957 resultados para Schreuder, Hans T.: Sampling methods for multiresource forest inventory


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Puisque l’altération des habitats d’eau douce augmente, il devient critique d’identifier les composantes de l’habitat qui influencent les métriques de la productivité des pêcheries. Nous avons comparé la contribution relative de trois types de variables d’habitat à l’explication de la variance de métriques d’abondance, de biomasse et de richesse à l’aide de modèles d’habitat de poissons, et avons identifié les variables d’habitat les plus efficaces à expliquer ces variations. Au cours des étés 2012 et 2013, les communautés de poissons de 43 sites littoraux ont été échantillonnées dans le Lac du Bonnet, un réservoir dans le Sud-est du Manitoba (Canada). Sept scénarios d’échantillonnage, différant par l’engin de pêche, l’année et le moment de la journée, ont été utilisés pour estimer l’abondance, la biomasse et la richesse à chaque site, toutes espèces confondues. Trois types de variables d’habitat ont été évalués: des variables locales (à l’intérieur du site), des variables latérales (caractérisation de la berge) et des variables contextuelles (position relative à des attributs du paysage). Les variables d’habitat locales et contextuelles expliquaient en moyenne un total de 44 % (R2 ajusté) de la variation des métriques de la productivité des pêcheries, alors que les variables d’habitat latérales expliquaient seulement 2 % de la variation. Les variables les plus souvent significatives sont la couverture de macrophytes, la distance aux tributaires d’une largeur ≥ 50 m et la distance aux marais d’une superficie ≥ 100 000 m2, ce qui suggère que ces variables sont les plus efficaces à expliquer la variation des métriques de la productivité des pêcheries dans la zone littorale des réservoirs.

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Evaluation of major feed resources was conducted in four crop-livestock mixed farming systems of central southern Ethiopia, with 90 farmers, selected using multi-stage purposive and random sampling methods. Discussions were held with focused groups and key informants for vernacular name identification of feed, followed by feed sampling to analyse chemical composition (CP, ADF and NDF), in-vitro dry matter digestibility (IVDMD), and correlate with indigenous technical knowledge (ITK). Native pastures, crop residues (CR) and multi-purpose trees (MPT) are the major feed resources, demonstrated great variations in seasonality, chemical composition and IVDMD. The average CP, NDF and IVDMD values for grasses were 83.8 (ranged: 62.9–190), 619 (ranged: 357–877) and 572 (ranged: 317–743) g kg^(−1) DM, respectively. Likewise, the average CP, NDF and IVDMD for CR were 58 (ranged: 20–90), 760 (ranged: 340–931) and 461 (ranged: 285–637)g kg^(−1) DM, respectively. Generally, the MPT and non-conventional feeds (NCF, Ensete ventricosum and Ipomoea batatas) possessed higher CP (ranged: 155–164 g kg^(−1) DM) and IVDMD values (611–657 g kg^(−1) DM) while lower NDF (331–387 g kg^(−1) DM) and ADF (321–344 g kg^(−1) DM) values. The MPT and NCF were ranked as the best nutritious feeds by ITK while crop residues were the least. This study indicates that there are remarkable variations within and among forage resources in terms of chemical composition. There were also complementarities between ITK and feed laboratory results, and thus the ITK need to be taken into consideration in evaluation of local feed resources.

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1. Suction sampling is a popular method for the collection of quantitative data on grassland invertebrate populations, although there have been no detailed studies into the effectiveness of the method. 2. We investigate the effect of effort (duration and number of suction samples) and sward height on the efficiency of suction sampling of grassland beetle, true bug, planthopper and spider Populations. We also compare Suction sampling with an absolute sampling method based on the destructive removal of turfs. 3. Sampling for durations of 16 seconds was sufficient to collect 90% of all individuals and species of grassland beetles, with less time required for the true bugs, spiders and planthoppers. The number of samples required to collect 90% of the species was more variable, although in general 55 sub-samples was sufficient for all groups, except the true bugs. Increasing sward height had a negative effect on the capture efficiency of suction sampling. 4. The assemblage structure of beetles, planthoppers and spiders was independent of the sampling method (suction or absolute) used. 5. Synthesis and applications. In contrast to other sampling methods used in grassland habitats (e.g. sweep netting or pitfall trapping), suction sampling is an effective quantitative tool for the measurement of invertebrate diversity and assemblage structure providing sward height is included as a covariate. The effective sampling of beetles, true bugs, planthoppers and spiders altogether requires a minimum sampling effort of 110 sub-samples of duration of 16 seconds. Such sampling intensities can be adjusted depending on the taxa sampled, and we provide information to minimize sampling problems associated with this versatile technique. Suction sampling should remain an important component in the toolbox of experimental techniques used during both experimental and management sampling regimes within agroecosystems, grasslands or other low-lying vegetation types.

