Search PubMed⌕ Search

Biomedical subjects

Florian Jeltsch

Publications and source records attributed to Florian Jeltsch.

8 recordsLinked to original sources

Does red noise increase or decrease extinction risk? Single extreme events versus series of unfavorable conditions.

Recent theoretical studies have shown contrasting effects of temporal correlation of environmental fluctuations (red noise) on the risk of population extinction. It is still debated whether and under which conditions red noise increases or decreases extinction risk compared with uncorrelated (white) noise. Here, we explain the opposing effects by introducing two features of red noise time series. On the one hand, positive autocorrelation increases the probability of series of poor environmental conditions, implying increasing extinction risk. On the other hand, for a given time period, the probability of at least one extremely bad year ("catastrophe") is reduced compared with white noise, implying decreasing extinction risk. Which of these two features determines extinction risk depends on the strength of environmental fluctuations and the sensitivity of population dynamics to these fluctuations. If extreme (catastrophic) events can occur (strong noise) or sensitivity is high (overcompensatory density dependence), then temporal correlation decreases extinction risk; otherwise, it increases it. Thus, our results provide a simple explanation for the contrasting previous findings and are a crucial step toward a general understanding of the effect of noise color on extinction risk.

Animals↗

Behavioural flexibility in the mating system buffers population extinction: lessons from the lesser spotted woodpecker Picoides minor.

1. In most stochastic models addressing the persistence of small populations, environmental noise is included by imposing a synchronized effect of the environment on all individuals. However, buffer mechanisms are likely to exist that may counteract this synchronization to some degree. 2. We have studied whether the flexibility in the mating system, which has been observed in some bird species, is a potential mechanism counteracting the synchronization of environmental fluctuations. Our study organism is the lesser spotted woodpecker Picoides minor (Linnaeus), a generally monogamous species. However, facultative polyandry, where one female mates with two males with separate nests, was observed in years with male-biased sex ratio. 3. We constructed an individual-based model from data and observations of a population in Taunus, Germany. We tested the impact of three behavioural scenarios on population persistence: (1) strict monogamy; (2) polyandry without costs; and (3) polyandry assuming costs in terms of lower survival and reproductive success for secondary males. We assumed that polyandry occurs only in years with male-biased sex ratio and only for females with favourable breeding conditions. 4. Even low rates of polyandry had a strong positive effect on population persistence. The increase of persistence with carrying capacity was slower in the monogamous scenario, indicating strong environmental noise. In the polyandrous scenarios, the increase of persistence was stronger, indicating a buffer mechanism. In the polyandrous scenarios, populations had a higher mean population size, a lower variation in number of individuals, and recovered faster after a population breakdown. Presuming a realistic polyandry rate and costs for polyandry, there was still a strong effect of polyandry on persistence. 5. The results show that polyandry and in general flexibility in mating systems is a buffer mechanism that can significantly reduce the impact of environmental and demographic noise in small populations. Consequently, we suggest that even behaviour that seems to be exceptional should be considered explicitly when predicting the persistence of populations.

Animals↗

Pattern-oriented modeling of agent-based complex systems: lessons from ecology.

Agent-based complex systems are dynamic networks of many interacting agents; examples include ecosystems, financial markets, and cities. The search for general principles underlying the internal organization of such systems often uses bottom-up simulation models such as cellular automata and agent-based models. No general framework for designing, testing, and analyzing bottom-up models has yet been established, but recent advances in ecological modeling have come together in a general strategy we call pattern-oriented modeling. This strategy provides a unifying framework for decoding the internal organization of agent-based complex systems and may lead toward unifying algorithmic theories of the relation between adaptive behavior and system complexity.

Animals↗

Extinction risk, coloured noise and the scaling of variance.

The impact of temporally correlated fluctuating environments (coloured noise) on the extinction risk of populations has become a main focus in theoretical population ecology. In this study we particularly focus on the extinction risk in strongly correlated environments. Here, we found that, in contrast to moderate auto-correlation, the extinction risk was highly dependent on the process of noise generation, in particular on the method of variance scaling. Such scaling is commonly applied to avoid variance-driven biases when comparing the extinction risk under white and coloured noise. We show that for strong auto-correlation often-used scaling techniques lead to a high variability in the variances of the resulting time series and thus to deviations in the subsequent extinction risk. Therefore, we present an alternative scaling method that always delivers the target variance, even in the case of strong auto-correlation. In contrast to earlier techniques, our very intuitive method is not bound to auto-regressive processes but can be applied to all types of coloured noises. We strongly recommend our method to generate time series when the target of interest is the effect of noise colour on extinction risk not obscured by any variance effects.

Animals↗

Modelling the impact of climate change on woody plant population dynamics in South African savanna.

