Authors:R. Okada, H. Ikeno, T. Kimura, Mizue Ohashi, H. Aonuma, and E. Ito
A honeybee informs her nestmates of the location of a flower by doing a waggle dance. The waggle dance encodes both the direction of and distance to the flower from the hive. To reveal how the waggle dance benefits the colony, we created a Markov model of bee foraging behavior and performed simulation experiments by incorporating the biological parameters that we obtained from our own observations of real bees as well as from the literature. When two feeders were each placed 400 m away from the hive in different directions, a virtual colony in which honeybees danced and correctly transferred information (a normal, real bee colony) made significantly greater numbers of successful visits to the feeders compared to a colony with inaccurate information transfer. Howerer, when five feeders were each located 400 m from the hive, the inaccurate information transfer colony performed better than the normal colony. These results suggest that dancing’s ability to communicate accurate information depends on the number of feeders. Furthermore, because non-dancing colonies always made significantly fewer visits than those two colonies, we concluded that dancing behavior is beneficial for hives’ ability to visit food sources.
With continuing proliferation of human influences on landscapes, there is mounting incentive to undertake quantification of relationships between spatial patterns of human populations and vegetation. In considering such quantification, it is apparent that investigations must be conducted at different scales and in a comparative manner across regions. At the broader scales it becomes necessary to utilize remote sensing of vegetation for comparative studies against map referenced census data. This paper explores such an approach for the urbanized area in the Tokyo vicinity. Vegetation is represented by the normalized difference vegetation index (NDVI) as determined from data acquired by the thematic mapper (TM) sensor of the Landsat satellite. Sparseness of vegetation is analyzed in relation to density of human residence, first by regression analysis involving stratified distance zones and then by the recent echelon approach for characterization of surfaces. Echelons reveal structural organization of surfaces in an objective and explicit manner. The virtual surface determined by census data collected on a grid is shown to have structural correspondence with the surface representing vegetation greenness as reflected in magnitude of NDVI values computed from red and infrared bands of image data.
Sampling effort in pitfall trapping sessions is routinely calculated as a product of trap numbers and time period, expressed in units of trap-days or trap-weeks. This assumes that these two components contribute equally to the catch, so that the catch from 2n traps run for z days should be equivalent to the catch of n traps run for 2z days. We tested this equivalence relationship by comparing two pitfall trapping sessions, representing an identical trapping effort, performed in the same habitat (an apple orchard in Hungary), using the same pitfall trapping arrangement. The Time Series session had 20 traps operating for 20 weeks (400 trap-weeks), while the Spatial Series session had 100 traps operating for 4 weeks (400 trap-weeks). The Time Series session caught 1265 individuals of 44 species, while the Spatial Series session had fewer (757) individuals but 52 species. The virtual structure of the two carabid assemblages was different, although the major species were the same. Rarefaction curves clearly show that the Spatial Series indicated the presence of a significantly more species-rich ground beetle assemblage than the Time Series. The “common currency” for trapping effort needs to be re-examined because its two components, number of traps and length of operation do not contribute to the final catch in the same way. This has an important consequence for the design of biodiversity monitoring: trapping effort allocation for monitoring may be better when the number of traps is at the possible maximum and the time of sampling shortened rather than the other way around.
global directory of public herbaria and associated staff. New York Botanical Garden's Virtual Herbarium
Vězda, A. (1964):
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