Egg and larval abundance and spawning localities of the anchovy (Engraulis australis) and pilchard (Sardinops neopilchardus) near Phillip Island, Victoria

1995 ◽  
Vol 46 (4) ◽  
pp. 735 ◽  
Author(s):  
FE Hoedt ◽  
WF Dimmlich
Keyword(s):  
Spatial Variability ◽  
Larval Abundance ◽  
Adult Fish ◽  
Spawning Area ◽  
Fish Spawning ◽  
The Mean ◽  
Eggs And Larvae

The distribution and abundance of the eggs and larvae of the anchovy (Engraulis australis) and pilchard (Sardinops neopilchardus) were determined for the waters near Phillip Island between May 1992 and January 1994. Eggs and larvae of both species were common in these waters, indicating that this region is an important spawning area for both species. Pilchard eggs and larvae occurred at sample stations in Bass Strait and in the western entrance to Western Port. Anchovy eggs and larvae were collected both within Western Port and at most plankton stations in Bass Strait. The mean density of anchovy eggs in Western Port differed markedly between the two spawning seasons, suggesting that the number of adult fish spawning therein can vary between years. Densities of pilchard eggs and of the larvae of both species exhibited considerable spatial variability in Bass Strait.

scholarly journals Threatened fish spawning area revealed by specific metabarcoding identification of eggs and larvae in the Beni River, upper Amazon

2020 ◽  
Vol 24 ◽  
pp. e01309
Author(s):  
Guido Miranda-Chumacero ◽  
Cédric Mariac ◽  
Fabrice Duponchelle ◽  
Lilian Painter ◽  
Robert Wallace ◽  
...  
Keyword(s):  
Threatened Fish ◽  
Spawning Area ◽  
Fish Spawning ◽  
Eggs And Larvae

Distribution and drift of Atlantic cod (Gadus morhua) eggs and larvae on the northeast Newfoundland Shelf

1997 ◽  
Vol 54 (3) ◽  
pp. 670-685 ◽  
Author(s):  
P Pepin ◽  
J A Helbig
Keyword(s):  
Spatial Patterns ◽  
Gadus Morhua ◽  
Atlantic Cod ◽  
Stage I ◽  
Surface Currents ◽  
Adult Fish ◽  
Northern Limit ◽  
Mean And Variance ◽  
The Mean ◽  
Eggs And Larvae

We present the results of a study designed to ascertain the importance of variations in transport of cod eggs and larvae on the northeast Newfoundland Shelf. The distribution of cod eggs and larvae is described from a series of ichthyoplankton surveys. The mean and variance in surface currents were estimated from five experiments in which clusters of drogued satellite-tracked drifters were released at the presumed northern limit of the stock's range. These data were used to project the patterns of drift both backward and forward in time and thus the possible sources and destinations of eggs and larvae. Considering the development from the youngest (stage I) to the oldest stages (larvae), we saw a north-to-south and an offshore-to-inshore progression in spatial patterns of spawning and a continuing increase in the overall level of dispersion with increasing age of offspring. The data do not support the hypothesis that coastal or offshore areas represent simple sources or sinks of cod eggs and larvae. Transport plays an important but highly variable role that is coupled to the spawning distribution of adult fish and the availability of suitable conditions or habitats when the young begin to undergo metamorphosis and settle.

Variation within and between Rivers in Adult Size and Sea Age at Maturity of Anadromous Brown Trout, Salmo trutta

1991 ◽  
Vol 48 (6) ◽  
pp. 1015-1021 ◽  
Author(s):  
Jan Henning L'Abée-Lund
Keyword(s):  
Brown Trout ◽  
Sexual Maturity ◽  
Salmo Trutta ◽  
Adult Size ◽  
Age At Maturity ◽  
Migration Distance ◽  
Spawning Area ◽  
Brown Trout Salmo Trutta ◽  
Males And Females ◽  
The Mean

I compared adult size and sea age at sexual maturity among nine populations of anadromous brown trout, Salmo trutta, in two Norwegian rivers to determine the extent of inter- and intrariverine variations. Variation in the mean length of spawners and in the mean sea age at sexual maturity were mainly dependent on the variations found within rather than between rivers. Mean lengths and mean age at maturity of males increased significantly with increasing altitude of the spawning area and with migration distance in freshwater. In females, positive significant correlations were found with mean lengths and altitude of the spawning area and with mean sea age at maturity and both spawning site altitude and migration distance. Mean lengths and ages of males and females were not significantly correlated with the rate of water discharge in the streams during spawning. The size of gravel substrate for spawning was of minor importance in explaining interpopulation variation in mean female size. The increase noted in mean length and in mean sea age at maturity of both males and females is probably an adaptation to greater energy expenditure to reach the uppermost natal spawning areas.