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Bee pollinators are currently recorded with many different sampling methods. However, the relative performances of these methods have not been systematically evaluated and compared. In response to the strong need to record ongoing shifts in pollinator diversity and abundance, global and regional pollinator initiatives must adopt standardized sampling protocols when developing large-scale and long-term monitoring schemes. We systematically evaluated the performance of six sampling methods (observation plots, pan traps, standardized and variable transect walks, trap nests with reed internodes or paper tubes) that are commonly used across a wide range of geographical regions in Europe and in two habitat types (agricultural and seminatural). We focused on bees since they represent the most important pollinator group worldwide. Several characteristics of the methods were considered in order to evaluate their performance in assessing bee diversity: sample coverage, observed species richness, species richness estimators, collector biases (identified by subunit-based rarefaction curves), species composition of the samples, and the indication of overall bee species richness (estimated from combined total samples). The most efficient method in all geographical regions, in both the agricultural and seminatural habitats, was the pan trap method. It had the highest sample coverage, collected the highest number of species, showed negligible collector bias, detected similar species as the transect methods, and was the best indicator of overall bee species richness. The transect methods were also relatively efficient, but they had a significant collector bias. The observation plots showed poor performance. As trap nests are restricted to cavity-nesting bee species, they had a naturally low sample coverage. However, both trap nest types detected additional species that were not recorded by any of the other methods. For large-scale and long-term monitoring schemes with surveyors with different experience levels, we recommend pan traps as the most efficient, unbiased, and cost-effective method for sampling bee diversity. Trap nests with reed internodes could be used as a complementary sampling method to maximize the numbers of collected species. Transect walks are the principal method for detailed studies focusing on plant-pollinator associations. Moreover, they can be used in monitoring schemes after training the surveyors to standardize their collection skills.

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The K-Means algorithm for cluster analysis is one of the most influential and popular data mining methods. Its straightforward parallel formulation is well suited for distributed memory systems with reliable interconnection networks. However, in large-scale geographically distributed systems the straightforward parallel algorithm can be rendered useless by a single communication failure or high latency in communication paths. This work proposes a fully decentralised algorithm (Epidemic K-Means) which does not require global communication and is intrinsically fault tolerant. The proposed distributed K-Means algorithm provides a clustering solution which can approximate the solution of an ideal centralised algorithm over the aggregated data as closely as desired. A comparative performance analysis is carried out against the state of the art distributed K-Means algorithms based on sampling methods. The experimental analysis confirms that the proposed algorithm is a practical and accurate distributed K-Means implementation for networked systems of very large and extreme scale.

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The K-Means algorithm for cluster analysis is one of the most influential and popular data mining methods. Its straightforward parallel formulation is well suited for distributed memory systems with reliable interconnection networks, such as massively parallel processors and clusters of workstations. However, in large-scale geographically distributed systems the straightforward parallel algorithm can be rendered useless by a single communication failure or high latency in communication paths. The lack of scalable and fault tolerant global communication and synchronisation methods in large-scale systems has hindered the adoption of the K-Means algorithm for applications in large networked systems such as wireless sensor networks, peer-to-peer systems and mobile ad hoc networks. This work proposes a fully distributed K-Means algorithm (EpidemicK-Means) which does not require global communication and is intrinsically fault tolerant. The proposed distributed K-Means algorithm provides a clustering solution which can approximate the solution of an ideal centralised algorithm over the aggregated data as closely as desired. A comparative performance analysis is carried out against the state of the art sampling methods and shows that the proposed method overcomes the limitations of the sampling-based approaches for skewed clusters distributions. The experimental analysis confirms that the proposed algorithm is very accurate and fault tolerant under unreliable network conditions (message loss and node failures) and is suitable for asynchronous networks of very large and extreme scale.

