Berg 1 Myrcia crocea (Vell.) Kiaersk. 1 Myrcia ilheosensis Kiaersk. 2 Myrcia splendens (Sw.) DC. 3 10 1
48 PHYLLANTHACEAE Hieronyma oblonga (Tul.) Müll.Arg. 3 SALICACEAE Casearia commersoniana Cambess. Casearia sylvestris Sw. 2 2 1 Xylosma glaberrima Sleumer 1 SAPINDACEAE Cupania furfuracea Radlk. 2 1 Cupania racemosa (Vell.) Radlk. 3 Cupania schizoneura Radlk. 1 SIMAROUBACEAE Simarouba amara Aubl. 1 URTICACEAE Cecropia pachystachya Trécul 1 VIOLACEAE Rinorea guianensis Aubl. 1 ASTERIDS APOCYNACEAE Himatanthus bracteatus (A.DC.) Woodson 2 ASTERACEAE Moquiniastrum polymorphum (Less.) G.Sancho 245 176 BIGNONIACEAE Jacaranda macrantha Cham. 1 Sparattosperma lencanthum (Vell.) K.Schum. 1 BORAGINACEAE Cordia trichoclada DC. 1 PRIMULACEAE Cybianthus sp. 1 1 Myrsine coriacea (Sw.) R.Br. ex Roem. & Schult. 3 16 RUBIACEAE Bathysa mendoncaei K.Schum. 24 Psychotria vellosiana Benth. 1 Rubiaceae sp. 7 SAPOTACEAE Ecclinusa ramiflora Mart. 5 Micropholis crassipedicellata (Mart. ex Eichler) Pierre 5 Micropholis gardneriana (A.DC.) Pierre 1 Pouteria bangii (Rusby) T.D.Penn. 1
49 Pouteria bullata (S.Moore) Baehni 1 Pouteria sp. 1 3 Pradosia lactescens (Vell.) Radlk. 1 Sapotaceae sp. 1 1 Sapotaceae sp. 2 1 Sapotaceae sp. 3 1 Sapotaceae sp. 4 1 Sapotaceae sp. 5 1 Sarcaulus brasiliensis (A.DC.) Eyma 1 SOLANACEAE Solanaceae sp. 1 MAGNOLIIDS ANNONACEAE Annona dolabripetala Raddi 2 Annona sylvatica A.St.-Hil. 3 Duguetia sessilis (Vell.) Maas 5 Guatteria campestris R.E.Fr. 1 4 Guatteria candolleana Schltdl. 2 Xylopia sericea A.St.-Hil. 1 8 LAURACEAE Cryptocarya moschata Nees & Mart. 1 Cryptocarya saligna Mez 1 Licaria bahiana Kurz 1 Licaria guianensis Aubl. 2 Nectandra nitidula Nees & Mart. ex Nees 2 Nectandra oppositifolia Nees & Mart. ex Nees 5 1 Nectandra reticulata (Ruiz & Pav.) Mez 2 Ocotea divaricata (Nees) Mez 3 Ocotea laxa (Nees) Mez 1 Ocotea odorifera (Vell.) Rohwer 1 Ocotea schottii (Meisn.) Mez 1 Rhodostemonodaphne macrocalyx (Meisn.) Rohwer ex 3 Madriñán Urbanodendron bahiense (Meisn.) Rohwer 2 Urbanodendron verrucosum (Nees) Mez 1 MONIMIACEAE Macrotorus utriculatus (Mart.) Perkins 1 Mollinedia glabra (Spreng.) Perkins 1 MYRISTICACEAE Virola bicuhyba (Schott ex Spreng.) Warb. 2 SIPARUNACEAE
50 Siparuna guianensis Aubl. 3 Siparuna reginae (Tul.)A.DC. 9 MONOCOTS ARECACEAE Astrocaryum aculeatissimum (Schott) Burret 17 Attalea humilis Mart. 1 10 Polyandrococos caudescens (Mart.) Barb.Rodr. 1 CARYOPHYLLALES NYCTAGINACEAE Guapira areolata (Heimerl) Lundell 2 Guapira nitida (Mart. ex J.A.Schmidt) Lundell 1 Guapira opposita (Vell.) Reitz 1 1 SANTALALES OLACACEAE Tetrastylidium grandifolium (Baill.) Sleumer 6 PROTEALES PROTEACEAE Roupala montana Aubl. 1 TOTAL 269 352 295
51 Figure 1. Phylogeny of tree families from a lowland Atlantic forest at Poço das Antas Biological Reserve, southeastern Brazil. The phylogenetic hypothesis is based on the phylogenetic tree of Magallón et al. (2015) and encompasses all tree species sampled along a gradient of disturbance history. Bars on the right side show the relative abundance of families in each forest type. OG, old- growth forests; BU, burned secondary forests; UN, unburned secondary forests.
52 Figure 2. Abundance-weighted mean family ages of tree communities in a lowland Atlantic forest at Poço das Antas Biological Reserve, southeastern Brazil. Tree communities were sampled in burned secondary forests (BU), unburned secondary forests (UN) and old-growth forests (OG). Family age estimates from Magallón et al. (2015). Error bars represent standard deviation.
53 Figure 3. Scatter diagram of lowland Atlantic tree communities as a function of their phylogenetic composition in Poço das Antas biological Reserve, southeastern Brazil. Principal coordinate analysis was applied on a matrix of tree communities described by their phylogeny-weighted species relative abundance, generating Principal Coordinates of Phylogenetic Structure (PCPS). Black dots are communities and grey crosses are species. BU, burned secondary forests; UN, unburned secondary forests; OG, old-growth forests.
