ORCID Profile
0000-0002-5816-7693
Current Organisation
Monash University
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Publisher: Elsevier BV
Date: 10-2013
Publisher: Springer International Publishing
Date: 2022
Publisher: Springer Science and Business Media LLC
Date: 26-02-2014
Publisher: Elsevier BV
Date: 11-2015
Publisher: Elsevier BV
Date: 10-2012
Publisher: Wiley
Date: 23-08-2012
DOI: 10.1111/J.1461-0248.2012.01854.X
Abstract: Large-scale habitat destruction and climate change result in the non-random loss of evolutionary lineages, reducing the amount of evolutionary history represented in ecological communities. Yet, we have limited understanding of the consequences of evolutionary history on the structure of food webs and the services provided by biological communities. Drawing on 11 years of data from a long-term plant ersity experiment, we show that evolutionary history of plant communities - measured as phylogenetic ersity - strongly predicts ersity and abundance of herbivorous and predatory arthropods. Effects of plant species richness on arthropods become stronger when phylogenetic ersity is high. Plant phylogenetic ersity explains predator and parasitoid richness as strongly as it does herbivore richness. Our findings indicate that accounting for evolutionary relationships is critical to understanding the severity of species loss for food webs and ecosystems, and for developing conservation and restoration policies.
Publisher: Elsevier BV
Date: 09-2023
Publisher: Elsevier BV
Date: 11-2011
Publisher: Informa UK Limited
Date: 23-09-2015
Publisher: Elsevier BV
Date: 2021
Publisher: Elsevier BV
Date: 08-2003
Publisher: IEEE
Date: 14-06-2023
Publisher: Wiley
Date: 25-07-2014
DOI: 10.1111/MICE.12035
Publisher: Informa UK Limited
Date: 10-06-2015
Publisher: Elsevier BV
Date: 06-2021
Publisher: Elsevier BV
Date: 10-2021
Publisher: Informa UK Limited
Date: 09-01-2019
Publisher: Elsevier BV
Date: 07-2016
Publisher: Elsevier BV
Date: 2021
Publisher: Wiley
Date: 18-01-2021
DOI: 10.1002/ECY.3218
Publisher: Wiley
Date: 31-12-2019
DOI: 10.1111/GCB.14904
Abstract: Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to bio ersity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on in idual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.
Publisher: American Society of Civil Engineers
Date: 02-07-2019
Publisher: Springer Science and Business Media LLC
Date: 08-08-2020
Publisher: Springer Science and Business Media LLC
Date: 25-07-2022
DOI: 10.1038/S41559-022-01809-9
Abstract: Ecological models predict that the effects of mammalian herbivore exclusion on plant ersity depend on resource availability and plant exposure to ungulate grazing over evolutionary time. Using an experiment replicated in 57 grasslands on six continents, with contrasting evolutionary history of grazing, we tested how resources (mean annual precipitation and soil nutrients) determine herbivore exclusion effects on plant ersity, richness and evenness. Here we show that at sites with a long history of ungulate grazing, herbivore exclusion reduced plant ersity by reducing both richness and evenness and the responses of richness and ersity to herbivore exclusion decreased with mean annual precipitation. At sites with a short history of grazing, the effects of herbivore exclusion were not related to precipitation but differed for native and exotic plant richness. Thus, plant species' evolutionary history of grazing continues to shape the response of the world's grasslands to changing mammalian herbivory.