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The bubble crab Dotilla fenestrata forms very dense populations on the sand flats of the eastern coast of Inhaca Island, Mozambique, making it an interesting biological model to examine spatial distribution patterns and test the relative efficiency of common sampling methods. Due to its apparent ecological importance within the sandy intertidal community, understanding the factors ruling the dynamics of Dotilla populations is also a key issue. In this study, different techniques of estimating crab density are described, and the trends of spatial distribution of the different population categories are shown. The studied populations are arranged in discrete patches located at the well-drained crests of nearly parallel mega sand ripples. For a given sample size, there was an obvious gain in precision by using a stratified random sampling technique, considering discrete patches as strata, compared to the simple random design. Density average and variance differed considerably among patches since juveniles and ovigerous females were found clumped, with higher densities at the lower and upper shore levels, respectively. Burrow counting was found to be an adequate method for large-scale sampling, although consistently underestimating actual crab density by nearly half. Regression analyses suggested that crabs smaller than 2.9 mm carapace width tend to be undetected in visual burrow counts. A visual survey of sampling plots over several patches of a large Dotilla population showed that crab density varied in an interesting oscillating pattern, apparently following the topography of the sand flat. Patches extending to the lower shore contained higher densities than those mostly covering the higher shore. Within-patch density variability also pointed to the same trend, but the density increment towards the lowest shore level varied greatly among the patches compared.

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A lagarta-do-cartucho, Spodoptera frugiperda (J.E. Smith), é uma das principais pragas do milho nas Américas. O estudo de sua distribuição espacial é fundamental para a utilização de estratégias de controle, otimização de técnicas de amostragens, determinação de danos econômicos e incorporação de um programa de agricultura de precisão. em uma área cultivada com milho foram realizadas amostragens com intervalo semanal, correspondendo ao estádio vegetativo que compreende desde a germinação até o pendoamento. Foram amostradas 10 plantas ao acaso por parcela, no total de 2000 plantas em cada amostragem. A produtividade foi obtida através da colheita de todas as parcelas que eram pesadas separadamente no campo e em cada parcela foram coletadas 15 espigas aleatoriamente para estimar o comprimento e o diâmetro médio. As análises espaciais, utilizando geoestatística, mostraram que o modelo esférico apresentou o melhor ajuste às lagartas pequenas. À medida que as lagartas foram se desenvolvendo sua distribuição foi tornando aleatória, representada por um modelo ajustado por uma reta, não tendo sido detectado nenhum tipo de dependência espacial nos pontos de amostragem. A produtividade e o diâmetro e comprimento da espiga foram descritos por modelos esféricos, indicando uma variabilidade espacial nos parâmetros de produtividade na área cultivada. A geoestatística mostrou-se promissora para a aplicação de métodos precisos no controle integrado de pragas.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Este estudo teve por objetivo avaliar métodos de amostragem, abundância sazonal e diversidade da população de Hemerobiidae associada a cultivo de café Coffea arabica L. cv. Obatã em Cravinhos, São Paulo, Brasil. Para tanto foram realizadas amostragens semanais no período de maio de 2005 a abril de 2006. Os métodos de amostragem utilizados foram: rede de varredura e armadilhas de Möericke e luminosa. Foram coletados 491 exemplares de Hemerobiidae pertencentes a quatro gêneros: Nusalala (231 espécimes / 47,2% do total de hemerobiídeos coletados), Megalomus (110 / 22,5%), Hemerobius (104 / 21,3%) e Sympherobius (44 / 9%). A rede de varredura foi a mais eficiente para a captura de Hemerobiidae e a armadilha de Möericke foi o método de amostragem que apresentou os maiores valores de diversidade (H'= 0,56) e de equitabilidade (J= 0,93). Os hemerobiídeos estiveram presentes na área estudada durante o ano todo; as maiores freqüências foram registradas entre agosto e março (final do inverno, primavera e verão) e o maior pico populacional ocorreu em janeiro (na metade do verão). Megalomus apresentou correlação positiva e significativa (p< 0,05) com a precipitação pluviométrica e as temperaturas máxima e mínima; Nusalala com as temperaturas máxima e mínima e, Sympherobius apenas com a temperatura máxima.