54
Capítulo 2
Tree phylogenetic beta diversity and habitat loss in the Atlantic forest of Rio de Janeiro State – implications for the conservation of Angiosperm phylogenetic diversity*
*manuscrito a ser submetida ao periódico Diversity and Distributions
55 Tree phylogenetic beta diversity and habitat loss in the Atlantic forest of Rio de Janeiro State – implications for the conservation of Angiosperm phylogenetic diversity
Pablo Viany Prieto Guilherme Dubal dos Santos Seger Ary Teixeira de Oliveira-Filho Felipe Sodré Barros Marinez Ferreira de Siqueira
Introduction There is an ongoing debate on how phylogenetic information may be used to orientate conservation actions (Faith et al. 2004, Rolland et al. 2011, Winter et al 2013). This represents a shift from traditional, species-focused conservation thinking to an approach in which the evolutionary relationships between species are taken into account. The rationale underlying such approach is that if species loss is inevitable, we must try to save as much evolutionary information as possible (Rolland et al. 2011). The most common approach used to incorporate phylogenetic information into conservation planning is to map phylogenetic diversity (PD; Faith 1992) across landscapes or regions and then identify areas with higher PD (e.g. Pollock et al 2015). More recently, metrics of phylogenetic beta diversity (sensu Graham & Fine 2008) began to be employed as well (Devictor et al 2010, Morlon et al. 2011). Because phylogenetic beta diversity captures spatial variation in biodiversity better than species composition alone (Swenson et al 2012, Duarte et al. 2014), it stands as a powerful tool for analyzing spatial patterns of biodiversity and selecting important areas for conservation.
Setting conservation priorities at most spatial scales is unavoidably hampered by our limited knowledge of virtually all basic aspects of biodiversity. Hortal et al. (2015) have summarized these
56 knowledge gaps (or shortfalls) and classified them into seven categories, with each category referring to a distinct aspect of biodiversity. Among these shortfalls, the Linnean (i.e. the existence of many undescribed species) and Wallacean (uncomplete knowledge of species distributions) shortfalls play a critical role in conservation planning, as the spatial distribution of species richness and endemism is frequently used to set conservation priorities (Whitaker et al. 2005, Hortal et al. 2015). In recent years, species distribution models (SDMs) have been increasingly employed to deal with the
Wallacean shortfall, that is, lack of knowledge of species geographic distribution. As more data became available through databases and more powerful analytical tools have been developed, there was a boom in studies applying SDMs to predict species potential geographic distribution based on point occurrences and (most frequently) climatic data (Elith & Leathwick 2009). This approach, however, has some limitations. For instance, modelling the distribution of a large number of rare species - which constitute the bulk of species richness in most communities, and especially in highly diverse systems such as tropical forests - may be a hard task, given that point occurrences are highly biased in space due to a strongly biased distribution of collection effort. So, if any given species is represented by a few points that are highly biased in geographic space, a SDM is expected not to represent correctly the species's climatic requirements and tolerances (Hortal et al. 2008). In this context, community-level models (CLMs) represent a promising alternative to single-species models
(Maguire et al 2015), and the performance of CLMs may be improved by incorporating phylogenetic relationships between species in the response variable (e.g. Rosauer et al 2014). By analyzing data at higher taxonomic levels CLMs rely on a higher number of observations, allowing one to develop consistent models which may include data from a high number of rare, poorly known species. This may represent a useful tool for overcoming the Wallacean shortfall, especially while setting conservation priorities in regions with a high number of rare species whose distributions are barely known.
The Atlantic forest Biome, originally found all along the eastern Brazilian coast, is regarded
57 as one of the main hotspots for biodiversity conservation on Earth due to its high endemism levels in both plant and animal groups and the widespread deforestation to which it has been subjected (Myers et al. 2000). Nowadays, remaining forest sums up only ~13% of the original forest cover, and the spatial distribution of the vegetation remnants is strongly biased toward a few regions (Ribeiro et al
2009). Many studies have documented the expressive variation in tree species composition among distinct forest physiognomies of the Atlantic forest biome, and the role of climatic factors in driving such variation (Oliveira-Filho & Fontes 2000, Bergamin et al. 2012, Saiter et al. 2016). Moreover, it has been shown that climatic factors also drive variations in the phylogenetic composition of Atlantic tree communities at the regional scale (Duarte et al. 2012), in such a way that each forest type shows a distinctive tree phylogenetic composition (Duarte et al. 2014). So, considering that (1) certain tree clades are associated with specific forest physiognomies within the Atlantic forest biome (Duarte et al. 2014) and (2) the spatial distribution of forest remnants is highly biased toward some forest physiognomies (Costa et al. 2009, Ribeiro et al. 2009), we can hypothesize that some tree clades are associated with highly deforested regions and/or vegetation physiognomies. From the perspective of conserving phylogenetic diversity, those clades most associated to deforested regions may be prioritized for conservation. For instance, endemic species from these clades could receive higher attention than species from clades associated to regions and/or vegetation physiognomies less impacted by human activities. This may be an important tool to define priorities for conservation in a scenario of high deforestation at the Biome scale, as is the case of the Brazilian Atlantic forest.
In this study we used selected checklists of angiosperm tree and shrub species together with information from published phylogenies to assess the phylogenetic diversity and composition of tree/shrub communities in distinct forest physiognomies of the Atlantic forest biome within Rio de
Janeiro State, southeastern Brazil. We combined multivariate and modelling approaches to predict the phylogenetic composition and diversity of communities in all unsampled sites within the State.
Then we correlated the resulting models with maps of vegetation cover and protected areas, to identify
58 clades subjected to higher habitat loss in Rio de Janeiro state. Finally, we discuss the implications of our findings for the conservation of tree phylogenetic diversity in the Atlantic forest biome and propose actions to conserve endangered tree/shrub lineages.
Methods
Study area - Rio de Janeiro State occupies an area of ~44.000 km2 in the southeastern coast of Brazil
(Figure 1). The State is characterized by a strong topographic variation, including coastal lowlands and mountain ranges up to ~2800 m, and originally was totally covered by distinct physiognomies of the Atlantic forest domain ranging from coastal dry forests to montane rain forests and high-altitude cloud forests. Within the Atlantic forest Biome, Rio de Janeiro State is considered one of the main endemism centers for both plants (Murray-Smith et al. 2009, Werneck et al. 2011) and birds (Harris et al 2005). Since the arrival of European settlers ~500 years ago there was a steep intensification of human occupation and exploration of natural resources (Dean 1996), and consequently the forest cover has been reduced to 18.8% of its original extension in Rio de Janeiro State (SOS Mata Atlântica
& INPE 2015). Habitat loss, however, differs markedly among distinct physiognomies, with more seasonal forests being much more deforested than rain forests (Fidalgo et al 2009) and lowlands being more deforested than montane regions (Costa et al. 2009).