Publisher: Elsevier BV
Date: 05-2016
Publisher: IEEE
Date: 03-11-2020
Publisher: Elsevier BV
Date: 02-2016
Publisher: SAGE Publications
Date: 04-04-2019
Abstract: The accurate depiction of the existing traffic state on a road network is essential in reducing congestion and delays at signalized intersections. The existing literature in the optimization of signal timings either utilizes prediction of traffic state from traffic flow models or limited real-time measurements available from sensors. Prediction of traffic state based on historic data cannot represent the dynamics of change in traffic demand or network capacity. Similarly, data obtained from limited point sensors in a network provides estimates which contain errors. A reliable estimate of existing traffic state is, therefore, necessary to obtain signal timings which are based on the existing condition of traffic on the network. This research proposes a framework which utilizes estimates of traffic flows and travel times based on real-time estimated traffic state for obtaining optimal signal timings. The prediction of traffic state from the cell transmission model (CTM) and measurements from traffic sensors are combined in the recursive algorithm of extended Kalman filter (EKF) to obtain a reliable estimate of existing traffic state. The estimate of traffic state obtained from the CTM-EKF model is utilized in the optimization of signal timings using genetic algorithm (GA) in the proposed CTM-EKF-GA framework. The proposed framework is applied to a synthetic signalized intersection and the results are compared with a model-based optimal solution and simulated reality. The optimal delay estimated by CTM-EKF-GA framework is only 0.6% higher than the perfect solution, whereas the delay estimated by CTM-GA model is 12.9% higher than the perfect solution.
Publisher: Elsevier BV
Date: 07-2021
Publisher: Elsevier BV
Date: 12-2019
Publisher: Informa UK Limited
Date: 2006
Publisher: Informa UK Limited
Date: 15-01-2014
Publisher: Informa UK Limited
Date: 06-02-2019
Publisher: Authorea, Inc.
Date: 20-05-2022
DOI: 10.22541/AU.164197604.41103734/V3
Abstract: Global change drivers such as anthropogenic nutrient inputs simultaneously alter bio ersity, species composition, and ecosystem functions such as aboveground biomass. These changes are interconnected by complex feedbacks among extinction, colonization, and shifting relative abundance. Here, we use a novel temporal application of the Price equation to quantify the functional contributions of species that are lost, gained, and persist under ambient and experimental nutrient addition in 59 global grasslands. Under ambient conditions, compositional and biomass turnover was high, but species losses (i.e., local extinctions) were balanced by gains (i.e. colonization). There was biomass loss associated with species loss under fertilization. Few species were gained in fertilized conditions over time but those that were, and species that persisted, contributed to net biomass gains, outweighing biomass loss. These components of community change are key to understanding the relationship between change in composition, ersity and functioning.
Publisher: Authorea, Inc.
Date: 06-05-2022
Publisher: SAGE Publications
Date: 2005
DOI: 10.1177/0361198105192300108
Abstract: The traffic control task in heterogeneous multilane motorways and urban networks is complicated because it concerns multiple objectives and multiple target groups (user classes). Furthermore, it is characterized by large differences in driving behaviors between user classes and network types. The latter are caused by the interaction between user classes, the interplay between control measures, and the interaction between different parts of the networks. This complexity requires a model-based approach for achieving better understanding of the complicated process at hand and for the subsequent efficient control of these processes, for ex le, by applying model-based optimal controls. However, the contemporary macroscopic traffic flow models for urban networks are deficient in that they fail to deal adequately with heterogeneous traffic on multilane links. The aim of this paper is to devise a much more elaborate macroscopic traffic flow model, focusing on urban networks, to be able to cope with the complex control task and its application. The model proposed here is then implemented in the urban part of a computer-based network model, HELENA.
Publisher: Authorea, Inc.
Date: 12-01-2022
DOI: 10.22541/AU.164197604.41103734/V1
Abstract: Global change drivers such as anthropogenic nutrient inputs simultaneously alter bio ersity, species composition, and ecosystem functions such as above ground biomass. These changes are interconnected by complex feedbacks among extinction, invasion, and shifting relative abundance. Here, we use a novel temporal application of the Price equation to separate species richness and biomass change through time and quantify the functional contributions of species that are lost, gained, and persist under ambient and experimental nutrient addition in 59 global grasslands. Under ambient conditions, compositional and biomass turnover was high, but species losses (i.e., local extinctions) were balanced by gains (i.e. colonization). Under fertilization, there was biomass loss associated with species loss. Few species were gained in fertilized conditions over time but those that were, and species that persisted, contributed to net biomass gains, outweighing biomass loss. These components of community change are associated with distinct effects on measures of ecosystem functioning.
