Leaf area controls on energy partitioning of a temperate mountain grassland

Using a six year data set of eddy covariance flux measurements of sensible and latent heat, soil heat flux, net radiation, above-ground phytomass and meteorological driving forces energy partitioning was investigated at a temperate mountain grassland managed as a hay meadow in the Stubai Valley (Austria). The main findings of the study were: (i) Energy partitioning was dominated by latent heat, followed by sensible heat and the soil heat flux; (ii) When compared to standard environmental forcings, the amount of green plant matter, which due to three cuts varied considerably during the vegetation period, explained similar, and partially larger, fractions of the variability in energy partitioning; (iii) There were little, if any, indications of water stress effects on energy partitioning, despite reductions in soil water availability in combination with high evaporative demand, e.g. during the summer drought of 2003

Leaf area controls on energy partitioning of a mountain grassland

International audienceUsing a six year data set of eddy covariance flux measurements of sensible and latent heat, soil heat flux, net radiation, above-ground phytomass and meteorological driving forces energy partitioning was investigated at a temperate mountain grassland managed as a hay meadow in the Stubai Valley (Austria). The main findings of the study were: i) Energy partitioning was dominated by latent heat, followed by sensible heat and the soil heat flux; ii) When compared to standard environmental forcings, the amount of green plant matter, which due to three cuts varied considerably during the vegetation period, explained similar, and partially larger, fractions of the variability in energy partitioning; ii) There were little, if any, indications of water stress effects on energy partitioning, despite reductions in soil water availability in combination with high evaporative demand, e.g. during the summer drought of 2003

Biodiversitätsmonitoring im Südtiroler Kräuteranbau = Biodiversity surveys in medicinal and aromatic plant fields in South Tyrol

Medicinal and aromatic plants in mountain regions such as South Tyrol are cultivated on small-scale farms, which are characterized by a high diversity of cultivated crop species grown on a relatively small area. This small-scale cultivation of medicinal and aromatic plants suggests that MAP fields are of high ecological value. However, research on this topic is generally lacking. In this study flower-visiting arthropods were recorded with pan traps in three herb fields during three survey events conducted in 2021. Our results indicate that medicinal and aromatic plant fields are valuable habitats for several taxa. In total 12.570 individuals were collected. Wild bees were particularly species-rich, accounting for 10 % of the regional wild bee species pool. Next to beneficial arthropods, potential pests, such as aphids were also highly abundant. However, natural enemies possibly counteracting pests were also numerous. Overall, we conclude that medicinal and aromatic plant cultivation may act as resource-rich oases for several arthropod groups, thereby promoting biodiversity also on a broader scale.Der Anbau von Arznei- und Gewürzpflanzen zeichnet sich in der Regel durch vielfältige Anbaukulturen auf relativ kleinen Flächen aus. Dies gilt insbesondere für Südtirol, wo diese Kulturen hauptsächlich von kleinen Betrieben im Berggebiet angebaut werden. Dieser kleinflächige Anbau von Arznei- und Gewürzpflanzen lässt vermuten, dass die Betriebe einen hohen ökologischen Wert haben. Es gibt wenige Studien zur Erfassung der Biodiversität im Anbau von Arznei- und Gewürzpflanzen. Daher wurden in dieser Arbeit Kräuteranbau-Betriebe als Lebensraum für blütenbesuchende Arthropoden untersucht. An drei Untersuchungsstandorten wurden im Jahr 2021 jeweils an drei Terminen Farbschalen zur Sammlung von Arthropoden verwendet. Kräuteranbau-Betriebe stellten sich als ein wertvoller Lebensraum für verschiedene Arthropoden heraus. Insgesamt wurden 12.570 Individuen mit den Farbschalen gesammelt. Insbesondere Wildbienen waren mit 10 % des regionalen Artenpools sehr artenreich. Auch potenzielle Schädlinge, wie zum Beispiel Blattläuse, waren sehr häufig anzutreffen, wobei natürliche Feinde, wie zum Beispiel Parasitoide, ebenfalls zahlreich vertreten waren. Insgesamt können Kräuteranbaubetriebe als strukturreiche Oasen für Arthropoden fungieren und sich somit auf einer breiteren Skala positiv auf die Biodiversität auswirken

TRY plant trait database - enhanced coverage and open access

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 biodiversity 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 individual 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

Measuring efficiency of innovation using combined Data Envelopment Analysis and Structural Equation Modeling:empirical study in EU regions

The main aim of this paper is to investigate the impact of patent applications, development level, employment level and degree of technological diversity on innovation efficiency. Innovation efficiency is derived by relating innovation inputs and innovation outputs. Expenditures in Research and Development and Human Capital stand for innovation inputs. Technological knowledge diffusion that comes from spatial and technological neighborhood stands for innovation output. We derive innovation efficiency using Data Envelopment Analysis for 192 European regions for a 12-year period (1995–2006). We also examine the impact of patents production, development and employment level and the level of technological diversity on innovation efficiency using Structural Equation Modeling. This paper contributes a method of innovation efficiency estimation in terms of regional knowledge spillovers and causal relationship of efficiency measurement criteria. The study reveals that the regions presenting high innovation activities through patents production have higher innovation efficiency. Additionally, our findings show that the regions characterized by high levels of employment achieve innovation sources exploitation efficiently. Moreover, we find that the level of regional development has both a direct and indirect effect on innovation efficiency. More accurately, transition and less developed regions in terms of per capita GDP present high levels of efficiency if they innovate in specific and limited technological fields. On the other hand, the more developed regions can achieve high innovation efficiency if they follow a more decentralized innovation policy