Beyea, Jan, Mitschka Hartley, and Michael Burger

Use of meta-analysis to assign bird species to assemblages indicative of responsiveness to logging intensity in northeastern, hardwood forests.  Consulting in the Public Interest, Lambertville, NJ, 08520 (JB); National Audubon Society of New York, Cornell Laboratory of Ornithology, 159 Sapsucker Woods Road, Ithaca, NY, 14850
 (MH, MB)

Presented at The Wildlife Society 10th Annual Conference, Burlington, Vt., September, 2003

To assign bird species to assemblages associated with responses to forest harvest intensity, we performed a meta-analysis on studies carried out in Northern hardwoods in the northeastern US.  Five suitable studies were located in the peer-reviewed literature relating bird abundance to residual stand basal area.  Supplemental information was obtained from three of the studies’ authors.  The measure of effect was taken as the correlation coefficient, r, between bird count and residual stand basal area.  A composite r-value and composite r-variance for each of 99 bird species was obtained using a variety of weighting methods that attempted to account for both within- and across-study variance.  Composite variances were used to compute tests of statistical significance.  Sixteen bird species with an r-value sufficiently positive to meet a significance test (alpha=0.1) were assigned to the “mature” forest assemblage.  Thirty bird species with an r-value sufficiently negative were assigned to the “early successional” assemblage.  The remaining fifty bird species were assigned to the “generalist” category.  Assignments to assemblages were insensitive to the weighting and variance methods used for 69 out of 99 bird species considered.  For 21 of the remaining 30, the two methods considered most likely to be valid produced the same assemblage assignments.  To facilitate future meta-analyses, authors should include measures of effect in their publications, such as correlation coefficients or chi-square values, for all species detected regardless of their significance value.  It would also be useful to include intercepts and slopes derived from univariate regressions.