581 research outputs found
Seed terminal velocity, wind turbulence and demography drive the spread of an invasive tree in an analytical model
Little is known about the relative importance of mechanistic drivers of plant spread, particularly when long-distance dispersal (LDD) events occur. Most methods to date approach LDD phenomenologically, and all mechanistic models, with one exception, have been implemented through simulation. Furthermore, the few recent mechanistically derived spread models have examined the relative role of different dispersal parameters using simulations, and a formal analytical approach has not yet been implemented. Here we incorporate an analytical mechanistic wind dispersal model (WALD) into a demographic matrix model within an analytical integrodifference equation spread model. We carry out analytical perturbation analysis on the combined model to determine the relative effects of dispersal and demographic traits and wind statistics on the spread of an invasive tree. Models are parameterized using data collected in situ and tested using independent data on historical spread. Predicted spread rates and direction match well the two historical phases of observed spread. Seed terminal velocity has the greatest potential influence on spread rate, and three wind properties (turbulence coefficient, mean horizontal wind speed, and standard deviation of vertical wind speed) are also important. Fecundity has marginal importance for spread rate, but juvenile survival and establishment are consistently important. This coupled empirical/theoretical framework enables prediction of plant spread rate and direction using fundamental dispersal and demographic parameters and identifies the traits and environmental conditions that facilitate spread. The development of an analytical perturbation analysis for a mechanistic spread model will enable multispecies comparative studies to be easily implemented in the future
Usefulness of species traits in predicting range shifts
Information on species’ ecological traits might improve predictions of climate-driven range shifts. However, the usefulness of traits is usually assumed rather than quantified. We present a framework to identify the most informative traits, based on four key range-shift processes: (i) emigration of individuals or propagules away from the natal location, (ii) the distance a species can move, (iii) establishment of self-sustaining populations, and (iv) proliferation following establishment. We propose a framework that categorises traits according to their contribution to range-shift processes. We demonstrate how the framework enables the predictive value of traits to be evaluated empirically, how this categorisation can be used to better understand range shift processes, and illustrate how range shift estimates can be improved
Electrical valley filtering in transition metal dichalcogenides
This work investigates the feasibility of electrical valley filtering for
holes in transition metal dichalcogenides. We look specifically into the scheme
that utilizes a potential barrier to produce valley-dependent tunneling rates,
and perform the study with both a k.p based analytic method and a recursive
Green's function based numerical method. The study yields the transmission
coefficient as a function of incident energy and transverse wave vector, for
holes going through lateral quantum barriers oriented in either armchair or
zigzag directions, in both homogeneous and heterogeneous systems. The main
findings are the following: 1) the tunneling current valley polarization
increases with increasing barrier width or height, 2) both the valley-orbit
interaction and band structure warping contribute to valley-dependent
tunneling, with the former contribution being manifest in structures with
asymmetric potential barriers, and the latter being orientation-dependent and
reaching maximum for transmission in the armchair direction, and 3) for
transmission ~ 0.1, a tunneling current valley polarization of the order of 10%
can be achieved.Comment: 12 pages, 8 figure
The efficiency of individual optimization in the conditions of competitive growth
The paper aims to discuss statistical properties of the multi-agent based
model of competitive growth. Each of the agents is described by growth (or
decay) rule of its virtual "mass" with the rate affected by the interaction
with other agents. The interaction depends on the strategy vector and mutual
distance between agents and both are subjected to the agent's individual
optimization process. Steady-state simulations yield phase diagrams with the
high and low competition phases (HCP and LCP, respectively) separated by
critical point. Particular focus has been made on the indicators of the
power-law behavior of the mass distributions with respect to the critical
regime. In this regime the study has revealed remarkable anomaly in the
optimization efficiency
Impacts of global change on species distributions: obstacles and solutions to integrate climate and land use
Aim The impact of multiple stressors on biodiversity is one of the most pressing questions in ecology and biodiversity conservation. Here we critically assess how often and efficiently two main drivers of global change have been simultaneously integrated into research, with the aim of providing practical solutions for better integration in the future. We focus on the integration of climate change (CC) and land-use change (LUC) when studying changes in species distributions. Location Global. Methods We analysed the peer-reviewed literature on the effects of CC and LUC on observed changes in species distributions, i.e. including species range and abundance, between 2000 and 2014. Results Studies integrating CC and LUC remain extremely scarce, which hampers our ability to develop appropriate conservation strategies. The lack of CC-LUC integration is likely to be a result of insufficient recognition of the co-occurrence of CC and LUC at all scales, covariation and interactions between CC and LUC, as well as correlations between species thermal and habitat requirements. Practical guidelines for the study of these interactive effects include considering multiple drivers and processes when designing studies, using available long-term datasets on multiple drivers, revisiting single-driver studies with additional drivers or conducting comparative studies and meta-analyses. Combining various methodological approaches, including time lags and adaptation processes, represent further avenues to improve global change science. Main conclusions Despite repeated claims for a better integration of multiple drivers, the effects of CC and LUC on species distributions and abundances have been mostly studied in isolation, which calls for a shift of standards towards more integrative global change science. The guidelines proposed here will encourage study designs that account for multiple drivers and improve our understanding of synergies or antagonisms among drivers