Publisher: Institution of Engineering and Technology (IET)
Date: 12-2020
Publisher: Wiley
Date: 25-08-2021
DOI: 10.1002/ECY.3504
Abstract: Spatial rarity is often used to predict extinction risk, but rarity can also occur temporally. Perhaps more relevant in the context of global change is whether a species is core to a community (persistent) or transient (intermittently present), with transient species often susceptible to human activities that reduce niche space. Using 5-12 yr of data on 1,447 plant species from 49 grasslands on five continents, we show that local abundance and species persistence under ambient conditions are both effective predictors of local extinction risk following experimental exclusion of grazers or addition of nutrients persistence was a more powerful predictor than local abundance. While perturbations increased the risk of exclusion for low persistence and abundance species, transient but abundant species were also highly likely to be excluded from a perturbed plot relative to ambient conditions. Moreover, low persistence and low abundance species that were not excluded from perturbed plots tended to have a modest increase in abundance following perturbance. Last, even core species with high abundances had large decreases in persistence and increased losses in perturbed plots, threatening the long-term stability of these grasslands. Our results demonstrate that expanding the concept of rarity to include temporal dynamics, in addition to local abundance, more effectively predicts extinction risk in response to environmental change than either rarity axis predicts alone.
Publisher: Informa UK Limited
Date: 2008
Publisher: Elsevier BV
Date: 08-2019
Publisher: Elsevier BV
Date: 08-2019
Publisher: Elsevier BV
Date: 10-2021
Publisher: Informa UK Limited
Date: 28-07-2021
Publisher: Wiley
Date: 23-09-2023
Publisher: Elsevier BV
Date: 2014
Publisher: Elsevier BV
Date: 06-2022
Publisher: Informa UK Limited
Date: 24-09-2019
Publisher: Informa UK Limited
Date: 08-2013
Publisher: Wiley
Date: 22-11-2021
DOI: 10.1002/ECE3.8266
Abstract: Biotic and abiotic factors interact with dominant plants—the locally most frequent or with the largest coverage—and nondominant plants differently, partially because dominant plants modify the environment where nondominant plants grow. For instance, if dominant plants compete strongly, they will deplete most resources, forcing nondominant plants into a narrower niche space. Conversely, if dominant plants are constrained by the environment, they might not exhaust available resources but instead may ameliorate environmental stressors that usually limit nondominants. Hence, the nature of interactions among nondominant species could be modified by dominant species. Furthermore, these differences could translate into a disparity in the phylogenetic relatedness among dominants compared to the relatedness among nondominants. By estimating phylogenetic dispersion in 78 grasslands across five continents, we found that dominant species were clustered (e.g., co‐dominant grasses), suggesting dominant species are likely organized by environmental filtering, and that nondominant species were either randomly assembled or overdispersed. Traits showed similar trends for those sites ( %) with sufficient trait data. Furthermore, several lineages scattered in the phylogeny had more nondominant species than expected at random, suggesting that traits common in nondominants are phylogenetically conserved and have evolved multiple times. We also explored environmental drivers of the dominant/nondominant disparity. We found different assembly patterns for dominants and nondominants, consistent with asymmetries in assembly mechanisms. Among the different postulated mechanisms, our results suggest two complementary hypotheses seldom explored: (1) Nondominant species include lineages adapted to thrive in the environment generated by dominant species. (2) Even when dominant species reduce resources to nondominant ones, dominant species could have a stronger positive effect on some nondominants by ameliorating environmental stressors affecting them, than by depleting resources and increasing the environmental stress to those nondominants. These results show that the dominant/nondominant asymmetry has ecological and evolutionary consequences fundamental to understand plant communities.
