Ecological Complexity最新文献

Unraveling the patterns of animals’ movements is crucial to understanding the basics of biogeography, tracking range shifts resulting from climate change, and predicting and preventing biological invasions. Many researchers have modeled animals’ dispersal under the assumptions of various movement strategies, either predetermined or directed by external factors, but none have compared the effects of different movement strategies on population survival and fitness. In this paper, using an agent-based model with a landscape divided into cells of varying quality, we compare the ecological success of three movement and habitat selection strategies (MHSSs): (i) Smart, in which animals choose the locally optimal cell; (ii) Random, in which animals move randomly between cells without taking into account their quality; (iii) Dreamer, in which animals attempt to find a habitat of dream whose quality is much higher than that of the habitat available on the map. We compare the short-term success of these MHSSs in good, medium and bad environments. We also assess the effect of temporal variation of habitat quality (specifically, winter harshness) on the success of each MHSS. Success is measured in terms of survival rate, dispersal distance, accumulated energy and quality of settled habitat. The most general conclusion is that while survival rate, accumulated energy and quality of settled habitat are affected primarily by overall habitat composition (proportions of different habitat types in the landscape), dispersal distance depends mainly on the MHSS. In medium and good environments, the Dreamer strategy is highly successful: it simultaneously outperforms the Smart strategy in dispersal distance and the Random strategy in terms of the other metrics.

The Tuta absoluta (Meyrick) (Lepidoptera, Gelechiidae), or tomato leafminer, is one of the most devastating pests of tomato crops in South America. The use of parasitoids and predators as biocontrol agents of this pest is an alternative to chemical insecticides and an environmentally safe strategy. However, an outcome of a three-way interspecific interaction (pest-parasitoid-predator) may bring surprises. The question is thus how a combination of enemies can contribute most effectively to reduction of the pest density. We examine this using an ordinary differential equations model. The formal and numerical analyses show that the joint use of both biological controls is the best option to decrease the tomato leafminer population, in contrast to the use of each biological control agent separately. Specifically, the numerical results show that in a scenario where the only biological control is given by the parasitoid, the introduction of the predator decreases the adult Tuta population by $28\%$, reducing even more the damage caused in tomato crops compared to the use of parasitoid alone.

Soil organic carbon is the largest carbon pool in the terrestrial biosphere. Large uncertainties exist in the numerical simulations of soil organic carbon due to inaccuracies in their mathematical descriptions of hydrological processes. In this study, the upper limit of uncertainty in modeled soil organic carbon that is induced by hydrological parameter errors, which may stem from measurement or experiential errors, is estimated in China under four different arid and humid conditions. The study was conducted using a conditional nonlinear optimal perturbation related to parameters (CNOP-P) approach and a model of the coupled water-carbon cycle (the Lund-Potsdam-Jena Wetland Hydrology and Methane Dynamic Global Vegetation Model, LPJ-WHyMe). Uncertainties in hydrological processes resulted in the largest error (2.73 kg C m⁻² yr⁻¹, 20.2%) in the modeled soil organic carbon in the arid and semiarid regions of northern China, with errors of 1.20 kg C m⁻² yr⁻¹ (6.1%) in northeastern China, 0.45 kg C m⁻² yr⁻¹ (3.3%) in southern China, and -1.71 kg C m⁻² yr⁻¹ (13.7%) in the semihumid region of northern China. By analyzing the three components of soil organic carbon, the fast soil carbon pool was found to be the main cause of the uncertainties in modeled soil organic carbon in the four regions of China. Moreover, belowground litter was another cause of the uncertainties in the modeled soil organic carbon in northeastern China and in the semihumid region of northern China. Additional results indicated that the simulation and prediction abilities of soil organic carbon could be improved by reducing parameter errors in hydrological processes through observations or targeted observations. The parameter sensitivity test showed that the benefits to modeling soil organic carbon were similar when reducing the errors in the sensitive hydrological parameter subset, compared to the benefits of reducing the errors in all the hydrological parameters.

