Life in the Slow Lane: Ecology and Conservation of Long-Lived Marine Animals

1999 ◽  
Keyword(s):  
Time Series ◽  
Crude Birth Rate ◽  
Humpback Whales ◽  
Surveillance Program ◽  
Aerial Surveillance ◽  
Time Series Regression ◽  
Group V ◽  
Juvenile Recruitment ◽  
Breeding Grounds ◽  
Using Data

<em>Abstract.</em> —The spatial and seasonal distribution of humpback whales in the Great Barrier Reef Marine Park (GBRMP) was defined using data from a systematic aerial surveillance program. The data comprised 414 pod sightings (812 individuals) recorded from July 1982 to March 1996. These sightings were supposedly of humpbacks from the east Australian Group V substock that migrates during the austral autumn from Antarctic feeding grounds to winter breeding grounds in GBR waters. Humpbacks were sighted in all months and throughout the GBRMP. However, most pods (75%) were sighted in southern GBR waters (below 19°S) and mainly during winter and spring ( July to September). Occasional sightings of humpbacks in northern GBR waters (above 16°S) in summer supports previous claims of a substock resident year-round in northern Australian tropical waters. Mother–calf sightings were rare with most recorded below 21°S and mainly in August and September. These limited sightings suggest that the main calving grounds for the east Australian Group V substock occur in the extensive southern GBR lagoonal waters defined northward by the Whitsunday Group of islands and reefs and eastward by the Pompey/Swains reef complex. An estimate of the crude birth rate was 0.072 (95% confidence interval [CI]: 0.06–0.11) with Monte Carlo estimates of the median calving rate at 0.3 calves per mature female per year (95% CI: 0.22–0.43) and the median interbirth interval at 3.4 years (95% CI: 2.3–4.5) indicating low and variable juvenile recruitment. Nonparametric time series analysis (seasonal and trend decomposition using loess, STL) of monthly humpback sightings showed that the long-term trend in sightings was increasing but that there was significant inter-annual variability in the seasonal abundance of humpbacks in the GBRMP. The STL analysis also suggested that the frequency of sightings increased earlier in winter (June) and later in the season during spring/summer (October to December). Time series regression analysis of the STL-derived trend in sightings suggested that the east Australian Group V substock increased slowly in abundance over the 14 years from 1982 to 1996 at about 3.9% per year (95% CI: 1.9% to 5.7%)—a finding consistent with an estimate of low and variable juvenile recruitment.

Site fidelity and residence times of humpback whales (Megaptera novaeangliae) on the Brazilian coast

2012 ◽  
Vol 92 (8) ◽  
pp. 1783-1791 ◽  
Author(s):  
Clarêncio G. Baracho-Neto ◽  
Elitieri Santos Neto ◽  
Marcos R. Rossi-Santos ◽  
Leonardo L. Wedekin ◽  
Mariana C. Neves ◽  
...  
Keyword(s):  
Residence Time ◽  
Site Fidelity ◽  
Megaptera Novaeangliae ◽  
Humpback Whales ◽  
Brazilian Coast ◽  
Northern Coast ◽  
Occupancy Rate ◽  
Breeding Grounds ◽  
Minimum Number ◽  
Using Data

Humpback whales (Megaptera novaeangliae) migrate between their feeding grounds, located in high latitudes, and their breeding grounds, located in low latitudes, exhibiting certain levels of site fidelity to their migratory destinations. The residence time, also known as occupancy rate, can be defined as the minimum number of days that those individuals remained in the same area. In this paper, site fidelity and residence time of humpback whales that breed off the northern coast of Bahia, Brazil were investigated. Data were collected between 2000 and 2009 on-board research cruises and whale watching vessels. This paper also studies possible differences between males and females with respect to site fidelity off the Brazilian coast, using data collected since 1989. A total of 841 whales were photo-identified. The vast majority of the whales (96%, N = 809) were seen only once in the studied area, while 4% (32 individuals) were seen twice. Most of the resights occurred within the same season (72%, N = 23), while 9 resights (28%) occurred in different years. None of the individuals were seen more than twice. The average site fidelity rate was 1% and the occupancy rate varied from one up to 21 days (mean = 5.3; SD = 5.4, N = 23).

