European beech stem diameter grows better in mixed than in mono-specific stands at the edge of its distribution in mountain forests

Recent studies show that several tree species are spreading to higher latitudes and elevations due to climate change. European beech, presently dominating from the colline to the subalpine vegetation belt, is already present in upper montane subalpine forests and has a high potential to further advance to higher elevations in European mountain forests, where the temperature is predicted to further increase in the near future. Although essential for adaptive silviculture, it remains unknown whether the upward shift of beech could be assisted when it is mixed with Norway spruce or silver fir compared with mono-specific stands, as the species interactions under such conditions are hardly known. In this study, we posed the general hypotheses that the growth depending on age of European beech in mountain forests was similar in mono-specific and mixed-species stands and remained stable over time and space in the last two centuries. The scrutiny of these hypotheses was based on increment coring of 1240 dominant beech trees in 45 plots in mono-specific stands of beech and in 46 mixed mountain forests. We found that (i) on average, mean tree diameter increased linearly with age. The age trend was linear in both forest types, but the slope of the age–growth relationship was higher in mono-specific than in mixed mountain forests. (ii) Beech growth in mono-specific stands was stronger reduced with increasing elevation than that in mixed-species stands. (iii) Beech growth in mono-specific stands was on average higher than beech growth in mixed stands. However, at elevations > 1200 m, growth of beech in mixed stands was higher than that in mono-specific stands. Differences in the growth patterns among elevation zones are less pronounced now than in the past, in both mono-specific and mixed stands. As the higher and longer persisting growth rates extend the flexibility of suitable ages or size for tree harvest and removal, the longer-lasting growth may be of special relevance for multi-aged silviculture concepts. On top of their function for structure and habitat improvement, the remaining old trees may grow more in mass and value than assumed so far.The authors would like to acknowledge networking support by the COST (European Cooperation in Science and Technology) Action CLIMO (Climate-Smart Forestry in Mountain Regions—CA15226) financially supported by the EU Framework Programme for Research and Innovation HORIZON 2020. This publication is part of a project that has received funding from the European Union’s HORIZON 2020 research and innovation programme under the Marie Skłodowska-Curie Grant Agreement No 778322. Thanks are also due to the European Union for funding the project ‘Mixed species forest management. Lowering risk, increasing resilience (REFORM)’ (# 2816ERA02S under the framework of Sumforest ERA-Net). Further, we would like to thank the Bayerische Staatsforsten (BaySF) for providing the observational plots and to the Bavarian State Ministry of Food, Agriculture, and Forestry for permanent support of the Project W 07 ‘Long-term experimental plots for forest growth and yield research’ (#7831-26625-2017). We also thank the Forest Research Institute, ERTI Sárvár, Hungary, for assistance and for providing observational plots. Furthermore, our work was partially supported by the SRDA via Project No. APVV-16-0325 and APVV-15-0265, the Ministry of Science and Higher Education of the Republic of Poland, the Project “EVA4.0” No. CZ.02.1.01/0.0/0.0/16_019/0000803 funded by OP RDE and the Project J4-1765 funded by the Slovenian Research Agency and also by the Bulgarian National Science Fund (BNSF) and the Project No. DCOST 01/3/19.10.2018

A harmonized database of European forest simulations under climate change

Process-based forest models combine biological, physical, and chemical process understanding to simulate forest dynamics as an emergent property of the system. As such, they are valuable tools to investigate the effects of climate change on forest ecosystems. Specifically, they allow testing of hypotheses regarding long-term ecosystem dynamics and provide means to assess the impacts of climate scenarios on future forest development. As a consequence, numerous local-scale simulation studies have been conducted over the past decades to assess the impacts of climate change on forests. These studies apply the best available models tailored to local conditions, parameterized and evaluated by local experts. However, this treasure trove of knowledge on climate change responses remains underexplored to date, as a consistent and harmonized dataset of local model simulations is missing. Here, our objectives were (i) to compile existing local simulations on forest development under climate change in Europe in a common database, (ii) to harmonize them to a common suite of output variables, and (iii) to provide a standardized vector of auxiliary environmental variables for each simulated location to aid subsequent investigations. Our dataset of European stand- and landscape-level forest simulations contains over 1.1 million simulation runs representing 135 million simulation years for more than 13,000 unique locations spread across Europe. The data were harmonized to consistently describe forest development in terms of stand structure (dominant height), composition (dominant species, admixed species), and functioning (leaf area index). Auxiliary variables provided include consistent daily climate information (temperature, precipitation, radiation, vapor pressure deficit) as well as information on local site conditions (soil depth, soil physical properties, soil water holding capacity, plant-available nitrogen). The present dataset facilitates analyses across models and locations, with the aim to better harness the valuable information contained in local simulations for large-scale policy support, and for fostering a deeper understanding of the effects of climate change on forest ecosystems in Europe

