Abstract With the development of quantitative transfer functions to relate community structure to physicochemical variables, reconstructions of past environmental conditions have been possible and have enhanced our understanding of various ecosystem processes. There are cases, however, in which this approach is not applicable, or does not provide enough information for the questions being asked. In these cases, some alternatives are to conduct experiments or to examine the distribution of species at a finer spatial resolution. These two approaches have been used as alternatives to or in conjunction with the development of transfer functions. In this review, I discuss the ways in which these two approaches are now being used in paleolimnological studies to enhance our understanding of the ecology of the species found in sediment records and thus refine interpretations of environmental change. My focus is primarily on studies that deal with establishing clearer relationships between environmental variables and the growth or distribution of organisms. I present examples of how these approaches have been integrated in a variety of studies, including those designed to: (1) refine and enhance reconstructions that are based on transfer functions; (2) develop new paleolimnological tools to reconstruct environmental change; (3) explore mechanistic links in the relationships between organisms and commonly reconstructed environmental variables; and (4) pose and test hypotheses based on patterns in the sediment record. These cases demonstrate that the use of these approaches was essential to clarify species-environment relationships as well as lake responses to disturbance. As in all disciplines, however, there are many challenges in this area of research. In particular, the quantitative integration of these approaches with the sediment record is a major challenge, due to disparate spatial and temporal scales. This research can also be quite labor-intensive, and provides information on fewer taxa than in the calibration set approach. It also requires interdisciplinary training and/or collaboration in fields that have historically been less integrated, hence they may require greater effort. These issues may hinder the use of these approaches because of the perceived difficulty. I discuss these challenges and address possible solutions
