Alternativa de modelo linear para estimação da biomassa verde de Bambusa vulgaris Schrad. ex J.C. Wendl na existência de multicolinearidade.

The objective of this work was to use a multivariate statistical method as an alternative to estimate the green biomass of the main bamboo rod, Bambusa vulgaris Schrad. i.e.: J.C. Wendl., in the presence of multicollinearity. The data came from an experiment carried out for the Agroindustrial Excelsior S. A. (Agrimex) company located in the city of Goiana – PE. Quantified by their green biomass weight, 450 bamboo rods were used and 4 independent variables measured in the rod. Initially, the presence of the multicollinearity could be verified through the correlation matrix of the independent variables and the varience inflation factors, the alternative used was the regression of the principal components based on the covariate matrix. The result indicates that, when there is an interpretation to the main components, the model shows a satisfactory data adjust, and it could be used to estimate the green biomass of the main bamboo rod.O objetivo deste trabalho foi utilizar um método estatístico multivariado como opção para estimar a biomassa verde da haste principal do bambu, Bambusa vulgaris Schrad. ex J. C. Wendl., na existência de multicolinearidade. Os dados foram provenientes de um experimento conduzido pela empresa Agroindustrial Excelsior S. A. (Agrimex) localizada no Engenho Itapirema, município de Goiana, PE. Foram utilizadas 450 hastes de bambu, que tiveram sua biomassa verde quantificada por meio do peso e mensuração de quatro variáveis independentes. Inicialmente, comprovou-se a existência da multicolinearidade por meio da matriz de correlação das variáveis independentes e pelo fator de inflação da variância e a opção utilizada foi à regressão linear com os componentes principais que tem como base a matriz de covariância. O resultado indicou que ao existir uma interpretação para os componentes principais o modelo apresenta um ajuste satisfatório aos dados, podendo ser utilizado para estimar a biomassa verde da haste principal do bambu

AJUSTES DE MODELOS VOLUMÉTRICOS PARA O CLONE Eucalyptus grandis x E. urophylla CULTIVADOS NO AGRESTE DE PERNAMBUCO

This research aimed to evaluate the volumetric models fitting for Eucalyptus clone using normal and t-Student distributions, based on data from an experiment implanted at the Agronomic Institute of Pernambuco (IPA) in São Bento do Una, PE. In order to set the modified volumetric models of Silva and Bailey, modified Chapman and Richard, Schumacher and Hall, and modified Brody, we used data from 62 trees rigorously scaled by Smalian method. The criteria for equation comparing were the weighted value (PV) between the corrected index adjustment (IAc) and absolute mean error percentage (EPAM). According to the results, the model that best fits for the two distributions is Schumacher and Hall, with better adjustment related to the Student-t distribution. The t-Student distribution promoted improvements of equations regarding the Normal distribution, compared to the two distributions per equation.O presente trabalho teve como objetivo avaliar o ajuste de modelos volumétricos para um clone de Eucalyptus usando distribuição normal e t-Student, utilizando dados de um experimento implantado no Instituto Agronômico de Pernambuco (IPA) em São Bento do Una, PE. Para o ajuste dos modelos volumétricos de Silva e Bailey modificado, Chapman e Richard modificado, Schumacher e Hall e, Brody modificado, foram utilizados dados de 62 árvores cubadas rigorosamente pelo método de Smalian. Os critérios usados nas comparações das equações foi o valor ponderado (VP) entre o Índice de Ajuste corrigido (IAc) e o erro percentual absoluto médio (EPAM). De acordo com os resultados o modelo que mostrou melhores ajustes nas duas distribuições foi o de Schumacher e Hall, com melhores ajuste quando da distribuição t-Student. A distribuição t-Student promoveu melhorias nos ajustes das equações em relação à distribuição Normal, quando comparando as duas distribuições em cada equação.AbstractAdjustment of volumetric models for clone of Eucalyptus grandis x E. Urophylla grown on agreste, Pernambuco. This research aimed to evaluate the volumetric models fitting for Eucalyptus clone using normal and t-Student distributions, based on data from an experiment implanted at the Agronomic Institute of Pernambuco (IPA) in São Bento do Una, PE. In order to set the modified volumetric models of Silva and Bailey, modified Chapman and Richard, Schumacher and Hall, and modified Brody, we used data from 62 trees rigorously scaled by Smalian method. The criteria for equation comparing were the weighted value (PV) between the corrected index adjustment (IAc) and absolute mean error percentage (EPAM). According to the results, the model that best fits for the two distributions is Schumacher and Hall, with better adjustment related to the Student-t distribution. The t-Student distribution promoted improvements of equations regarding the Normal distribution, compared to the two distributions per equation.Keywords: Forest management; symmetric distributions; volume equations

Modelos de crescimento resultantes da combinação e variações dos modelos de Chapman-Richards e Silva-Bailey aplicados em Leucaena leucocephala (Lam.) de Wit.