scholarly journals Peramalan Data Runtun Waktu menggunakan Model Hybrid Time Series Regression – Autoregressive Integrated Moving Average

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Melisa Arumsari ◽  
◽  
Andrea Dani ◽  
Keyword(s):  
Time Series ◽  
Hybrid Method ◽  
Time Series Data ◽  
Moving Average ◽  
Series Data ◽  
Time Series Regression ◽  
Accurate Forecast ◽  
Using Data ◽  
The Individual ◽  
Time Series Data Analysis

Forecasting is a method used to estimate or predict a value in the future using data from the past. With the development of methods in time series data analysis, a hybrid method was developed in which a combination of several models was carried out in order to produce a more accurate forecast. The purpose of this study was to determine whether the TSR-ARIMA hybrid method has a better level of accuracy than the individual TSR method so that more accurate forecasting results are obtained. The data in this study are monthly data on the number of passengers on American airlines for the period January 1949 to December 1960. Based on the analysis, the TSR-ARIMA hybrid method produces a MAPE of 3,061% and the TSR method produces an MAPE of 7,902%.

Effect of annual road safety publicity and enforcement campaign on road fatalities in Japan: a time series study from 1949 to 2019

2021 ◽  
pp. jech-2021-216532
Author(s):  
Haruhiko Inada ◽  
Jun Tomio ◽  
Shinji Nakahara ◽  
Masao Ichikawa
Keyword(s):  
Time Series ◽  
Traffic Safety ◽  
Short Term ◽  
Time Series Regression ◽  
Middle Income ◽  
Police Data ◽  
Using Data ◽  
Natural Cubic Spline ◽  
Cubic Spline Function ◽  
National Police

BackgroundIn 1948, Japan started a short-term publicity and enforcement campaign for traffic safety nationwide, and since 1952, the campaign has been conducted twice a year for 10 days. We aimed to quantify the short-term effect of the spring sessions of the campaign, which were conducted in different months in different years, on road fatalities in Japan using data from 1949 to 2019.MethodsWe obtained national police data on the monthly number of road deaths and conducted a time series regression analysis with three steps: smoothing the long-term patterns with the natural cubic spline function, calculating the ratio of the monthly number of deaths to the corresponding smoothed value, and regressing the ratio on the number of months from January 1949 and the binary variable for the conduct of spring sessions. We repeated the analysis for four subperiods (1949–1964, 1965–1989, 1990–2004 and 2005–2019).ResultsDuring the study period, there were 632577 road deaths. Our analysis revealed that the spring sessions changed the number of deaths per day by −2.5% (95% CI −4.1% to −0.9%) in the months when they were conducted. In the four subperiods, the estimated changes were −4.5% (95% CI −8.9% to −0.1%), −2.6% (95% CI −5.0% to −0.1%), −0.1% (95% CI −2.9 to 2.7) and −3.5% (95% CI −7.9 to 0.9).ConclusionsRoad fatalities were reduced in the months when the spring sessions of the campaign were conducted, but the reduction was modest. The effect might have been somewhat larger until 1964, when Japan was a middle-income country.

scholarly journals Time-Series Regression Model for Prediction of Mean Daily Global Solar Radiation in Al-Ain, UAE

2012 ◽  
Vol 2012 ◽  
pp. 1-11 ◽  
Author(s):  
Hassan A. N. Hejase ◽  
Ali H. Assi
Keyword(s):  
Time Series ◽  
Solar Radiation ◽  
Global Solar Radiation ◽  
Bias Error ◽  
Time Series Regression ◽  
Weather Model ◽  
Al Ain ◽  
Using Data ◽  
Long Term Prediction