Sampling - We used a large database containing checklists of tree and shrub (> 3 m) species from selected Neotropical sites (NeoTropTree; Oliveira-Filho 2014). Species lists for each site were obtained from floristic and phytosociological surveys and herbarium records. NeoTropTree also contains detailed geographical and environmental information for each site, including data on climate, geomorphology and soils. We extracted data from Rio de Janeiro State, which consists of species checklists and geographical/environmental data from 110 sites spread all over the State’s area (Figure
1). Only native angiosperm species were included in the analyses. Each site was classified into one
59 of the following vegetation physiognomies: (1) Rain forest; (2) Seasonal forest; (3) Cloud forest; and
(4) Restinga, which includes both open shrubland and closed-canopy forests that grow on nearshore sand deposits of Quaternary origin.
Data analyses - We constructed a phylogenetic tree based on the hypothesis proposed by Magallón et al. (2015), with resolution at family level. Branch lengths within families were adjusted using the
BLADJ algorithm of Phylocom 4.2 software (Webb et al. 2008). Then we generated the phylogenetic tree using the Phylomatic 2 module of Phylocom 4.2 software (Webb & Donoghue 2005) and calculated the phylogenetic pairwise distance matrix (Dp; in millions of years) among all sampled species. To calculate phylogenetic alfa diversity of communities we computed the phylogenetic version of Rao’s quadratic entropy (QE), which measures within-community mean pairwise phylogenetic distance among species (Tucker et al 2016). This index has the advantage of being insensitive to community species richness, which is highly desirable in our case because variation in species richness between sites are partially driven by differences in sampling method and effort. To calculate phylogenetic beta diversity we employed the phylogenetic fuzzy-weighting method developed by Pillar & Duarte (2010), which combines the phylogenetic information contained in Dp and a matrix of sites described by species presence/absence to generate a matrix P expressing the representativeness of different lineages within samples (Duarte et al. 2014). The matrix P was subjected to principal coordinates analysis (PCoA) using square-root of Bray-Curtis dissimilarities between plots. The resulting principal coordinates of phylogenetic structure (PCPS; Duarte 2011) describe orthogonal phylogenetic gradients in the data set. The PCPS with the highest eingenvalues describes phylogenetic gradients related to wide phylogenetic clades, represented by deep nodes in the phylogenetic tree, while PCPS with lower eingenvalues are related to shallow nodes representing finer taxonomic scales (e.g. families and genera; Duarte et al. 2012). This procedure was carried out using the PCPS package (Debastiani & Duarte 2014) in the R Statistical Environment. We applied the function PCPS.sig to test for the significance of the relationship between the PCPSs and the
60 distinct forest types. The function uses two null models, one that shuffles the sites across the forest types (site shuffle) and one that shuffles the species across the tips of the phylogenetic tree (taxa shuffle; Duarte et al. 2016). The first null model tests whether variation in phylogenetic composition among plots is driven by the environmental gradient, while the second null model tests whether the association between the environmental gradient and the PCPSs is driven either by the phylogenetic position of species or merely by species composition. We also tested for differences among forest types in their ordination scores in the two first PCPSs by means of one-way ANOVAs followed by
Tukey's HSD test.
To predict the phylogenetic diversity (Rao’s QE) and the phylogenetic composition (i.e. ordination scores in PCPS 1 and 2) of tree communities in unsampled sites within Rio de Janeiro state we employed the Random Forests algorithm (Breiman 2001, Prasad et al 2006). Random Forests generates multiple decision trees (the forest) by taking bootstrap samples of the dataset, and averages all the trees to build a more robust tree. In each node a random subset of environmental predictors is tested. Thus, the algorithm has two sources of randomness, the bootstrap sampling of the response vector in each tree and the sampling of predictor variables in each node. We used a set of 21 bioclimatic variables (Wordclim; Hijmann et al 2005), five soil variables (organic carbon content and percentage of sand, clay, silt and coarse fragments; Hengl et al 2014) and two geographic variables
(altitude and distance to ocean). First, we applied the randomForests algorithm to select the best subset of environmental predictors of phylogenetic diversity and PCPS1 and 2 ordination scores of sampled sites, using the procedure developed by Genuer et al (2010). This procedure eliminates both variables with poor explanatory power and variables that are highly correlated to others, generating the best subset of independent variables for model prediction. We built the final randomForest models using the respective subset of selected environmental predictors of phylogenetic diversity and ordination scores along PCPS1 and 2. To predict the phylogenetic diversity and the phylogenetic composition (i.e. ordination scores along PCPS axes 1 and 2) of unsampled sites in Rio de Janeiro
61 state we applied the function predict of package Raster, using as predictors the rasters of environmental variables selected for each model. All rasters were set to a pixel size of 30 m by applying the bilinear method. Finally, we correlated the models of PCPS1, PCPS2 and Rao’s QE with maps of remnant vegetation cover (SOS Mata Atlântica & INPE 2015). Correlations were calculated from 1000 random points placed in each model and in a raster where each pixel represents the amount of vegetation cover in a 1-km radius.
Results
The 110 sites contain 2095 tree and shrub species distributed across the phylogenetic tree of
Angiosperms (Figure 2). Rosids accounted for 60% of total number of species, followed by Asterids
(24%), Magnoliids (11%) and Caryophyllales (2%). Monocots, Proteales, Santalales and
Ranunculales had less than 1%, each one. Within Rosids, Myrtales appears as the richest order, with
500 species (24% of total richness) belonging mostly to Myrtaceae and Melastomataceae. Other important orders within Rosids are Fabales (11% of total richness), Malpighiales (11%) and
Sapindales (6%). Within Asterids, Gentianales and Ericales appear as the richest orders, with 7% and
6% of total richness, respectively. Laurales was the richest order among Magnoliids, accounting for
7% of total richness.