Predicting future stability of ecosystem functioning under climate change
To maintain food security under global change, we need to consider the stability of ecosystem functioning into the future, particularly in resource production landscapes such as agricultural pasture. With ongoing climate change, extreme climatic events are predicted to become more frequent and severe globally, impacting crop production. The whole process of farming will become more uncertain, from choice of crop and crop productivity to the timing of the windows of opportunity for management decisions. Future agricultural policies, therefore, should not only consider changes in grassland production, but also its future stability. We use a case study of agricultural pastures on the island of Ireland to project different components of ecosystem stability (resistance, recovery time and recovery rate) to 2050 and 2080 under different future climate scenarios: a peak and decline scenario; and a continued emissions scenario. We show that future climate change will have substantial effects on both the future resistance and the recovery of ecosystem functioning following environmental disturbances, but the spatial pattern of effect sizes is not the same for these two measures of stability. National level analyses and agricultural policies, therefore, are likely to ignore regional variation in future change. From this, we encourage the translation of stability-based constructs, as well as maximum yield considerations, into future agricultural policy at the regional level
Methods and approaches to advance soil macroecology
Motivation and aim Soil biodiversity is central to ecosystem function and services. It represents most of terrestrial biodiversity and at least a quarter of all biodiversity on Earth. Yet, research into broad, generalizable spatial and temporal patterns of soil biota has been limited compared to aboveground systems due to complexities of the soil system. We review the literature and identify key considerations necessary to expand soil macroecology beyond the recent surge of global maps of soil taxa, so that we can gain greater insight into the mechanisms and processes shaping soil biodiversity. We focus primarily on three groups of soil taxa (earthworms, mycorrhizal fungi and soil bacteria) that represent a range of body sizes and ecologies, and, therefore, interact with their environment at different spatial scales. Results The complexities of soil, including fine-scale heterogeneity, 3-D habitat structure, difficulties with taxonomic delimitation, and the wide-ranging ecologies of its inhabitants, require the classical macroecological toolbox to be expanded to consider novel sampling, molecular identification, functional approaches, environmental variables, and modelling techniques. Main conclusions Soil provides a complex system within which to apply macroecological research, yet, it is this property that itself makes soil macroecology a field ripe for innovative methodologies and approaches. To achieve this, soil-specific data, spatio-temporal, biotic, and abiotic considerations are necessary at all stages of research, from sampling design to statistical analyses. Insights into whole ecosystems and new approaches to link genes, functions and diversity across spatial and temporal scales, alongside methodologies already applied in aboveground macroecology, invasion ecology and aquatic ecology, will facilitate the investigation of macroecological processes in soil biota, which is key to understanding the link between biodiversity and ecosystem functioning in terrestrial ecosystems
Ecosystem stability at the landscape scale is primarily associated with climatic history
There is an increasing interest in landscape-scale perspectives of ecosystem functioning to inform policy and conservation decisions. However, we need a better understanding of the stability of ecosystem functioning (e.g. plant productivity) at the landscape scale to inform policy around topics such as global food security.
We investigate the role of the ecological and environmental context on landscape-scale stability of plant productivity in agricultural pasture using remotely sensed enhanced vegetation index data. We determine whether four measures of stability (variability, magnitude of extreme anomalies, recovery time and recovery rate) are predicted by (a) species richness of vascular plants, (b) regional land cover heterogeneity and (c) climatic history.
Stability of plant productivity was primarily associated with climatic history, particularly a history of extreme events. These effects outweighed any positive effects of species richness in the agricultural landscape.
A history of variable and extreme climates both increased and decreased contemporary ecosystem stability, suggesting both cumulative and legacy effects, whereas land cover heterogeneity had no effect on stability.
The landscape scale is a relevant spatial scale for the management of an ecosystem's stability. At this scale, we find that past climate is a stronger driver of stability in plant productivity than species richness, differing from results at finer field scales. Management should take an integrated approach by incorporating the environmental context of the landscape, such as its climatic history, and consider multiple components of stability to maintain functioning in landscapes that are particularly vulnerable to environmental change
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