The availability of short-term forecast weather model for a particular country or region is essential for operation planning of energy systems. This paper presents the first step by a group of researchers at UAE University to establish a weather model for the UAE using the weather data for at least 10 years and employing various models such as classical empirical models, artificial neural network (ANN) models, and time-series regression models with autoregressive integrated moving-average (ARIMA). This work uses time-series regression with ARIMA modeling to establish a model for the mean daily and monthly global solar radiation (GSR) for the city of Al-Ain, United Arab Emirates. Time-series analysis of solar radiation has shown to yield accurate average long-term prediction performance of solar radiation in Al-Ain. The model was built using data for 10 years (1995–2004) and was validated using data of three years (2005–2007), yielding deterministic coefficients (R2) of 92.6% and 99.98% for mean daily and monthly GSR data, respectively. The low corresponding values of mean bias error (MBE), mean absolute bias error (MABE), mean absolute percentage error (MAPE), and root-mean-square error (RMSE) confirm the adequacy of the obtained model for long-term prediction of GSR data in Al-Ain, UAE.

Site-specific female-biased sex ratio of humpback whales (Megaptera novaeangliae) during a stopover early in the southern migration

2018 ◽  
Vol 96 (6) ◽  
pp. 533-544 ◽  
Author(s):  
Trish Franklin ◽  
Wally Franklin ◽  
Lyndon Brooks ◽  
Peter Harrison
Keyword(s):  
Sex Ratio ◽  
Habitat Preferences ◽  
Megaptera Novaeangliae ◽  
Humpback Whales ◽  
Site Specific ◽  
Breeding Grounds ◽  
Biased Sex Ratio ◽  
Males And Females ◽  
Using Data ◽  
Migration Modeling

Previous research on humpback whales (Megaptera novaeangliae (Borowski, 1781)), in both the Northern and Southern hemispheres, has reported site-specific male-biased sex ratios in breeding grounds and along migratory corridors. However, one recent Southern Hemisphere study reported a female-biased sex ratio in a feeding area within a coastal migratory corridor, indicating that females may preferentially occupy some habitats. We investigated the classes and relative seasonal timing of humpback whales using Hervey Bay (Queensland, Australia) as a stopover early in the southern migration. Modeling and analyzes were undertaken using data from resighting histories of 361 individually identified whales between 1992 and 2009. The data consisted of 2131 sightings categorized by either sex, age, reproductive status, or maturational status. A female-biased sex ratio of 2.94:1 indicates that Hervey Bay is a preferential stopover for females. The data revealed that the bay is important for mature females who co-occur with immature males and females during August. During September and October, mothers with calves accompanied by a few escorts dominate the Bay. Immature males and females socialize with mature females during August and September. The data support the hypothesis that habitat preferences and differential migration of females and males provide a plausible explanation for site-specific sex-bias in breeding grounds, migratory stopovers, and along migratory corridors.

Improving Runoff Simulations using Satellite-observed Time-series of Snow Covered Area

2003 ◽  
Vol 34 (4) ◽  
pp. 281-294 ◽  
Author(s):  
R.V. Engeset ◽  
H-C. Udnæs ◽  
T. Guneriussen ◽  
H. Koren ◽  
E. Malnes ◽  
...  
Keyword(s):  
Time Series ◽  
Radar Sensors ◽  
Noaa Avhrr ◽  
Runoff Forecasting ◽  
Snow Covered Area ◽  
Covered Area ◽  
Satellite Sensors ◽  
Major Floods ◽  
Using Data ◽  
Southern Norway

Snowmelt can be a significant contributor to major floods, and hence updated snow information is very important to flood forecasting services. This study assesses whether operational runoff simulations could be improved by applying satellite-derived snow covered area (SCA) from both optical and radar sensors. Currently the HBV model is used for runoff forecasting in Norway, and satellite-observed SCA is used qualitatively but not directly in the model. Three catchments in southern Norway are studied using data from 1995 to 2002. The results show that satellite-observed SCA can be used to detect when the models do not simulate the snow reservoir correctly. Detecting errors early in the snowmelt season will help the forecasting services to update and correct the models before possible damaging floods. The method requires model calibration against SCA as well as runoff. Time-series from the satellite sensors NOAA AVHRR and ERS SAR are used. Of these, AVHRR shows good correlation with the simulated SCA, and SAR less so. Comparison of simultaneous data from AVHRR, SAR and Landsat ETM+ for May 2000 shows good inter-correlation. Of a total satellite-observed area of 1,088 km2, AVHRR observed a SCA of 823 km2 and SAR 720 km2, as compared to 889 km2 using ETM+.

