Ecological footprint (EF): An expanded role in calculating resource productivity (RP) using China and the G20 member countries as examples

AbstractAs resources become scarcer measuring resource productivity (RP) is more important. Quantifying the value of natural resources is challenging but the ecological footprint (EF) concept provides one method of uniformly describing a variety of natural resources. Current assessments of RP mainly revolve around output efficiency of resources, namely the ratio of GDP to natural resource usage.This paper develops a new method of calculating the RP by using the EF as an indicator of the natural resource input and gross domestic product (GDP) as the output in the equation of RP=GDP/EF. A regression analysis is carried out using GDP per capita and RP of China from 1997 to 2011, and a comparative analysis with the members of the G20 countries according to their RP and per capita GDP in 2008. The results indicate that RP correlates with the per capita GDP, showing that RP is a valid indicator which can be used to measure a country’s level of economic development

Abundance- and functional-based mechanisms of plant diversity loss with fertilization in the presence and absence of herbivores

Nutrient supply and herbivores can regulate plant species composition, biodiversity and functioning of terrestrial ecosystems. Nutrient enrichment frequently increases plant productivity and decreases diversity while herbivores tend to maintain plant diversity in productive systems. However, the mechanisms by which nutrient enrichment and herbivores regulate plant diversity remain unclear. Abundance-based mechanisms propose that fertilization leads to the extinction of rare species due to random loss of individuals of all species. In contrast, functional-based mechanisms propose that species exclusion is based on functional traits which are disadvantageous under fertilized conditions. We tested mechanistic links between fertilization and diversity loss in the presence or absence of consumers using data from a 4-year fertilization and fencing experiment in an alpine meadow. We found that both abundance- and functional-based mechanisms simultaneously affected species loss in the absence of herbivores while only abundance-based mechanisms affected species loss in the presence of herbivores. Our results indicate that an abundance-based mechanism may consistently play a role in the loss of plant diversity with fertilization, and that diversity decline is driven primarily by the loss of rare species regardless of a plant's functional traits and whether or not herbivores are present. Increasing efforts to conserve rare species in the context of ecosystem eutrophication is a central challenge for grazed grassland ecosystems

MMPosE: Movie-induced multi-label positive emotion classification through EEG signals

Emotional information plays an important role in various multimedia applications. Movies, as a widely available form of multimedia content, can induce multiple positive emotions and stimulate people's pursuit of a better life. Different from negative emotions, positive emotions are highly correlated and difficult to distinguish in the emotional space. Since different positive emotions are often induced simultaneously by movies, traditional single-target or multi-class methods are not suitable for the classification of movie-induced positive emotions. In this paper, we propose TransEEG, a model for multi-label positive emotion classification from a viewer's brain activities when watching emotional movies. The key features of TransEEG include (1) explicitly modeling the spatial correlation and temporal dependencies of multi-channel EEG signals using the Transformer structure based model, which effectively addresses long-distance dependencies, (2) exploiting the label-label correlations to guide the discriminative EEG representation learning, for that we design an Inter-Emotion Mask for guiding the Multi-Head Attention to learn the inter-emotion correlations, and (3) constructing an attention score vector from the representation-label correlation matrix to refine emotion-relevant EEG features. To evaluate the ability of our model for multi-label positive emotion classification, we demonstrate our model on a state-of-the-art positive emotion database CPED. Extensive experimental results show that our proposed method achieves superior performance over the competitive approaches

Space resource utilization of dominant species integrates abundance- and functional-based processes for better predictions of plant diversity dynamics

Sustainable ecosystem management relies on our ability to predict changes in plant diversity and to understand the underlying mechanisms. Empirical evidence demonstrates that abundance- and functional-based processes simultaneously explain the loss of plant diversity in response to human activities. Recently, a novel indicator based on percent cover (CoverD) and maximum height (HeightD) of the dominant plant species – space resource utilization (SRUD) – has proven to give robust and better predictions of plant diversity dynamics than community biomass. Whether the superior predictive ability of SRUD is due to its capacity to simultaneously capture abundance- and functional-based processes remains unknown. Here, we tested this hypothesis by quantifying mechanistic links between changes in SRUD and biodiversity in response to nutrients and herbivores. Furthermore, we assessed the relative contribution of dominant, intermediate and rare species to reduced density of individuals by combining null model analysis with field experiments. We found that SRUD successfully captured changes in ground-level light availability and changes in the number of individuals to predict plant diversity dynamics, and each of CoverD and HeightD partly and independently contributed to both processes. Comparative results from null model analysis and field experiments confirmed that individual losses of dominant, intermediate and rare species followed non-random processes. Specifically, compared with random loss process, rare species lost proportionally more individuals and thus disproportionately contributed to species loss, while dominant and intermediate species lost less. Our results demonstrate that SRUD captures both abundance- and functional-based processes thus explaining why SRUD provides more accurate predictions of changes in species diversity. Given that rare species can play an important role in shaping community structure, resisting against invasion, impacting higher trophic levels and providing multiple ecosystem functions, reducing the SRU of dominant species could alleviate the risk of exclusion of rare species by mitigating abundance- and functional-based competition processes

Linking changes in species composition and biomass in a globally distributed grassland experiment

