Ecological Complexity最新文献

Dissimilarity indices differ in the relative weight given to rare species. Heavy-weighting of rare species may be justified in terms of sampling. An index may erroneously estimate high dissimilarity between two identical communities if they are composed of many rare species and the sampling effort is insufficient to observe most of them in both samples. Heavy-weighting of rare species is thought to compensate for this negative bias. I evaluated two quantitative indices that heavy-weight rare species, NNESS (New Normalized Expected Species Shared) and Goodall, and two probability versions of the Sørensen index, one that takes into account shared unseen rare species and the other that does not. They were compared against the widely used Bray-Curtis (or Sørensen quantitative) and the Morisita-Horn. Indices were computed using raw abundance data or coded data that heavy-weight rare species (frequency in sample units, log-transformation and standardization by the maximum abundance within species). Indices were evaluated for their ability to distinguish, using distance-based MANOVA, season-defined (summer, winter) groups of samples of stream macroinvertebrates and groups of samples obtained by simulation. Sørensen corrected for unseen shared species performed poorly in the empirical study and intermediate in the simulations. NNESS was good in the empirical study and intermediate in the simulations. Goodall scored inversely as NNESS, being intermediate in the empirical assessment and very good in the simulations. The Sørensen uncorrected for unseen shared species, Bray-Curtis and the Morisita-Horn presented poor or intermediate results using raw abundance data. Their performance, however, improved consistently using coded data that heavy-weight rare species and made them good or very good. I conclude that heavy-weighting rare species improves the ability to detect multivariate groups. Heavy-weighting of rare species may be achieved either by using specific formulae (NNESS, Goodall) or using coded data.

The augmentation of natural enemies against agricultural pests is a common tactic undertaken to minimize crop damage without the use of chemical pesticides. Failures of this strategy may result from (i) Allee effects acting on biological control agent; (ii) trophic interactions between the released control agent and native species in the local ecosystem; (iii) excessively rapid spreading agents. To investigate the interplay of these mechanisms in pest biocontrol efficiency in the context of intraguild predation (IGP), we develop a one-dimensional dynamical model of a spatial, tritrophic food web with intraguild predation. We show that the agent’s diffusivity (i.e., agent’s dispersal speed), and intraguild predator’s addition of alternative food sources are important factors in determining the success or failure of pest biocontrol. These results are obtained for spatially explicit models by considering the speed of dispersal of the control agent and the pest. Feedback from theoretical models as the one constructed in this work can provide useful guidelines for practitioners in biological control.

In this paper, a mathematical model for the interacting dynamics of phytoplankton-zooplankton is proposed. The phytoplankton have the ability to take refuge and release toxins to avoid over predation by zooplankton. The zooplankton are provided some additional food to persist in the system. The phytoplankton are assumed to be affected directly by external toxic substances whereas zooplankton are affected indirectly by feeding on the affected phytoplankton. We incorporate seasonal variations in the model, assuming the level of nutrients, refuge and the rate of toxins released by phytoplankton as functions of time. Our results show that when high toxicity and refuge cause extinction of zooplankton, providing additional food supports the survival of zooplankton population and controls the phytoplankton population. Prey refuge and additional food have stabilizing effects on the system; higher values of the former results in extinction of zooplankton whereas phytoplankton disappear for larger values of the latter. Seasonality in nutrients level and toxins released by phytoplankton generate higher periodic solutions while time-dependent refuge of phytoplankton causes the occurrence of a period-three solution. The possibility of finding additional food for zooplankton may push back the ecosystem to a simple stable state from a complex dynamics.

