Aim The aim of this study is to answer the questions: (1) do small organisms disperse farther than large, or vice versa; and (2) does the observed pattern differ for passive and active dispersers? These questions are central to several themes in biogeography (including microbial biogeography), macroecology, metacommunity ecology and conservation biology.Location The meta-analysis was conducted using published data collected worldwide. MethodsWe collected and analysed 795 data values in the peer-reviewed literature for direct observations of both maximal dispersal distance and mass of the dispersing organisms (e.g. seeds, not trees). Analysed taxa ranged in size from bacteria to whales. We applied macroecology analyses based on null models (using Monte Carlo randomizations) to test patterns relative to specific hypotheses. ResultsCollected dispersal distance and mass data spanned 9 and 21 orders of magnitude, respectively. Active dispersers dispersed significantly farther ( P < 0.001) and were significantly greater in mass ( P < 0.001) than passive dispersers. Overall, size matters: larger active dispersers attained greater maximum observed dispersal distances than smaller active dispersers. In contrast, passive-disperser distances were random with respect to propagule mass, but not uniformly random, in part due to sparse data available for tiny propagules. ConclusionsSize is important to maximal dispersal distance for active dispersers, but not for passive dispersers. Claims that microbes disperse widely cannot be tested by current data based on direct observations of dispersal: indirect approaches will need to be applied. Distance-mass relationships should contribute to a resolution of neutral and niche-based metacommunity theories by helping scale expectations for dispersal limitation. Also, distance-mass relationships should inform analyses of latitudinal species richness and conservation biology topics such as fragmentation, umbrella species and taxonomic homogenization.

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Parasites have been suggested to influence many aspects of host behaviour. Some of these effects may be mediated via their impact on host energy budgets. This impact may include effects on both energy intake and absorption as well as components of expenditure, including resting metabolic rate (RMR) and activity (e.g. grooming). Despite their potential importance, the energy costs of parasitism have seldom been directly quantified in a field setting. Here we pharmacologically treated female Cape ground squirrels (Xerus inauris) with anti-parasite drugs and measured the change in body composition, the daily energy expenditure (DEE) using doubly labelled water, the RMR by respirometry and the proportions of time spent looking for food, feeding, moving and grooming. Post-treatment animals gained an average 19g of fat or approximately 25kJd-1. DEE averaged 382kJd-1 prior to and 375kJd-1 post treatment (p>0.05). RMR averaged 174kJd-1 prior to and 217kJd-1 post treatment (p<0.009). Post-treatment animals spent less time looking for food and grooming, but more time on feeding. A primary impact of infection by parasites could be suppression of feeding behaviour and, hence, total available energy resources. The significant elevation of RMR after treatment was unexpected. One explanation might be that parasites produce metabolic by-products that suppress RMR. Overall, these findings suggest that impacts of parasites on host energy budgets are complex and are not easily explained by simple effects such as stimulation of a costly immune response. There is currently no broadly generalizable framework available for predicting the energetic consequences of parasitic infection.