Deviation from both null models (site shuffle and taxa shuffle) was significant for the first three PCPS, indicating the existence of three orthogonal gradients of phylogenetic composition which together account for 50% of total variation in matrix P (Figure 3). We focused our analyses on the two first PCPSs, which account for most variation (44%) and whose predictive models performed better than that of PCPS3 (explained in details below). The first PCPS describes a gradient in the importance of major Angiosperm clades across distinct forest types, with Rosids (except most
Myrtales) strongly associated with seasonal forests and restingas, while Magnoliids are associated
62 with rain forests and cloud Forests (Figure 3). Melastomataceae (Myrtales) constitute a notable exception within Rosids, as it appears highly associated with cloud forests rather than with seasonal forests and restingas. Not surprisingly, Monocots (represented mostly by palms) are associated with rain forests. Asterid clades are scattered along this axis: while Campanulids and Lamiids appear associated with rain and cloud forests, Ericales is more associated with restingas and seasonal forests.
Finally, the orders Caryophyllales and Santalales are strongly associated with restingas and seasonal forests. The second PCPS shows a gradient of importance of distinct Rosid orders, with Fabales being strongly associated with seasonal forests and (to a lesser extent) with rain forests, and Myrtales more associated with cloud forests and restingas. Forest types differed significantly in their ordination scores both in PCPS 1 and 2 (ANOVA; PCPS 1: F(3, 106) = 102, P < 0.0001; PCPS2: F(3, 106) = 58, P <
2 2 0.0001). Model fit was better in PCPS1 (R adj = 0.73) than in PCPS2 (R adj = 0.61). Pairwise comparisons shows that all forest types differed from each other along PCPS 1 (TukeyHSD; P <
0.0001 for all pairwise comparisons, except restinga vs seasonal forest with P < 0.05). In the PCPS
2, all pairwise comparisons were highly significant (P < 0.0001), except the contrast between restinga and cloud forest which was not significant (P = 0.81).
The randomForests-based variable selection procedure (Genuer et al 2010) generated distinct subsets of environmental predictors for each PCPS axis and for Rao’s quadratic entropy (Figures 4).
For the first axis, eight variables were selected (in decreasing order of importance; Figure 4): annual precipitation, precipitation of the wettest month, elevation, mean temperature of the driest quarter, precipitation seasonality, mean temperature of the wettest quarter, precipitation of the driest quarter and distance to ocean. For the second axis, only four variables were selected (Figure 4): distance to ocean, altitude, precipitation of the wettest month and mean temperature of the hottest quarter. For the Rao’s quadratic entropy, six variables were selected (Figure 4): precipitation of the wettest month, precipitation of the wettest quarter, distance to ocean, altitude, precipitation seasonality and soil clay content. The final randomForest model of the first PCPS axis (Figure 5) explained 76% of the
63 phylogenetic variation along this axis (mean squared residuals: 0.003), and the final model of the
PCPS 2 (Figure 6) explained 68% of the phylogenetic variation in this axis (mean squared residuals:
0.002). The final model of Rao’s quadratic entropy (Figure 7) explained 58% of variation in phylogenetic diversity among plots (mean squared residuals: 0.95). The first PCPS is positively correlated with the map of remnant vegetation (Spearman rank correlation: 0.59, P < 0.0001; Figure
8), indicating that clades with negative ordination scores (i.e. left side of the scatterplot in Figure 3) are associated with more deforested sites than clades with positive scores (i.e. right side of the scatterplot). So, most Rosids (excluding Myrtaceae and Melatomataceae), Ericales (Asterids),
Caryophyllales and Santalales are strongly associated with highly deforested forest types, that is, seasonal forests and restingas. On the other hand, clades that are associated to less deforested forest types include Magnoliids, Monocots and some Lamids and Campanulids (both Asterids). Both the
PCPS 2 axis and Rao’s quadratic entropy are weakly correlated with the map of vegetation remnants
(Spearman rank correlation = 0.11 and 0.29; P < 0.01 and P<0.0001, respectively).
Discussion
We presented a novel modelling approach that allowed us to predict the phylogenetic diversity and composition of tree communities based on species checklists, a published phylogeny and a set of environmental predictors. Our randomForest-based modelling approach was able to identify a distinct set of environmental predictors for each response variable, and to successfully predict the phylogenetic composition of tree/shrub communities in unsampled sites, especially along the PCPS1 axis. Furthermore, we developed a simple method that relates the phylogenetic diversity and composition of communities to the spatial distribution of vegetation remnants, which allowed us to identify vegetation types and associated clades that are more threatened by habitat loss. The modelling approach we present here may be useful for a range of applications, from conservation planning to vegetation mapping. We discuss some of these issues in detail in the following paragraphs.
64 We showed that Angiosperm tree lineages are highly structured across distinct forest types within the Atlantic forest of Rio de Janeiro state, with each forest type being characterized by a unique combination of Angiosperm clades. We also show that variation in tree phylogenetic composition is paralleled by a steep gradient of habitat loss, in such a way that some clades are strongly associated with highly deforested vegetation physiognomies, i.e. restingas and seasonal forests. So, we demonstrate unequivocally that some Angiosperm tree lineages are subjected to significantly more habitat loss than others at this regional scale. Specifically, Rosids (except most Myrtales), Ericales
(Asterids), Caryophyllales and Santalales appear associated with the highly-deforested extreme of the phylogenetic gradient expressed by the first ordination axis. Therefore, we propose that tree and shrub species from these lineages should be prioritized for conservation actions, especially those that are endemic and rare. It is worth noting that clades subjected to high habitat loss differ markedly in their number of species. While Rosids (except Myrtales) has 766 species, Ericales (Asterids),
Caryophyllales and Santalales have 130, 43 and 11 species, respectively. The order Santalales deserves attention for a number of reasons. Besides showing the lowest species richness among threatened clades, two out of these 11 species occur only in Rio de Janeiro state, and a third species is found only in Rio de Janeiro state and in the neighboring Espírito Santo. Interestingly, Santalales is comprised predominantly by parasitic species (Kujit & Hansen 2015). Parasitic plants perform a quite distinctive and important role in the ecosystems where they occur, especially in nutrient poor ones (Press 1998), and for this reason they may be considered keystone species (Press & Phoenix
2005). So, Santalales represents a highly endangered, species-poor clade whose species may perform a specific and relevant function in the nutrient-poor restingas, where they are mostly found. Therefore, the extinction of all tree species from these clade could impact significantly the structure and dynamics of the ecosystems where they are found.
