Soil sampling intensity and spatial distribution pattern of soils attributes and corn yield in no-tillage system

Taking into account that the sampling intensity of soil attributes is a determining factor for applying of concepts of precision agriculture, this study aims to determine the spatial distribution pattern of soil attributes and corn yield at four soil sampling intensities and verify how sampling intensity affects cause-effect relationship between soil attributes and corn yield. A 100-referenced point sample grid was imposed on the experimental site. Thus, each sampling cell encompassed an area of 45 m² and was composed of five 10-m long crop rows, where referenced points were considered the center of the cell. Samples were taken from at 0 to 0.1 m and 0.1 to 0.2 m depths. Soil chemical attributes and clay content were evaluated. Sampling intensities were established by initial 100-point sampling, resulting data sets of 100; 75; 50 and 25 points. The data were submitted to descriptive statistical and geostatistics analyses. The best sampling intensity to know the spatial distribution pattern was dependent on the soil attribute being studied. The attributes P and K+ content showed higher spatial variability; while the clay content, Ca2+, Mg2+ and base saturation values (V) showed lesser spatial variability. The spatial distribution pattern of clay content and V at the 100-point sampling were the ones which best explained the spatial distribution pattern of corn yield.

Soil sampling intensity and spatial distribution pattern of soils attributes and corn yield in no-tillage system

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

Variograms of ancillary data to aid sampling for soil surveys

To provide reliable estimates for mapping soil properties for precision agriculture requires intensive sampling and costly laboratory analyses. If the spatial structure of ancillary data, such as yield, digital information from aerial photographs, and soil electrical conductivity (EC) measurements, relates to that of soil properties they could be used to guide the sampling intensity for soil surveys. Variograins of permanent soil properties at two study sites on different parent materials were compared with each other and with those for ancillary data. The ranges of spatial dependence identified by the variograms of both sets of properties are of similar orders of magnitude for each study site, Maps of the ancillary data appear to show similar patterns of variation and these seem to relate to those of the permanent properties of the soil. Correlation analysis has confirmed these relations. Maps of kriged estimates from sub-sampled data and the original variograrns showed that the main patterns of variation were preserved when a sampling interval of less than half the average variogram range of ancillary data was used. Digital data from aerial photographs for different years and EC appear to show a more consistent relation with the soil properties than does yield. Aerial photographs, in particular those of bare soil, seem to be the most useful ancillary data and they are often cheaper to obtain than yield and EC data.

Distribution and abundance of dugongs in Moreton Bay, Queensland, Australia

Dugong abundances in Moreton Bay (south-east Queensland) were estimated during six bi- monthly aerial surveys throughout 1995. Sampling intensity ranged between 20 and 80% for different sampling zones within the Bay, with a mean intensity of 40.5%. Population estimates for dugongs were corrected for perception bias ( the proportion of animals visible in the transect that were missed by observers), and standardised for availability bias ( the proportion of animals that were invisible due to water turbidity) with survey and species-specific correction factors. Population estimates for dugongs in Moreton Bay ranged from 503 +/- 64 (s.e.) in July to 1019 +/- 166 in January. The highest uncorrected count was 857 dugongs in December. This is greater than previous population estimates, suggesting that either previous surveys have underestimated abundance and/or that this population may have increased through recruitment, immigration, or a combination of both. The high degree of variation in population estimates between surveys may be due to temporal differences in distribution and herding behaviour. In winter, dugongs were found in smaller herds and were dispersed over a wider area than in summer. The Eastern Banks region of the bay supported 80 - 98% of the dugong population at any one time. Within this region, there were several dugong 'hot spots' that were visited repeatedly by large herds. These 'hot spots' contained seagrass communities that were dominated by species that dugongs prefer to eat. The waters of Rous Channel, South Passage and nearby oceanic waters are also frequently inhabited by dugongs in the winter months. Dugongs in other parts of Moreton Bay were at much lower densities than on the Eastern Banks.

Spatial relationships between soil attributes and corn yield in no-tillage system

Soil properties play an important role in spatial variability of crop yield. However, a low spatial correlation has generally been observed between maps of crop yield and of soil properties. The objectives of the present investigation were to assess the spatial pattern variability of soil properties and of corn yield at the same sampling intensity, and evaluate its cause-and-effect relationships. The experimental site was structured in a grid of 100 referenced points, spaced at 10 m intervals along four parallel 250 m long rows spaced 4.5 m apart. Thus, points formed a rectangle containing four columns and 25 rows. Therefore, each sampling cell encompassed an area of 45 m² and consisted of five 10 m long crop rows, in which the referenced points represented the center. Samples were taken from the layers 0-0.1 m and 0.1-0.2 m. Soil physical and chemical properties were evaluated. Statistical analyses consisted of data description and geostatistics. The spatial dependence of corn yield and soil properties was confirmed. The hypothesis of this study was confirmed, i.e., when sampling the soil to determine the values of soil characteristics at similar to sampling intensity as for crop yield assessments, correlations between the spatial distribution of soil characteristics and crop yield were observed. The spatial distribution pattern of soil properties explained 65 % of the spatial distribution pattern of corn yield. The spatial distribution pattern of clay content and percentage of soil base saturation explained most of the spatial distribution pattern of corn yield.