Publisher: Elsevier BV
Date: 2018
Publisher: Wiley
Date: 27-07-2022
DOI: 10.1111/MICE.12895
Abstract: Large‐scale urban networks are usually loaded heterogeneously with a polycentric congestion pattern, resulting in a highly scattered network macroscopic fundamental diagram (NMFD or MFD). Thus, researchers have tried to partition city networks into homogeneous subzones. In this study, a six‐step partitioning algorithm is proposed. The framework allows the NMFD information to be used. It combines traffic variables and geographic connectivity to obtain partitions. The framework includes graph definition, data preprocessing, feature handling, clusters and partitions identification, and boundaries reshaping. Tests on a simplified grid network and the city of the Melbourne road network demonstrate the suitability of the framework for characterizing the traffic states by the partitions. The framework on the missing data scenarios and monocentric and polycentric traffic concentrations scenarios, as well as applying multiple data types, has been challenged. Thereafter, parameter impact analysis demonstrates that manipulation of the parameters enables users to find the desired partitions. Last but not least, a comparison with an existing method also implies the uniqueness and efficiency of the developed framework.
Publisher: Elsevier BV
Date: 09-2019
Publisher: Elsevier BV
Date: 04-2019
Publisher: Wiley
Date: 08-2012
DOI: 10.1890/11-0426.1
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 10-2017
Publisher: SAGE Publications
Date: 2011
DOI: 10.3141/2260-13
Abstract: Data assimilation techniques are a process of using measurements combined with model predictions to (optimally) estimate the value of a certain set of variables. These techniques belong to a group of model-based estimation approaches. In traffic science, the Kalman filter and its family, namely, the extended Kalman filter (EKF), have been widely applied to problems of traffic state estimation. The EKF is successful for computation and provides some reasonably accurate results. However, traffic systems are generally so nonlinear that the linearization used in the EKF is not always straightforward. To avoid such linearization, another family of Kalman filter, the unscented Kalman filter (UKF), has been designed to account for the nonlinear system in which a set of deterministic s le points is chosen to capture the initial probability distribution. These s le points are then propagated through the nonlinear system, and the probability density function of the actual state is approximated by the ensemble of the estimates. In the UKF, the number of s le points is determined by the dimension of the states to be estimated so that it becomes computationally expensive when the size of traffic networks is increased. Thus an effort was made to approximate a UKF in which the required s le points were reduced. Numerical experiments were carried out to assess the relevance of the proposed approach with real traffic data, and comparisons with the UKF for the level of accuracy and computational time were made.
Publisher: SAGE Publications
Date: 2009
DOI: 10.3141/2124-10
Abstract: Intelligent transportation systems have been considered an important solution in enhancing freeway capacity and suppressing traffic congestion. One recent automotive technology has enabled a vehicle to communicate with several vehicles ahead via a wireless system. Such a communication system constitutes so-called multianticipative driving behavior. In general, the effect of multianticipative interactions on traffic flow dynamics has been studied widely in the literature on the basis of a microscopic modeling approach. This paper presents an alternative approach to gain insights into the effect of multianticipative driving behavior on traffic flow characteristics from a macroscopic model. The model is obtained from a gas-kinetic theory in which the multianticipative interactions are taken into consideration. It is found that the analytical and numerical results of the model are consistent with those obtained from microscopic models. It is argued that the results provide a better understanding of the effect of multianticipative interactions on traffic flow characteristics.
Publisher: Elsevier BV
Date: 2023
DOI: 10.2139/SSRN.4442134
Publisher: Informa UK Limited
Date: 2006
Publisher: Informa UK Limited
Date: 03-2011
Publisher: Informa UK Limited
Date: 16-09-2020
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 08-2016
Publisher: SAGE Publications
Date: 2010
DOI: 10.3141/2188-13
Abstract: Traffic state estimation problems must deal with imperfect information. Imperfect information may occur as a result of misalignments between reality and the assumptions or simplifications made when developing the models as well as incomplete or corrupted data. One of the well-known methods of handling imperfect information is the Kalman filter algorithm and its variations, such as the extended Kalman filter and the unscented Kalman filter. While the standard Kalman filter and the extended Kalman filter have been widely applied to the state estimation of linear systems, the unscented Kalman filter has been reported the better choice in the multiclass traffic state estimation. In many applications of Kalman filters to traffic estimation problems, the model and measurement noise covariance matrices are normally estimated. When there is a mismatch between the true and the assumed noise distribution, however, the filter often suffers from performance degradation and even ergence in certain situations. To this end, this paper presents a more efficient and accurate algorithm embedded in the unscented Kalman filter to simultaneously estimate the traffic state and the model noise distribution statistics. The proposed method is facilitated through a simultaneous update of the model noise covariance matrix in the predicted covariance equations of the unscented Kalman filter algorithm. It is found through simulation that the proposed algorithm may improve the model performance over the standard algorithm.