RandomForest models of beta diversity, and particularly the PCPS1 model, performed better than the model of alpha diversity (Rao’s QE). The implications for conservation from each of these
65 models are also contrasting. The correlation between the PCPS1 model and the amount of remnant vegetation points to restingas and seasonally dry forests as the highest priorities for conservation based in a complementarity approach, while the Rao’s QE model indicates that seasonally dry coastal forests and restingas have the lowest values of phylogenetic alfa diversity, thus having less value for conservation. We argue that the PCPS1 is more appropriate for conservation planning because of its better model performance and also because it presents the highest correlation with the amount of remaining vegetation, thus allowing for a more clear picture of the relationship between tree phylogenetic diversity and habitat loss. The PCPS1 model highlights the conservation importance of the Cabo Frio region, a small cape that presents a distinctive dry vegetation with a high incidence of endemic species (Araújo et al. 2009). The seasonally dry forests of Cabo Frio have been historically explored for the extraction of brazilwood (Paubrasilia echinata, Leguminosae) (Dean 1996).
Currently, the region is under extreme pression from urban expansion, which is aggravated by the low degree of land protection (Costa et al. 2009). So, besides presenting a distinctive biota and being highly deforested, this region is also poorly protected. Therefore, the Cabo Frio region should be of highest priority for conservation actions, which should focus on restoring the typical vegetation and increasing the degree of land protection.
An important question is whether our results can be extrapolated to larger scales within the
Atlantic forest biome. The transferability of our results depends on two conditions: (1) tree and shrub communities at larger scales should present a similar pattern of phylogenetic beta diversity; and (2) large-scale variation in habitat loss among distinct vegetation physiognomies should be similar to that observed in Rio de Janeiro. The condition (1) can be assessed by comparing our results with those of
Duarte et al. (2014), who investigated the phylogenetic beta diversity of tree communities (including gimnosperms) over a much broader region within the Brazilian Atlantic forest. The authors also found a strong association of most Rosids (except Myrtales) and Ericales with seasonal forests, while
Myrtales, and especially Myrtaceae, were associated with rainforests (which in this case also included
66 restingas and cloud forests). So, the similarity between our results and those obtained by Duarte et al.
(2014) from a much larger region suggests that the patterns we found within Rio de Janeiro state may replicate over a range of spatial scales, from small to large regions and possibly up to the Biome scale
(i.e. the whole Atlantic forest). The condition (2) can be assessed by comparing patterns of deforestation observed in Rio de Janeiro to the patterns found in the Atlantic forest biome. Ribeiro et al. (2009) provided a detailed analysis of the amount of remaining habitat in the Atlantic forest, including comparisons between distinct biogeographical sub-regions. The biogeographic sub-regions with the highest proportions of remaining forest correspond to rain forest regions, while the sub- regions with the highest habitat loss correspond to hinterland, seasonal forests (Ribeiro et al. 2009).
So, the unbalance in habitat loss between distinct forest physiognomies observed in Rio de Janeiro state, with seasonal forests showing a much higher habitat loss than rain forests (Fidalgo et al 2009), seems to scale up to the whole Atlantic forest biome, where seasonal forests are much more deforested than rain forests (Ribeiro et al. 2009). So, if there is a correspondence between distinct spatial scales in both tree phylogenetic beta diversity and patterns of habitat loss, we argue that the same clades that are more threatened by habitat loss at the scale of Rio de Janeiro state may also be so at the scale of the Atlantic forest biome.
The phylogenetic priorization scheme proposed here is not intended to substitute but rather to complement other priorization schemes such as IUCN’s extinction risk assessments (IUCN 2001).
The IUCN’s framework does not take into account the phylogenetic relationships between species, and there has been some attempts to test whether the phylogenetic position of a species may predict its extinction risk (Vamosi & Wilson 2008) and how threat status relates to the evolutionary uniqueness of species (Mooers et al 2008). We propose that threatened species can also be ranked according to the threat status of the lineages they belong to. It is sure that a critically endangered (CR) species should always be prioritized for conservation regardless of the threat status of its lineage.
However, if one must choose between two vulnerable (VU) species to conserve, and these species
67 belong to distinct lineages with contrasting threat statuses, then it would be recommendable to conserve the species from the more endangered clade. In some cases, it even may be preferable to conserve a VU species from a highly threatened clade than an endangered (EN) species from a clade subjected to a low threat. This method may be particularly useful in regions with a high number of threatened species, where it may not be feasible to plan and execute conservation actions for all endangered species. Furthermore, our results also emphasize the relevance of conserving distinct vegetation physiognomies within a region in order to get a complete representation of angiosperm tree and shrub lineages.
