10 Matching Annotations
  1. Oct 2025
    1. In previous years, such in situ deaths had occurred only in association with heavy mosquito parasitism (Gaston et al., 2002; A.J. Gaston, unpubl. data). A minimum of 25 additional deaths were observed elsewhere on the colony, but the total number of deaths was probably higher: our observations covered only a small part of the mosquito-affected zone, as large parts of the colony were not visible from the cliff top.

      What evidence suggests that mosquito parasitism was the primary cause of adult murre deaths in 2011, and how might limited visibility of the colony have affected the accuracy of mortality estimates?

    2. Northern Hudson Bay, Canada, has been subject to recent temperature increases (Galbraith and Larouche, 2011) and is situated on the borderline between Low and High Arctic regions, making it a particularly suitable area for the study of climate change effects. Their proximity to the Low/High Arctic boundary makes local ecosystems susceptible to rapid transition from food webs characteristic of the High Arctic to more Low Arctic configurations.

      How might the location of northern Hudson Bay at the transition between the Low and High Arctic make its ecosystems more vulnerable to climate-driven shifts in species composition and food web structure?

    1. Our study was conducted predominantly within the tropical montane forest of the Talamanca Cordillera, but also included data from lowland forests of the Pacific slope (Figure 2). Both lowland and highland sites are characterized by a dry season (December-April) and a wet season (May-November), with average annual precipitation ranging from 300 to 800 cm. The average temperature in the highlands varies between 10–20°C; lowland temperatures average 24–32°C (CCSA, 2019; Herrera, 2004).

      These areas experience distinct wet and dry seasons with high rainfall and temperature variation between elevations. How might differences in elevation, temperature, and rainfall influence mammal behavior and activity patterns in the study?

    2. Our results support the underlying assumptions of the predation risk and visual acuity models, but indicate that neither can fully predict lunar-related activity patterns. With diurnal human “super predators” forcing a global increase in activity during the night by mammals, our findings can contribute to a better understanding of nocturnal activity patterns and the development of conservation approaches to mitigate forced temporal niche shifts.

      The authors found that while their results support aspects of both the predation risk and visual acuity models, neither model alone fully explains how mammals respond to moonlight. How might these findings help guide conservation strategies to reduce the negative impacts of human-caused shifts in animal activity?

  2. Sep 2025
    1. In non-clonal organisms, single-generation breeding designs and parent–offspring comparisons can be used to estimate additive genetic variance (h2), the variance component that can readily respond to selection (variance due to heritable, genetic variation that is additive in nature)

      Why are single-generation breeding designs and parent–offspring comparisons useful in estimating additive genetic variance (h²), and how does identifying this variance help predict a population’s capacity to evolve under selection pressures like ocean acidification?

    2. Quantitative genetics approaches use comparisons among relatives with known genetic relatedness to partition observed phenotypic variance into their environmental and genetic components [13]. The advantage of these methods is that they can be applied to a range of organisms without requiring prior molecular genetic information and they can focus directly on fitness traits with no need to identify the specific genes involved.

      How can quantitative genetics help researchers determine whether variation in organismal responses to ocean acidification is due to genetic inheritance or environmental factors, and why is this distinction important for predicting evolutionary potential?

    3. Ocean acidification – the increase in partial pressure of CO2 (pCO2) and reduction in pH associated with uptake of fossil fuel-derived CO2 from the atmosphere – profoundly alters the inorganic conditions of the oceans. Although increased pCO2 can enhance photosynthesis and growth of photoautotrophic organisms, ocean acidification is a stressor for many organisms (i.e., decreases fitness, reviewed in [4]).

      Why might species be unable to escape the negative effects of ocean acidification through migration, unlike their ability to adapt to temperature changes across spatial thermal gradients?

    1. Temperature also affected the behavioural preferences of the infauna associated with mussels. Polychaetes, crustaceans, and molluscs altered their behaviour to colonise the habitat created by one species of mussel to another. This altered behavioural preference of infauna can be driven by habitat-specific cues and the ability of infauna to make habitat choices

      The authors talked about some behavioral changes to the infauna that is associated with the mussels. Would the behavioral changes be positive or negative effect towards them or other species in their environment?

    2. After the 4-week acclimation period, the mussels were defaunated by carefully removing all infauna and separating adult mussels (>1 cm) into 10-cm-diameter clumps (Cole, 2010).

      Would we have seen different result if they acclimation period was longer for the mussels? Would a longer acclimation or a shorter one not really affect the mussels or the result to much?

    3. The outdoor experiment was performed in a purpose-built facility (Pereira et al., 2019) at the Sydney Institute of Marine Science (SIMS), Chowder Bay, Sydney Harbour, New South Wales, Australia. The experiment was performed during the summer peak recruitment period of marine invertebrates in Sydney Harbour.

      Would the researchers get similar or the same results, if they did not perform the experiment during the peak recruitment period? How different would the results be if they where during the low recruitment period?