Publisher: Elsevier BV
Date: 10-2016
Publisher: Wiley
Date: 15-11-2011
Publisher: Elsevier BV
Date: 10-2018
Publisher: Informa UK Limited
Date: 29-12-2018
Publisher: Informa UK Limited
Date: 21-03-2017
Publisher: Informa UK Limited
Date: 2012
Publisher: Wiley
Date: 06-2023
DOI: 10.1002/ECS2.4542
Abstract: Human activities are altering ecological communities around the globe. Understanding the implications of these changes requires that we consider the composition of those communities. However, composition can be summarized by many metrics which in turn are influenced by different ecological processes. For ex le, incidence‐based metrics strongly reflect species gains or losses, while abundance‐based metrics are minimally affected by changes in the abundance of small or uncommon species. Furthermore, metrics might be correlated with different predictors. We used a globally distributed experiment to examine variation in species composition within 60 grasslands on six continents. Each site had an identical experimental and s ling design: 24 plots × 4 years. We expressed compositional variation within each site—not across sites—using abundance‐ and incidence‐based metrics of the magnitude of dissimilarity (Bray–Curtis and Sorensen, respectively), abundance‐ and incidence‐based measures of the relative importance of replacement (balanced variation and species turnover, respectively), and species richness at two scales (per plot‐year [alpha] and per site [gamma]). Average compositional variation among all plot‐years at a site was high and similar to spatial variation among plots in the pretreatment year, but lower among years in untreated plots. For both types of metrics, most variation was due to replacement rather than nestedness. Differences among sites in overall within‐site compositional variation were related to several predictors. Environmental heterogeneity (expressed as the CV of total aboveground plant biomass in unfertilized plots of the site) was an important predictor for most metrics. Biomass production was a predictor of species turnover and of alpha ersity but not of other metrics. Continentality (measured as annual temperature range) was a strong predictor of Sorensen dissimilarity. Metrics of compositional variation are moderately correlated: knowing the magnitude of dissimilarity at a site provides little insight into whether the variation is driven by replacement processes. Overall, our understanding of compositional variation at a site is enhanced by considering multiple metrics simultaneously. Monitoring programs that explicitly incorporate these implications, both when designing s ling strategies and analyzing data, will have a stronger ability to understand the compositional variation of systems and to quantify the impacts of human activities.
Publisher: Informa UK Limited
Date: 25-06-2022
Publisher: Wiley
Date: 2021
Abstract: 1. To be effective, the next generation of conservation practitioners and managers need to be critical thinkers with a deep understanding of how to make evidence‐based decisions and of the value of evidence synthesis. 2. If, as educators, we do not make these priorities a core part of what we teach, we are failing to prepare our students to make an effective contribution to conservation practice. 3. To help overcome this problem we have created open access online teaching materials in multiple languages that are stored in Applied Ecology Resources. So far, 117 educators from 23 countries have acknowledged the importance of this and are already teaching or about to teach skills in appraising or using evidence in conservation decision‐making. This includes 145 undergraduate, postgraduate or professional development courses. 4. We call for wider teaching of the tools and skills that facilitate evidence‐based conservation and also suggest that providing online teaching materials in multiple languages could be beneficial for improving global understanding of other subject areas.
