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Abstract AimPatterns of genetic diversity within species’ ranges can reveal important insights into effects of past climate on species’ biogeography and current population dynamics. While numerous biogeographic hypotheses have been proposed to explain patterns of genetic diversity within species’ ranges, formal comparisons and rigorous statistical tests of these hypotheses remain rare. Here, we compared seven hypotheses for their abilities to describe the geographic pattern of two metrics of genetic diversity in balsam poplar (Populus balsamifera), a northern North American tree species. LocationNorth America. TaxonBalsam poplar (Populus balsamiferaL.). MethodsWe compared seven hypotheses, representing effects of past climate and current range position, for their ability to describe the geographic pattern of expected heterozygosity and per cent polymorphic loci across 85 populations of balsam poplar. We tested each hypothesis using spatial and non‐spatial least‐squares regression to assess the importance of spatial autocorrelation on model performance. ResultsWe found that both expected heterozygosity and per cent polymorphic loci could best be explained by the current range position and genetic structure of populations within the contemporary range. Genetic diversity showed a clear gradient of being highest near the geographic and climatic range centre and lowest near range edges. Hypotheses accounting for the effects of past climate (e.g. past climatic suitability, distance from the southern edge), in contrast, had comparatively little support. Model ranks were similar among spatial and non‐spatial models, but residuals of all non‐spatial models were significantly autocorrelated, violating the assumption of independence in least‐squares regression. Main conclusionsOur work adds strong support for the “Central‐Periphery Hypothesis” as providing a predictive framework for understanding the forces structuring genetic diversity across species’ ranges, and illustrates the value of applying a robust comparative model selection framework and accounting for spatial autocorrelation when comparing biogeographic models of genetic diversity.