Fire effects on demography of the invasive shrub brazilian pepper (Schinus terebinthifolius) in Florida pine savannas

Fire is a common disturbance in savanna ecosystems that may either facilitate or impede non-native plant invasions. Although fire can create recruitment opportunities for non-native plants, it can also prevent their invasion if it exerts strong negative effects on their demographic processes. Some savannas may, therefore, be able to resist invasion provided the natural, frequent-fire regime remains intact. We examined the effects of fire on the demography of the invasive shrub Brazilian pepper, Schinus terebinthifolius Raddi., which is invading fire-prone slash pine savannas of southern Florida. We studied survivorship, growth, and reproduction of low-density populations of Brazilian pepper in a pine savanna within Everglades National Park to investigate whether fire might suppress Brazilian pepper in the early stages of invasion. We found a significant decrease in Brazilian pepper survivorship following fire, particularly among small individuals. We further found that fire reduced fecundity of surviving Brazilian pepper individuals for at least two years. However, resprouting individuals that survived fire had high relative growth rates the following year, which could facilitate population recovery during inter-fire periods. We used a simple population simulation to show that a low-density cohort of Brazilian pepper may be rapidly eliminated from pine savannas with fire-return intervals of four years or less, but individuals may persist for \u3e 50 years with fire-return intervals of eight years or more. Our study suggests the need to maintain the historical frequent-fire regime in pine savannas in order to prevent their invasion by fire-intolerant shrubs such as Brazilian pepper

Predicting severe wildfire years in the Florida Everglades

© 2003 The Ecological Society of America. Wildfires result in important ecological benefits to many ecosystems, but have costs associated with fire fighting and property loss. Accurate, timely forecasts of the severity of upcoming wildfire seasons could facilitate wildfire management, limiting the most destructive aspects of fires, while preserving their ecological benefits. We demonstrate an approach where time series models are used to predict the severity of the wildfire season in Everglades National Park in southern Florida 3 months and 1 year beforehand. Model predictions contained all obserations within a 90% credible interval and also anticipated severe wildfire seasons. These models may be used to implement more ecologically sound wildfire management

Climate Seasonality, fire and global patterns of tree cover

Vegetation systems with varying levels of tree cover are widely distributed globally, but the determinants of vegetation and tree cover still lack a consistent global framework. How thesesystems\u27 distribution responds to spatial variability of climate seasonality and associated fire regimes therefore remains unclear. Here, we focus on tree cover distribution at the global level. We develop a model that accounts for the role of seasonality and moisture in the dynamics that link climate, fire and tree cover. We choose predictors that have a clear link to functional processes that control tree physiology and growth, such as freezing tolerance (accounted for in the variable growing season length, GSL) and the balance between water availability and evapotranspiration (accounted for in the variables moisture index and moisture season length). The results show that the relative importance of climate factors and fire frequency as determinants of tree cover hinges on the GSL conditions. For example, significant interactions of tree cover with fire only occur in regions with GSL of 6-7 months or of 12 months. Our data also show a general relationship between maximum tree cover and moisture at the global level that is not visible when examining precipitation. Discontinuities in this relationship occur with frequent fires found under specific levels of seasonal moisture and temperature. A common climatic trait of frequent fires is moisture with a pronounced seasonality and an overall negative balance over the growing season. Frequent fires allow grassland to persist where there could be savanna/woodland as in the case of the North American grasslands. Frequent fires also allow savanna to persist where there could be forest, as found in tropical regions. This quantitative work is useful in improving large-scale land-atmosphere models as well as for identifying conditions of vulnerability for ecosystem diversity

The limits to prediction in ecological systems

Predicting the future trajectories of ecological systems is increasingly important as the magnitude of anthropogenic perturbation of the earth systems grows.We distinguish between two types of predictability: the intrinsic or theoretical predictability of a system and the realized predictability that is achieved using available models and parameterizations. We contend that there are strong limits on the intrinsic predictability of ecological systems that arise from inherent characteristics of biological systems. While the realized predictability of ecological systems can be limited by process and parameter misspecification or uncertainty, we argue that the intrinsic predictability of ecological systems is widely and strongly limited by computational irreducibility. When realized predictability is low relative to intrinsic predictability, prediction can be improved through improved model structure or specification of parameters. Computational irreducibility, however, asserts that future states of the system cannot be derived except through computation of all of the intervening states, imposing a strong limit on the intrinsic or theoretical predictability. We argue that ecological systems are likely to be computationally irreducible because of the difficulty of pre-stating the relevant features of ecological niches, the complexity of ecological systems and because the biosphere can enable its own novel system states or adjacent possible. We argue that computational irreducibility is likely to be pervasive and to impose strong limits on the potential for prediction in ecology. Copyright