The main objective of this work was to develop new growth models for forest resources, applied to (leucena) [Leucaena leucocephala (Lam.) of Wit], based on the biological hypotheses proposed by Chapman-Richards and Silva-Bailey. The experiment of the leucena was carried out in the Experimental Station of the Agricultural and Liverstock Research Company of Pernambuco - IPA, in the municipal district of Caruaru - PE. Five hundred and forty four trees of Leucaena leucocephala (Lam.) of Wit were used, with 20 measures along the time. It was compared new growth models resulting from the combination and variation of the Chapman-Richards and Silva-Bailey models, as well other models used in forest resources. For the selection of the final equations, the fit of index, standard error of estimate and the graphic distribution of the residues were used. Results show that new models were as good as Chapman-Richards and Silva-Bailey and other tested. Therefore, any one of them can be applied to estimate  the growth of leucena.O objetivo deste trabalho foi desenvolver novos modelos de crescimento para recursos florestais aplicados à leucena [Leucaena leucocephala (Lam.) de Wit], tendo como base as hipóteses biológicas propostas por Chapman-Richards e Silva-Bailey. O experimento de leucena foi conduzido na Estação Experimental da Empresa Pernambucana de Pesquisa Agropecuária - IPA, Caruaru, PE. Foram utilizadas 544 árvores de leucena de um experimento com vinte remedições realizadas ao longo de 12 anos. Compararam-se novos modelos de crescimento resultantes da combinação e variações dos modelos de Chapman-Richards e Silva-Bailey, bem como outros comumente usados em recursos florestais. Para a seleção das equações, utilizaram-se o Índice de Ajuste (IA), o erro-padrão da estimativa e a distribuição gráfica dos resíduos. Os resultados indicaram que todos os modelos testados se ajustaram de maneira satisfatória aos dados, podendo ser utilizados para se estimar o crescimento em altura da leucena

Curvas de índice de sítio para leucena [Leucaena leucocephala (Lam.) De Wit] no agreste de Pernambuco.

The main goal of this work was to set and compare site index curves for leucena [Leucaena leucocephala (Lam.) de Wit] variety Hawaii (cv K8) in Agreste of Pernambuco. The data set came from Empresa Pernambucana de Pesquisa Agropecuária (IPA), Experimental Station of Caruaru, in which 544 trees cultivated with and without organic compound were measured 19 times during the period of 1990 – 2003. The models of Schumacher, Chapman-Richards, Silva-Bailey, Mitscherlich, Weibull and Clutter-Jones were tested and compared. To select the best equations, the Index of Fit (IF), standard error of estimate (), identity model test and the graphic of residuals distribution were used and results show that the model of Clutter-Jones provided a better IF for both treatments. The graphic of residual distribution did not show tendency among the models. The model identity test showed no differences among the models tested. As Schumacher’s model has been used frequently in forestry and presented the smallest number of parameters, it deserves special focus in studies of site index.O objetivo deste trabalho foi ajustar e comparar modelos de curvas de índice de sítio para Leucaena leucocephala (Lam.) de Wit., variedade Hawaii (cv. K8), no Agreste de Pernambuco. Os dados foram obtidos na Estação Experimental da Empresa Pernambucana de Pesquisa Agropecuária (IPA), no município de Caruaru - PE, considerando-se 544 árvores, cultivadas com e sem composto orgânico, com 19 mensurações ao longo do tempo (1990-2003). Foram ajustados e comparados os modelos de Schumacher, Chapman-Richards, Silva-Bailey, Mitscherlich, Weibull e Clutter-Jones. Para a seleção das equações, utilizaram-se os índices de ajuste (IA), o erro padrão da estimativa (), a distribuição gráfica dos resíduos e o teste de identidade dos modelos. O modelo de Clutter-Jones apresentou o maior valor de IA nos dois tratamentos. Nos gráficos das distribuições residuais, os modelos não apresentaram tendências. No teste de identidade dos modelos de regressão, verificou-se não haver diferença significativa ao nível de 5 % de probabilidade. Por ser um modelo com o menor número de parâmetros entre os testados e por ser freqüentemente utilizado na Ciência Florestal, o modelo de Schumacher merece especial destaque em trabalhos de índice de sítio

Uma abordagem multivariada em experimento silvipastoril com Leucaena leucocephala (Lam.) De Wit no agreste de Pernambuco.

