Rethinking trophic niches: Speed and body mass colimit prey space of mammalian predators

1. Realized trophic niches of predators are often characterized along a one‐dimensional range in predator–prey body mass ratios. This prey range is constrained by an “energy limit” and a “subdue limit” toward small and large prey, respectively. Besides these body mass ratios, maximum speed is an additional key component in most predator–prey interactions.
2. Here, we extend the concept of a one‐dimensional prey range to a two‐dimensional prey space by incorporating a hump‐shaped speed‐body mass relation. This new “speed limit” additionally constrains trophic niches of predators toward fast prey.
3. To test this concept of two‐dimensional prey spaces for different hunting strategies (pursuit, group, and ambush predation), we synthesized data on 63 terrestrial mammalian predator–prey interactions, their body masses, and maximum speeds.
4. We found that pursuit predators hunt smaller and slower prey, whereas group hunters focus on larger but mostly slower prey and ambushers are more flexible. Group hunters and ambushers have evolved different strategies to occupy a similar trophic niche that avoids competition with pursuit predators. Moreover, our concept suggests energetic optima of these hunting strategies along a body mass axis and thereby provides mechanistic explanations for why there are no small group hunters (referred to as “micro‐lions”) or mega‐carnivores (referred to as “mega‐cheetahs”).
5. Our results demonstrate that advancing the concept of prey ranges to prey spaces by adding the new dimension of speed will foster a new and mechanistic understanding of predator trophic niches and improve our predictions of predator–prey interactions, food web structure, and ecosystem functions.

     

Times for recovery from cold-torpor in the Queensland fruit fly Dacus tryoni: the relation to temperature during and after chilling

Recovery time after experience of a given minimum temperature below torpor threshold is related to the value of that minimum, the length of time spent at that minimum, and the temperature prevailing during the recovery period above torpor threshold. A model can predict recovery time for flies experiencing a given temperature fluctuation if the length of time spent at the minimum is expressed as a proportion of LE₅₀ at that minimum.The model has applications in defining the optimal protocol for chilling insects for use in the Sterile Insect Release Method. The model was confirmed by experiments showing that it is likely that flies will recover from non-lethal frosts before ant predators become active.

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Résumé Le temps de récupération après avoir subi une température minimal située au-dessous du seuil d'engourdissement dépend de la valeur de ce minimum, du temps passé à ce minimum, et de la température au-dessus du seuil d'engourdissement pendant la période de récupération. Un modèle mathématique permet d'estimer le temps de récupération après avoir subi une chute de température déterminée, en fonction du temps passé au minimum thermique exprimé comme une fraction du LE₅₀ (temps nécessaire pour tuer 50% des mouches) à ce minimum.Ce modèle s'est trouvé étayé par des observations montrant qu'il est probable que les mouches se remettent des gelées sublétales avant la reprise d'activité des fourmis prédatrices. Ce modèle peut être utilisé pour définir les conditions optimales de refroidissement des insectes utilisés lors de la libération d'individus stériles.

     

Exclosure fences around nests of imperiled Florida Grasshopper Sparrows reduce rates of predation by mammals

Increasing nest survival by excluding predators is a goal of many bird conservation programs. However, new exclosure projects should be carefully evaluated to assess the potential risks of disturbance. We tested the effectiveness of predator exclosure fences (hereafter, fences) for nests of critically endangered Florida Grasshopper Sparrows (Ammodramus savannarum floridanus) at a dry prairie site (Three Lakes; 2015–2018) and a pasture site (the Ranch; 2015–2016) in Osceola County, Florida, USA. We installed fences at nests an average of 8 days after the start of incubation, and nest abandonment after fence installation was rare (2 of 149 installations). Predation was the leading cause of failure for unfenced nests at both sites (48–73%). At Three Lakes, nest cameras revealed that mammals and snakes were responsible for 61.5% and 38.5% of predation events, respectively, at unfenced nests. Fences reduced the daily probability of predation (0.016 for fenced nests vs. 0.074 for unfenced nests). The probability that a fenced nest would survive from discovery to fledging was more than double that of unfenced nests (60.4% vs. 27.7%). However, we found no difference in daily nest survival at the Ranch between the year before nests were fenced (2015; 0.874) and the year when all but one nest were fenced (2016; 0.867) because red imported fire ants (Solenopsis invicta) were responsible for 86% of predation events at fenced nests at the Ranch. The use of cameras at fenced nests revealed that site‐specific differences in nest predators explained variation in fence efficiency between sites. Our fence design may be useful for other species of grassland birds, but site‐specific predator communities and species‐specific response of target bird species to fences should be assessed before installing fences at other sites.     

Predator detection and avoidance by starlings under differing scenarios of predation risk

Practically all animals must find food while avoiding predators.An individual's perception of predation risk may depend on manyfactors, such as distance to refuge and group size, but it isunclear whether individuals respond to different factors ina similar manner. We tested whether flocks of foraging starlingsresponded in the same way to an increased perception of predationrisk by assessing three factors: (1) neighbor distances, (2)habitat obstruction, and (3) recent exposure to a predator.We found that in all three scenarios of increased risk, starlingsreduced their interscan intervals (food-searching bouts), whichincreased the frequency of their vigilance periods. We thenexamined how one of these factors, habitat obstruction, affectedescape speed by simulating an attack with a model predator.Starlings were slower to respond in visually obstructed habitats(long grass swards) and slower when they had their head downin obstructed habitats than when they had their head down inopen habitats. In addition, reaction times were quicker whenstarlings could employ their peripheral fields of vision. Ourresults demonstrate that different sources of increased riskcan generate similar behavioral responses within a species.The degree of visibility in the physical and social environmentaffects both the actual and perceived risk of predation.     

Pore-forming Activity of the Escherichia coli Type III Secretion System Protein EspD

Enterohemorrhagic Escherichia coli is a causative agent of gastrointestinal and diarrheal diseases. Pathogenesis associated with enterohemorrhagic E. coli involves direct delivery of virulence factors from the bacteria into epithelial cell cytosol via a syringe-like organelle known as the type III secretion system. The type III secretion system protein EspD is a critical factor required for formation of a translocation pore on the host cell membrane. Here, we show that recombinant EspD spontaneously integrates into large unilamellar vesicle (LUV) lipid bilayers; however, pore formation required incorporation of anionic phospholipids such as phosphatidylserine and an acidic pH. Leakage assays performed with fluorescent dextrans confirmed that EspD formed a structure with an inner diameter of ∼2.5 nm. Protease mapping indicated that the two transmembrane helical hairpin of EspD penetrated the lipid layer positioning the N- and C-terminal domains on the extralumenal surface of LUVs. Finally, a combination of glutaraldehyde cross-linking and rate zonal centrifugation suggested that EspD in LUV membranes forms an ∼280–320-kDa oligomeric structure consisting of ∼6–7 subunits.