Multiplex lexical networks reveal patterns in early word acquisition in children

Network models of language have provided a way of linking cognitive processes to language structure. However, current approaches focus only on one linguistic relationship at a time, missing the complex multi-relational nature of language. In this work, we overcome this limitation by modelling the mental lexicon of English-speaking toddlers as a multiplex lexical network, i.e. a multi-layered network where N = 529 words/nodes are connected according to four relationship: (i) free association, (ii) feature sharing, (iii) co-occurrence, and (iv) phonological similarity. We investigate the topology of the resulting multiplex and then proceed to evaluate single layers and the full multiplex structure on their ability to predict empirically observed age of acquisition data of English speaking toddlers. We find that the multiplex topology is an important proxy of the cognitive processes of acquisition, capable of capturing emergent lexicon structure. In fact, we show that the multiplex structure is fundamentally more powerful than individual layers in predicting the ordering with which words are acquired. Furthermore, multiplex analysis allows for a quantification of distinct phases of lexical acquisition in early learners: while initially all the multiplex layers contribute to word learning, after about month 23 free associations take the lead in driving word acquisition

Small-scale genotypic richness stabilizes plot biomass and increases phenotypic variance in the invasive grass Phalaris arundinacea

Published by Oxford University Press on behalf of the Institute of Botany, Chinese Academy of Sciences and the Botanical Society of China. All rights reserved. Aims We aim to understand how small-scale genotypic richness and genotypic interactions influence the biomass and potential invasiveness of the invasive grass, Phalaris arundinacea under two different disturbance treatments: intact plots and disturbed plots, where all the native vegetation has been removed. Specifically, we address the following questions (i) Does genotypic richness increase biomass production? (ii) Do genotypic interactions promote or reduce biomass production? (iii) Does the effect of genotypic richness and genotypic interactions differ in different disturbance treatments? Finally (iv) Is phenotypic variation greater as genotypic richness increases? Methods We conducted a 2-year common garden experiment in which we manipulated genotype richness using eight genotypes planted under both intact and disturbed conditions in a wetland in Burlington, Vermont (44°27′23″N, 73°11′29″W). The experiment consisted of a randomized complete block design of three blocks, each containing 20 plots (0.5 m 2) per disturbed treatment. We calculated total plot biomass and partitioned the net biodiversity effect into three components: dominance effect, trait-dependent complementarity and trait-independent complementarity. We calculated the phenotypic variance for each different genotype richness treatment under the two disturbance treatments. Important Findings Our results indicate that local genotypic richness does not increase total biomass production of the invasive grass P. arundinacea in either intact or disturbed treatments. However, genotypic interactions underlying the responses showed very different patterns in response to increasing genotypic richness. In the intact treatment, genotypic interactions resulted in the observed biomass being greater than the predicted biomass from monoculture plots (e.g., overyielding) and this was driven by facilitation. However, facilitation was reduced as genotypic richness increased. In the disturbed treatment, genotypic interactions resulted in underyielding with observed biomass being slightly less than expected from the performance of genotypes in monocultures; however, underyielding was reduced as genotypic richness increased. Thus, in both treatments, higher genotypic richness resulted in plot biomass nearing the additive biomass from individual monocultures. In general, higher genotypic richness buffered populations against interactions that would have reduced biomass and potentially spread. Phenotypic variance also had contrasting patterns in intact and disturbed treatments. In the intact treatment, phenotypic variance was low across all genotypic richness levels, while in the disturbed treatment, phenotypic variance estimates increased as genotypic richness increased. Thus, under the disturbed treatment, plots with higher genotypic richness had a greater potential response to selection. Therefore, limiting the introduction of new genotypes, even if existing genotypes of the invasive species are already present, should be considered a desirable management strategy to limit the invasive behavior of alien species

Cognitive network science: A review of research on cognition through the lens of network representations, processes, and dynamics

10.1155/2019/2108423Complexity2019210842

Simulating phase transitions and control measures for network epidemics caused by infections with presymptomatic, asymptomatic, and symptomatic stages

This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. We investigate phase transitions associated with three control methods for epidemics on small world networks. Motivated by the behavior of SARS-CoV-2, we construct a theoretical SIR model of a virus that exhibits presymptomatic, asymptomatic, and symptomatic stages in two possible pathways. Using agent-based simulations on small world networks, we observe phase transitions for epidemic spread related to: 1) Global social distancing with a fixed probability of adherence. 2) Individually initiated social isolation when a threshold number of contacts are infected. 3) Viral shedding rate. The primary driver of total number of infections is the viral shedding rate, with probability of social distancing being the next critical factor. Individually initiated social isolation was effective when initiated in response to a single infected contact. For each of these control measures, the total number of infections exhibits a sharp phase transition as the strength of the measure is varied