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The importance and strength of density dependence continues to engender debate because of its central importance to population dynamics and regulation. Here, we show how confounding effects of site quality can mask strong effects of density dependence. In particular, we explore spatiotemporal variation and covariation among (1) densities of newly settled coral reef fish (Thalassoma hardwicke), (2) environmental characteristics, and (3) the strength of density-dependent mortality. Environmental features of patch reefs were spatially and temporally variable and influenced density-dependent survival. Higher- quality sites (i.e., reefs possessing features that yield greater numbers of recruits at any given settlement level) received greater settlement, and this relationship masked the op- eration of density dependence when variation in quality among sites (or times) was not distinguished (a common approach in many observational studies of density dependence). Our work illustrates how spatiotemporal covariation in settlement density and site quality can obscure patterns of density dependence at larger scales, contributing to a phenomenon we call ''cryptic density dependence.'' Acknowledging patterns and consequences of co- variance may alter the way we study population dynamics, especially of marine organisms, where the link between processes that affect settlement and post-settlement survival remains relatively poorly understood.

Multiple processes typically influence patterns of abundance. Despite this widely accepted view, many studies continue to approach ecological questions from a single-factor, or, at most, a two-factor perspective. Here, I evaluate the consequences of considering, separately and jointly, the effects of three factors (larval settlement, reef resources, and postsettlement losses) on spatial patterns of abundance of a marine reef fish, the six bar wrasse (Thalassoma hardwicke). Using correlational methods commonly employed in single-factor studies, I show that local patterns of abundance of juvenile wrasse could be attributed entirely to either (1) patterns of abundance of settlement habitat, or (2) patterns of larval settlement. This result occurred because habitat and presumed larval delivery covaried in space. I manipulated abundance of settlement habitat in a field experiment to uncouple this covariation and found subsequent settlement to be simultaneously influenced by both factors. However, joint effects of habitat and settlement failed to account for patterns of abundance of juvenile wrasse without also considering a third factor - postsettlement losses - which were density-dependent and substantially modified patterns of settlement. These results illustrate (1) how multifactorial explanations may be falsely refuted when incomplete sets of multiple factors are considered, and (2) how single-factor explanations may misrepresent underlying multifactorial causation of ecological patterns. Uncovering the interactive role of multiple factors in determining ecological patterns of interest requires a shift from single-factor approaches to more pluralistic perspectives.

Multiple processes can act together to determine abundance of organisms and structure of communities. Recently, appreciation of this fact has motivated development of conceptual and statistical frameworks that quantitatively assess the relative importance of multiple causal factors. However, little consideration has been given to variability in the "importance" of processes through space and time (i.e. robustness), which represents another facet of a process's importance. Here, I focused on populations of a coral reef fish (Thalassoma hardwicke) and used an existing analytical method to assess the relative importance of initial population inputs (larval supply) and subsequent juvenile mortality in determining the average abundances of juvenile fish populations in different locations and times. The relative importance of processes varied significantly both temporally and spatially across a range of scales, and indicate a need for future assessments of relative importance to incorporate this variability.