How landscape and climate affect the spatial variability of the Italian rainfall extremes? Some initial clues based on I2-RED

2021 ◽  
Author(s):  
Paola Mazzoglio ◽  
Ilaria Butera ◽  
Pierluigi Claps
Keyword(s):  
Spatial Variability ◽  
Linear Regression Analysis ◽  
Alpine Region ◽  
Annual Rainfall ◽  
Mean Values ◽  
Rainfall Extremes ◽  
Geomorphological Parameters ◽  
The Mean ◽  
The Relationship ◽  
Italian Territory

<p>The intensity and the spatial distribution of precipitation depths are known to be highly dependent on relief and geomorphological parameters. Complex environments like mountainous regions are prone to intense and frequent precipitation events, especially if located near the coastline. Although the link between the mean annual rainfall and geomorphological parameters has received substantial attention, few literature studies investigate the relationship between the sub-daily maximum annual rainfall depth and geographical or morphological landscape features.<br>In this study, the mean of the rainfall extremes in Italy, recently revised in the so-called I<sup>2</sup>-RED dataset, are investigated in their spatial variability in comparison with some landscape and also some broad climatic characteristics. The database includes all sub-daily rainfall extremes recorded in Italy from 1916 until 2019 and this analysis considers their mean values (from 1 to 24 hours) in stations with at least 10 years of records, involving more than 3700 stations.<br>The geo-morpho-climatic factors considered range from latitude, longitude and minimum distance from the coastline on the geographic side, to elevation, slope, openness and obstruction morphological indices, and also include an often-neglected robust climatological information, as the local mean annual rainfall.<br>Obtained results highlight that the relationship between the annual maximum rainfall depths and the hydro-geomorphological parameters is not univocal over the entire Italian territory and over different time intervals. Considering the whole of Italy, the highest correlation is reached between the mean values of the 24-hours records and the mean annual precipitation (correlation coefficient greater than 0.75). This predominance remains also in sub-areas of the Italian territory (i.e., the Alpine region, the Apennines or the coastal areas) but correlation decreases as the time interval decreases, except for the Alpine region (0.73 for the 1-hour maximum). The other geomorphological parameters seem to act in conjunction, making it difficult to evaluate, with a simple linear regression analysis, their impact. As an example, the absolute value of the correlation coefficient between the elevation and the 1-hour extremes is greater than 0.35 for the Italian and the Alpine regions, while for the 24-hours interval it is greater than 0.35 over the coastal areas.<br>To further investigate the spatial variability of the relationship between rainfall and elevation, a spatial linear regression analysis has been undertaken. Local linear relationships have been fitted in circles centered on any of the 0.5-km size pixels in Italy, with 1 to 30 km radius and at least 5 stations included. Results indicate the need of more comprehensive terrain analysis to better understand the causes of local increasing or decreasing relations, poorly described in the available literature.</p>

Spatial dynamics of soil moisture and temperature in a black spruce boreal chronosequence

2006 ◽  
Vol 36 (11) ◽  
pp. 2794-2802 ◽  
Author(s):  
Ben Bond-Lamberty ◽  
Karen M Brown ◽  
Carol Goranson ◽  
Stith T Gower
Keyword(s):  
Soil Moisture ◽  
Spatial Variability ◽  
Sampling Design ◽  
Black Spruce ◽  
Structural Characteristics ◽  
Spatial Dynamics ◽  
Spherical Model ◽  
Local Scale ◽  
Spatial Dependencies ◽  
The Mean