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Este trabalho foi realizado na Faculdade de Ciências Agrárias Veterinárias - Unesp - Jaboticabal e foi conduzido, com o objetivo de avaliar a influência do método de amostragem do pasto sobre a degradabilidade in situ da matéria seca e da fração fibrosa de capim Marandu, colhido no período seco dos anos de 2003 e 2005. O experimento foi instalado em delineamento de blocos casualizados com parcela subdividida, com três repetições, representadas pelos piquetes amostrados. Nas parcelas, foram avaliados cinco métodos de amostragens de forragem (método do quadrado metálico; método de avaliação através de extrusa de bovino da raça Nelore; método de avaliação por meio de extrusa de bovino Cruzado (Red Angus x Nelore); método de avaliação por meio do pastejo, simulando bovino da raça Nelore; método de avaliação por meio do pastejo, simulando bovino Cruzado (Red Angus x Nelore) e as subparcelas foram constituídas pelos anos de amostragem, 2003 e 2005. Foram determinadas as frações da cinética ruminal: solúvel A; insolúvel potencialmente degradável B; taxa de degradação Kd; degradação potencial (DP) e fração não degradável C da MS e degradação potencial (DP), fração não degradável C e taxa de degradação Kd da FDN e da FDA. de acordo com os resultados obtidos, observou-se que o método do quadrado metálico subestimou as características da degradação do capim. Os métodos do pastejo simulado se assemelharam muito ao das extrusas, no entanto, a prática do simulador é que assegurou a amostragem eficiente, conforme foi constatado pelos dados obtidos no ano de 2003 e 2005.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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O presente trabalho objetivou verificar a possibilidade da utilização de métodos estatísticos multivariados na caracterização das fases do desenvolvimento do mosaico sucessional de um trecho de floresta estacional semidecidual, através de variáveis estruturais. Foram alocadas parcelas de 10 m x 10 m, em que se procedeu à análise estrutural, ou seja, levantamento fitossociológico acrescido das variáveis Porcentagem de Cobertura (PC), Altura do Dossel (AD) e Cobertura por Lianas (CL). Os métodos estatísticos empregados foram Análise de Componentes Principais e Análise de Agrupamento, mais especificamente Classificação Hierárquica Ascendente. O primeiro componente principal explicou 43,96% da variância total, enquanto o segundo, 25,66%. As variáveis Área Basal (AB), Diâmetro Médio (DM) e Dominância Média (DOM) apresentaram correlações positivas entre si superiores a 0,75, podendo ser DM e DOM consideradas como um grupo de variáveis. As variáveis Número de Indivíduos (NI) e Número de Espécies (NE) apresentaram correlação 0,60, enquanto AD, CL e PC baixas correlações com as demais, indicando a importância da inclusão destas na análise. A classificação hierárquica e a partição dos grupos em quatro foram feitas considerando os dois primeiros eixos fatoriais. Os resultados indicaram dois comportamentos diferenciados: 1) valores baixos para AD e AB: Grupo 1, com valores baixos também para NI, NE e PC (fase de clareira); e Grupo 2, com valores elevados para NI e CL e baixos para DOM e DM (fase de construção); e 2) valores altos para AD e AB: Grupo 3, com valores altos também para NI, NE e PC e valor baixo para CL (fase madura); e Grupo 4, com valores elevados para DOM e DM e mais baixos para CL (fase de degradação). Os métodos estatísticos multivariados permitiram caracterizar as fases do desenvolvimento do mosaico sucessional, através das variáveis estruturais. A forma como foram estimadas as variáveis AD, CL e PC, porém, deve ser aprimorada, assim como é preciso incluir variáveis que discriminem melhor cada fase.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)