scholarly journals Multi-year presence of humpback whales in the Atlantic sector of the Southern Ocean but not during El Niño

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Elena Schall ◽  
Karolin Thomisch ◽  
Olaf Boebel ◽  
Gabriele Gerlach ◽  
Sari Mangia Woods ◽  
...  
Keyword(s):  
Southern Ocean ◽  
El Niño ◽  
El Nino ◽  
Humpback Whales ◽  
Low Latitude ◽  
Sea Ice Extent ◽  
Atlantic Sector ◽  
Acoustic Data ◽  
Breeding Grounds ◽  
Passive Acoustic

AbstractHumpback whales are thought to undertake annual migrations between their low latitude breeding grounds and high latitude feeding grounds. However, under specific conditions, humpback whales sometimes change their migratory destination or skip migration overall. Here we document the surprising persistent presence of humpback whales in the Atlantic sector of the Southern Ocean during five years (2011, 2012, 2013, 2017, and 2018) using passive acoustic data. However, in the El Niño years 2015 and 2016, humpback whales were virtually absent. Our data show that humpback whales are systematically present in the Atlantic sector of the Southern Ocean and suggest that these whales are particularly sensitive to climate oscillations which have profound effects on winds, sea ice extent, primary production, and especially krill productivity.

A longitudinal study of humpback whales in Irish waters

2015 ◽  
Vol 96 (4) ◽  
pp. 877-883 ◽  
Author(s):  
Conor Ryan ◽  
Pádraig Whooley ◽  
Simon D. Berrow ◽  
Colin Barnes ◽  
Nick Massett ◽  
...  
Keyword(s):  
Longitudinal Study ◽  
North Atlantic ◽  
Spatial Scales ◽  
Humpback Whales ◽  
Migratory Species ◽  
The Public ◽  
Photo Identification ◽  
The North ◽  
Breeding Grounds ◽  
Eastern North Atlantic

Knowledge on the ecology of humpback whales in the eastern North Atlantic is lacking by comparison with most other ocean basins. Humpback whales were historically over-exploited in the region and are still found in low relative abundances. This, coupled with their large range makes them difficult to study. With the aim of informing more effective conservation measures in Ireland, the Irish Whale and Dolphin Group began recording sightings and images suitable for photo-identification of humpback whales from Irish waters in 1999. Validated records submitted by members of the public and data from dedicated surveys were analysed to form a longitudinal study of individually recognizable humpback whales. The distribution, relative abundance and seasonality of humpback whale sighting records are presented, revealing discrete important areas for humpback whales in Irish coastal waters. An annual easterly movement of humpback whales along the southern coast of Ireland is documented, mirroring that of their preferred prey: herring and sprat. Photo-identification images were compared with others collected throughout the North Atlantic (N = 8016), resulting in matches of two individuals between Ireland and Iceland, Norway and the Netherlands but no matches to known breeding grounds (Cape Verde and West Indies). This study demonstrates that combining public records with dedicated survey data is an effective approach to studying low-density, threatened migratory species over temporal and spatial scales that are relevant to conservation and management.

scholarly journals Time series regression studies in environmental epidemiology

2013 ◽  
Vol 42 (4) ◽  
pp. 1187-1195 ◽  
Author(s):  
Krishnan Bhaskaran ◽  
Antonio Gasparrini ◽  
Shakoor Hajat ◽  
Liam Smeeth ◽  
Ben Armstrong
Keyword(s):  
Time Series ◽  
Environmental Epidemiology ◽  
Time Series Regression
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