Publisher: Institution of Engineering and Technology (IET)
Date: 24-02-2020
Publisher: Springer Science and Business Media LLC
Date: 27-05-2016
Publisher: Elsevier BV
Date: 2018
Publisher: Elsevier BV
Date: 07-2009
Publisher: Wiley
Date: 31-10-2021
Abstract: Plant damage by invertebrate herbivores and pathogens influences the dynamics of grassland ecosystems, but anthropogenic changes in nitrogen and phosphorus availability can modify these relationships. Using a globally distributed experiment, we describe leaf damage on 153 plant taxa from 27 grasslands worldwide, under ambient conditions and with experimentally elevated nitrogen and phosphorus. Invertebrate damage significantly increased with nitrogen addition, especially in grasses and non‐leguminous forbs. Pathogen damage increased with nitrogen in grasses and legumes but not forbs. Effects of phosphorus were generally weaker. Damage was higher in grasslands with more precipitation, but climatic conditions did not change effects of nutrients on leaf damage. On average, invertebrate damage was relatively higher on legumes and pathogen damage was relatively higher on grasses. Community‐weighted mean damage reflected these functional group patterns, with no effects of N on community‐weighted pathogen damage (due to opposing responses of grasses and forbs) but stronger effects of N on community‐weighted invertebrate damage (due to consistent responses of grasses and forbs). Synthesis . As human‐induced inputs of nitrogen and phosphorus continue to increase, understanding their impacts on invertebrate and pathogen damage becomes increasingly important. Our results demonstrate that eutrophication frequently increases plant damage and that damage increases with precipitation across a wide array of grasslands. Invertebrate and pathogen damage in grasslands is likely to increase in the future, with potential consequences for plant, invertebrate and pathogen communities, as well as the transfer of energy and nutrients across trophic levels.
Publisher: Elsevier BV
Date: 08-2016
Publisher: Elsevier BV
Date: 03-2021
Publisher: Proceedings of the National Academy of Sciences
Date: 06-07-2021
Abstract: Predicting the effects of anthropogenic nutrient enrichment on plant communities is critical for managing implications for bio ersity and ecosystem services. Plant functional types that fix atmospheric nitrogen (e.g., legumes) may be at particular risk of nutrient-driven global decline, yet global-scale evidence is lacking. Using an experiment in 45 grasslands across six continents, we showed that legume cover, richness, and biomass declined substantially with nitrogen additions. Although legumes benefited from phosphorus, potassium, and other nutrients, these nutrients did not ameliorate nitrogen-induced legume decline. Given global trends in anthropogenic nutrient enrichment, our results indicate the potential for global decline in grassland legumes, with likely consequences for bio ersity, food webs, soil health, and genetic improvement of protein-rich plant species for food production.
Publisher: Elsevier BV
Date: 2023
DOI: 10.2139/SSRN.4440204
Publisher: SAGE Publications
Date: 21-03-2022
DOI: 10.1177/03611981221083289
Abstract: A variety of methods have been proposed in the existing literature for the estimation of passenger car equivalent (PCE) factors. These methods are based on the comparison of selected attributes of different vehicles. This research, for the first time, utilizes the basic notion of the linear relationship between road area occupancy and density for the estimation of PCE factors for different vehicle types in heterogeneous traffic. Aerial photographs obtained from an unmanned aerial vehicle (UAV) were analyzed to estimate the road area occupancy and the number of vehicles classified in seven selected groups. A linear least-squares regression model was developed between road area occupancy and classified vehicle count. The coefficients of the occupancy-density linear regression model were used to estimate PCE and motorcycle equivalent (MCE) factors. The comparison of the estimated set of PCE values with the values reported in the literature shows that PCE factors estimated using the proposed method are reasonable and produce a better occupancy-density relationship than the other studies. In comparison with the existing methods that rely on lane-based measurements, the proposed method is well suited for traffic with weak/no lane discipline, as it considers the entire road width and the dynamics of lateral movement of different types of vehicles. The proposed method does not need extensive traffic data of speeds, headways, flow rates, and so forth, and is applicable on aerial photographs obtained from other sources, such as satellites.
