Biology subjects

Radchuk, V.

Publications and source records attributed to Radchuk, V..

6 recordsLinked to original sources

bioRxiv2024

demres: An R package to study time-varying demographic resilience

1- Quantifying the resilience of populations to disturbances is essential to assess how threatened populations are. Demographic resilience has been defined as the ability of populations to resist and recover from alterations in their demographic structures. Resilience metrics are typically obtained by applying transient analyses to matrix population models. Until now, the questions of how demographic resilience can change over time, how to quantify such temporal variation and when it is important to account for it have not yet been studied. However, since demographic rates fluctuate over time, it is essential to evaluate whether and under what conditions the assumption of time-constant demographic resilience remains appropriate. 2- In this study we introduce demres - an R package that offers functions to quantify time-varying and time-constant demographic resilience metrics, including time to convergence, damping ratio, inertia, maximum amplification, maximum attenuation and reactivity. The package also allows the comparison of these two approaches, both visually and by means of distance metrics. 3- We use a case study to illustrate the versatility of demres and demonstrate how this tool can be readily used by conservation biologists, managers and others to assess the time-varying resilience of wildlife populations using long-term demographic data. Our framework facilitates standardised comparisons of demographic resilience metrics, for example by means of comparative studies across populations and species.

ecology↗

bioRxiv2024

Effects of environmental change on population growth: monitoring time-varying carrying capacity in free-ranging spotted hyenas

In conservation, a growing population is often taken as a sign of success. But trends in population size can be misleading. When individuals are long-lived, populations may keep growing--for a time--even as the environment begins to stabilize or deteriorate. Trends in carrying capacity (K) would better reflect the situation that a population finds itself in, yet K is commonly assumed to be static. We developed an individual-based modelling approach to estimate time-varying carrying capacity (Kt) in a population of free-ranging spotted hyenas. Kt noticeably varied due to events such as disease outbreaks, but not in response to recent conservation interventions. Although the population tripled in size during the 26-year study period, we found no corresponding trend in Kt. Rather, population recovery resulted from earlier environmental improvements. Our approach, which can be applied to populations of other species, allows for a faster and more accurate assessment of conservation needs.

ecology↗

bioRxiv2022

Resource asynchrony and landscape homogenization as drivers of virulence evolution

In the last years, the emergence of zoonotic diseases and the frequency of disease outbreaks have increased substantially, fuelled by habitat encroachment and asynchrony of biological cycles due to global change. The virulence of these diseases is a key aspect for their success. In order to understand the complex processes of pathogen virulence evolution in the global change context, we adapted an established individual-based model of host-pathogen dynamics. Our model simulates a population of social hosts affected by an evolving pathogen in a dynamic landscape. Pathogen virulence evolution is explored by the inclusion of multiple strains in the model that differ in their transmission capability and lethality. Simultaneously, the hosts resource landscape is subjected to spatial and temporal dynamics, emulating effects of global change. We found an increase in pathogenic virulence and a shift in strain dominance with increasing landscape homogenisation. Our model further shows a trend to lower virulence pathogens being dominant in fragmented landscapes, although pulses of highly virulent strains are expected under resource asynchrony. While all landscape scenarios favour coexistence of low and high virulent strains, when host density increases, the high virulence strains capitalize on the high possibility for transmission and are likely to become dominant. Author SummaryDisease outbreaks primarily caused by contact with animals are increasing in recent years, related to habitat destruction and altered biological cycles due to climate change. Pathogens associated with such outbreaks will be more successful the more effectively they can spread in a population. Thus, understanding the conditions over which those pathogens evolve will help us to limit the impact of disease outbreaks in the future. To this end, we used an individual based model that allowed us to study different scenarios. Our model had three main components: a host-pathogen system, a dynamic resource landscape with different degrees of fragmentation and temporal resource mismatches. We used dynamic landscapes with varying resource amounts over the years and consisting of multiple large or smaller habitat clusters. Our simulations showed that homogenous landscapes resulted in higher virulent pathogens and fragmented landscapes in lesser virulent pathogens. However, across all scenarios, high and low virulent pathogen strains were able to coexist.

ecology↗

bioRxiv2021

Halfway to self-sustainability: Reintroduced migratory European Northern Bald Ibises (Geronticus eremita) still need management interventions for population viability

