National Marine Fisheries Service

About: National Marine Fisheries Service is a government organization based out in Silver Spring, Maryland, United States. It is known for research contribution in the topics: Population & Fisheries management. The organization has 3949 authors who have published 7053 publications receiving 305073 citations. The organization is also known as: NOAA Fisheries & NOAA National Marine Fisheries Service.

Predation on Eggs and Larvae of Marine Fishes and the Recruitment Problem

Abstract: Publisher Summary This chapter discusses predation as a factor that may regulate levels of recruitment or generate variations in it. It also discusses predation on fish eggs and larvae as an ecological process and review what is known of its importance in the dynamics of fish populations. Only rarely has predation been recognized in past conceptual models dealing with recruitment variations, but it is increasingly viewed as an important factor influencing egg and larval survival. To manage exploited fishes, it is important to understand the causes of changes in abundance and to know whether the observed changes are natural or induced by man. Predation, including cannibalism, is especially important from a manager's perspective because it is often proposed as a cause of density-dependent regulation in stock-recruitment relationships. Multi-species interactions that focus on predator-prey relationships are of increasing interest, especially when fishing pressure on one species may influence the abundance of other species. This chapter examines predation on fish eggs and larvae by invertebrate predators and fishes. Primary focus is on mid- to high-latitude marine fishes. The chapter discusses the types of predators on fish eggs and larvae and assesses how ecological and behavioral interactions influence the vulnerability of individuals and populations. It then reviews methods and discusses problems of studying the impact of predation on egg and larval survival in the sea. In the end, there is discussion about adaptations of fishes to avoid predation on early life stages, processes of starvation versus predation, and the role of predation in regulating fish recruitment.

Quasi-poisson vs. negative binomial regression: how should we model overdispersed count data?

Abstract: Quasi-Poisson and negative binomial regression models have equal numbers of parameters, and either could be used for overdispersed count data. While they often give similar results, there can be striking differences in estimating the effects of covariates. We explain when and why such differences occur. The variance of a quasi-Poisson model is a linear function of the mean while the variance of a negative binomial model is a quadratic function of the mean. These variance relationships affect the weights in the iteratively weighted least-squares algorithm of fitting models to data. Because the variance is a function of the mean, large and small counts get weighted differently in quasi-Poisson and negative binomial regression. We provide an example using harbor seal counts from aerial surveys. These counts are affected by date, time of day, and time relative to low tide. We present results on a data set that showed a dramatic difference on estimating abundance of harbor seals when using quasi-Poisson vs. negative binomial regression. This difference is described and explained in light of the different weighting used in each regression method. A general understanding of weighting can help ecologists choose between these two methods.

A major ecosystem shift in the northern Bering Sea.

Abstract: Until recently, northern Bering Sea ecosystems were characterized by extensive seasonal sea ice cover, high water column and sediment carbon production, and tight pelagic-benthic coupling of organic production. Here, we show that these ecosystems are shifting away from these characteristics. Changes in biological communities are contemporaneous with shifts in regional atmospheric and hydrographic forcing. In the past decade, geographic displacement of marine mammal population distributions has coincided with a reduction of benthic prey populations, an increase in pelagic fish, a reduction in sea ice, and an increase in air and ocean temperatures. These changes now observed on the shallow shelf of the northern Bering Sea should be expected to affect a much broader portion of the Pacific-influenced sector of the Arctic Ocean.

Standardized diet compositions and trophic levels of sharks

Abstract: Sharks are marine consumers believed to occupy top positions in marine food webs. But surprisingly, trophic level estimates for these predators are almost non-existent. With the hope of helping better define the ecological role of sharks in marine communities, this paper presents standardized diet compositions and trophic levels calculated for a suite of species. Dietary composition for each species was derived from published quantitative studies using a weighted average index that takes into account sample size in each study. The trophic level (TL) values of the 11 food types used to characterize the diet (obtained from published accounts) were then used to calculate fractional trophic levels for 149 species representing eight orders and 23 families. Sharks as a group are tertiary consumers (TL>4), and significant differences were found among the six orders compared, which were attributable to differences between orectolobiforms (TL<4) and all other orders, and between hexanchiforms and both carcharhiniforms and squatiniforms. Among four families of carcharhiniform sharks, carcharhinids (TL=4.1, n=39) had a significantly higher TL than triakids (TL=3.8, n=19) and scyliorhinids (TL=3.9, n=21), but not sphyrnids (TL=3.9, n=6). When compared to trophic levels for other top predators of marine communities obtained from the literature, mean TL for sharks was significantly higher than for seabirds (n=28), but not for marine mammals (n=97). Trophic level and body size were positively correlated (r s =0.33), with the fit increasing (r s =0.41) when the three predominantly zooplanktivorous sharks were omitted, and especially when considering only carcharhinid sharks (r s =0.55).