The order Myrtales is remarkably distinguished from all other angiosperm orders for two reasons: (1) It accounts for 24% of total angiosperm species richness, being as rich as the Asterids and having more than two-fold the richness of Fabales and Malpighiales, which are respectively the second and third richest orders within Rosids; and (2) It successfully occupies the whole range of vegetation physiognomies within the Atlantic forest of Rio de Janeiro state, with its constituent families arrayed along the distinct forest types found in this region. The family Combretaceae is associated with restingas and seasonal forests, resembling the habitat preferences of most Rosids (see
Figure 3). Interestingly, this family is associated with forest areas under low rainfall in central Panama and in the Western Ghats region in India (Hardy et al. 2012), indicating a widespread conservatism of its climatic niche. Phylogenetic evidence suggests that Combretaceae is sister to all other Myrtales, thus consisting in the oldest extant lineage within the order (Berger et al 2016). So, it seems that the early-diverging Combretaceae conserved the Rosid climatic niche, while younger Myrtales lineages such as Myrtaceae, Vochysiaceae and Melastomataceae successfully adapted to a colder and wetter montane climate under which cloud forests are found. Therefore, we hypothesize that the climatic niche shift that occurred within Myrtales could have contributed to the high species richness observed in Myrtaceae and Melastomataceae.
In conclusion, we found that angiosperm tree/shrub lineages are highly structured across
68 distinct vegetation physiognomies in Rio de Janeiro state, and that a steep deforestation gradient parallels the phylogenetic gradient formed by the distinct vegetation types. Consequently, some vegetation physiognomies and its associated angiosperm lineages are much more threatened by habitat loss than others. Specifically, most Rosids (except Myrtales), Ericales (Asterids),
Caryophyllales and Santalales are the most threatened clades in this region, along with their preferred habitats, seasonal forests and restingas. We argue that the patterns we found in Rio de Janeiro may mirror patterns at larger scales, in such a way that the same clades and vegetation physiognomies that are more threatened at this small region are so at larger spatial scales as well. Modelling the phylogenetic beta diversity of communities may be quite useful for conservation planning that aims at representing the diversity of vegetation formations within a region or biome.
References
Araujo, D.S.D., Sá, C.F.C., Fontella-Pereira, J., Garcia, D.S., Ferreira, M.V., Paixão, R.J., Schneider,
S.M. & Fonseca-Kruel, V.S. 2009 Área de proteção ambiental de Massambaba, Rio de Janeiro:
caracterização fitofisionômica e florística. Rodriguésia 60: 67-96.
Bergamin R.S., Mello R.S.P. & Müller S.C. 2012. Indicator species and floristic patterns in different
forest formations in southern Atlantic rainforests of Brazil. Community Ecology 13: 167-170.
Breiman, L. 2001. Random Forests. Machine Learning 45: 5-32.
Brent, A.B., Kriebel, R., Spalink, D. & Systma, K.J. 2016. Divergence times, historical biogeography,
and shifts in speciation rates of Myrtales. Molecular Phylogenetics and Evolution 95: 116-136.
Cavender-Bares, J., Kozak, K., Fine, P. & Kembel, S. 2009. The merging of community ecology and
phylogenetic biology. Ecology Letters 12: 693-715.
69 Costa, T.C.C., Fidalgo, E.C.C., Santos, R.F., Rocha, J.V., Metzgre, J.P., Vicens, R.S., Tanizaki-
Fonseca, K. e Bohrer, C.B.A. 2009. Diversidade de paisagens no estado do Rio de Janeiro. In:
Bergallo et al. (orgs). Estratégias e ações para a conservação da biodiversidade no Estado do
Rio de Janeiro. Rio de Janeiro: Instituto Biomas. p.101-110.
Debastiani, V.J. & Duarte, L.D.S. 2014. PCPS - an R-package for exploring phylogenetic
eigenvectors across metacommunities. Frontiers of Biogeography 6: 144-148.
Duarte, L.S. 2011. Phylogenetic habitat filtering influences forest expansion over grasslands. Oikos
120: 208–215.
Duarte, L.D.S., Both, C., Debastiani, V.J., Carlucci, M.B., Gonçalves, L.O., Capelatti, L., Seger,
G.D.S., Bastazini, V.A.G., Brum, F.T., Salengue, E.V. & Bernardo-Silva,J.S. 2014. Climate
effects on amphibians distributions depend on phylogenetic resolution and the biogeographical
history of taxa. Global Ecology and Biogeography 23: 213-222.
Duarte LS, Debastiani VJ, Freitas AVL, Pillar VP. 2016. Dissecting phylogenetic fuzzy weighting:
theory and application in metacommunity phylogenetics. Methods in Ecology and Evolution.
doi:10.1111/2041-210X.12547
Duarte, L.S., Prieto, P.V. & Pillar, V.P. 2012. Assessing spatial and environmental drivers of
phylogenetic structure in Brazilian Araucaria forests. Ecography 35: 952-960.
Elith, J. & Leathwick, J.R. 2009. Species distribution models: ecological explanation and prediction
across space and time. Annual Review of Ecology, Evolution and Systematics 40: 677-697.
Faith, D.P. 1992. Conservation evaluation and phylogenetic diversity. Biological Conservation 61:
1-10.
Faith, D.P, Reid, C.A.M. e Hunter, J. 2004. Integrating phylogenetic diversity, complementarity, and
endemism for conservation assessment. Conservation Biology 18: 255-261.
Genuer, R., Poggi, J.-M. & Tuleau-Malot, C. Variable selection using Random Forests. Pattern
Recognition Letters 31: 2225-2236.
70 Graham, C.H. e Fine, P.V.A. 2008. Phylogenetic beta diversity: linking ecological and evolutionary
processes across space in time. Ecology Letters 11: 1265-1277.
Hardy, O.J., Couteron, P., Munoz, F., Ramesh, B.R. e Pélissier, R. 2012. Phylogenetic turnover
in tropical tree communities: impact of environmental filtering, biogeography and
mesoclimatic niche conservatism. Global Ecology and Biogeography 21: 1007-1016.
Hortal, J., Bello, F., Diniz-Filho, J.A.F., Lewinsohn, T.M., Lobo, J.M. e Ladle, R.J. 2015. Seven
shortfalls that beset large-scale knowledge of biodiversity. Annual review of Ecology, Evolution
and Systematics 46: 523-549.
Kujit, J. & Hansen, B. 2015. The families and genera of vascular plants XII: Santalales,
Balanophorales. Springer International Publishing.
