The coevolutionary dynamics of lytic viruses and microbes with CRISPR-Cas immunity exhibit alternations between sustained host control of viral proliferation and major viral epidemics in previous computational models. These alternating dynamics have yet to be observed in other host-pathogen systems. Here, we address the breakdown of control and transition to large outbreaks with a stochastic eco-evolutionary model. We establish the role of host density-dependent competition in punctuated virus-driven succession and associated diversity trends that concentrate escape pathways during control phases. Using infection and escape networks, we derive the viral emergence probability whose fluctuations of increasing size and frequency characterize the approach to large outbreaks. We explore alternation probabilities as a function of non-dimensional parameters related to the probability of viral escape and host competition. Our results demonstrate how emergent feedbacks between host competition and viral diversification render the host immune structure fragile, potentiating a dynamical transition to large epidemics.

We investigate how the Helobdella spp. freshwater leeches capture and consume Lumbriculus variegatus blackworms despite the blackworm\'s ultrafast helical swimming escape reflex and ability to form large tangled \'blobs\'. We describe our discovery of a unique spiral \'entombment\' strategy used by these leeches to overcome the blackworms\' active and collective defenses. Unlike their approach to less reactive and solitary prey like mollusks, where leeches simply attach and suck, Helobdella leeches employ this spiral entombment strategy specifically adapted for blackworms. Our findings highlight the complex interactions between predator and prey in freshwater ecosystems, providing insights into ecological adaptability and predator-prey dynamics.

Dispersal evolution modifies diverse spatial processes, such as range expansions or biological invasions of single species, but we are currently lacking a realistic vision for metacommunities. Focusing on antagonistic species interactions, we review existing theory of dispersal evolution between natural enemies, and explain how this might be relevant for classic themes in host-parasite evolutionary ecology, namely virulence evolution or local adaptation. Specifically, we highlight the importance of considering the simultaneous (co)evolution of dispersal and interaction traits. Linking such multi-trait evolution with reciprocal demographic and epidemiological feedbacks might change basic predictions about coevolutionary processes and spatial dynamics of interacting species. Future challenges concern the integration of system-specific disease ecology or spatial modifiers, such as spatial network structure or environmental heterogeneity.

A coastal predator-prey system, juvenile green crabs (Carcinus maenas) preying upon juvenile hard clams (Mercenaria mercenaria), was used to explore the link between crab predation rates and clam density and small-scale distribution patterns. The channel working area of a racetrack flume was adapted to form a sedimentary arena in a flowing seawater system (5 cm s-1) to assess crab predation rates in relation to clam density and distribution patterns (clams clustered in one patch vs two nearby vs two farther apart). The trials detected significant differences in relation to clam initial density and distribution with strong (∼50%) declines in clam mortality levels among spatial arrangements (one patch > two nearby > two farther apart). Feeding of clams was associated with the time taken by crabs to handle the first clam (first patch), and the frequency of three distinct types of crab behavior (eating, resting, and searching). Altogether these results suggest that small-scale changes in number and distribution of juvenile clams matter and may have unexpectedly strong effects on the outcome of predator-prey interactions.

Acoustic tags fitted with predation sensors, which trigger following ingestion by piscivorous predators, were used to compare direct predation rates during downstream migration (out-migration) of potamodromous (freshwater) brown trout (Salmo trutta L.) parr from their natal river into a large freshwater lake system during spring and autumn. Thirty-eight spring migrants were tagged across two study years (2021 and 2022) of which 13 individuals (34%) were predated. By contrast 40 autumn migrants were tagged (2020 and 2021) of which three individuals (7.5%) experienced predation. The overall predation loss rate for spring migrants was 0.342% day-1 and was 0.075% day-1 for autumn migrants. Most predation events during spring (77%) occurred within the lower river before tagged fish entered the lake, whilst no predation events were recorded within the river in the autumn. Predation events were significantly linked to tagging season (spring or autumn), with the probability of tags remaining untriggered (as a proxy for survival) being higher 93% (95% confidence interval [CI] [87%, 100%]) in autumn than in spring 66% (95% CI [53%, 83%]). The spring migration periods showed significantly lower river discharge (0.321 m3 /s mean daily discharge, April 1 to May 31) to those measured during autumn (1.056 m3 /s mean daily discharge, October 1 to November 30) (Mann-Whitney U-test, U = 1149, p < 0.001). Lower flows, clearer water, and longer sojourn in the river may have contributed to greater predation losses in the spring relative to the autumn.

Outside of the laboratory, animals behave in spaces where they can transition between open areas and coverage as they interact with others. Replicating these conditions in the laboratory can be difficult to control and record. This has led to a dominance of relatively simple, static behavioral paradigms that reduce the ethological relevance of behaviors and may alter the engagement of cognitive processes such as planning and decision-making. Therefore, we developed a method for controllable, repeatable interactions with others in a reconfigurable space. Mice navigate a large honeycomb lattice of adjustable obstacles as they interact with an autonomous robot coupled to their actions. We illustrate the system using the robot as a pseudo-predator, delivering airpuffs to the mice. The combination of obstacles and a mobile threat elicits a diverse set of behaviors, such as increased path diversity, peeking, and baiting, providing a method to explore ethologically relevant behaviors in the laboratory.