The main objective of the present work was to evaluate the use of the leucena [Leucaena leucocephala (Lam.) of Wit] as direct pasture in the field. A multivariate silvopastoral experiment with repeated measures, carried out in the experimental station of Pernambucana Company of Agricultural Research (IPA) in Caruaru, Agreste of Pernambuco, was used for this purpose. The plant spacing of 0.5m x 1.0m, 1.0m x 1.0m and 1.5m x 1.0m with the heights of cut of 20cm, 40cm and 60cm, was tested. The measurements have been carried through at same month of the year (August) along five years.  The presented result shows that the measures along the time are correlated and there were significant differences among the plant spacing during the period of the experiment.  No significant differences among the heights of cut and its interactions with the plant spacing occurred.  Because of a larger number of plants per unit area, yielding greater productivity of biomass per hectare, the plant spacing of 0.5m x 1.0m is recommended for silvopastoral systems in the Agreste of Pernambuco.O principal objetivo do presente trabalho foi avaliar o uso da leucena [Leucaena leucocephala (Lam.) de Wit] como pastagem direta no campo, utilizando-se, para tanto, de um experimento silvipastoril multivariado, com medidas repetidas, realizado na região Agreste do Estado de Pernambuco. Estudou-se a leucena submetida a diferentes espaçamentos e alturas de corte com a finalidade de produção de biomassa. O experimento foi realizado na estação experimental da Empresa Pernambucana de Pesquisa Agropecuária (IPA), no município de Caruaru. Testaram-se os espaçamentos 0,5m x 1,0m ; 1,0m x 1,0m e 1,5m x 1,0m; e as alturas de corte 20cm, 40cm e 60cm. As medições foram realizadas na mesma época do ano (mês de agosto) durante o período de cinco anos. Os resultados apresentados mostraram que as medidas ao longo do tempo são correlacionadas e que houve diferenças significativas entre os espaçamentos durante todo o período do experimento. Não ocorreram diferenças significativas entre as alturas de corte e suas interações com os espaçamentos em todos os tempos. Por se usar um maior número de plantas por unidade de área e uma conseqüente maior produtividade de biomassa por hectare, recomenda-se o uso do espaçamento 0,5m x 1,0m, em sistemas silvipastoris com leucena, no Agreste de Pernambuco

Data standardization of plant–pollinator interactions

Background: Animal pollination is an important ecosystem function and service, ensuring both the integrity of natural systems and human well-being. Although many knowledge shortfalls remain, some high-quality data sets on biological interactions are now available. The development and adoption of standards for biodiversity data and metadata has promoted great advances in biological data sharing and aggregation, supporting large-scale studies and science-based public policies. However, these standards are currently not suitable to fully support interaction data sharing. Results: Here we present a vocabulary of terms and a data model for sharing plant–pollinator interactions data based on the Darwin Core standard. The vocabulary introduces 48 new terms targeting several aspects of plant–pollinator interactions and can be used to capture information from different approaches and scales. Additionally, we provide solutions for data serialization using RDF, XML, and DwC-Archives and recommendations of existing controlled vocabularies for some of the terms. Our contribution supports open access to standardized data on plant–pollinator interactions. Conclusions: The adoption of the vocabulary would facilitate data sharing to support studies ranging from the spatial and temporal distribution of interactions to the taxonomic, phenological, functional, and phylogenetic aspects of plant–pollinator interactions. We expect to fill data and knowledge gaps, thus further enabling scientific research on the ecology and evolution of plant–pollinator communities, biodiversity conservation, ecosystem services, and the development of public policies. The proposed data model is flexible and can be adapted for sharing other types of interactions data by developing discipline-specific vocabularies of termsinfo:eu-repo/semantics/publishedVersio

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

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 understanding 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,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 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 underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities 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 organism 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 neglected 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 lost