In Silico and Biochemical Analysis of Physcomitrella patens Photosynthetic Antenna: Identification of Subunits which Evolved upon Land Adaptation

Background. In eukaryotes the photosynthetic antenna system is composed of subunits encoded by the light harvesting complex (Lhc) multigene family. These proteins play a key role in photosynthesis and are involved in both light harvesting and photoprotection. The moss Physcomitrella patens is a member of a lineage that diverged from seed plants early after land colonization and therefore by studying this organism, we may gain insight into adaptations to the aerial environment. Principal Findings. In this study, we characterized the antenna protein multigene family in Physcomitrella patens, by sequence analysis as well as biochemical and functional investigations. Sequence identification and analysis showed that some antenna polypeptides, such as Lhcb3 and Lhcb6, are present only in land organisms, suggesting they play a role in adaptation to the sub-aerial environment. Our functional analysis which showed that photo-protective mechanisms in Physcomitrella patens are very similar to those in seed plants fits with this hypothesis. In particular, Physcomitrella patens also activates Non Photochemical Quenching upon illumination, consistent with the detection of an ortholog of the PsbS protein. As a further adaptation to terrestrial conditions, the content of Photosystem I low energy absorbing chlorophylls also increased, as demonstrated by differences in Lhca3 and Lhca4 polypeptide sequences, in vitro reconstitution experiments and low temperature fluorescence spectra. Conclusions. This study highlights the role of Lhc family members in environmental adaptation and allowed proteins associated with mechanisms of stress resistance to be identified within this large family

An integrated pan-tropical biomass map using multiple reference datasets (PAN-TROPICAL FUSED BIOMASS MAP)

Abstract We combined two existing datasets of vegetation aboveground biomass (AGB) (Saatchi et al., 2011; Baccini et al., 2012) into a pan-tropical AGB map at 1-km resolution using an independent reference dataset of field observations and locally-calibrated high-resolution biomass maps, harmonized and upscaled to 14,477 1-km AGB estimates. Our data fusion approach uses bias removal and weighted linear averaging that incorporates and spatializes Accepted Article This article is protected by copyright. All rights reserved. existing regional biomass maps as input maps and additional, country-specific reference datasets

Variações interanuais na fenologia de uma comunidade arbórea de floresta semidecídua no sudeste do Brasil Interannual variation in the phenology of a tree community in a semideciduous seasonal forest in southeast Brazil

As comunidades arbóreas de florestas tropicais localizadas em regiões com clima sazonal tendem a ajustar a fenologia da queda de folhas e da produção de flores e frutos à sazonalidade climática. Neste estudo monitoramos a comunidade arbórea de uma floresta semidecidual no período de quatro anos (2001 a 2004), a fim de analisar a relação entre o número de espécies perdendo folhas, florescendo e frutificando e a variação anual do comprimento do dia, precipitação e temperatura durante o período de observação. Além disso, avaliamos se essas três fenofases repetem os mesmos padrões em anos sucessivos. Regressões lineares simples indicaram que o número de espécies perdendo folhas foi negativamente relacionado com as três variáveis ambientais para os quatro anos de estudo, sendo o comprimento do dia e a temperatura os melhores preditores para esta fenofase. Houve também relação significativa do comprimento do dia com o número de espécies florescendo e frutificando nos quatro anos, porém, precipitação e temperatura não foram relacionadas com estas fenofases em todos os anos de estudo. Os testes de estatística circular indicaram forte sazonalidade para queda foliar, com data média durante o mês de julho independente do ano, ao passo que para floração e frutificação não foi detectada sazonalidade significativa. Como resultado, o número de espécies perdendo folhas foi correlacionado entre todos os anos sucessivos. Entretanto, não houve correlação do número de espécies florescendo e frutificando em 2003 e 2004, provavelmente devido às altas temperaturas ocorridas neste último ano. Os resultados deste estudo sugerem que a queda de folhas é uma fenofase altamente previsível temporalmente. Ao contrário, a floração e a frutificação podem variar ano a ano como conseqüência de anomalias climáticas. Essas variações podem ser relevantes para o entendimento dos efeitos em longo prazo de mudanças climáticas sobre as florestas sazonais.<br>Tropical tree communities in regions with seasonal climate usually adjust leaf-fall, flowering and fruiting phenology to climate seasonality. Here we monitored a tree community over a 4-year period in order to assess the relationship between the number of species presenting leaf fall, flower and fruit and annual variation in day length, precipitation and temperature. Moreover, we asked whether the three phenological variables have the same patterns in successive years. Simple regression analyses showed that the number of species shedding leaves was negatively related to the three environmental variables during the four years, with day length and temperature as the best predictors. There was also a relationship between day length and the number of species flowering and fruiting, while rainfall and temperature were only related to these phenophases in some years. The circular statistics indicate highly significant seasonality only for leaf fall, whereas for flowering and fruiting significant seasonal patterns were not detected. The number of species in leaf fall was correlated between all successive years. However, the number of species in flower and fruit was not significantly correlated between 2003 and 2004. Overall, our results suggest that leaf fall is highly predictable over time. On the contrary, flowering and fruiting may present year-to-year variation as a result of climatic anomalies such as the high temperatures detected in 2004. These variations may be relevant to understand the effects of climate change on seasonal forests in long-term studies