This study analyzed the spatial dependencies of soil moisture and temperature in a six-stand chronosequence of boreal black spruce (Picea mariana (Mill.) BSP) stands. Spatial variability of soil temperature (TSOIL) was evaluated twice during the growing season using four transects in each stand, employing a cyclic sampling design with measurements spaced 2–92 m apart. Soil moisture (θg) was measured on one occasion. A spherical model was used to analyze the geostatistical correlation structure; θg and TSOIL at the 7- and 21-year-old stands did not exhibit stable ranges or sills. The fits with stable ranges and sills modeled the spatial patterns in the older stands reasonably well, although unexplained variability was high. Calculated ranges varied from 3 to 150 m for these stands, lengths probably related to structural characteristics influential in local-scale energy transfer. Transect-to-transect variability was significant and typically 5%–15% of the mean for TSOIL and 10%–70% for θg. TSOIL and θg were negatively correlated for most stands and depths, with TSOIL dropping 0.5–0.9 °C for every 1% rise in θg. The results reported here provide initial data to assess the spatial variability of TSOIL and θg in a variety of boreal forest stand ages.

scholarly journals Probabilistic Bearing Capacity of a Pavement Resting on Fibre Reinforced Embankment Considering Soil Spatial Variability

2021 ◽  
Vol 7 ◽  
Author(s):  
Kouseya Choudhuri ◽  
Debarghya Chakraborty
Keyword(s):  
Spatial Variability ◽  
Soil Properties ◽  
Bearing Capacity ◽  
Coefficient Of Variation ◽  
Friction Angle ◽  
Horizontal Scale ◽  
Vertical Scale ◽  
Scale Of Fluctuation ◽  
The Mean ◽  
The Finite Difference Method

This paper intends to examine the influence of spatial variability of soil properties on the probabilistic bearing capacity of a pavement located on the crest of a fibre reinforced embankment. An anisotropic random field, in combination with the finite difference method, is used to carry out the probabilistic analyses. The cohesion and internal friction angle of the soil are assumed to be lognormally distributed. The Monte Carlo simulations are carried out to obtain the mean and coefficient of variation of the pavement bearing capacity. The mean bearing capacity of the pavement is found to decrease with the increase in horizontal scale of fluctuation for a constant vertical scale of fluctuation; whereas, the coefficient of variation of the bearing capacity increases with the increase in horizontal scale of fluctuation. However, both the mean and coefficient of variation of bearing capacity of the pavement are observed to be increasing with the increase in vertical scale of fluctuation for a constant horizontal scale of fluctuation. Apart from the different scales of fluctuation, the effects of out of the plane length of the embankment and randomness in soil properties on the probabilistic bearing capacity are also investigated in the present study.

Variation in Dispersal of Galjoen (Coracinus capensis) (Teleostei: Coracinidae) from a Marine Reserve

1994 ◽  
Vol 51 (6) ◽  
pp. 1247-1257 ◽  
Author(s):  
Colin G. Attwood ◽  
Bruce A. Bennett
Keyword(s):  
South Africa ◽  
Spatial Variability ◽  
Surf Zone ◽  
Marine Reserve ◽  
Adult Fish ◽  
Large Uncertainty ◽  
Dispersal Behaviour ◽  
Movement Rates ◽  
Random Dispersal

The dispersal of the surf-zone teleost galjoen (Coracinus capensis) from the De Hoop Marine Reserve, South Africa, was investigated. Over a period of 5.5 yr, 11 022 galjoen were tagged in the centre of the reserve. Most of the 1008 recoveries were at the site of release, while the remainder covered a distance of up to 1040 km. There was no difference with respect to age, sex, or season between those that dispersed and those that did not. Six models were developed to test the hypotheses that (1) galjoen are polymorphic with respect to dispersal behaviour, (2) nonreporting of tags masks a random dispersal process, and (3) the recovery distribution is the result of unequal movement rates in different areas. It is inferred from the likelihoods of the various models that the tagged population was polymorphic, with fish displaying either resident or nomadic behaviour. This conclusion is unaffected by a large uncertainty in the extent of nonreporting of recoveries, or by spatial variability of movement rates. The estimate of emigration from the reserve implies that the unharvested reserve population is restocking adjacent exploited areas with adult fish.