Magallón, S., Gómez-Acevedo, S., Sánchez-Reyes, L.L. & Hernández-Hernández, T. 2015. A
metacalibrated time-tree documents the early rise of flowering plant phylogenetic diversity. New
Phytologist 207: 437-453.
Morlon, H., Scwilk, D.W., Bryant, J.A., Marquet, P.A., Rebelo, A.G., Tauss, C., Bohannan,
B.J.M. e Green, J. 2011. Spatial patterns of phylogenetic diversity. Ecology Letters 14:
141-149.
Mooers, A.Ø., Faith, D.P. & Maddison, W.P. 2008. Converting endangered species categories
to probabilities of extinction for phylogenetic conservation priorization. PLoS ONE 3:
e3770.
Murray-Smith, C., Brummitt, N.A., Oliveira-Filho, A.T., Bachman, S., Moat, J., Lughadha,
E.M.L. e Lucas, E.J. 2008. Plant diversity hotspots in the Atlantic coastal forests of Brazil.
Conservation Biology 23: 151-163.
Myers, N., Mittermeier, R. A., Mittermeier, C. G., Fonseca, G. A. B. & Kent, J. 2000. Biodiversity
hotsposts for conservation priorities. Nature 403: 853-858.
71 Oliveira-Filho, A.T. 2014. NeoTropTree, Flora arbórea da Região Neotropical: Um banco de dados
envolvendo biogeografia, diversidade e conservação. Universidade Federal de Minas Gerais.
Available at http://www.icb.ufmg.br/treeatlan/.
Oliveira-Filho AT, Fontes MAL. 2000. Patterns of floristic differentiation among Atlantic Forests in
southeastern Brazil and the influence of climate. Biotropica 32:793–810.
Pillar, V.D. & Duarte, L.S. 2010. A framework for metacommunity analysis of phylogenetic structure.
Ecology Letters 13: 587–596.
Press, M.C. 1998. Dracula or Robin Hood? A functional role for root hemiparasites in nutrient poor
ecosystems. Oikos 82: 609-611.
Press, M.C. & Phoenix, G.K. 2005. Impacts of parasitic plants on natural communities. New
Phytologist 166: 737-751.
Ribeiro MC, Metzger JP, Martensen AC, Ponzoni FJ, Hirota MM. 2009. The Brazilian Atlantic
Forest: how much is left, and how is the remaining forest distributed? Implications for
conservation. Biological Conservation 142:1141–1153.
Ricklefs, R.E. 2008. Disintegration of the ecological community. American Naturalist 172: 741-750.
Rolland, J., Cadotte, M.W., Davies, J., Devictor, V., Lavergne, S., Mouquet, N., Pavoine, S.,
Rodrigues, A., Thuiller, W., Turcati, L., Winter, M., Zupan, L., Jabot, F. & Morlon, H. 2012
Using phylogenies in conservation: new perspectives. Biology Letters 8: 692-694.
Rosauer, D.F., Ferrier, S., Williams, K.J., Manion, G., Keogh, J.S. e Laffan, S.W. 2014. Phylogenetic
generalised dissimilarity modelling: a new approach to analysing and predicting spatial turnover
in the phylogenetic composition of communities. Ecography 37: 21-32.
Saiter, F.Z., Brown, J.L., Thomas, W.W., Oliveira-Filho, A.T. & Carmaval, A.C. 2016.
Environmental correlates of floristic regions and plant turnover in the Atlantic forest hotspot.
Journal of Biogeography 43: 2322-2331.
72 Swenson, N.G. 2013. The assembly of tropical tree communities - the advances and shortcomings of
phylogenetic and functional trait analyses. Ecography 36: 264-276.
Swenson, N.G., Erickson, D.L., Mi, X., Bourg, N.A., Forero-Montana, J., Ge, X., Howe, R., Lake,
J.K., Liu, X., Ma, K. et al. 2012. Phylogenetic and functional alpha and beta diversity in temerate
and tropical tree communities. Ecology 93: S112-S125.
Vamosi, J.C. & Wilson, J.R.U. 2008 Nonrandom extinction leads to elevated loss of angiosperm
evolutionary history. Ecology Letters 11: 1047-1053.
Vamosi, S.M., Heard, S.B., Vamosi, J.C. & Webb, C.O. 2009. Emerging patterns in the comparative
analysis of phylogenetic community structure. Molecular Ecology 18: 572-592.
Webb, C.O., Ackerly, D.D., McPeek, M.A. & Donoghue, M.J. 2002. Phylogenies and community
ecology. Annual Review of Ecology and Systematics 33: 475-505.
Webb, C.O., Ackerly, D.D. & Kembel, S.W. 2008. Phylocom: software for the analysis of
phylogenetic community structure and trait evolution. Bioinformatics 24: 2098-2100.
Webb, C.O. & Donoghue, M.J. 2005. Phylomatic: Tree assembly for applied phylogenetics.
Molecular Ecology Notes 5: 181-183.
Wernek, M. S., Sobral, M.E.G., Rocha, C.T.V., Landau, E.C. e Stehmann, J.R. 2011.
Distribution and endemism of angiosperms in the Atlantic forest. Natureza & Conservação
9: 188-193.
Whitaker, R.J., Araújo, M.B., Jepson, P., Ladle, R.J., Watson, J.E.M. e Willis, K.J. 2005.
Conservation biogeography: assessment and prospect. Diversity and Distributions 11: 3-
23.
Winter, M., Devictor, V. & Schweiger, O. 2013. Phylogenetic diversity and nature conservation:
where are we? Trends in Ecology and Evolution 28: 199-204.
73 Figure 1. Map of Rio de Janeiro State. Symbols indicate sampling sites in the distinct vegetation types. Black saquares, rain forest; grey squares, seasonal forest; White triangle, restinga; and White square, cloud forests.