Weekly averaged datasets from fourteen AmeriFlux ecosystem monitoring sites spread across the Americas, processed to the FLUXNET2015 standard, are statistically evaluated to characterize their seasonal net ecosystem exchange (NEE) trends. The sites cover wetland, cropland, woodland, grassland and tundra ecosystems. Up to twenty measured variables from the sites are variously correlated with NEE. A comparison of Pearson and Spearman correlation coefficients reveals that the variables are behaving parametrically with respect to NEE for the wetland, woodland (two out of three sites) and tundra locations, but non-parametrically for cropland and grassland sites. Multi-linear regression (MLR) analysis also distinguishes those ecosystems. MLR predicted versus calculated NEE follow Y ≈ X relationships for the wetland and tundra sites, whereas for the other ecosystems the MLR results follow Y≠X trends. Moreover, the coefficient values of the MLR optimum solutions for each ecosystem reveal quite distinct relative influences of the measured variables on the NEE predicted values. These results imply that NEE at wetland and tundra sites can be relatively easily predicted from the FLUXNET2015 set of recorded variables. On the other hand, the other three types of ecosystem sites cannot be easily predicted from those variables, implying that other factors substantially influence NEE at those sites.

Interactions with pollinators underlie the structure and function of plant communities. Network analysis is a valuable tool for studying plant-pollinator interactions, but these networks are most frequently built by aggregating interactions at the species level. Interactions are between individuals and an advantage of individual-based networks is the ability to integrate inter-individual variation in traits and environmental context within complex ecological networks. We studied the influence of inter-individual variation on pollinator sharing among foundation shrubs and cactus in a desert ecosystem using plant individual-based pollinator visitation networks. We hypothesized that the traits that alter attractiveness of plants to pollinators will also influence an individual plant's role within the visitation network. Foundation plants growing with higher densities of nearby blooming shrubs had higher pollinator visitation rates and had greater access to the conspecific mating pool, suggesting widespread and diffuse pollination facilitation within this community. Further, shrub density influenced the role of betweenness centrality and the effective number of partners (e^H). Floral display size also influenced the effective number of interaction partners but did not directly influence the centrality measures for individual plants or other measures of network structure despite increasing visitation rates. The individual-based visitation networks were significantly modular and module membership was predicted by species identity and pollinator visitation rates. Ecological and individual context mediate the outcome of pollinator-mediated interactions and are fundamental drivers of whole community structure. This study shows that the density of immediate neighbours can influence the overall structure of plant-pollinator interaction networks. Exploring the contribution of intraspecific variation to community interaction networks will improve our understanding of drivers of community-level ecological dynamics.

This paper presents a conceptual framework for analyzing forest complexity as the combination of the variety of species and key structures that are associated with the composition, structure, and function of forest stands. Several spatial indicators have been developed to characterize the biodiversity, the structural complexity, and anthropogenic effects that can be observed in Mexican forests. By integrating several stand complexity attributes, the forest condition can be characterized as a function of species composition, stand structural attributes, and forest development. In addition, indicators of anthropogenic effects were also analyzed to identify their influence on forest eco-complexity, and therefore, on the current condition of forests. The results of applying this conceptual framework showed that Mexican forest are ecologically complex, with varying levels of anthropogenic impacts that modify the structural forest characteristics, particularly in tropical forests. The main factor explaining the current eco-complexity condition in tropical forests was associated with early stages of forest development, due to ecological degradation, and showed a generalized loss of attributes, particularly for stand complexity and stand development. In contrast, temperate forests exhibited better eco-complexity conditions, especially for those attributes that define forest stand occupancy and development. Mining activities, forest extraction as selective harvesting, forest fires, land use change, and road openings are critical human activities that directly affect forest structure and, ultimately, modify forest eco-complexity and integrity. This eco-complexity index derived for Mexican forests can be used to integrate measures of forest structure and functioning, and thereby better inform decision making and policy development.

