Ecological Complexity最新文献

Understanding dynamical behavior of a spatially distributed population is crucial to conservation and management of endangered species. This paper considers predator–prey systems with Beddington–DeAngelis functional response, where the predator moves between source–sink patches asymmetrically and acts as an agent. Our aim is to show how agent-based diffusion affects dynamics of the system and total population abundance of the species. Using dynamical systems theory, we demonstrate stability of positive equilibria in the system, which implies coexistence of the species and change of abundance by diffusion. Moreover, we show Hopf and Bautin bifurcations with multiple limit cycles, which implies multiple oscillations of populations and even extinction of species. Furthermore, this work demonstrates that diffusion in the system may lead to results reversing those without diffusion. The diffusion could change dynamics of the system between coexistence at a steady state and persistence in periodic oscillation, while evolution in asymmetry of diffusion could make the predator reach a total abundance larger than that without diffusion, even reach the maximal abundance. Our results are consistent with experimental observations and are important in studying conservation of biodiversity.

Incorporating temporal variation in models is one of the most important challenges in food web research. One of the environments where time causes profound changes is the intertidal zone, where the immersion-emersion cycle drastically changes the abiotic and biotic conditions. Intertidal rocky shores have been intensively studied, however the variation in the complex food web network that occurs during a tidal cycle remains undescribed. Highly resolved food web networks were assembled for an intertidal reef depicting the food web during low and high tide, and with and without tide pools. It was concluded that high tide adds new species to the web, but it does not add complexity since network connectance was not changed. This occurs because incoming species are mostly highly generalist fish, which add many new links to the web. Tide pools, however, add not only diversity but also complexity. Webs were dominated by intermediate species, with the proportion of top consumers fluctuating throughout the tidal cycle, being lowest during low tide and highest at high tide, due to the incoming larger vertebrate predators. Consumer taxa outnumbered resource taxa, except at low tide when pools are present. Mean trophic level was lowest at low tide (2.3) and highest at high tide with pools (2.6). Omnivory was high and showed little change. “Chain”, the number of links connecting top to basal species, was stable but low. This implies that disturbance can rapidly travel bottom-up or top-down through predator-prey links. The increased connectance given by the addition of tide pools likely increases robustness to disturbances, an important feature in coastal areas so often impacted by human action.

Dynamical systems modeling (DSM) explores how a system evolves in time when its elements and the relationships between them are known. The basic idea is that the structure of a dynamical system, expressed by coupled differential or difference equations, determines attractors of the system and, in turn, its behavior. This leads to structural understanding that can provide insights into qualitative properties of real systems, including ecological and social-ecological systems (SES). DSM generally does not aim to make specific quantitative predictions or explain singular events, but to investigate consequences of different assumptions about a system's structure. SES dynamics and possible causal relationships in SES get revealed through manipulation of individual interactions and observation of their consequences. Structural understanding is therefore particularly valuable for assessing and anticipating the consequences of interventions or shocks and managing transformation toward sustainability. Taking into account social and ecological dynamics, recognizing that SES may operate on different time scales simultaneously and that achieving an attractor might not be possible or relevant, opens up possibilities for DSM setup and analysis. This also highlights the importance of assumptions and research questions for model results and calls for closer connection between modeling and empirics. Understanding the potential and limitations of DSM in SES research is important because the well-developed and established framework of DSM provides a common language and helps break down barriers to shared understanding and dialog within multidisciplinary teams. In this primer we introduce the basic concepts, methods, and possible insights from DSM. Our target audience are both beginners in DSM and modelers who use other model types, both in ecology and SES research.

In this paper, in view of the senescence of plant and the decay of wrack, time delays are introduced into the plant-wrack model. The effects of wrack decay and time delay on the dynamical behaviors of the diffusive plant-wrack model are studied analytically and numerically. When the delay is zero, the wrack decay will induce the change of stability of the unique equilibrium point, further lead to the occurrence of the Hopf bifurcation and the Turing instability. When the delay is present, the conditions for the occurrence of the Hopf bifurcation are established. By comparing the results of the model without and with delay, it is found that the increases of delay may induce no stability switches, a single stability switch or multiple stability switches, when the value of wrack decay can stabilize model with zero delay. When the value of wrack decay can destabilize model with zero delay, numerical simulations show that the small delay may cause homogeneous distributions of vegetation, while the larger delay may cause the emergence of periodic oscillation of vegetation. The obtained results provide a basis for understanding the spatiotemporal evolution of such a plant-wrack model with delay.

