Adaptabilidade e estabilidade de híbridos de milho para o sul do bioma Amazônia via GGE biplot

The objective of this work was to select maize hybrids using the GGE biplot analysis, as well as to evaluate their stability and adaptability in different environments of the North and Midwest regions of Brazil. Thirty-six maize hybrids were evaluated in 2018, in the following five environments in the Northern and Midwestern regions, respectively: in the municipality of Vilhena, in the state of Rondônia; and in the municipalities of Sorriso, Sinop, Alta Floresta, and Carlinda, in the Northern region of the state of Mato Grosso. The experimental design was a randomized complete block design. The analysis of variance was performed, and adaptability and stability were estimated by the GGE biplot method based on grain yield performance. A significant interaction between genotypes and environments was detected, and the biplot analysis was efficient in explaining 62.74% of the total variation in the first two principal components, with the formation of three macroenvironments. The 1P2227, 'BRS 3042', and 1P2265 hybrids showed high yield, responsiveness, and stability in the evaluated environments. The DKB310VTPRO2 hybrid was the most unstable genotype. The recommended hybrids are: DKB310 for the Sorriso and Vilhena macroenvironment; 1M1810 and 1O2106 for the Carlinda environment; and 1M1807 for the Sinop environment.O objetivo deste trabalho foi selecionar híbridos de milho, por meio da análise GGE biplot, bem como avaliar sua estabilidade e adaptabilidade em diferentes ambientes das regiões Centro-Oeste e Norte do Brasil. Trinta e seis híbridos de milho foram avaliados em 2018, nos seguintes cinco ambientes das regiões Norte e Centro-Oeste, respectivamente: no município de Vilhena, no estado de Rondônia; e nos municípios de Sorriso, Sinop, Alta Floresta e Carlinda, na região norte do estado de Mato Grosso. O delineamento experimental foi em blocos completos ao acaso. Realizou-se a análise de variância, e estimaram-se a adaptabilidade e a estabilidade pelo método GGE biplot com base na produtividade. Detectou-se interação significativa entre genótipos e ambientes, e a análise biplot foi eficiente para explicar 62,74% da variação total nos dois primeiros componentes principais, com a formação de três macroambientes. Os híbridos 1P2227, 'BRS 3042' e 1P2265 apresentam alta produtividade, capacidade de resposta e estabilidade nos ambientes avaliados. O híbrido DKB310VTPRO2 foi o genótipo mais instável. Os híbridos recomendados são: DKB310 para o macroambiente Sorriso e Vilhena; 1M1810 e 1O2106 para o ambiente Carlinda; e 1M1807 para o ambiente Sinop

Bioassay-guided evaluation of central nervous system effects of citronellal in rodents

The central nervous system (CNS) depressant and anticonvulsant activities of citronellal (CT) were investigated in animal models. The CT in doses of 100, 200 and 400 mg/kg injected by i.p. route in mice caused a significant decrease in the motor activity of animals when compared with the control group. The highest dose of CT significantly reduced the remaining time of the animals on the Rota-rod apparatus up to 2 h. Additionally, CT at doses 100, 200 and 400 mg/ kg (i.p.) was also capable to promote an increase of latency for development of convulsions induced by pentylenetetrazole (PTZ). It was efficient in prevents the tonic convulsions induced by maximal electroshock (MES) in doses of 200 and 400 mg/kg, resulting in 30 and 40% of protection, respectively. This compound was also capable to promote an increase of latency for development of convulsions induced by picrotoxin (PIC) at 400 mg/kg. In the same way, the anticonvulsant effect of CT was affected by pretreatment with flumazenil, a selective antagonist of benzodiazepine site of GABAA receptor. These results suggest a possible CNS depressant and anticonvulsant activities

Geographic patterns of tree dispersal modes in Amazonia and their ecological correlates

Aim: To investigate the geographic patterns and ecological correlates in the geographic distribution of the most common tree dispersal modes in Amazonia (endozoochory, synzoochory, anemochory and hydrochory). We examined if the proportional abundance of these dispersal modes could be explained by the availability of dispersal agents (disperser-availability hypothesis) and/or the availability of resources for constructing zoochorous fruits (resource-availability hypothesis). Time period: Tree-inventory plots established between 1934 and 2019. Major taxa studied: Trees with a diameter at breast height (DBH) ≥ 9.55 cm. Location: Amazonia, here defined as the lowland rain forests of the Amazon River basin and the Guiana Shield. Methods: We assigned dispersal modes to a total of 5433 species and morphospecies within 1877 tree-inventory plots across terra-firme, seasonally flooded, and permanently flooded forests. We investigated geographic patterns in the proportional abundance of dispersal modes. We performed an abundance-weighted mean pairwise distance (MPD) test and fit generalized linear models (GLMs) to explain the geographic distribution of dispersal modes. Results: Anemochory was significantly, positively associated with mean annual wind speed, and hydrochory was significantly higher in flooded forests. Dispersal modes did not consistently show significant associations with the availability of resources for constructing zoochorous fruits. A lower dissimilarity in dispersal modes, resulting from a higher dominance of endozoochory, occurred in terra-firme forests (excluding podzols) compared to flooded forests. Main conclusions: The disperser-availability hypothesis was well supported for abiotic dispersal modes (anemochory and hydrochory). The availability of resources for constructing zoochorous fruits seems an unlikely explanation for the distribution of dispersal modes in Amazonia. The association between frugivores and the proportional abundance of zoochory requires further research, as tree recruitment not only depends on dispersal vectors but also on conditions that favour or limit seedling recruitment across forest types

