MAXIMUM SWIM SPEEDS OF CAPTIVE AND FREE-RANGING DELPHINIDS: CRITICAL ANALYSIS OF EXTRAORDINARY PERFORMANCE

Research into dolphin swimming historically was guided by false assumptions pertaining to maximum speed. Accurate measurements on swimming speed and duration of effort of free-ranging dolphins are rare. To examine the variance of maximum swimming speeds, nearly 2,000 speed measurements were obtained for both captive and free-ranging dolphins, including Tursiops truncatus, Pseudorca crassidens, Delphinus capensis , and Delphinus delpbis . Measurements were made from videotapes of dolphins trained to swim fast around a large pool or jumping to a maximum height, videotapes of captured wild dolphins immediately after release, and sequential aerial photographs of a school of free-ranging dolphins startled by a passing airplane. Maximum horizontal speeds for trained animals were 8.2 m/sec for T. truncatus , 8.0 m/sec for D. delphis , and 8.0 m/sec for P. crassidens . Maximum speeds for T. truncatus swimming upwards, prior to vertical leaps ranged from 8.2 to 11.2 m/sec. Wild T. truncatus demonstrated a maximum speed of 5.7 m/sec. Maximum swimming speed of free-ranging D. capensis responding to multiple passes by a low flying airplane was 6.7 m/sec. There was no evidence that the freeranging dolphins have superior swimming capabilities to captive animals. The results of this study imply that realistic maximum swimming speeds for dolphins are lower than previous reports which were based on sparse data and imprecise measurement techniques.     

Identification of quantitative trait loci influencing aerial morphogenesis in the model legume <Emphasis Type="Italic">Medicago truncatula</Emphasis>

In many legume crops, especially in forage legumes, aerial morphogenesis defined as growth and development of plant organs, is an essential trait as it determines plant and seed biomass as well as forage quality (protein concentration, dry matter digestibility). Medicago truncatula is a model species for legume crops. A set of 29 accessions of M. truncatula was evaluated for aerial morphogenetic traits. A recombinant inbred lines (RILs) mapping population was used for analysing quantitative variation in aerial morphogenetic traits and QTL detection. Genes described to be involved in aerial morphogenetic traits in other species were mapped to analyse co-location between QTLs and genes. A large variation was found for flowering date, morphology and dynamics of branch elongation among the 29 accessions and within the RILs population. Flowering date was negatively correlated to main stem and branch length. QTLs were detected for all traits, and each QTL explained from 5.2 to 59.2% of the phenotypic variation. A QTL explaining a large part of genetic variation for flowering date and branch growth was found on chromosome 7. The other chromosomes were also involved in the variation detected in several traits. Mapping of candidate genes indicates a co-location between a homologue of Constans gene or a flowering locus T (FT) gene and the QTL of flowering date on chromosome 7. Other candidate genes for several QTLs are described. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Population Dynamics and Behavior of Bighorn Sheep with Infectious Keratoconjunctivitis

ABSTRACT Introduced disease is a major mortality factor in some populations of bighorn sheep (Ovis canadensis). Epizootics of infectious keratoconjunctivitis (IKC) and contagious ecthyma occurred in bighorn sheep in the Silver Bell Mountains of south-central Arizona, USA, from 1 December 2003 to 31 March 2004. Our objectives were to 1) investigate the influence of the epizootic on abundance and demographics and 2) examine how IKC affected the mortality, behavior, and movements of clinically affected animals. Morbidity was 39%, and all sex and age classes were affected. The population declined 23%, with most mortality in the adult female (1 M, 11 F) segment of the population. Of the diseased animals that were marked (n = 27), 44% recovered and 44% died. Predation (50%) and starvation (33%) were the primary causes of mortality of diseased bighorn sheep. Bighorn sheep that were infected spent less time feeding and moved less than noninfected animals during the epizootic. Managers might be able to minimize losses of infected animals through predator control. To minimize losses to starvation, managers should refrain from any activity that disturbs infected animals (including treatment) because disturbances increase energy expenditures and expose infected animals to injury.     

