Ecological Complexity最新文献

Mitigating the poaching pressure on food webs under multiple constraints (including financial and ecological ones) remains an open problem within conservation. Within this field, mathematically modeling the effects of poaching threats on managerial decision-making is a novel approach. To fill this scientific gap, the present paper uses a security game approach to model the interactions between an environmental manager (defender) and a group of profit-seeking pursuit poachers (attackers) who target species which are nodes of the food web. Based upon the non-cooperative Stackelberg game, the objective of the defender (as leader) is to keep the food web at or near equilibrium through optimally manipulating the populations of an optimal subset of species. In contrast, each attacker strives to maximize monetary profit by hunting an optimal population size of the selected species. The model is validated by a numerical example examining the food web of the endangered Persian leopard (Panthera pardus saxicolor), which lives in Golestan National Park (GNP), Iran. The model provides an overarching biotic intervention strategy to keep the (1 predator-4 prey) food web near equilibrium, while only 2 prey species (the urial (Ovis vignei) and the red deer (Cervus elaphus)) are directly threatened by poachers. The examination revealed that both species population data and poaching data should be taken into account to set effective multi-species conservation prioritization levels. In a sensitivity analysis approach, it was found that, despite the fact that red deer is endangered and preferred by poachers, the deterrent penalty measure should be 1.5 times greater for poaching urial than red deer. The output analysis illustrated that, in order to bring the urial deterrent penalty measure closer to the red deer one, enforcement measures should be about 2.5 times stricter for poaching urial than red deer. The results specifically yield insight into how to optimally conserve a food web equilibrium under poaching pressure and within several constraints.

In this paper, the dynamical behaviours and mathematics of the fractional order atmosphere-soil-land plant carbon cycle system involving the time dependent variable of carbon flux in atmosphere, the carbon flux of soil, and the carbon flux of animals and plants are qualitatively and numerically investigated. Explicit solutions in terms of the Mittag-Leffler functions to the terrestrial carbon cycle system around the equilibrium point are first time reported by applying Laplace transform of Caputo fractional derivative. The graphs of obtained solutions the time dependent variable of carbon flux in atmosphere, the carbon flux of soil and the carbon flux of animals and plants are plotted against each other. Explicit solutions to original system and stability of the fractional order linearized system around the equilibrium point are graphically compared as well.

Human activities severely impact the distribution and behaviour of apex predators in numerous terrestrial and aquatic ecosystems, with cascading effects on several species. Mesopredator outbreaks attributable to the removal of an apex predator have often been recorded and described in the literature as “mesopredator release”. During recent decades several examples of the phenomenon have been observed and studied in many different parts of the world. In this paper, we quantitatively reviewed the existing literature on mesopredator release using two software packages (VOSviewer and CiteSpace) to investigate patterns and trends in author keywords through occurrences and temporal analyses, and creating relative network maps. The results showed that even though the general scientific interest in mesopredator release has increased in recent decades, the vast majority of studies focus on canid species, leaving many other species or entire taxa (e.g., reptiles) understudied and under-described. The connection between invasive species and mesopredator release has only recently been more extensively explored and also the effects of apex predators declining in aquatic ecosystems are still only partially investigated. Due to the increasing effect of biological invasions, overfishing, and either the decline or the rise of apex predators in different parts of the world, we expect an even higher increase in interest and number of published documents on the subject. We also encourage widening the research focus beyond canids to include other important taxa.

Population aging has become a global phenomenon. Whereas, the ecological consequences of population aging are rarely addressed in current research. In this context, this study contributes to the existing literature by providing new empirical evidence on how population aging along with globalization, economic growth, energy consumption, natural resource rent, and human capital affect ecological footprint for selected 27 Organization for Economic Cooperation and Development (OECD) countries during 1970–2017. This study utilizes an advanced econometric approach, Pooled Mean Group (PMG) estimator for empirical estimation, that allows heterogeneity in the slope parameters and dependencies across countries. The long-term results disclose that globalization (overall) decreases the ecological footprint. On the other hand, financial and political globalization poses a favorable impact on environmental quality, while economic and social globalization is found to increase environmental degradation. Population aging has a statistically significant negative effect on the ecological footprint, but its non-linear term increases the ecological footprint. Additionally, economic growth, energy consumption, and natural resource rent exacerbate environmental deterioration. In contrast, human capital decreases ecological footprint. Based on the empirical results, important policy implications have been provided.

We present a continuous time predator-prey model and predator’s growth subjected to component Allee effect. The model also includes density dependent mortality of predator. We investigate our model both analytically and numerically, and highlighted the effect of density independent mortality and Allee effect. In our system, we find that a fixed point representing the extinction of predator is always a stable point. When coexistence equilibria exists our system is bistable. We have observed that tristability is possible for our model that includes two stable co-existence fixed point. The most important phenomena which we have observed are hydra effect and cascading effect. Due to component Allee effect in predator the system shows multiple hydra effect. We discuss the phenomenon of bubbling, which indicates increasing and decreasing of amplitudes of cycles. We have presented one-parametric as well as two-parametric bifurcation diagram and also all possible bifurcations that the system could go through.

