Sources of variation in haematocrit in birds

The validity of the haematocrit or packed cell volume as an indicator of condition in wild birds has recently been questioned. We reviewed over 300 published papers on haematocrit values for wild birds. These studies show that changes in haematocrit could be caused by a number of different natural factors that include age, sex, geographical elevation, energy expenditure, parasitism, nutrition and genetics. Haematocrit also increased with age from hatching, due to increased erythropoiesis, so that adult birds generally have greater haematocrit values than nestlings or juveniles. Haematocrit values were either independent of elevation or increased with elevation. A meta-analysis of 36 studies showed no difference in haematocrit between the sexes. Relationships between haematocrit value and both energy expenditure and parasitic infection vary between studies. In temperate climates, haematocrit tended to be higher in winter than in summer, which may be due to dehydration or increased oxygen demand caused by thermogenesis, moult or acquisition of reproductive status. Our review indicates that the use of haematocrit as a sole indicator of condition or health could lead to incorrect conclusions if natural factors that can affect haematocrit are not taken into consideration.     

Statistical Confusion Among Graduate Students: Sickness or Symptom?

Abstract: Statistics is one of the most important yet difficult subjects for many ecology and wildlife graduate students to learn. Insufficient knowledge about how to conduct quality science and the ongoing debate about the relative value of competing statistical ideologies contribute to uncertainties among graduate students regarding which statistical tests are most appropriate. Herein, we argue that increased education of the available statistical tests alone is unlikely to ameliorate the problem. Instead, we suggest that statistical uncertainties among graduate students are a secondary symptom of a larger problem. We believe the root cause lies in the lack of education on how to conduct science as an integrated process from hypothesis creation through statistical analysis. We argue that if students are taught to think about how each step of the process will affect all other steps, many statistical uncertainties will be avoided.     

Fine scale genetic structure in the wild ancestor of maize (Zea mays ssp. parviglumis)

Analysis of fine scale genetic structure in continuous populations of outcrossing plant species has traditionally been limited by the availability of sufficient markers. We used a set of 468 SNPs to characterize fine‐scale genetic structure within and between two dense stands of the wild ancestor of maize, teosinte (Zea mays ssp. parviglumis). Our analyses confirmed that teosinte is highly outcrossing and showed little population structure over short distances. We found that the two populations were clearly genetically differentiated, although the actual level of differentiation was low. Spatial autocorrelation of relatedness was observed within both sites but was somewhat stronger in one of the populations. Using principal component analysis, we found evidence for significant local differentiation in the population with stronger spatial autocorrelation. This differentiation was associated with pronounced shifts in the first two principal components along the field. These shifts corresponded to changes in allele frequencies, potentially due to local topographical features. There was little evidence for selection at individual loci as a contributing factor to differentiation. Our results demonstrate that significant local differentiation may, but need not, co‐occur with spatial autocorrelation of relatedness. The present study represents one of the most detailed analyses of local genetic structure to date and provides a benchmark for future studies dealing with fine scale patterns of genetic diversity in natural plant populations.