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Abstract Dopamine has been implicated in circadian timing underlying the food entrainable oscillator (FEO) circuitry and overexpression of the dopamine D2 receptor (D2R) in the striatum has been reported to reduce motivation to obtain food rewards in operant tasks. In the present study, we explored both of these mechanisms by examining food anticipatory activity (FAA) in dopamine D2 receptor‐overexpressing (D2R‐OE) mice under various durations of food availability. First, we noted that at baseline, there were no differences between D2R‐OEmice and their littermates in activity level, food intake, and body weight or in circadian activity. Under conditions of very restricted food availability (4 or 6 hr), both genotypes displayedFAA. In contrast, under 8‐hr food availability, control mice showedFAA, but D2R‐OEmice did not. Normalization of D2R by administration of doxycycline, a tetracycline analogue, rescuedFAAunder 8‐hr restricted food. We next tested for circadian regulation ofFAA. When given ad libitum access to food, neither D2R‐OEnor controls were active during the daytime. However, after an interval of food restriction, all mice showed elevated locomotor activity at the time of previous food availability in the day, indicating circadian timing of anticipatory activity. In summary, motivation is reduced in D2R‐OEmice but circadian timing behavior is not affected. We conclude that an increase in striatal D2R reducesFAAby modulating motivation and not by acting on a clock mechanism.
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Signal from the noise: model‐based interpretation of variable correspondence between active and passive samplers
Abstract Combining information from active and passive sampling of mobile animals is challenging because active‐sampling data are affected by limited detection of rare or sparse taxa, while passive‐sampling data reflect both density and movement. We propose that a model‐based analysis allows information to be combined between these methods to interpret variation in the relationship between active estimates of density and passive measurements of catch per unit effort to yield novel information on activity rates (distance/time). We illustrate where discrepancies arise between active and passive methods and demonstrate the model‐based approach with seasonal surveys of fish assemblages in the Florida Everglades, where data are derived from concurrent sampling with throw traps, an enclosure‐type sampler producing point estimates of density, and drift fences with unbaited minnow traps that measure catch per unit effort (CPUE). We compared incidence patterns generated by active and passive sampling, used hierarchical Bayesian modeling to quantify the detection ability of each method, characterized interspecific and seasonal variation in the relationship between density and passively measuredCPUE, and used a predator encounter‐rate model to convert variableCPUE–density relationships into ecological information on activity rates. Activity rate information was used to compare interspecific responses to seasonal hydrology and to quantify spatial variation in non‐native fish activity. Drift fences had higher detection probabilities for rare and sparse species than throw traps, causing discrepancies in the estimated spatial distribution of non‐native species from passively measuredCPUEand actively measured density. Detection probability of the passive sampler, but not the active sampler, varied seasonally with changes in water depth. The relationship betweenCPUEand density was sensitive to fluctuating depth, with most species not having a proportional relationship betweenCPUEand density until seasonal declines in depth. Activity rate estimates revealed interspecific differences in response to declining depths and identified locations and species with high rates of activity. We propose that variation in catchability from methods that passively measureCPUEcan be sources of ecological information on activity. We also suggest that model‐based combining of data types could be a productive approach for analyzing correspondence of incidence and abundance patterns in other applications.
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- PAR ID:
- 10445298
- Publisher / Repository:
- Wiley Blackwell (John Wiley & Sons)
- Date Published:
- Journal Name:
- Ecosphere
- Volume:
- 10
- Issue:
- 9
- ISSN:
- 2150-8925
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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