74 Figure 2. Phylogeny of 2109 angiosperm tree/shrub species occuring in 110 Atlantic forest sites in
Rio de Janeiro State, southeastern Brazil. Numbers indicate clades above order level and letters indicate main orders. 1-Magnoliids; 2-Monocots; 3-Eudicots; 4-Core Eudicots; 5-Rosids; 6-Malvids;
7-Fabids; 8-Asterids; 9-Core Asterids; 10-Lamiids; 11-Campanulids; a-Myrtales; b-Malvales; c-
Sapindales; d-Fabales; e-Rosales; f-Malpighiales; g-Caryophyllales; h-Ericales; i-Solanales
(Solanaceae); j-Gentianales; k-Lamiales; l-Laurales. Colors indicate distinct genera.
75 Figure 3. Scatter diagram of Atlantic tree communities as a function of their phylogenetic composition in Rio de Janeiro State, southeastern Brazil. Principal coordinate analysis was employed on a matrix of sites described by their phylogeny-weighted tree/shrub species composition, generating
Principal Coordinates of Phylogenetic Structure (PCPS).
76 Figure 4. Importance of environmental predictors selected for each randomForest model. Variable importance expresses the contribution of each variable to decrease the mean square error in the model.
The community data consists in selected checklists of tree and shrub angiosperms species from
Atlantic forest sites in Rio de Janeiro State, southeastern Brazil. RF.PCPS1 and RF.PCPS2 are the randomForest models built for the two first ordination axes of a principal coordinate analysis performed on a matrix of phylogeny-weighted species presence/absence. RF.Rao is the randomForest model built for the phylogenetic version of the within-community Rao’s quadratic entropy. Pwm, precipitation of the wettest month; dist, distance to ocean; elev, elevation; ps, precipitation seasonality; mthq, mean temperature of the hottest quarter; pre, annual precipitation; pwq, precipitation of the wettest quarter; mtdq, mean temperature of the driest quarter; mtwq, mean temperature of the wettest quarter; pdq, precipitation of the driest quarter; clay, soil clay content.
77
Figure 5. Predicted phylogenetic composition of Atlantic forest tree communities in Rio de Janeiro
State, southeastern Brazil. The model describes the position of communities along the first axis of a principal coordinates of phylogenetic structure (PCPS) analysis. PCPS were calculated by applying a principal coordinates analysis on a matrix of phylogeny-weighted tree/shrub species presence/absence. The phylogenetic structure of unsampled sites, as expressed by the ordination scores along the first PCPS axis, was modelled using the randomForest algorithm and a set of 28 bioclimatic, geographic and soil variables.
78 Figure 6. Predicted phylogenetic composition of Atlantic forest tree communities in Rio de Janeiro
State, southeastern Brazil. The model describes the position of communities along the second axis of a principal coordinates of phylogenetic structure (PCPS) analysis. PCPS were calculated by applying a principal coordinates analysis on a matrix of phylogeny-weighted tree/shrub species presence/absence. The phylogenetic structure of unsampled sites, as expressed by the ordination scores along the second PCPS axis, was modelled using the randomForest algorithm and a set of 28 bioclimatic, geographic and soil variables.
79 Figure 7. Predicted phylogenetic alpha diversity of Atlantic forest tree communities in Rio de Janeiro
State, southeastern Brazil. The model describes variation in the phylogenetic version of Rao’s quadratic entropy. Phylogenetic diversity was modelled using the randomForest algorithm and a set of 28 bioclimatic, geographic and soil variables.
80 Figure 8. Scatterplot diagram showing the relationship between the ordination scores in PCPS1 axis and the amount of remnant vegetation cover. X-axis values were obtained from 1000 random points spread over a randomForest model which predicts the variation in ordination scores of unsampled communities along the PCPS1 axis. Y-values were obtained from the same 1000 random points spread over a raster in which the values of each pixel represents the amount of remaining vegetation cover in a 1-km radius.
81 Considerações finais
Ao longo desta tese, eu utilizei ferramentas de análise da estrutura filogenética de comunidades para tentar responder a algumas questões que são relevantes para a conservação da diversidade de árvores da Mata Atlântica no Estado do Rio de Janeiro. No primeiro capítulo, eu verifiquei que florestas secundárias estabelecidas em locais com um longo histórico de perturbações dentro da Reserva Biológica de Poço das Antas são dominadas pela Asteraceae
Gochnatia polymorpha, espécie pertencente a uma linhagem recentemente evoluída em meio ao ambiente aberto, de solos pobres e sujeito a incêndios do Cerrado. Na floresta em estágio avançado de sucessão, por outro lado, são encontradas linhagens antigas e tipicamente florestais, como Magnoliids e palmeiras. Os resultados indicam que as linhagens mais antigas tendem a preferir ambientes florestais pouco perturbados; assim, sugere-se que a idade média das linhagens de árvores em uma comunidade pode ser um indicativo do grau de perturbação do local. Além disso, também é enfatizada a importância de remanescentes florestais grandes e pouco perturbados para a conservação da diversidade filogenética de árvores da Mata
Atlântica. No segundo capítulo, eu mostrei que cada uma das principais fisionomias de vegetação encontradas no estado do Rio de Janeiro é caracterizada por um conjunto distinto de linhagens de angiospermas arbustivas e arbóreas. O grau de perda de habitat também difere fortemente entre as fitofisionomias, com as restingas e florestas estacionais sendo muito mais desmatadas que as florestas ombrófilas e nebulares. Dessa forma, as linhagens de angiospermas mais fortemente associadas a restingas e florestas estacionais – a maioria das
Rosids, Ericales, Caryophyllales e Santalales – estão sujeitas a uma perda de habitat muito maior do que as linhagens associadas aos outros tipos de vegetação. Tomados em conjunto, os resultados dos dois capítulos mostram a utilidade e o potencial que a abordagem filogenética possui para responder a questões de conservação. A conservação, portanto, pode se beneficiar largamente dessa aplicação, de forma a refinar suas prioridades e a otimizar o
82 emprego dos recursos. Especificamente, o cálculo da beta diversidade filogenética é altamente promissor tanto para o planejamento em escala regional como para testar as respostas das linhagens a distúrbios em escala local. Espera-se que outras aplicações possam surgir, de forma a consolidar o uso da filogenia em abordagens conservacionistas.
83