Over the last several years, the IUCN Red List approach for assessing the risk of extinction faced by species has been adapted into a Red List of Ecosystems methodology. This endeavor faces several important challenges, including how to define the types of ecosystems to which the Red List criteria are applied, and how to manage information on the geographic distribution of ecosystems in an open, transparent, and standardized manner linking mapping, typology, and field studies. We propose a fundamentally novel approach that differs from currently available ecosystem typologies in three important aspects by (1) offering a new way of conceptualizing types of ecosystems, (2) providing an explicit method for communicating the conceptualized ecosystems and how they are circumscribed, and (3) developing technical tools for managing the resulting conceptual model. Firstly, ecosystem types are defined by studying biogeoclimatic gradients using an approach that is both modular (in which combinations of ecological factors are studied at a given scale) and hierarchical (involving relative spatial and temporal scales in which local/site gradients are dependent on bioclimatic/regional gradients). This avoids the problem of classes that are not mutually exclusive and enables the classification of all types of ecosystems, including for example marshes on rocky outcrops in superhumid tropical montane areas. Secondly, the names of ecosystem species are linked to a nomenclatural type defined by a ‘type site’ or ‘biotype’, adopting a principle that makes clear a given author's notion of an ecosystem type even if the accompanying name and description are partial or imperfect, or when the ecosystem type is delimited too broadly according to the interpretation of another author. Ecosystem names are structured as a descriptive diagnosis based on a standardized set of characters and character states. This typological approach for facilitating the naming and comparison of ecosystem circumscriptions is thus truly taxonomic in nature. Thirdly, in order to facilitate the use and application of the conceptual approach presented here, we translate it into a practical tool by developing a smartphone-based system to collect data for observing and describing virtual ecosystem specimens in the field, along with the "Bio" database, which manages ecosystem data and also enables tracking synonymies using an open system that entails assigning determinavits to biotypes.

The changing climate is expected to alter the timings of key events in species life-histories. These shifts are likely to have important consequences for infectious disease dynamics, as the distribution and abundance of host species will lead to a different environment for parasites. Previous work has shown how seasonality in single host traits - most commonly the reproduction rate or transmission rate - can lead to an array of complex epidemiological dynamics, including chaos and multiple-stable states, with changes to the timing and amplitude of the seasonal peaks often driving drastic changes in behaviour. However, more than one life-history trait is likely to be seasonal, and changing environmental conditions may impact each of them in different ways, yet there have been few studies of host-parasite dynamics that include more than one seasonal trait. Here we examine a Susceptible-Infected-Recovered epidemiological model in which both reproduction and transmission exhibit seasonal fluctuations. We examine how the amplitude and timing of these seasonal peaks impact disease dynamics. We show that the relative timing of the two events is key, with the most stable dynamics when births peak a few months before transmission. We also show that chaotic dynamics become more likely when transmission in particular has a high amplitude, and when baseline transmission and virulence are high. Our results emphasise the importance of seasonality and timing of host life-history events to disease dynamics.

An epidemiological model based on probabilistic cellular automaton is proposed to investigate the dynamics of two co-circulating infections. In the model, one of these two diseases compromises the immune response to future infections; however, there is vaccine against this immunosuppressive disease. The goal is to evaluate the impact of the vaccination coverage on the prevalence and on the cumulative deaths associated with both contagious diseases. The performed numerical simulations highlight the importance of vaccination on decreasing morbidity and mortality. The results are discussed from a public health standpoint, by taking into account outbreaks of measles and COVID-19.

Excessive infrastructural developments, driven by urbanization, have not only brought destruction of forests, but also exacerbated the temperature of cities (or towns) due to formation of urban heat islands. Keeping such an urban system in mind, a nonlinear dynamical model is formulated in the proposed work in terms of system of differential equations. The model, comprising of forest resources, human population, urban infrastructural developments and temperature as system variables, is formulated on the assumption that infrastructural developments, induced through human population, escalate temperature of the region at the cost of deforestation. The derived model is mathematically analyzed for qualitative properties of its equilibrium solutions, extending from their existences to stabilities. Further, to demonstrate the impact of parametric variations on dynamical behavior, the system is also investigated for transcritical and Hopf - bifurcations. Quantitative analysis is also being executed with available numerical data to substantiate qualitative findings and to determine sensitiveness of equilibrium values of model outcomes towards system parameters. The results reveal that any of the parameters, which directly or indirectly, responsible for escalation in temperature of the region can put the system in a state of periodic oscillations, arises through Hopf - bifurcation. Therefore, it is suggested to control urban infrastructural developments through implementation of government strategies, which should include check over illegal encroachment of forested land for infrastructural developments.

The capacity of highly diverse systems to prevail has proven difficult to explain. In addition to methodological issues, the inherent complexity of ecosystems and issues like multicausality, non-linearity and context-specificity make it hard to establish general and unidirectional explanations. Nevertheless, in recent years, high order interactions have been increasingly discussed as a mechanism that benefits the functioning of highly diverse ecosystems and may add to the mechanisms that explain their persistence. Until now, this idea has been explored by means of hypothetical simulated networks. Here, we test this idea using an updated and empirically documented network for a coffee agroecosystem. We identify potentially key nodes and measure network robustness in the face of node removal with and without incorporation of high order interactions. We find that the system's robustness is either increased or unaffected by the addition of high order interactions, in contrast with randomized counterparts with similar structural characteristics. We also propose a method for representing networks with high order interactions as ordinary graphs and a method for measuring their robustness.