Monitoring of hunting resources: population-based approach

It is recognized that the objects of the hunting economy are populations of game animals. However, there is no term “population” in current Russian legislation, the undefined expression “hunting resources” is used instead. The monitoring of the hunting resources status is currently limited by regulatory documents only to the analysis of materials based on the winter route census (WRC). This is insufficient to establish the nature of population dynamics, acquire knowledge about population cycles in different populations, and collect the data on the qualitative composition of populations and their changes over time. For hunting providers, simple methods of collecting and processing material on the qualitative composition of populations are offered. They can be carried out both during the hunting season and during the purchase of products from hunters. Systematic observations and analysis of the obtained materials will allow accumulating knowledge about a specific exploited population. Hunting providers should use different methods of registration of hunting animals to monitor exploited populations. To control registration, state game wardens can use the WRC. The state control should proceed from the confidence in the results of the registration work of hunting providers since they are those interested in the long-term use of hunting resources.

Estimating abundance, temporary emigration and the pattern of density dependence in a cyclic snowshoe hare population in Yukon, Canada

Estimates of demographic parameters based on capture-mark-recapture (CMR) methods may be biased when some individuals in the population are temporarily unavailable for capture (temporary emigration). We estimated snowshoe hare abundance, apparent survival, and probability of temporary emigration in a population of snowshoe hares (Lepus americanus Erxleben 1777) in the Yukon using Pollock’s robust design CMR model, and population density using spatially-explicit CMR models. Survival rates strongly varied among cyclic phases, seasons, and across five population cycles. We found strong evidence that temporary emigration was Markovian (i.e., non-random), suggesting that it varied among individuals that were temporary emigrant in the previous sampling period and those that were present in the sampled area. The probability of temporary emigration for individuals that were in the study area during the previous sampling occasion (γ´´) varied among cycles. Probability that individuals that were temporarily absent from the sampled area would remain temporary emigrants (γ´) showed strongly seasonal pattern, low in winter and high during summers. Snowshoe hare population density ranged from 0.017 (0.015–0.05) hares/ha to 4.43 (3.90–5.00) hares/ha and large-scale cyclical fluctuation. Autocorrelation functions and autoregressive analyses revealed that our study population exhibited statistically significant cyclic fluctuations, with a periodicity of 9-10 years.

Host in reserve: the role of common shrews (Sorex araneus) as a stable supplementary source of tick hosts in small mammal communities influenced by rodent population cycles

In recent decades, warming temperatures and changes in land use are supposed to have enabled several tick species to expand their distribution limit northwards. The progression of ticks to new areas may introduce new and emerging tick-borne pathogens as well as increase existing diseases. Aside from climatic conditions, ticks are dependent on hosts for survival, and rodents often act as important hosts for ticks and as pathogen reservoirs. At northern latitudes, rodents often undergo multi-annual population cycles, and the periodic absence of hosts may inhibit the further progression of ticks. We investigated the potential role of common shrews (Sorex araneus) to serve as a stable host source to immature life stages of a generalist tick Ixodes ricinus and a specialist tick I. trianguliceps, during decreasing abundances of bank voles (Myodes glareolus). We tested whether ticks would have a propensity to parasitize a certain host type dependent on host population size and composition in two high latitude locations in southern Norway, by comparing tick burdens on trapped animals. We found that I. ricinus larvae showed an equal propensity to parasitize both host types as the host population composition changed, but voles had a higher level of parasitism by nymphs (p< 0.004). An overall larger host population size favored the parasitism of voles by larvae (p= 0.027), but not by nymphs (p= 0.074). I. trianguliceps larvae showed a higher propensity to parasitize shrews, regardless of host population size or composition (p= 0.004), while nymphs parasitized shrews more as vole abundance increased (p= 0.002). The results indicate that common shrews may have the potential to act as a replacement host during periods of low rodent availability, but long-term observations encompassing complete rodent cycles may determine whether shrews are able to maintain tick range expansion despite low rodent availability.

Selection on Functional Response Parameters

In this chapter I show why there should be selection on traits associated with functional response parameters. I describe this using standard quantitative genetics techniques to show how a classic evolutionary arms race arises and how it depends on key features of the functional response. I suggest this arms race is more aptly described as a tug-of-war. I then show that selection on the predator and prey components of space clearance rate is synchronous for predator and prey through population cycles but alternating between predator and prey for handling time. I suggest that trade-offs, ecological pleiotropy, and phenotypic plasticity can slow natural selection on traits that influence functional response parameters.