Spatial relationships between soil attributes and corn yield in no-tillage system

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

Variabilidade espacial de atributos do solo antes e após calagem e fosfatagem em doses variadas na cultura de cana-de-açúcar

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Variabilidade espacial de atributos do solo e da produtividade de milho

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Understanding bias in geographic range size estimates

Aim Estimates of geographic range size derived from natural history museum specimens are probably biased for many species. We aim to determine how bias in these estimates relates to range size. Location We conducted computer simulations based on herbarium specimen records from localities ranging from the southern United States to northern Argentina. Methods We used theory on the sampling distribution of the mean and variance to develop working hypotheses about how range size, defined as area of occupancy (AOO), was related to the inter-specific distribution of: (1) mean collection effort per area across the range of a species (MC); (2) variance in collection effort per area across the range of a species (VC); and (3) proportional bias in AOO estimates (PBias: the difference between the expected value of the estimate of AOO and true AOO, divided by true AOO). We tested predictions from these hypotheses using computer simulations based on a dataset of more than 29,000 herbarium specimen records documenting occurrences of 377 plant species in the tribe Bignonieae (Bignoniaceae). Results The working hypotheses predicted that the mean of the inter-specific distribution of MC, VC and PBias were independent of AOO, but that the respective variance and skewness decreased with increasing AOO. Computer simulations supported all but one prediction: the variance of the inter-specific distribution of VC did not decrease with increasing AOO. Main conclusions Our results suggest that, despite an invariant mean, the dispersion and symmetry of the inter-specific distribution of PBias decreases as AOO increases. As AOO increased, range size was less severely underestimated for a large proportion of simulated species. However, as AOO increased, range size estimates having extremely low bias were less common.

Quantificação de biomassa e carbono da parte aérea em uma área de Mata Atlântica, na Serra da Cantareira, São Paulo

A atividade humana tem contribuído com as emissões de gases de efeito estufa (GEE) associadas, principalmente, com queima de combustíveis fósseis e mudanças no uso da terra. Assim, se faz necessário que sejam adotadas medidas visando o retardamento dos efeitos das mudanças climáticas. As florestas exercem papel essencial no balanço de carbono principalmente por funcionarem como sumidouros de CO2. Por outro lado, se desmatadas, promovem emissões e liberam parte do carbono estocado. A quantidade de biomassa florestal e o teor de carbono podem variar em função do tipo florestal, bem como de sua localização. Entretanto, fator importante diz respeito à confiabilidade dos dados mensurados neste tipo de pesquisa. A biomassa e o carbono da parte aérea podem ser determinados via método destrutivo, ou estimados via método não destrutivo. A construção do Rodoanel Mário Covas trecho norte e a supressão de uma área de Mata Atlântica possibilitou a realização de estudo de biomassa da parte aérea via método destrutivo. O objetivo deste trabalho foi estudar o tamanho e forma de parcelas, a intensidade amostral, quantificar a biomassa e o carbono na parte aérea, comparar métodos destrutivos e não destrutivos para a quantificação de biomassa e carbono na parte aérea, estudar a variação da densidade básica da madeira das espécies nas diferentes classes de DAP e grupos sucessionais e comparar as medidas de altura total e DAP obtidas a campo no inventário com as medidas coletadas após o corte. O tamanho mais conveniente de parcela foi 400 m 2, com forma retangular e dimensão de 10 x 40 m. A intensidade amostral variou entre 39 e 75 unidades amostrais. A biomassa da parte aérea obtida, via método destrutivo, foi de 188,3 Mg ha-1 e o carbono, 85,1 Mg ha-1. A biomassa estimada por equações alométricas da literatura foi subestimada, quando comparada ao valor real, obtido via método destrutivo. As menores classes de DAP apresentaram as maiores densidades básicas da madeira. A densidade básica foi 0,488 g cm-3 na média das espécies. A porcentagem de carbono contida nos troncos e galhos não diferiu entre as classes de DAP. O teor de carbono foi 45,41%, na média dos troncos e galhos. Espécies pioneiras acumularam maior quantidade de biomassa e carbono nos galhos e apresentaram maior densidade básica que as não pioneiras. A utilização dos dados coletados na fase de inventário e após o corte não afetaram os valores de biomassa estimados.

