340 research outputs found

    Mechanisms of maintenance and restoration of plant diversity

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    Human activities are triggering some of the most rapid losses of biodiversity in the history of life on Earth. Eutrophication, overexploitation, habitat destruction and fragmentation are the main drivers of this decrease in species richness. There is increasing evidence that this reduction of diversity will have dramatic impacts on the functioning of the natural ecosystems of the world, and on their ability to provide society with a variety of essential ecosystem services. It is therefore urgent to understand the causal mechanisms responsible for the maintenance of diversity and their potential use for restoration to develop effective conservation policies. In this thesis, I examine several potential mechanisms for the maintenance or loss of plant diversity. These include resource competition (competition for light and nutrients) and the effects of natural enemies (plant hemiparasites and seed predators)

    Changes in reproductive investment with altitude in an alpine plant

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    Aims In perennial species, the allocation of resources to reproduction results in a reduction of allocation to vegetative growth and, therefore, impacts future reproductive success. As a consequence, variation in this trade-off is among the most important driving forces in the life-history evolution of perennial plants and can lead to locally adapted genotypes. In addition to genetic variation, phenotypic plasticity might also contribute to local adaptation of plants to local conditions by mediating changes in reproductive allocation. Knowledge on the importance of genetic and environmental effects on the trade-off between reproduction and vegetative growth is therefore essential to understand how plants may respond to environmental changes. Methods We conducted a transplant experiment along an altitudinal gradient from 425 m to 1921 m in the front range of the Western Alps of Switzerland to assess the influence of both altitudinal origin of populations and altitude of growing site on growth, reproductive allocation and local adaptation in Poa alpina. The proportion of the number of reproductive tillers by the total number of tillers - was used as a proxy for reproductive allocation. Important findings In our study, the investment in reproduction increased with plant size. Plant growth and the relative importance of reproductive investment decreased in populations originating from higher altitudes compared to populations originating from lower altitudes. The changes in reproductive investment were mainly explained by differences in plant size. In contrast to genetic effects, phenotypic plasticity of all traits measured was low and not related to altitude. As a result, the population from the lowest altitude of origin performed best at all sites. Our results indicate that in P. alpina genetic differences in growth and reproductive investment are related to local conditions affecting growth, i.e. interspecific competition and soil moisture content

    Effects of seed predators of different body size on seed mortality in Bornean logged gorest

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    Background The Janzen-Connell hypothesis proposes that seed and seedling enemies play a major role in maintaining high levels of tree diversity in tropical forests. However, human disturbance may alter guilds of seed predators including their body size distribution. These changes have the potential to affect seedling survival in logged forest and may alter forest composition and diversity. Methodology/Principal Findings We manipulated seed density in plots beneath con- and heterospecific adult trees within a logged forest and excluded vertebrate predators of different body sizes using cages. We show that small and large-bodied predators differed in their effect on con- and heterospecific seedling mortality. In combination small and large-bodied predators dramatically decreased both con- and heterospecific seedling survival. In contrast, when larger-bodied predators were excluded small-bodied predators reduced conspecific seed survival leaving seeds coming from the distant tree of a different species. Conclusions/Significance Our results suggest that seed survival is affected differently by vertebrate predators according to their body size. Therefore, changes in the body size structure of the seed predator community in logged forests may change patterns of seed mortality and potentially affect recruitment and community composition

    Biodiversity-productivity relationships are key to nature-based climate solutions

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    The global impacts of biodiversity loss and climate change are interlinked, but the feedbacks between them are rarely assessed. Areas with greater tree diversity tend to be more productive, providing a greater carbon sink, and biodiversity loss could reduce these natural carbon sinks. Here, we quantify how tree and shrub species richness could affect biomass production on biome, national and regional scales. We find that GHG mitigation could help maintain tree diversity and thereby avoid a 9–39% reduction in terrestrial primary productivity across different biomes, which could otherwise occur over the next 50 years. Countries that will incur the greatest economic damages from climate change stand to benefit the most from conservation of tree diversity and primary productivity, which contribute to climate change mitigation. Our results emphasize an opportunity for a triple win for climate, biodiversity and society, and highlight that these co-benefits should be the focus of reforestation programmes

    Grand challenges in biodiversity-ecosystem functioning research in the era of science-policy platforms require explicit consideration of feedbacks

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    Feedbacks are an essential feature of resilient socio-economic systems, yet the feedbacks between biodiversity, ecosystem services and human wellbeing are not fully accounted for in global policy efforts that consider future scenarios for human activities and their consequences for nature. Failure to integrate feedbacks in our knowledge frameworks exacerbates uncertainty in future projections and potentially prevents us from realizing the full benefits of actions we can take to enhance sustainability. We identify six scientific research challenges that, if addressed, could allow future policy, conservation and monitoring efforts to quantitatively account for ecosystem and societal consequences of biodiversity change. Placing feedbacks prominently in our frameworks would lead to (i) coordinated observation of biodiversity change, ecosystem functions and human actions, (ii) joint experiment and observation programmes, (iii) more effective use of emerging technologies in biodiversity science and policy, and (iv) a more inclusive and integrated global community of biodiversity observers. To meet these challenges, we outline a five-point action plan for collaboration and connection among scientists and policymakers that emphasizes diversity, inclusion and open access. Efforts to protect biodiversity require the best possible scientific understanding of human activities, biodiversity trends, ecosystem functions and—critically—the feedbacks among them