Survival of Wood Duck Ducklings and Broods in Mississippi and Alabama

ABSTRACT Although North American wood ducks (Aix sponsa) are well-studied throughout their range, researchers know little about demographic and environmental factors influencing survival of ducklings and broods, which is necessary information for population management. We studied radiomarked female and duckling wood ducks that used nest boxes and palustrine wetlands at Noxubee National Wildlife Refuge (NNWR) in Mississippi, USA, in 1996–1999, and riverine wetlands of the Tennessee-Tombigbee Rivers and Waterway (TTRW) system in Alabama in 1998–1999. We estimated survival of ducklings and broods and evaluated potentially important predictors of duckling survival, including age and body mass of brood-rearing females, hatch date of ducklings, duckling mass, brood size at nest departure, inter-day travel distance by ducklings, site and habitat use, and daily minimum air temperature and precipitation. At NNWR, survival of 300 radiomarked ducklings ranged from 0.15 (95% CI = 0.04-0.27) to 0.24 (95% CI = 0.13-0.38) and was 0.21 (95% CI = 0.15-0.28) for 1996–1999. Our overall estimate of brood survival was 0.64 (n = 91; 95% CI = 0.54-0.73). At TTRW, survival of 129 radiomarked ducklings was 0.29 in 1998 (95% CI = 0.20-0.41) and 1999 (95% CI = 0.13-0.45) and was 0.29 (95% CI = 0.20-0.40) for 1998–1999. Our overall estimate of brood survival was 0.71 (n = 38; 95% CI = 0.56-0.85). At NNWR, models that included all predictor variables best explained variation in duckling survival. Akaike weight (w_i) for the best model was 0.81, suggesting it was superior to other models (<0.01 < w_i < 0.18). We detected 4 competing models for duckling survival at TTRW. Inter-day distance traveled by ducklings was important as this variable appeared in all 4 models; duckling survival was positively related to this variable. Patterns of habitat-related survival were similar at both study areas. Ducklings in broods that used scrub-shrub habitats disjunct from wetlands containing aggregations of nest boxes had greater survival probabilities than birds remaining in wetlands with such nest structures. Managers may increase local wood duck recruitment by promoting availability of suitable brood habitats (e.g., scrub-shrub wetlands) without aggregations of nest boxes that may attract predators and by dispersing nest boxes amid or adjacent to these habitats. We did not determine an optimal density of nest boxes relative to local or regional population goals, which remains important research and conservation needs.     

Past and present distribution, densities and movements of blue whales Balaenoptera musculus in the Southern Hemisphere and northern Indian Ocean

• 1 Blue whale locations in the Southern Hemisphere and northern Indian Ocean were obtained from catches (303 239), sightings (4383 records of ≥8058 whales), strandings (103), Discovery marks (2191) and recoveries (95), and acoustic recordings.
• 2 Sighting surveys included 7 480 450 km of effort plus 14 676 days with unmeasured effort. Groups usually consisted of solitary whales (65.2%) or pairs (24.6%); larger feeding aggregations of unassociated individuals were only rarely observed. Sighting rates (groups per 1000 km from many platform types) varied by four orders of magnitude and were lowest in the waters of Brazil, South Africa, the eastern tropical Pacific, Antarctica and South Georgia; higher in the Subantarctic and Peru; and highest around Indonesia, Sri Lanka, Chile, southern Australia and south of Madagascar.
• 3 Blue whales avoid the oligotrophic central gyres of the Indian, Pacific and Atlantic Oceans, but are more common where phytoplankton densities are high, and where there are dynamic oceanographic processes like upwelling and frontal meandering.
• 4 Compared with historical catches, the Antarctic (‘true’) subspecies is exceedingly rare and usually concentrated closer to the summer pack ice. In summer they are found throughout the Antarctic; in winter they migrate to southern Africa (although recent sightings there are rare) and to other northerly locations (based on acoustics), although some overwinter in the Antarctic.
• 5 Pygmy blue whales are found around the Indian Ocean and from southern Australia to New Zealand. At least four groupings are evident: northern Indian Ocean, from Madagascar to the Subantarctic, Indonesia to western and southern Australia, and from New Zealand northwards to the equator. Sighting rates are typically much higher than for Antarctic blue whales.
• 6 South‐east Pacific blue whales have a discrete distribution and high sighting rates compared with the Antarctic. Further work is needed to clarify their subspecific status given their distinctive genetics, acoustics and length frequencies.
• 7 Antarctic blue whales numbered 1700 (95% Bayesian interval 860–2900) in 1996 (less than 1% of original levels), but are increasing at 7.3% per annum (95% Bayesian interval 1.4–11.6%). The status of other populations in the Southern Hemisphere and northern Indian Ocean is unknown because few abundance estimates are available, but higher recent sighting rates suggest that they are less depleted than Antarctic blue whales.