Marine ecosystems are open, complex, adaptive, and hierarchical systems highly integrated through the exchange of matter and energy flows. This flows exchange allows marine ecosystems to operate at different scales acting as dissipative structures, building natural capital stocks capable of generating several ecosystem services vital for human well-being. Humans derive a wide range of goods and services from marine ecosystems while, at the same time, generate several impacts causing biodiversity loss and seriously affecting their capacity to provide benefits to humans. Effective management strategies are crucial to conserve healthy and diverse marine and coastal ecosystems, maintain the valuable functions and services they provide, and allow for sustainable human activities. In recent years, Marine Protected Areas (MPAs) have been increasingly acknowledged worldwide as important tools to conserve biodiversity and achieve human well-being and sustainable development goals. Assessing the value of natural capital and ecosystem services is crucial to raise awareness on their importance, support conservation strategies, and ensure the sustainable management of marine ecosystems. This study aimed at calculating biomass and emergy-based indicators to assess the value of natural capital stocks in a Mediterranean MPA. The assessment was performed through a biophysical and trophodynamic environmental accounting model fed with field biomass data collected through ad hoc sampling campaigns performed in the MPA. Four main macro-habitats were investigated: sciaphilic hard bottom (coralligenous bioconstructions), photophilic hard bottom, soft bottom, and Posidonia oceanica seagrass beds. The biomass density of the main autotrophic and heterotrophic taxonomic groups identified in the four macro-habitats of the MPA was evaluated. Based on this biomass matrix, the emergy value of natural capital stocks was assessed. The Posidonia oceanica seagrass beds habitat showed the highest biophysical value (2.32·10¹⁹ sej) at MPA scale, while coralligenous bioconstructions resulted the habitat with the highest biophysical value per unit area (2.72·10¹² sej m⁻²). In addition, to complement the biophysical assessment with an economic perspective, the emergy-based indicators were converted into monetary units. The total value of natural capital of the whole MPA resulted in about 46 M€. The results of this study can support local managers and policy makers in the development of management strategies to ensure nature conservation and sustainable human activities. They can be also used as a benchmark for the assessment of natural capital value at larger scales in support of a proper consideration and inclusion of nature value into processes of policy making.

We study an integral-differential equation that models a pure birth-jump process, where birth and dispersal cannot be decoupled. A case has been made that these processes are more suitable for phenomena such as plant dynamics, fire propagation, and cancer cell dynamics. We contrast the dynamics of this equation with those of the classical reaction-diffusion equation, where the reaction term models either logistic growth or a strong Allee effect. Recent evidence of an Allee effect has been found in plant dynamics during the germination process (due to seed predation) but not in the generation of seeds. This motivates where the Allee effect is included in our model. We prove the global existence and uniqueness of solutions with bounded initial data and analyze some properties of the solutions. Additionally, we prove results related to the persistence or extinction of a species, which are analogous to those of the classical reaction-diffusion equation. A key finding is that in some cases a population which is initially below the Allee threshold in some area, even if small, will actually survive. This is in contrast to solutions of the classical reaction-diffusion with the same initial data. Another difference of note is the lack of regularization and an infinite number of discontinuous equilibrium solutions to the birth-jump model.

In order to reduce carbon emissions and improve environmental governance, the paper discusses the interactive forms of environmental regulation based on the two-regime spatial Durbin model. The effects of environmental regulation and interactive behavior of environmental regulation on carbon dioxide (CO₂) emissions are explored by using the spatial lag of X (SLX) model. It is found that there is a diversified competitive behavior in the enforcement of environmental regulation among local governments in China. And the diversified competitive behavior results in the nearby transfer of pollution, which increases local CO₂ emissions. In addition, there is an inverted "U" curve between environmental regulation and CO₂ emissions, and China is still in the "green paradox" stage. Furthermore, it is found that the environmental regulation mainly affects CO₂ emissions through industrial structure and technological progress. Also, there are differences in the spatial spillover effect of environmental regulation due to the existence of regional heterogeneity, and its impact on CO₂ is particularly significant in the western region. The findings indicate that the central government should strengthen targeted supervision and adaptive incentives for local governments to implement environmental regulation so that joint emission reduction can be promoted.