On the determinants of census area: implications for mammalian macroecological patterns

Abstract

The aim of this study was to examine the effects of various biological factors such as body mass, trophic level, climate and geography on census area in terrestrial mammals. We also examine the effects of census area on the population density–body mass relationship. The geographic areas covered in this study include most major terrestrial biomes including taïga, desert, savanna, grassland, tropical dry forest, temperate dry forest, tropical rain forest and temperate rain forest. An extensive literature search was conducted and we compiled data on census area and body mass from 377 mammalian populations and 59 communities. Statistical analyses include linear regression, Kruskal–Wallis analysis of variance, LOWESS, and multiple regression. Overall, the regression between log census area (A) and log body mass (M) yielded a slope of 0.710, which did not differ significantly from 0.75, but it was significantly different from 1.0. The analyses also showed that the log A–log M relationship is constrained within a well‐defined space in a similar fashion to the home range–body mass relationship. When mammals were separated into trophic groups, regression lines differed significantly in their intercepts, but not in slopes. At the community level, the census area was particularly affected by the population with the largest body mass within the community. Both the number of species and number of taxa encompassed by the community were found to be correlated positively with log A (r = 0.26, P = 0.0464 and r = 0.27, P = 0.0398, respectively). Sampling of mammalian species is not usually random. Not only is census area significantly associated with the technique used to sample a given species, but it is also influenced by biological factors that have been shown previously to influence population density. Striking similarities were found between the census area–body mass relationship and the home range–body mass relationship, suggesting that investigators may sample mammalian populations over areas that actually reflect the use of space of their focal species.

Temporal and Spatial Variation in Metric Asymmetry in Skulls of Polar Bears (Ursus maritimus) from East Greenland and Svalbard

“…For all traits, the linear regression and the LOESS lines largely followed the same path (Fig. 3), which rendered the linear correlation a plausible model for the nine traits in each subgroup (Cleveland 1979, Prince & Silva 2002, Vieth et al 2003. There was a clear trend in the three significant results from the Pearson correlation analyses, as they all exhibited a negative correlation of FA over time: adult females, traits P4-M2 ( Fig.…”

“…Linear regression lines (including 95% confidence intervals) and LOESS (locally weighted scatterplot smoothing) lines were added to each scatterplot. The LOESS line was applied to allow the data to reveal its own natural pattern (Cleveland 1979, Prince & Silva 2002, Vieth et al 2003. As the LOESS line confirmed the linearity of the relationship between year of birth and FA for the nine traits, Pearson correlation analyses were performed for each sex/age group on each trait, assessing the degree to which the individuals' year of birth had a significant effect on the observed FA.…”

Body mass as a predictive variable of home‐range size among Italian mammals and birds

“…For omnivores and herbivores, food items may not necessarily occupy home ranges themselves, their presence and spatial aggregation being more strongly influenced by environmental conditions. Indirect evidence of the influence of the spatial distribution of resources in mammals' ecology can be seen in the recording of comparatively larger home ranges (Kelt & Van Vuren, 2001) and census areas (Prince & Silva, 2002) for carnivorous mammals than for herbivorous mammals of the same size.…”

A test of the mechanisms behind avian generalized individuals-area relationships

“…Engstrom & James, 1981;Smallwood, 1995; and further references cited below) as well as for mammals (e.g. Schonewald-Cox et al ., 1991;Smallwood, 1998;Smallwood & Schonewald, 1998;Silva et al ., 2001;Prince & Silva, 2002;Schaefer & Mahoney, 2003;Mayor & Schaefer, 2005).…”