Effects of Degraded Optical Conditions on Behavioural Responses to Alarm Cues in a Freshwater Fish

Prey organisms often use multiple sensory cues to gain reliable information about imminent predation threat. In this study we test if a freshwater fish increases the reliance on supplementary cues when the reliability of the primary cue is reduced. Fish commonly use vision to evaluate predation threat, but may also use chemical cues from predators or injured conspecifics. Environmental changes, such as increasing turbidity or water colour, may compromise the use of vision through changes in the optical properties of water. In an experiment we tested if changes in optical conditions have any effects on how crucian carp respond to chemical predator cues. In turbidity treatments we added either clay or algae, and in a brown water colour treatment we added water with a high humic content. We found that carp reduced activity in response to predator cues, but only in the turbidity treatments (clay, algae), whereas the response in the brown water treatment was intermediate, and not significantly different from, clear and turbid water treatments. The increased reliance on chemical cues indicates that crucian carp can compensate for the reduced information content from vision in waters where optical conditions are degraded. The lower effect in brown water may be due to the reduction in light intensity, changes in the spectral composition (reduction of UV light) or to a change in chemical properties of the cue in humic waters

Satellite-based terrestrial production efficiency modeling

Production efficiency models (PEMs) are based on the theory of light use efficiency (LUE) which states that a relatively constant relationship exists between photosynthetic carbon uptake and radiation receipt at the canopy level. Challenges remain however in the application of the PEM methodology to global net primary productivity (NPP) monitoring. The objectives of this review are as follows: 1) to describe the general functioning of six PEMs (CASA; GLO-PEM; TURC; C-Fix; MOD17; and BEAMS) identified in the literature; 2) to review each model to determine potential improvements to the general PEM methodology; 3) to review the related literature on satellite-based gross primary productivity (GPP) and NPP modeling for additional possibilities for improvement; and 4) based on this review, propose items for coordinated research

ICAR: endoscopic skull‐base surgery

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Biophysical interactions in tropical agroforestry systems

sequential systems, simultaneous systems Abstract. The rate and extent to which biophysical resources are captured and utilized by the components of an agroforestry system are determined by the nature and intensity of interac-tions between the components. The net effect of these interactions is often determined by the influence of the tree component on the other component(s) and/or on the overall system, and is expressed in terms of such quantifiable responses as soil fertility changes, microclimate modification, resource (water, nutrients, and light) availability and utilization, pest and disease incidence, and allelopathy. The paper reviews such manifestations of biophysical interactions in major simultaneous (e.g., hedgerow intercropping and trees on croplands) and sequential (e.g., planted tree fallows) agroforestry systems. In hedgerow intercropping (HI), the hedge/crop interactions are dominated by soil fertility improvement and competition for growth resources. Higher crop yields in HI than in sole cropping are noted mostly in inherently fertile soils in humid and subhumid tropics, and are caused by large fertility improvement relative to the effects of competition. But, yield increases are rare in semiarid tropics and infertile acid soils because fertility improvement does not offse

Comparison of uncertainty sources for climate change impacts: flood frequency in England

This paper investigates the uncertainty in the impact of climate change on flood frequency in England, through the use of continuous simulation of river flows. Six different sources of uncertainty are discussed: future greenhouse gas emissions; Global Climate Model (GCM) structure; downscaling from GCMs (including Regional Climate Model structure); hydrological model structure; hydrological model parameters and the internal variability of the climate system (sampled by applying different GCM initial conditions). These sources of uncertainty are demonstrated (separately) for two example catchments in England, by propagation through to flood frequency impact. The results suggest that uncertainty from GCM structure is by far the largest source of uncertainty. However, this is due to the extremely large increases in winter rainfall predicted by one of the five GCMs used. Other sources of uncertainty become more significant if the results from this GCM are omitted, although uncertainty from sources relating to modelling of the future climate is generally still larger than that relating to emissions or hydrological modelling. It is also shown that understanding current and future natural variability is critical in assessing the importance of climate change impacts on hydrology