In Earth surface systems (ESS), everything is connected to everything else, an aphorism often called the First Law of Ecology and of geography. Such linkages are not always direct and unmediated, but many ESS, represented as networks of interacting components, attain or approach full, direct connectivity among components. The question is how and why this happens at the system or network scale. The crowded landscape concept dictates that linkages and connections among ESS components are inevitable. The connection selection concept holds that the linkages among components are (often) advantageous to the network and are selected for, and thereby preserved and enhanced. These network advantages are illustrated via algebraic graph theory. For a given number of components in an ESS, as the number of links or connections increases, spectral radius, graph energy, and algebraic connectivity increase. While the advantages (if any) of increased complexity are unclear, higher spectral radii are directly correlated with higher graph energy. The greater graph energy is associated with more intense feedback in the system, and tighter coupling among components. This in turn reflects advantageous properties of more intense cycling of water, nutrients, and minerals, as well as multiple potential degrees of freedom for individual components to respond to changes. The increase of algebraic connectivity reflects a greater ability or tendency for the network to respond to changes in concert.

In this paper, we study the vulnerability of forest ecosystems perturbed by extreme events, such as those arising from climate change. To investigate the complex interactions between the biological dynamics of the forest and the climatic activity, we construct an original hybrid model, obtained by coupling a continuous reaction–diffusion system, which describes the spatio-temporal dynamics of the forest ecosystem, with a discrete probabilistic process, which models the possible occurrences of extreme events. Properties of ecological interest are considered: invariance of the persistence equilibrium, attraction to the extinction equilibrium and emergence of degraded states. Those properties of the hybrid model are verified through an extension of the Statistical Model Checking framework. We establish the existence of a threshold above which the persistence equilibrium of the forest ecosystem is compromised and give a numerical assessment of this threshold in terms of the probability and intensity of extreme events. We also present non-trivial parameter conditions for which the forest ecosystem converges to a degraded savanna-like state.

Climate change may modify environmental conditions creating suitable environments for phytopathogen vectors in places that were not suitable before. The present study aimed to contrast current and future spatial distribution of Diaphorina citri in Mexico under two climate change scenarios, Shared Socioeconomic Pathways (SSP) 4.5 and 8.5 for years 2050 and 2070. Non-correlated bioclimatic variables from eight General Circulation Models derived from the Coupled Model Intercomparison Project-6 and presence point data were used to generate distribution models with MaxEnt. Future projections showed that current suitable areas, equivalent to a 38.6% of coverage persist across all scenarios, new suitability areas appear, and no reduction is expected. All the models coincide on a potential increase in relation to the current national distribution of 11.1, 14.8, 13.8 and 25.5% for SSP2 4.5–50 SSP2 4.5–70 SSP5 8.5–50, and SSP5 8.5–70 respectively. Most of the new areas are not currently dedicated to citriculture; however, an increase in the risk of Huanglongbing is expected because most of the new areas are contiguous to the current presence areas, and cover urban zones where there may exist rutaceous hosts, from which the vector may spread the disease to the production zones.

Human-carnivore systems are built on multi-scalar complex processes often resulting in conflicts that force wildlife managers to address what are conceived as problem individuals. In North America, the grizzly bear (Ursus arctos) is often involved in human-bear conflict with management measures such as translocations, in which problem individuals are moved to new areas, being used to reduce conflict risk. While translocations offer a non-lethal alternative to managing conflict animals, they show varying levels of success. Our objective was to perform a novel assessment of grizzly bear translocation success through agent-based simulation by evaluating how familiarity with landscape features coupled with behavioral traits affects the way individuals use resources in a new environment. Our results showed that bears translocated to familiar habitat used high-quality habitat more than bears moved to areas with unfamiliar landscape characteristics. Increased exploration led to greater use of high-quality habitat in the long run but resulted in reduced use of high-quality habitat during the first two years following a translocation. Habitat quality use depended on scale, with bears translocated to less familiar environments accessing higher quality areas at a finer scale than bears translocated to familiar habitats. We emphasize the need to account for wildlife behavioral traits and habitat characteristics at multiple scales when selecting suitable translocation locations. Understanding the role of factors such as these on translocation outcome will help ensure the success of translocations not only as a method for managing problem wildlife, but also for population restoration, species reestablishment, and conservation translocations across the globe.

The negative effect of fragmentation is one of the main concerns in the study of biodiversity loss in landscape ecology. The use of the matrix has been considered an important factor because it can change a population's relationship with the configuration of the landscape. A systematic way to assess the effect of matrix quality in fragmented landscapes could lead to a better understanding of how matrices can suppress the negative effect of fragmentation. We built a computational individual-based model capable of simulating bi-dimensional landscapes with three types of land cover (habitat, suitable matrix and hostile matrix) and individuals that inhabit those landscapes. We explored in which situations suitable matrix proportions and the degree of usability of this suitable matrix mitigate the negative effect of fragmentation per se. We observed that (i) an increase in the general matrix quality (increases in the suitable matrix proportion and/or usability) can suppress the fragmentation effect in 47% of the simulated scenarios; (ii) the less usable the matrix is, the more of it is needed to suppress the fragmentation effect; (iii) there is a level of usability below which increasing the suitable matrix proportion does cause the fragmentation effect to cease. These results point toward landscape management decisions that consider the similarity of the matrix to the native habitat under management. We suggest that an index to measure the usability of elements of the matrix could be an important tool for using computational models in landscape management more efficiently.