In ecological systems, multiple interactions connect various kinds of components. Strong and weak as well as positive and negative effects cause complex dynamics and often quite unpredictable processes. Human impact is added to this complexity, with all of its diverse effects. In this paper, we present a case study on the Kelian river ecosystem (Borneo), connecting pristine habitats upstream, a gold mine close to the middle section and human settlements downstream. For six locations, separate food web models had been developed earlier. Here we first analyze the ecological system by loop analysis and compare its outcome for different sites. Second, we identify the most crucial human impacts and implement these in modified loop analysis models. We determine the sign of various effects and study the consistency of human impact on different sites and various organisms. Adding human impact to the models (1) increased the ratio of clear predictions, (2) caused the appearance of “zero” predictions in three sites and (3) reduced the variability of predictability along the river.

Abies religiosa's forests are severely endangered as a result of climate change; to save this species and its biological interactions, population assisted migration is discussed in forest management, but not in the microbial ecology field. Our objectives were to analyze its mycorrhizal networks; and, with this data, to identify potential facilitator plants and it's most important mycorrhizal fungal links. This information could be used together in assisted migration programs to connect Abies religiosa saplings to their mycorrhizal network and improve their field establishment. We collected 47 rhizosphere samples from 19 plant species and sequenced their fungal ITS2 region by Illumina. In the whole fungal community, 464 species were mycorrhizal fungi with assigned guild (32%). In this subset, 85 fungi are arbuscular, 365 ectomycorrhizal and 14 from orchid-mycorriza. The Abies religiosa bipartite network is low nested and highly modular, and has a scale-free architecture. Besides Abies religiosa, the plants with the largest degree and the lowest average shortest path were Salix paradoxa, Muhlenbergia spp., and Baccharis conferta. The most important fungal nodes are species of Cortinarius, Genea, Rhodoscypha, Russula, and Tomentella. We suggest to evaluate the Abies' future establishment in the following scheme: in the first year reintroduce Muhlenbergia spp., and Baccharis conferta, in the second year Salix paradoxa, and in the third year–once the mycorrhizal network is reestablished– Abies religiosa' saplings in close proximity of these plants. This scheme is proposed using the data and network analyses of the present study.

Anti-predator behavior in the form of vigilance greatly influences the dynamics of a predator-prey system. In the present work, we investigate the impact of prey vigilance in a three-species food chain model where both prey and middle predator use vigilance as a survival strategy in the presence of their respective predators. We present basic mathematical results such as local and global stability, bifurcation behavior of the system. We explore the variation of the densities of the populations in different bi-parameter spaces and observe that vigilance plays a crucial role in the survival and extinction of the populations.

Allelopathy plays a crucial role in providing competitive advantage to several alien invasive species, and assists in their establishment beyond native boundaries. Role of allelopathy in the invasion success of the alien weed, Parthenium hysterophorus is well established; however, the ecological and evolutionary factors that could affect its allelopathic interactions are relatively unexplored. In our earlier findings, we suggested the presence of two morphotypes (P_A and P_B) in the population of P. hysterophorus, with variable morphology, physiology, and level of ecological impacts. Here, we hypothesize that phenotypically distinct morphotypes of P. hysterophorus may vary in their phytotoxicity and allelochemistry, thereby producing differential ecological impact. To test this hypothesis, effects of rhizospheric soil (RS) and plant amended soils (PAS) of the two morphotypes of P. hysterophorus (P_A and P_B) were studied on selected dicot (Bidens pilosa and Senna occidentalis) and monocot species (Phalaris minor and Avena fatua). Also, the composition of allelochemicals in P_A and P_B was assessed using Liquid Chromatography and Mass Spectrometry (LC-MS). The study revealed that the phytotoxic effect of P_B was greater than P_A in all the parameters measured for dicot species and in most of the parameters studied in monocot species. A generalized dose-dependent response was observed in the test species (PAS0 < PAS10 < PAS20 < PAS40) and the effect of RS was comparable to PAS20 and PAS40. A greater number of allelochemicals were reported from P_B, which is in accordance with the growth studies. The study concludes that intraspecific variations account for differential phytotoxicity and allelochemistry in P. hysterophorus.