BACKGROUND: In Southern Africa savannas climate change has been proposed to alter rainfall, the most important environmental driver for woody plants. Woody plants are a major component of savanna vegetation determining rangeland condition and biodiversity. In this study we use a spatially explicit, stochastic computer model to assess the impact of climate change on the population dynamics of Grewia flava, a common, fleshy-fruited shrub species in the southern Kalahari. Understanding the population dynamics of Grewia flava is a crucial task, because it is widely involved in the shrub/bush encroachment process, a major concern for rangeland management due to its adverse effect on livestock carrying capacity and biodiversity. RESULTS: For our study we consider four climate change scenarios that have been proposed for the southern Kalahari for the coming decades: (1) an increase in annual precipitation by 30-40%, (2) a decrease by 5-15%, (3) an increase in variation of extreme rainfall years by 10-20%, (4) and increase in temporal auto-correlation, i.e. increasing length and variation of periodic rainfall oscillations related to El Nino/La Nina phenomena. We evaluate the slope z of the time-shrub density relationship to quantify the population trend. For each climate change scenario we then compared the departure of z from typical stable population dynamics under current climatic conditions. Based on the simulation experiments we observed a positive population trend for scenario (1) and a negative trend for scenario (2). In terms of the projected rates of precipitation change for scenario (3) and (4) population dynamics were found to be relatively stable. However, for a larger increase in inter-annual variation or in temporal auto-correlation of rainfall population trends were negative, because favorable rainfall years had a limited positive impact due to the limited shrub carrying capacity. CONCLUSIONS: We conclude that a possible increase in precipitation will strongly facilitate shrub encroachment threatening savanna rangeland conditions and regional biodiversity. Furthermore, the negative effects found for positive auto-correlated rainfall support current ecological theory stating that periodically fluctuating environments can reduce population viability because species suffer disproportionately from poor environmental conditions.

Biodiversity↗

Minimum recruitment frequency in plants with episodic recruitment.

There is concern about the lack of recruitment of Acacia trees in the Negev desert of Israel. We have developed three models to estimate the frequency of recruitment necessary for long-term population survival (i.e. positive average population growth for 1,000 years and < 10% probability of extinction). Two models assume purely episodic recruitment based on the general notion that recruitment in arid environments is highly episodic. They differ in that the deterministic model investigates average dynamics while the stochastic model does not. Studies indicating that recruitment episodes in arid environments have been overemphasized motivated the development of the third model. This semi-stochastic model simulates a mixture of continuous and episodic recruitment. Model analysis was done analytically for the deterministic model and via running model simulations for the stochastic and semi-stochastic models. The deterministic and stochastic models predict that, on average, 2.2 and 3.7 recruitment events per century, respectively, are necessary to sustain the population. According to the semi-stochastic model, 1.6 large recruitment events per century and an annual probability of 50% that a small recruitment event occurs are needed. A consequence of purely episodic recruitment is that all recruitment episodes produce extremely large numbers of recruits (i.e. at odds with field observations), an evaluation that holds even when considering that rare events must be large. Thus, the semi-stochastic model appears to be the most realistic model. Comparing the prediction of the semi-stochastic model to field observations in the Negev desert shows that the absence of observations of extremely large recruitment events is no reason for concern. However, the almost complete absence of small recruitment events is a serious reason for concern. The lack of recruitment may be due to decreased densities of large mammalian herbivores and might be further exacerbated by possible changes in climate, both in terms of average precipitation and the temporal distribution of rain.

Acacia↗

Controlling Echinococcus multilocularis-ecological implications of field trials.

Two field trials to reduce the prevalence of Echinococcus multilocularis in foxes have been conducted in recent years. Although both trials reduced prevalence considerably, they failed to eradicate the parasite in the study region. Following the control trial in northern Germany, prevalence recovered unexpectedly and rapidly, reaching pre-control levels five quarters (15 months) after the end of control. To understand the internal dynamics of the parasite-host system's reaction to control, we developed a spatially explicit simulation model, Echi. The simulation model incorporates the information available concerning fox tapeworm population dynamics. Using epidemiological parameters to adjust pre-control prevalence, the model predicts the temporal evolution of the prevalence of E. multilocularis in controlled foxes without departing from the range of uncertainty of the field data. However, the model does not predict the rapid pre-control recovery observed in the field trial. The deviation of the model's prediction from field data indicates the involvement of processes not yet taken into account. We modified the model step by step to mimic processes with the potential to cause the rapid post-control recovery of the prevalence of E. multilocularis in foxes. Neither the longevity of tapeworm eggs nor the migratory behaviour of foxes showed any influence on the post-control reaction of the parasite-host system. However, landscape structures leading to a heterogeneous distribution of infected foxes have the potential to alter the system's reaction to control. If infected foxes are concentrated in multiple clusters in the landscape, the model prediction tallied with the range of uncertainty of the field data. Such spatial distribution of infected foxes may be caused by differential abiotic conditions influencing the survival of tapeworm eggs. The model was found to comply best with field data if the foxes acquire partial immunity by being exposed to the fox tapeworm. Both hypotheses explaining the rapid post-control recovery of the prevalence of E. multilocularis observed in the fox population were supported by field data. Both hypotheses have far-reaching consequences for future control trials. The spatial aggregation of infected foxes would enable control efforts to be concentrated on these highly infected areas. However, the acquisition of immunity acts as a buffer to control, necessitating intensified control measures.

Animals↗

[Baiting intervals and duration of control of the small fox tapeworm: a simulation study].

Field trials to control the small fox tapeworm Echinococcus multilocularis failed to reduce the prevalence of the parasite persistently. With the experience from this empirical work, a simulation model for the population dynamics of the small fox tapeworm was developed. This model is used to examine the effect of different control strategies. Sufficient control duration is able to eradicate the parasite in simulation experiments. Baiting intervals of 4 or 6 weeks were found to be more efficient than shorter or longer intervals. The strategy used in field trials showed no sustainable effect in any of the simulation experiments. The applicability of simulation models for the planning of control measures for wildlife diseases is discussed.

Animals↗