Global change drivers, such as anthropogenic nutrient inputs, are increasing globally. Nutrient deposition simultaneously alters plant biodiversity, species composition and ecosystem processes like aboveground biomass production. These changes are underpinned by species extinction, colonisation and shifting relative abundance. Here, we use the Price equation to quantify and link the contributions of species that are lost, gained or that persist to change in aboveground biomass in 59 experimental grassland sites. Under ambient (control) conditions, compositional and biomass turnover was high, and losses (i.e. local extinctions) were balanced by gains (i.e. colonisation). Under fertilisation, the decline in species richness resulted from increased species loss and decreases in species gained. Biomass increase under fertilisation resulted mostly from species that persist and to a lesser extent from species gained. Drivers of ecological change can interact relatively independently with diversity, composition and ecosystem processes and functions such as aboveground biomass due to the individual contributions of species lost, gained or persisting.Fil: Ladouceur, Emma. Martin Luther University Halle-Wittenberg; Alemania. Universitat Leipzig; Alemania. German Centre for Integrative Biodiversity Research (iDiv) Leipzig-Halle-Jena; AlemaniaFil: Blowes, Shane A.. Martin Luther University Halle-Wittenberg; Alemania. German Centre for Integrative Biodiversity Research (iDiv) Leipzig-Halle-Jena; AlemaniaFil: Chase, Jonathan M.. German Centre for Integrative Biodiversity Research (iDiv) Leipzig-Halle-Jena; Alemania. Martin Luther University Halle-Wittenberg; AlemaniaFil: Clark, Adam T.. Martin Luther University Halle-Wittenberg; Alemania. German Centre for Integrative Biodiversity Research (iDiv) Leipzig-Halle-Jena; Alemania. University of Graz; AustriaFil: Garbowski, Magda. German Centre for Integrative Biodiversity Research (iDiv) Leipzig-Halle-Jena; Alemania. Universitat Leipzig; AlemaniaFil: Alberti, Juan. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata. Instituto de Investigaciones Marinas y Costeras. Universidad Nacional de Mar del Plata. Facultad de Ciencias Exactas y Naturales. Instituto de Investigaciones Marinas y Costeras; ArgentinaFil: Arnillas, Carlos Alberto. University of Toronto; CanadáFil: Bakker, Jonathan. University of Washington; Estados UnidosFil: Barrio, Isabel C.. Agricultural University of Iceland; IslandiaFil: Bharath, Siddharth. Atria University; IndiaFil: Borer, Elizabeth. University of Minnesota; Estados UnidosFil: Brudvig, Lars A.. Michigan State University; Estados UnidosFil: Cadotte, Marc W.. University of Toronto; CanadáFil: Chen, Qingqing. Peking University; ChinaFil: Collins, Scott L.. University of New Mexico; Estados UnidosFil: Dickman, Christopher R.. The University Of Sydney; AustraliaFil: Donohue, Ian. Trinity College Dublin; IrlandaFil: Du, Guozhen. Lanzhou University; ChinaFil: Ebeling, Anne. Universitat Jena; AlemaniaFil: Eisenhauer, Nico. Martin Luther University Halle—Wittenberg; Alemania. German Centre For Integrative Biodiversity Research (idiv) Halle-jena-leipzig; AlemaniaFil: Fay, Philip A.. USDA-ARS Grassland Soil and Water Research Lab; Estados UnidosFil: Hagenah, Nicole. University Of Pretoria; SudáfricaFil: Hautier, Yann. University of Utrecht; Países BajosFil: Jentsch, Anke. University of Bayreuth; AlemaniaFil: Jónsdóttir, Ingibjörg S.. University of Iceland; IslandiaFil: Komatsu, Kimberly J.. Smithsonian Environmental Research Center; Estados UnidosFil: MacDougall, Andrew. University of Guelph; CanadáFil: Martina, Jason P.. Texas State University; Estados UnidosFil: Moore, Joslin L.. Arthur Rylah Institute For Environmental Research; Australia. Monash University; AustraliaFil: Morgan, John W.. La Trobe University; AustraliaFil: Peri, Pablo Luis. Instituto Nacional de Tecnología Agropecuaria; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin

Grassland productivity limited by multiple nutrients

Terrestrial ecosystem productivity is widely accepted to be nutrient limited1. Although nitrogen (N) is deemed a key determinant of aboveground net primary production (ANPP)2,3, the prevalence of co-limitation by N and phosphorus (P) is increasingly recognized4,​5,​6,​7,​8. However, the extent to which terrestrial productivity is co-limited by nutrients other than N and P has remained unclear. Here, we report results from a standardized factorial nutrient addition experiment, in which we added N, P and potassium (K) combined with a selection of micronutrients (K+μ), alone or in concert, to 42 grassland sites spanning five continents, and monitored ANPP. Nutrient availability limited productivity at 31 of the 42 grassland sites. And pairwise combinations of N, P, and K+μ co-limited ANPP at 29 of the sites. Nitrogen limitation peaked in cool, high latitude sites. Our findings highlight the importance of less studied nutrients, such as K and micronutrients, for grassland productivity, and point to significant variations in the type and degree of nutrient limitation. We suggest that multiple-nutrient constraints must be considered when assessing the ecosystem-scale consequences of nutrient enrichment