Publisher: Springer Science and Business Media LLC
Date: 13-01-2012
Publisher: Elsevier BV
Date: 05-2015
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 04-2022
Publisher: Elsevier BV
Date: 02-2013
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 12-2019
Publisher: Informa UK Limited
Date: 09-2013
Publisher: Elsevier BV
Date: 08-2003
Publisher: Wiley
Date: 17-07-2018
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2023
Publisher: Informa UK Limited
Date: 31-12-2020
Publisher: Springer Science and Business Media LLC
Date: 27-11-2020
DOI: 10.1038/S41467-020-19870-Y
Abstract: Human activities are transforming grassland biomass via changing climate, elemental nutrients, and herbivory. Theory predicts that food-limited herbivores will consume any additional biomass stimulated by nutrient inputs (‘consumer-controlled’). Alternatively, nutrient supply is predicted to increase biomass where herbivores alter community composition or are limited by factors other than food (‘resource-controlled’). Using an experiment replicated in 58 grasslands spanning six continents, we show that nutrient addition and vertebrate herbivore exclusion each caused sustained increases in aboveground live biomass over a decade, but consumer control was weak. However, at sites with high vertebrate grazing intensity or domestic livestock, herbivores consumed the additional fertilization-induced biomass, supporting the consumer-controlled prediction. Herbivores most effectively reduced the additional live biomass at sites with low precipitation or high ambient soil nitrogen. Overall, these experimental results suggest that grassland biomass will outstrip wild herbivore control as human activities increase elemental nutrient supply, with widespread consequences for grazing and fire risk.
Publisher: IOP Publishing
Date: 20-07-2009
Publisher: Elsevier BV
Date: 11-2007
Publisher: IEEE
Date: 11-2016
Publisher: SAGE Publications
Date: 2004
DOI: 10.3141/1876-06
Abstract: Accurate and reliable numerical algorithms for the solution of macroscopic traffic flow models are very important to ensure that the models' properties are accurately represented. An inappropriate numerical scheme may result in deviate or erratic model behavior, such as large numerical dissipations and numerical instabilities. A new computation scheme for the numerical approximation of solutions of Payne-type models is presented. This scheme is proved to satisfy the positive constraints of traffic variables and thus prevents traffic from moving upstream. In addition, an automated model calibration approach is proposed it is applied to determine the parameters of the considered macroscopic model for different numerical schemes (Steger-Warming, MacCormack, and the proposed numerical scheme). Predictions from the various numerical approximation models are compared with observations from the validation data set. On the basis of this comparison, it is concluded that the proposed numerical scheme is both more accurate and more robust than the other schemes considered. It yields a small mean squared error and fast computation due to the ability to use a larger time-step it also provides accurate results in regions in which the gradients of the speeds and densities are high.
Publisher: Elsevier BV
Date: 2023
Publisher: Wiley
Date: 09-04-2009
Publisher: Informa UK Limited
Date: 06-2021
Publisher: Springer Science and Business Media LLC
Date: 04-03-2006
Publisher: Elsevier BV
Date: 12-2023
Publisher: Elsevier BV
Date: 09-2023
Publisher: Elsevier BV
Date: 2008
Publisher: Elsevier BV
Date: 10-2013
Publisher: Elsevier BV
Date: 08-2021
Publisher: Informa UK Limited
Date: 21-01-2022
Publisher: Informa UK Limited
Date: 04-2010
Publisher: Informa UK Limited
Date: 02-01-2020
Publisher: Wiley
Date: 10-08-2005
Publisher: Open Book Publishers
Date: 06-12-2022
DOI: 10.11647/OBP.0321.12
Abstract: Delivering a revolution in evidence use requires a cultural change across society. For a wide range of groups (practitioners, knowledge brokers, organisations, organisational leaders, policy makers, funders, researchers, journal publishers, the wider conservation community, educators, writers, and journalists), options are described to facilitate a change in practice, and a series of downloadable checklists are provided.
Publisher: Springer Science and Business Media LLC
Date: 20-01-2021
DOI: 10.1038/S41467-021-20985-Z
Abstract: A Correction to this paper has been published: 0.1038/s41467-021-20985-z.
Location: United Kingdom of Great Britain and Northern Ireland
Start Date: 2011
End Date: 2016
Funder: Engineering and Physical Sciences Research Council
View Funded Activity