BioVeL : a virtual laboratory for data analysis and modelling in biodiversity science and ecology

Background: Making forecasts about biodiversity and giving support to policy relies increasingly on large collections of data held electronically, and on substantial computational capability and capacity to analyse, model, simulate and predict using such data. However, the physically distributed nature of data resources and of expertise in advanced analytical tools creates many challenges for the modern scientist. Across the wider biological sciences, presenting such capabilities on the Internet (as "Web services") and using scientific workflow systems to compose them for particular tasks is a practical way to carry out robust "in silico" science. However, use of this approach in biodiversity science and ecology has thus far been quite limited. Results: BioVeL is a virtual laboratory for data analysis and modelling in biodiversity science and ecology, freely accessible via the Internet. BioVeL includes functions for accessing and analysing data through curated Web services; for performing complex in silico analysis through exposure of R programs, workflows, and batch processing functions; for on- line collaboration through sharing of workflows and workflow runs; for experiment documentation through reproducibility and repeatability; and for computational support via seamless connections to supporting computing infrastructures. We developed and improved more than 60 Web services with significant potential in many different kinds of data analysis and modelling tasks. We composed reusable workflows using these Web services, also incorporating R programs. Deploying these tools into an easy-to-use and accessible 'virtual laboratory', free via the Internet, we applied the workflows in several diverse case studies. We opened the virtual laboratory for public use and through a programme of external engagement we actively encouraged scientists and third party application and tool developers to try out the services and contribute to the activity. Conclusions: Our work shows we can deliver an operational, scalable and flexible Internet-based virtual laboratory to meet new demands for data processing and analysis in biodiversity science and ecology. In particular, we have successfully integrated existing and popular tools and practices from different scientific disciplines to be used in biodiversity and ecological research.Peer reviewe

Mapping and linking supply- and demand-side measures in climate-smart agriculture. A review

Climate change and food security are two of humanity’s greatest challenges and are highly interlinked. On the one hand, climate change puts pressure on food security. On the other hand, farming significantly contributes to anthropogenic greenhouse gas emissions. This calls for climate-smart agriculture—agriculture that helps to mitigate and adapt to climate change. Climate-smart agriculture measures are diverse and include emission reductions, sink enhancements, and fossil fuel offsets for mitigation. Adaptation measures include technological advancements, adaptive farming practices, and financial management. Here, we review the potentials and trade-offs of climate-smart agricultural measures by producers and consumers. Our two main findings are as follows: (1) The benefits of measures are often site-dependent and differ according to agricultural practices (e.g., fertilizer use), environmental conditions (e.g., carbon sequestration potential), or the production and consumption of specific products (e.g., rice and meat). (2) Climate-smart agricultural measures on the supply side are likely to be insufficient or ineffective if not accompanied by changes in consumer behavior, as climate-smart agriculture will affect the supply of agricultural commodities and require changes on the demand side in response. Such linkages between demand and supply require simultaneous policy and market incentives. It, therefore, requires interdisciplinary cooperation to meet the twin challenge of climate change and food security. The link to consumer behavior is often neglected in research but regarded as an essential component of climate-smart agriculture. We argue for not solely focusing research and implementation on one-sided measures but designing good, site-specific combinations of both demand- and supply-side measures to use the potential of agriculture more effectively to mitigate and adapt to climate change

Autoimmune polyendocrine syndrome in a standard poodle with concurrent non-endocrine immune-mediated diseases

A 6-year-old female neutered standard poodle was referred with a 4-week history of rapidly progressive weight loss, muscle atrophy, hyporexia, hind limb weakness and lethargy. In the preceding 3-month period, the dog had been diagnosed with both keratoconjunctivitis sicca (KCS) and hypoadrenocorticism. Clinical deterioration had occurred despite treatment for hypoadrenocorticism. Following referral, the dog was diagnosed with concurrent hypothyroidism, exocrine pancreatic insufficiency (EPI) and suspected generalised myositis. Treatment with hormone replacement therapy, pancreatic enzyme supplementation and immunosuppressive doses of prednisolone and mycophenolate resulted in marked clinical improvement. This case describes a rapidly progressive, presumed autoimmune, polyglandular endocrinopathy in a dog with concurrent non-endocrine autoimmune diseases