Top-down and bottom-up control of infauna varies across the saltmarsh landscape

Author Posting. © The Author(s), 2007. This is the author's version of the work. It is posted here by permission of Elsevier B.V. for personal use, not for redistribution. The definitive version was published in Journal of Experimental Marine Biology and Ecology 357 (2008): 20-34, doi:10.1016/j.jembe.2007.12.003.Responses of infaunal saltmarsh benthic invertebrates to whole-ecosystem fertilization and predator removal were quantified in Plum Island Estuary, Massachusetts, USA. Throughout a growing season, we enriched an experimental creek on each flooding tide to 70 mM NO3 - and 4 mM PO4 -3 (a 10 x increase in loading above background), and we reduced Fundulus heteroclitus density by 60% in a branch of the fertilized and a reference creek. Macroinfauna and meiofauna were sampled in creek (mudflat and creek wall), marsh edge (tall form Spartina alterniflora) and marsh platform (Spartina patens and stunted S. alterniflora) habitats before and after treatments were begun; responses were tested with BACI-design statistics. Treatment effects were most common in the mid-range of the inundation gradient. Most fertilization effects were on creek wall where ostracod abundance increased, indices of copepod reproduction increased and copepod and annelid communities were altered. These taxa may use epiphytes (that respond rapidly to fertilization) of filamentous algae as a food source. Killifish reduction effects on meiobenthic copepod abundance were detected at the marsh edge and suggest predator limitation. Fish reduction effects on annelids did not suggest top-down regulation in any habitat; however, fish reduction may have stimulated an increased predation rate on annelids by grass shrimp. Interactions between fertilization and fish reduction occurred under S. patens canopy where indirect predator reduction effects on annelids were indicated. No effects were observed in mudflat or stunted S. alterniflora habitats. Although the responses of infauna to fertilization and predator removal were largely independent and of similar mild intensity, our data suggests that the effects of ecological stressors vary across the marsh landscape.This research was supported by the National Science Foundation under Grants No. 0213767 and 9726921

Effects of sleep deprivation on neural functioning: an integrative review

Sleep deprivation has a broad variety of effects on human performance and neural functioning that manifest themselves at different levels of description. On a macroscopic level, sleep deprivation mainly affects executive functions, especially in novel tasks. Macroscopic and mesoscopic effects of sleep deprivation on brain activity include reduced cortical responsiveness to incoming stimuli, reflecting reduced attention. On a microscopic level, sleep deprivation is associated with increased levels of adenosine, a neuromodulator that has a general inhibitory effect on neural activity. The inhibition of cholinergic nuclei appears particularly relevant, as the associated decrease in cortical acetylcholine seems to cause effects of sleep deprivation on macroscopic brain activity. In general, however, the relationships between the neural effects of sleep deprivation across observation scales are poorly understood and uncovering these relationships should be a primary target in future research

Length/weight relationships for 88 species of fish encountered in the North East Atlantic

SIGLEAvailable from British Library Document Supply Centre- DSC:8208.55(43) / BLDSC - British Library Document Supply CentreGBUnited Kingdo

Power of monitoring programmes to detect decline and recovery of rare and vulnerable fish

1. Abundance trends provide key guidance when setting conservation priorities, whether indicating population decline, stability or recovery. Knowledge of the power of surveys to detect trends is essential, as the consequences of not detecting a real trend can be profound. 2. Unfortunately, some surveys have been established with no assessment of power, and others are used to study species that were not their original focus. The latter is common in the marine environment, where rare fish are monitored using catch data from surveys that target more abundant commercially fished species. 3. We calculated the power of a large-scale annual monitoring survey (the English North Sea bottom trawl survey) to detect decline and recovery of species that are vulnerable to fishing. As fisheries exploitation invariably precedes scientific investigation, the survey began after many vulnerable species had already been depleted. 4. The power of the survey to detect declines in the abundance of vulnerable species on time scales of < 10 years was low and the survey often failed to detect declines that would lead to listings under the IUCN A1 Red List criteria. Thus conservation prioritization based solely on survey data may fail to identify species at risk of regional extinction. 5. If conservation measures were effective, and vulnerable populations recovered at the maximum potential rate, 5-10 years of monitoring would often be required to detect recovery. 6. Power to detect trends in abundance was increased by developing a composite indicator that reflected trends in abundance of several vulnerable species. This indicator provided an overview of their conservation status. 7. Synthesis and applications. Consistent with the precautionary principle, conservation prioritization and management action should not depend on the statistical significance of recent abundance trends when low power is a consequence of historical depletion. If the conservation prioritization and management of rare and/or vulnerable species have to be predicated on evidence of significant declines, then higher type 1 error rates (falsely detecting a decline) should be acceptable. This is because the costs of type 1 errors are lower than those of type 2 (failure to detect a real decline)

Environmental effects of dredging on sediment nutrients, carbon and granulometry in a tropical estuary

10.1007/s10661-006-9253-2Environmental Monitoring and Assessment1271-31-13EMAS

Fish abundance with no fishing: Predictions based on macroecological theory

1. Fishing changes the structure of fish communities and the relative impacts of fishing are assessed usefully against a baseline. A comparable baseline in all regions is fish community structure in the absence of fishing. 2. The structure of unexploited communities cannot always be predicted from historical data because fisheries exploitation usually precedes scientific investigation and non-fisheries impacts, such as climate change, modify ecosystems over time. 3. We propose a method, based on macroecological theory, to predict the abundance and size-structure of an unexploited fish community from a theoretical abundance-body mass relationship (size spectrum). 4. We apply the method in the intensively fished North Sea and compare the predicted structure of the unexploited fish community with contemporary community data. 5. We suggest that the current biomass of large fishes weighing 4-16 kg and 16-66 kg, respectively, is 97.4% and 99.2% lower than in the absence of fisheries exploitation. The results suggest that depletion of large fishes due to fisheries exploitation exceeds that described in many short-term studies. 6. Biomass of the contemporary North Sea fish community (defined as all fishes with body mass 64 g-66 kg) is 38% lower than predicted in the absence of exploitation, while the mean turnover time is almost twice as fast (falls from 3.5 to 1.9 years) and 70% less primary production is required to sustain it. 7. The increased turnover time of the fish community will lead to greater interannual instability in biomass and production, complicating management action and increasing the sensitivity of populations to environmental change. 8. This size-based method based on macroecological theory may provide a powerful new tool for setting ecosystem indicator reference levels, comparing fishing impacts in different ecosystems and for assessing the relative impacts of fishing and climate change