     

THE JUST-ABOUT-RIGHT INTENSITY SCALE: FUNCTIONAL ANALYSES AND RELATION TO HEDONICS

This study assessed the meaning of just‐about‐right (JAR) categories when used with a 5‐point intensity scale. The panelists comprised both consumer and in‐house respondents. The JAR categories have various meanings as perceived by the respondents: “prefer product,”“very good,”“I like the product,”“like it very much,”“highly favorable,”“high acceptability,”“desirable like the product,”“best for the situation” and “correct.” Thus, the JAR meanings invoke preference and acceptability. This article presents two additional analyses to help the product tested. One method of analysis divides below‐JAR deviation from the above‐JAR deviation, with standard statistical procedures applied in each data set. The second method introduces the signal‐to‐noise ratio statistic for analyzing the relation of JAR to overall liking. Both analytic methods provide new ways to look at the JAR data, especially with respect to hedonics and product improvement.     

Evolutionary dynamics of autosomal-heterosomal rearrangements in a multiple-X chromosome system of tiger beetles (Cicindelidae)

Background  

Genetic systems involving multiple X chromosomes have arisen repeatedly in sexually reproducing animals. Tiger beetles (Cicindelidae) exhibit a phylogenetically ancient multiple-X system typically consisting of 2–4 X chromosomes and a single Y. Because recombination rates are suppressed in sex chromosomes, changes in their numbers and movement of genes between sex chromosomes and autosomes, could have important consequences for gene evolution and rates of speciation induced by these rearrangements. However, it remains unclear how frequent these rearrangements are and which genes are affected.     

The Contribution of Agriculture,Forestry and other Land Use activities to Global Warming, 1990–2012

We refine the information available through the IPCC AR5 with regard to recent trends in global GHG emissions from agriculture, forestry and other land uses (AFOLU), including global emission updates to 2012. Using all three available AFOLU datasets employed for analysis in the IPCC AR5, rather than just one as done in the IPCC AR5 WGIII Summary for Policy Makers, our analyses point to a down‐revision of global AFOLU shares of total anthropogenic emissions, while providing important additional information on subsectoral trends. Our findings confirm that the share of AFOLU emissions to the anthropogenic total declined over time. They indicate a decadal average of 28.7 ± 1.5% in the 1990s and 23.6 ± 2.1% in the 2000s and an annual value of 21.2 ± 1.5% in 2010. The IPCC AR5 had indicated a 24% share in 2010. In contrast to previous decades, when emissions from land use (land use, land use change and forestry, including deforestation) were significantly larger than those from agriculture (crop and livestock production), in 2010 agriculture was the larger component, contributing 11.2 ± 0.4% of total GHG emissions, compared to 10.0 ± 1.2% of the land use sector. Deforestation was responsible for only 8% of total anthropogenic emissions in 2010, compared to 12% in the 1990s. Since 2010, the last year assessed by the IPCC AR5, new FAO estimates indicate that land use emissions have remained stable, at about 4.8 Gt CO₂ eq yr^?1 in 2012. Emissions minus removals have also remained stable, at 3.2 Gt CO₂ eq yr^?1 in 2012. By contrast, agriculture emissions have continued to grow, at roughly 1% annually, and remained larger than the land use sector, reaching 5.4 Gt CO₂ eq yr^?1 in 2012. These results are useful to further inform the current climate policy debate on land use, suggesting that more efforts and resources should be directed to further explore options for mitigation in agriculture, much in line with the large efforts devoted to REDD+ in the past decade.