    Biodiversity increases the resistance of ecosystem productivity to climate extremes

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    It remains unclear whether biodiversity buffers ecosystems against climate extremes, which are becoming increasingly frequent worldwide1. Early results suggested that the ecosystem productivity of diverse grassland plant communities was more resistant, changing less during drought, and more resilient, recovering more quickly after drought, than that of depauperate communities2. However, subsequent experimental tests produced mixed results3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13. Here we use data from 46 experiments that manipulated grassland plant diversity to test whether biodiversity provides resistance during and resilience after climate events. We show that biodiversity increased ecosystem resistance for a broad range of climate events, including wet or dry, moderate or extreme, and brief or prolonged events. Across all studies and climate events, the productivity of low-diversity communities with one or two species changed by approximately 50% during climate events, whereas that of high-diversity communities with 16–32 species was more resistant, changing by only approximately 25%. By a year after each climate event, ecosystem productivity had often fully recovered, or overshot, normal levels of productivity in both high- and low-diversity communities, leading to no detectable dependence of ecosystem resilience on biodiversity. Our results suggest that biodiversity mainly stabilizes ecosystem productivity, and productivity-dependent ecosystem services, by increasing resistance to climate events. Anthropogenic environmental changes that drive biodiversity loss thus seem likely to decrease ecosystem stability14, and restoration of biodiversity to increase it, mainly by changing the resistance of ecosystem productivity to climate events

    Exploring the Ni redox activity in polyanionic compounds as conceivable high potential cathodes for Na rechargeable batteries

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    Although nickel-based polyanionic compounds are expected to exhibit a high operating voltage for batteries based on the Ni2+/3+ redox couple activity, some rare experimental studies on the electrochemical performance of these materials are reported, resulting from the poor kinetics of the bulk materials in both Li and Na nonaqueous systems. Herein, the electrochemical activity of the Ni2+/3+ redox couple in the mixed-polyanionic framework Na4Ni3(PO4)2(P2O7) is reported for the first time. This novel material exhibits a remarkably high operating voltage when cycled in sodium cells in both carbonate- and ionic liquid-based electrolytes. The application of a carbon coating and the use of an ionic liquid-based electrolyte enable the reversible sodium ion (de-)insertion in the host structure accompanied by the redox activity of Ni2+/3+ at operating voltages as high as 4.8 V vs Na/Na+. These results present the realization of Ni-based mixed polyanionic compounds with improved electrochemical activity and pave the way for the discovery of new Na-based high potential cathode materials

    Carbon Stocks and Fluxes in Tropical Lowland Dipterocarp Rainforests in Sabah, Malaysian Borneo

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    Deforestation in the tropics is an important source of carbon C release to the atmosphere. To provide a sound scientific base for efforts taken to reduce emissions from deforestation and degradation (REDD+) good estimates of C stocks and fluxes are important. We present components of the C balance for selectively logged lowland tropical dipterocarp rainforest in the Malua Forest Reserve of Sabah, Malaysian Borneo. Total organic C in this area was 167.9 Mg C ha−1±3.8 (SD), including: Total aboveground (TAGC: 55%; 91.9 Mg C ha−1±2.9 SEM) and belowground carbon in trees (TBGC: 10%; 16.5 Mg C ha−1±0.5 SEM), deadwood (8%; 13.2 Mg C ha−1±3.5 SEM) and soil organic matter (SOM: 24%; 39.6 Mg C ha−1±0.9 SEM), understory vegetation (3%; 5.1 Mg C ha−1±1.7 SEM), standing litter (<1%; 0.7 Mg C ha−1±0.1 SEM) and fine root biomass (<1%; 0.9 Mg C ha−1±0.1 SEM). Fluxes included litterfall, a proxy for leaf net primary productivity (4.9 Mg C ha−1 yr−1±0.1 SEM), and soil respiration, a measure for heterotrophic ecosystem respiration (28.6 Mg C ha−1 yr−1±1.2 SEM). The missing estimates necessary to close the C balance are wood net primary productivity and autotrophic respiration

    Database-driven High-Throughput Calculations and Machine Learning Models for Materials Design

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    This paper reviews past and ongoing efforts in using high-throughput ab-inito calculations in combination with machine learning models for materials design. The primary focus is on bulk materials, i.e., materials with fixed, ordered, crystal structures, although the methods naturally extend into more complicated configurations. Efficient and robust computational methods, computational power, and reliable methods for automated database-driven high-throughput computation are combined to produce high-quality data sets. This data can be used to train machine learning models for predicting the stability of bulk materials and their properties. The underlying computational methods and the tools for automated calculations are discussed in some detail. Various machine learning models and, in particular, descriptors for general use in materials design are also covered.Comment: 19 pages, 2 figure
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