Tooth-marked bones provide important evidence for feeding choices made by extinct carnivorous animals. In the case of the dinosaurs, most bite traces are attributed to the large and robust osteophagous tyrannosaurs, but those of other large carnivores remain underreported. Here we report on an extensive survey of the literature and some fossil collections cataloging a large number of sauropod bones (68) from the Upper Jurassic Morrison Formation of the USA that bear bite traces that can be attributed to theropods. We find that such bites on large sauropods, although less common than in tyrannosaur-dominated faunas, are known in large numbers from the Morrison Formation, and that none of the observed traces showed evidence of healing. The presence of tooth wear in non-tyrannosaur theropods further shows that they were biting into bone, but it remains difficult to assign individual bite traces to theropod taxa in the presence of multiple credible candidate biters. The widespread occurrence of bite traces without evidence of perimortem bites or healed bite traces, and of theropod tooth wear in Morrison Formation taxa suggests preferential feeding by theropods on juvenile sauropods, and likely scavenging of large-sized sauropod carcasses.

A central debate in ecology has been the long-running discussion on the role of apex predators in affecting the abundance and dynamics of their prey. In terrestrial systems, research has primarily relied on correlational approaches, due to the challenge of implementing robust experiments with replication and appropriate controls. A consequence of this is that we largely suffer from a lack of mechanistic understanding of the population dynamics of interacting species, which can be surprisingly complex. Mechanistic models offer an opportunity to examine the causes and consequences of some of this complexity. We present a bioenergetic mechanistic model of a tritrophic system where the primary vegetation resource follows a seasonal growth function, and the herbivore and carnivore species are modeled using two integral projection models (IPMs) with body mass as the phenotypic trait. Within each IPM, the demographic functions are structured according to bioenergetic principles, describing how animals acquire and transform resources into body mass, energy reserves, and breeding potential. We parameterize this model to reproduce the population dynamics of grass, elk, and wolves in northern Yellowstone National Park (USA) and investigate the impact of wolf reintroduction on the system. Our model generated predictions that closely matched the observed population sizes of elk and wolf in Yellowstone prior to and following wolf reintroduction. The introduction of wolves into our basal grass-elk bioenergetic model resulted in a population of 99 wolves and a reduction in elk numbers by 61% (from 14,948 to 5823) at equilibrium. In turn, vegetation biomass increased by approximately 25% in the growing season and more than threefold in the nongrowing season. The addition of wolves to the model caused the elk population to switch from being food-limited to being predator-limited and had a stabilizing effect on elk numbers across different years. Wolf predation also led to a shift in the phenotypic composition of the elk population via a small increase in elk average body mass. Our model represents a novel approach to the study of predator-prey interactions, and demonstrates that explicitly considering and linking bioenergetics, population demography and body mass phenotypes can provide novel insights into the mechanisms behind complex ecosystem processes.

A decision model is developed by adopting two control techniques, combining cultural methods and pesticides in a hybrid approach. To control the adverse effects in the long term and to be able to evaluate the extensive use of pesticides on the environment and nearby ecosystems, the novel decision model assumes the use of pesticides only in an emergency situation. We, therefore, formulate a rice-pest-control model by rigorously modelling a rice-pest system and including the decision model and control techniques. The model is then extended to become an optimal control system with an objective function that minimizes the annual losses of rice by controlling insect pest infestations and simultaneously reduce the adverse impacts of pesticides on the environment and nearby ecosystems. This rice-pest-control model is verified by analysis, obtains the necessary conditions for optimality, and confirms our main results numerically. The rice-pest system is verified by stability analysis at equilibrium points and shows transcritical bifurcations indicative of acceptable thresholds for insect pests to demonstrate the pest control strategy.

Understanding community responses to climate is critical for anticipating the future impacts of global change. However, despite increased research efforts in this field, models that explicitly include important biological mechanisms are lacking. Quantifying the potential impacts of climate change on species is complicated by the fact that the effects of climate variation may manifest at several points in the biological process. To this end, we extend a dynamic mechanistic model that combines population dynamics, such as species interactions, with species redistribution by allowing climate to affect both processes. We examine their relative contributions in an application to the changing biomass of a community of eight species in the Gulf of Maine using over 30 years of fisheries data from the Northeast Fishery Science Center. Our model suggests that the mechanisms driving biomass trends vary across space, time, and species. Phase space plots demonstrate that failing to account for the dynamic nature of the environmental and biologic system can yield theoretical estimates of population abundances that are not observed in empirical data. The stock assessments used by fisheries managers to set fishing targets and allocate quotas often ignore environmental effects. At the same time, research examining the effects of climate change on fish has largely focused on redistribution. Frameworks that combine multiple biological reactions to climate change are particularly necessary for marine researchers. This work is just one approach to modeling the complexity of natural systems and highlights the need to incorporate multiple and possibly interacting biological processes in future models.