The sensitivity of mapping methods to reference data quality:training supervised image classifications with imperfect reference data

The accuracy of a map is dependent on the reference dataset used in its construction. Classification analyses used in thematic mapping can, for example, be sensitive to a range of sampling and data quality concerns. With particular focus on the latter, the effects of reference data quality on land cover classifications from airborne thematic mapper data are explored. Variations in sampling intensity and effort are highlighted in a dataset that is widely used in mapping and modelling studies; these may need accounting for in analyses. The quality of the labelling in the reference dataset was also a key variable influencing mapping accuracy. Accuracy varied with the amount and nature of mislabelled training cases with the nature of the effects varying between classifiers. The largest impacts on accuracy occurred when mislabelling involved confusion between similar classes. Accuracy was also typically negatively related to the magnitude of mislabelled cases and the support vector machine (SVM), which has been claimed to be relatively insensitive to training data error, was the most sensitive of the set of classifiers investigated, with overall classification accuracy declining by 8% (significant at 95% level of confidence) with the use of a training set containing 20% mislabelled cases.

The 'rotiferologist' effect and other global correlates of species richness in monogonont rotifers

Global biodiversity patterns are often driven by diff erent environmental variables at diff erent scales. However, it is still controversial whether there are general trends, whether similar processes are responsible for similar patterns, and/or whether confounding eff ects such as sampling bias can produce misleading results. Our aim is twofold: 1) assessing the global correlates of diversity in a group of microscopic animals little analysed so far, and 2) inferring the infl uence of sampling intensity on biodiversity analyses. As a case study, we choose rotifers, because of their high potential for dispersal across the globe. We assembled and analysed a new worldwide dataset of records of monogonont rotifers, a group of microscopic aquatic animals, from 1960 to 1992. Using spatially explicit models, we assessed whether the diversity patterns conformed to those commonly obtained for larger organisms, and whether they still held true after controlling for sampling intensity, variations in area, and spatial structure in the data. Our results are in part analogous to those commonly obtained for macroorganisms (habitat heterogeneity and precipitation emerge as the main global correlates), but show some divergence (potential absence of a latitudinal gradient and of a large-scale correlation with human population). Moreover, the eff ect of sampling eff ort is remarkable, accounting for 50% of the variability; this strong eff ect may mask other patterns such as latitudinal gradients. Our study points out that sampling bias should be carefully considered when drawing conclusions from large-scale analyses, and calls for further faunistic work on microorganisms in all regions of the world to better understand the generality of the processes driving global patterns in biodiversity.

Medical image registration based on random line sampling

One of the key aspects in 3D-image registration is the computation of the joint intensity histogram. We propose a new approach to compute this histogram using uniformly distributed random lines to sample stochastically the overlapping volume between two 3D-images. The intensity values are captured from the lines at evenly spaced positions, taking an initial random offset different for each line. This method provides us with an accurate, robust and fast mutual information-based registration. The interpolation effects are drastically reduced, due to the stochastic nature of the line generation, and the alignment process is also accelerated. The results obtained show a better performance of the introduced method than the classic computation of the joint histogram

Medical image registration based on random line sampling

One of the key aspects in 3D-image registration is the computation of the joint intensity histogram. We propose a new approach to compute this histogram using uniformly distributed random lines to sample stochastically the overlapping volume between two 3D-images. The intensity values are captured from the lines at evenly spaced positions, taking an initial random offset different for each line. This method provides us with an accurate, robust and fast mutual information-based registration. The interpolation effects are drastically reduced, due to the stochastic nature of the line generation, and the alignment process is also accelerated. The results obtained show a better performance of the introduced method than the classic computation of the joint histogram

Bats from Fazenda Intervales, Southeastern Brazil: species account and comparison between different sampling methods

Assessing the composition of an area's bat fauna is typically accomplished by using captures or by monitoring echolocation calls with bat detectors. The two methods may not provide the same data regarding species composition. Mist nets and harp traps may be biased towards sampling low flying species, and bat detectors biased towards detecting high intensity echolocators. A comparison of the bat fauna of Fazenda Intervales, southeastern Brazil, as revealed by mist nets and harp trap captures, checking roosts and by monitoring echolocation calls of flying bats illustrates this point. A total of 17 species of bats was sampled. Fourteen bat species were captured and the echolocation calls of 12 species were recorded, three of them not revealed by mist nets or harp traps. The different sampling methods provided different pictures of the bat fauna. Phyllostomid bats dominated the catches in mist nets, but in the field their echolocation calls were never detected. No single sampling approach provided a complete assessment of the bat fauna in the study area. In general, bats producing low intensity echolocation calls, such as phyllostomids, are more easily assessed by netting, and bats producing high intensity echolocation calls are better surveyed by bat detectors. The results demonstrate that a combined and varied approach to sampling is required for a complete assessment of the bat fauna of an area.