Reconstruction of GRACE Total Water Storage Through Automated Machine Learning

2020 ◽  
Author(s):  
Alex Sun ◽  
Bridget Scanlon ◽  
Himanshu Save ◽  
Ashraf Rateb
Keyword(s):  
Machine Learning ◽  
Spatial Variability ◽  
Large Scale ◽  
Water Storage ◽  
Total Water ◽  
New Paradigm ◽  
Satellite Mission ◽  
Automated Machine Learning ◽  
The Mean ◽  
The Impact

<p>The GRACE satellite mission and its follow-on, GRACE-FO, have provided unprecedented opportunities to quantify the impact of climate extremes and human activities on total water storage at large scales. The approximately one-year data gap between the two GRACE missions needs to be filled to maintain data continuity and maximize mission benefits. There is strong interest in using machine learning (ML) algorithms to reconstruct GRACE-like data to fill this gap. So far, most studies attempted to train and select a single ML algorithm to work for global basins. However, hydrometeorological predictors may exhibit strong spatial variability which, in turn, may affect the performance of ML models. Existing studies have already shown that no single algorithm consistently outperformed others over all global basins. In this study, we applied an automated machine learning (AutoML) workflow to perform GRACE data reconstruction. AutoML represents a new paradigm for optimal model structure selection, hyperparameter tuning, and model ensemble stacking, addressing some of the most challenging issues related to ML applications. We demonstrated the AutoML workflow over the conterminous U.S. (CONUS) using six types of ML algorithms and multiple groups of meteorological and climatic variables as predictors. Results indicate that the AutoML-assisted gap filling achieved satisfactory performance over the CONUS. For the testing period (2014/06–2017/06), the mean gridwise Nash-Sutcliffe efficiency is around 0.85, the mean correlation coefficient is around 0.95, and the mean normalized root-mean square error is about 0.09. Trained models maintain good performance when extrapolating to the mission gap and to GRACE-FO periods (after 2017/06). Results further suggest that no single algorithm provides the best predictive performance over the entire CONUS, stressing the importance of using an end-to-end workflow to train, optimize, and combine multiple machine learning models to deliver robust performance, especially when building large-scale hydrological prediction systems and when predictor importance exhibits strong spatial variability.</p>

The effects of spatial variability of nitrous oxide emissions from grazed pastures on the sampling distribution of chamber measurements

2015 ◽  
Vol 154 (2) ◽  
pp. 223-241 ◽  
Author(s):  
D. L. GILTRAP ◽  
A. J. R. GODFREY
Keyword(s):  
Nitrous Oxide ◽  
Spatial Variability ◽  
Agricultural Soils ◽  
Geometric Mean ◽  
Arithmetic Mean ◽  
Nitrous Oxide Emissions ◽  
Sample Mean ◽  
Grazed Pastures ◽  
Urine Patch ◽  
The Mean

SUMMARYChamber sampling is a common method for measuring nitrous oxide (N2O) emissions from agricultural soils. However, for grazed pastures, the patchy nature of urine deposition results in very high levels of spatial variability in N2O emissions. In the present study, the behaviour of the sample mean was examined by simulating a large number (9999) of random N2O chamber samples under different assumptions regarding the underlying N2O distribution. Using sample sizes of up to 100 chambers, the Central Limit Theorem did not apply. The distribution of the sample mean was always right-skewed with a standard deviation varying between 12·5 and 135% of the true mean. However, the arithmetic mean was an unbiased estimator and the mean of the sample mean distribution was close to the true mean of the simulated N2O distribution. The properties of the sample mean distribution (variance, skewness) were affected significantly by the assumed distribution of the emission factor, but not by distribution of the urine patch concentration. The geometric mean was also investigated as a potential alternative estimator. However, although its distribution had lower variance, it was also biased. Two methods for bias correcting the mean were investigated. These methods reduced the bias, but at the cost of increasing the variance. Neither of the bias-corrected estimators were consistently better than the arithmetic mean in terms of skewness and variance. To improve the estimation of N2O emissions from a grazed pasture using chambers, techniques need to be developed to identify urine patch and non-urine patch areas before sampling.

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