Northern Bald Ibis (NBI) have disappeared from Europe already in Middle Age. Since 2003 a migratory population is reintroduced in Central Europe. We conducted demographic analyses of survival and reproduction of 384 NBI over a period of 12 years (2008-2019). These data also formed the basis for a population viability analysis (PVA) simulating the possible future development of the NBI population in different scenarios. We tested life-stage specific survival rates for differences between these stages, raising types and colonies as well as the influence of stochastic events and NBI supplements on the population growth. Stage specific survival rates ranged from 0.64 to 0.78. 61% of the mature females reproduce with a mean fecundity of 2.15 fledglings per nest. The complementary PVA indicated that the release population is close to self-sustainability with a given lambda 0.95 and 24% extinction probability within 50 years. Of the 326 future scenarios tested, 94 % reached the criteria of <5% extinction probability and population growth rates >1. In case of positive population growth, stochastic events had a limited effect. Of 820 sub-scenarios with different stochastic event frequencies and severities 87 % show population growth despite the occurrence of stochastic events. Predictions can be made based on the results of the individual-based model as to whether and under what circumstances the reintroduced NBI population can survive. This study shows that a PVA can support reintroduction success that should work closely together with the project in the field for mutual benefit, to optimize future management decisions.

ecology↗

bioRxiv2019

Honeybee colony performance affected by crop diversity and farmland structure: a modelling framework

Forage availability has been suggested as one driver of the observed decline in honeybees. However, little is known about the effects of its spatiotemporal variation on colony success. We present a modelling framework for assessing honeybee colony viability in cropping systems. Based on two real farmland structures, we developed a landscape generator to design cropping systems varying in crop species identity, diversity, and relative abundance. The landscape scenarios generated were evaluated using the existing honeybee colony model BEEHAVE, which links foraging to in-hive dynamics. We thereby explored how different cropping systems determine spatiotemporal forage availability and, in turn, honeybee colony viability (e.g., time to extinction, TTE) and resilience (indicated by, e.g. brood mortality). To assess overall colony viability, we developed metrics, PH and PP, which quantified how much nectar and pollen provided by a cropping system per year was converted into a colonys adult worker population. Both crop species identity and diversity determined the temporal continuity in nectar and pollen supply and thus colony viability. Overall farmland structure and relative crop abundance were less important, but details mattered. For monocultures and for four-crop species systems composed of cereals, oilseed rape, maize and sunflower, PH and PP were below the viability threshold. Such cropping systems showed frequent, badly timed, and prolonged forage gaps leading to detrimental cascading effects on life stages and in-hive work force, which critically reduced colony resilience. Four-crop systems composed of rye-grass-dandelion pasture, trefoil-grass pasture, sunflower and phacelia ensured continuous nectar and pollen supply resulting in TTE > 5 years, and PH (269.5 kg) and PP (108 kg) being above viability thresholds for five years. Overall, trefoil-grass pasture, oilseed rape, buckwheat and phacelia improved the temporal continuity in forage supply and colonys viability. Our results are hypothetical as they are obtained from simplified landscape settings, but they nevertheless match empirical observations, in particular the viability threshold. Our framework can be used to assess the effects of cropping systems on honeybee viability and to develop land-use strategies that help maintain pollination services by avoiding prolonged and badly timed forage gaps.

ecology↗

bioRxiv2019

Resilience trinity: safeguarding ecosystem services across three different time horizons and decision contexts

Ensuring ecosystem resilience is an intuitive approach to safeguard future provisioning of ecosystem services (ES). However, resilience is an ambiguous concept and difficult to operationalize. Focusing on resilience mechanisms, such as diversity, network architectures or adaptive capacity, has recently been suggested as means to operationalize resilience. Still, the focus on mechanisms is not specific enough because the usefulness of a mechanism is context-dependent. We suggest a conceptual framework, resilience trinity, to facilitate management of resilience mechanisms in three distinctive decision contexts and time-horizons. i) reactive, when there is an imminent threat to ES resilience and a high pressure to act, ii) adjustive, when the threat is known in general but there is still time to adapt management, and iii) provident when time horizons are very long and the nature of the threats is uncertain, leading to a low willingness to act. This emphasizes that resilience has different interpretations and implications at different time horizons which however need to be reconciled. The inclusion of time into resilience thinking ensures that longer-term management actions are not missed while urgent threats to ES are given priority.

ecology↗