Individual-based models

Individual-based models (IBMs, also known as agent-based models) are mechanistic models in which demographic population trends emerge from processes at the individual level. IBMs are used instead of more aggregated approaches whenever one or more of the following aspects are deemed too relevant to be ignored: intraspecific trait variation, local interactions, adaptive behaviour, and response to spatially and temporally heterogeneous environments, which often results in nonlinear feedbacks. IBMs offer a high degree of flexibility and therefore vary widely in structure and resolution, depending on the research question, system under investigation, and available data. Data used to parameterise an IBM can be divided into two categories: species and environmental data. Unlike other model types, qualitative empirical knowledge can be taken into account via probabilistic rules. IBM flexibility is often associated with higher number of parameters and hence higher uncertainty; therefore sensitivity analysis and validation are extremely important tools for analysing these models. The chapter presents three examples: a vole–mustelid model used to understand the mechanisms underlying population cycles in rodents; a wild boar–virus model to study persistence of wildlife diseases in heterogeneous landscapes; and a wild tobacco-moth caterpillar model to study emergence of delayed chemical plant defence against insect herbivores. These examples demonstrate the ability of IBMs to decipher mechanisms driving observed phenomena at the population level and their role in planning applied conservation measures. IBMs typically require more data and effort than other model types, but rewards in terms of structural realism, understanding, and decision support are high.

Agent-Based Modeling for Archaeology

To fully understand not only the past, but also the trajectories, of human societies, we need a more dynamic view of human social systems. Agent-based modeling (ABM), which can create fine-scale models of behavior over time and space, may reveal important, general patterns of human activity. Agent-Based Modeling for Archaeology is the first ABM textbook designed for researchers studying the human past. Appropriate for scholars from archaeology, the digital humanities, and other social sciences, this book offers novices and more experienced ABM researchers a modular approach to learning ABM and using it effectively. Readers will find the necessary background, discussion of modeling techniques and traps, references, and algorithms to use ABM in their own work. They will also find engaging examples of how other scholars have applied ABM, ranging from the study of the intercontinental migration pathways of early hominins, to the weather–crop–population cycles of the American Southwest, to the trade networks of Ancient Rome. This textbook provides the foundations needed to simulate the complexity of past human societies, offering researchers a richer understanding of the past—and likely future—of our species.

Noise-Induced Versus Intrinsic Oscillation in Ecological Systems

Studies of populations oscillating through time have a long history in ecology as these dynamics can help provide insights into the causes of population regulation. A particularly difficult challenge is determining the relative role of deterministic versus stochastic forces in producing this oscillatory behavior. Another classic ecological study area is the study of spatial synchrony which also has helped unravel underlying population dynamic principles. One possible approach to understanding the causes of population cycles is based on the idea that a focus on spatiotemporal behavior, oscillations in coupled populations, can provide much further insight into the relative role of deterministic versus stochastic forces. Using ideas based on concepts from statistical physics, we develop results showing that in a system with coupling between adjacent populations, a study of spatial synchrony provides much information about the underlying causes of oscillations. Novel, to ecology, measures of spatial synchrony are a key step.

The regulating effect of growth plasticity on the dynamics of structured populations

Plasticity is the extent to which life history processes such as growth and reproduction depend on the environment. Plasticity in individual growth varies widely between taxa. Nonetheless, little is known about the effect of plasticity in individual growth on the ecological dynamics of populations. In this article we analyse a physiologically structured population model of a consumer population in which the individual growth rate can be varied between entirely plastic to entirely non-plastic. We derive this population level model from a dynamic energy budget model to ensure an accurate energetic coupling between ingestion, somatic maintenance, growth, and reproduction within an individual. We show that the consumer population is either limited by adult fecundity or juvenile survival up to maturation, depending on the level of growth plasticity and the non-plastic individual growth rate. Under these two regimes we also find two different types of population cycles which again arise due to fluctuation in respectively juvenile growth rate or adult fecundity. In the end our model not only provides insight into the effects of growth plasticity on population dynamics, but also provides a link between the dynamics found in age- and size-structured models.

How host phenology impacts multi-season epidemic cycles

Parasite-host interactions can result in periodic population dynamics when parasites over-exploit host populations. The timing of host seasonal activity, or host phenology, determines the frequency and demographic impact of parasite-host interactions which may govern if the parasite can sufficiently over-exploit their hosts to drive population cycles. We describe a mathematical model of a monocyclic, obligate-killer parasite system with seasonal host activity to investigate the consequences of host phenology on host-parasite dynamics. The results suggest that parasites can reach the densities necessary to destabilize host dynamics and drive cycling in only some phenological scenarios, such as environments with short seasons and synchronous host emergence. Further, only parasite lineages that are sufficiently adapted to phenological scenarios with short seasons and synchronous host emergence can achieve the densities necessary to over-exploit hosts and produce population cycles. Host-parasite cycles can also generate an eco-evolutionary feedback that slows parasite adaptation to the phenological environment as rare advantageous phenotypes are driven to extinction when introduced in phases of the cycle where host populations are small and parasite populations are large. The results demonstrate that seasonal environments can drive population cycling in a restricted set of phenological patterns and provides further evidence that the rate of adaptive evolution depends on underlying ecological dynamics.