Geography and ecology shape the phylogenetic composition of Amazonian tree communities

AimAmazonia hosts more tree species from numerous evolutionary lineages, both young and ancient, than any other biogeographic region. Previous studies have shown that tree lineages colonized multiple edaphic environments and dispersed widely across Amazonia, leading to a hypothesis, which we test, that lineages should not be strongly associated with either geographic regions or edaphic forest types.LocationAmazonia.TaxonAngiosperms (Magnoliids; Monocots; Eudicots).MethodsData for the abundance of 5082 tree species in 1989 plots were combined with a mega-phylogeny. We applied evolutionary ordination to assess how phylogenetic composition varies across Amazonia. We used variation partitioning and Moran's eigenvector maps (MEM) to test and quantify the separate and joint contributions of spatial and environmental variables to explain the phylogenetic composition of plots. We tested the indicator value of lineages for geographic regions and edaphic forest types and mapped associations onto the phylogeny.ResultsIn the terra firme and várzea forest types, the phylogenetic composition varies by geographic region, but the igapó and white-sand forest types retain a unique evolutionary signature regardless of region. Overall, we find that soil chemistry, climate and topography explain 24% of the variation in phylogenetic composition, with 79% of that variation being spatially structured (R2 = 19% overall for combined spatial/environmental effects). The phylogenetic composition also shows substantial spatial patterns not related to the environmental variables we quantified (R2 = 28%). A greater number of lineages were significant indicators of geographic regions than forest types.Main ConclusionNumerous tree lineages, including some ancient ones (>66 Ma), show strong associations with geographic regions and edaphic forest types of Amazonia. This shows that specialization in specific edaphic environments has played a long-standing role in the evolutionary assembly of Amazonian forests. Furthermore, many lineages, even those that have dispersed across Amazonia, dominate within a specific region, likely because of phylogenetically conserved niches for environmental conditions that are prevalent within regions

Geography and ecology shape the phylogenetic composition of Amazonian tree communities

Aim: Amazonia hosts more tree species from numerous evolutionary lineages, both young and ancient, than any other biogeographic region. Previous studies have shown that tree lineages colonized multiple edaphic environments and dispersed widely across Amazonia, leading to a hypothesis, which we test, that lineages should not be strongly associated with either geographic regions or edaphic forest types. Location: Amazonia. Taxon: Angiosperms (Magnoliids; Monocots; Eudicots). Methods: Data for the abundance of 5082 tree species in 1989 plots were combined with a mega-phylogeny. We applied evolutionary ordination to assess how phylogenetic composition varies across Amazonia. We used variation partitioning and Moran\u27s eigenvector maps (MEM) to test and quantify the separate and joint contributions of spatial and environmental variables to explain the phylogenetic composition of plots. We tested the indicator value of lineages for geographic regions and edaphic forest types and mapped associations onto the phylogeny. Results: In the terra firme and várzea forest types, the phylogenetic composition varies by geographic region, but the igapó and white-sand forest types retain a unique evolutionary signature regardless of region. Overall, we find that soil chemistry, climate and topography explain 24% of the variation in phylogenetic composition, with 79% of that variation being spatially structured (R$^{2}$ = 19% overall for combined spatial/environmental effects). The phylogenetic composition also shows substantial spatial patterns not related to the environmental variables we quantified (R$^{2}$ = 28%). A greater number of lineages were significant indicators of geographic regions than forest types. Main Conclusion: Numerous tree lineages, including some ancient ones (>66 Ma), show strong associations with geographic regions and edaphic forest types of Amazonia. This shows that specialization in specific edaphic environments has played a long-standing role in the evolutionary assembly of Amazonian forests. Furthermore, many lineages, even those that have dispersed across Amazonia, dominate within a specific region, likely because of phylogenetically conserved niches for environmental conditions that are prevalent within regions

Mapping density, diversity and species-richness of the Amazon tree flora

Using 2.046 botanically-inventoried tree plots across the largest tropical forest on Earth, we mapped tree species-diversity and tree species-richness at 0.1-degree resolution, and investigated drivers for diversity and richness. Using only location, stratified by forest type, as predictor, our spatial model, to the best of our knowledge, provides the most accurate map of tree diversity in Amazonia to date, explaining approximately 70% of the tree diversity and species-richness. Large soil-forest combinations determine a significant percentage of the variation in tree species-richness and tree alpha-diversity in Amazonian forest-plots. We suggest that the size and fragmentation of these systems drive their large-scale diversity patterns and hence local diversity. A model not using location but cumulative water deficit, tree density, and temperature seasonality explains 47% of the tree species-richness in the terra-firme forest in Amazonia. Over large areas across Amazonia, residuals of this relationship are small and poorly spatially structured, suggesting that much of the residual variation may be local. The Guyana Shield area has consistently negative residuals, showing that this area has lower tree species-richness than expected by our models. We provide extensive plot meta-data, including tree density, tree alpha-diversity and tree species-richness results and gridded maps at 0.1-degree resolution

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio