Understanding spatial distributions: negative density-dependence in prey causes predators to trade-off prey quantity with quality

Abstract

Negative density-dependence is generally studied within a single trophic level, thereby neglecting its effect on higher trophic levels. The 'functional response' couples a predator's intake rate to prey density. Most widespread is a type II functional response, where intake rate increases asymptotically with prey density; this predicts the highest predator densities at the highest prey densities. In one of the most stringent tests of this generality to date, we measured density and quality of bivalve prey (edible cockles Cerastoderma edule) across 50 km 2 of mudflat, and simultaneously, with a novel time-of-arrival methodology, tracked their avian predators (red knots Calidris canutus). Because of negative density-dependence in the individual quality of cockles, the predicted energy intake rates of red knots declined at high prey densities (a type IV, rather than a type II functional response). Resource-selection modelling revealed that red knots indeed selected areas of intermediate cockle densities where energy intake rates were maximized given their phenotype-specific digestive constraints (as indicated by gizzard mass). Because negative densitydependence is common, we question the current consensus and suggest that predators commonly maximize their energy intake rates at intermediate prey densities. Prey density alone may thus poorly predict intake rates, carrying capacity and spatial distributions of predators.

Presence-absence of marine macrozoobenthos does not generally predict abundance and biomass

“…Recruitment events could explain the opposing signs of abundance-occupancy versus biomass-occupancy relationships that were found for M. edulis , E. leei and C. edule . For instance, in 2011 C. edule had a uniquely strong recruitment with maximum densities of almost 19,000 juveniles per square meter 38 . Across the eight years of this study, 2011 had the largest abundance and occupancy, and indeed the smallest biomass as well.…”

Mechanisms and implications of a type IV functional response for short‐term intake rate of dry matter in large mammalian herbivores

“…The shape and parameters of this relationship influence consumer–resource interactions in many ways. It largely determines the type or density of resource consumers select (Stephens & Krebs, ) and, as a result, the spatial distribution of consumer populations across the landscape (Bijleveld et al., ; Fryxell, Wilmshurst, & Sinclair, ; Prins & van Langevelde, ). The functional response also plays a central role in the dynamics of consumer–resource systems (Lafferty et al., ; Murdoch, Briggs, & Nisbet, ; Schwinning & Parsons, ).…”

Biologging Special Feature

“…A key aim of movement ecology research is to quantify and predict habitat/resource selection by animals (Arthur, Manly, McDonald, & Garner, 1996;Christ, Hoef, & Zimmerman, 2008;Johnson, 1980;Matthiopoulos et al, 2015;Moorcroft & Barnett, 2008;Rhodes, McAlpine, Lunney, & Possingham, 2005). Importantly, individual movements lead to the emergence of habitat selection and space use patterns at larger scales Johnson, 1980;Moorcroft & Lewis, 2006) and differences in habitat use between individuals may be caused by differences in the individual state (Bijleveld et al, 2016) or the external environment (sensu Nathan et al, 2008). Quantifying individual differences in behaviour is a key focus of ecological research (Bolnick et al, 2003;Lomnicki, 1988) and implicit examples for resource selection functions (RSFs) have emerged as early as Gillies et al (2006) and Hebblewhite and Merrill (2008).…”