Bioenergy in Europe is unlikely to make a timely contribution to climate change targets

Increasing bioenergy production is a significant component of European efforts to mitigate climate change, but has contested potential for reducing emissions. We use an integrated land system model to explore the effects of large-scale bioenergy production within the European Union on carbon balances. We find that increased bioenergy crop production is likely to cause substantial deforestation and a commensurate loss of associated carbon stocks largely due to displacement of food production from other areas. Deforestation would occur either within the EU if European forests were not protected, or in other parts of the world arising from indirect land use change if European forests were protected. The net carbon benefit of bioenergy production is largely negative, or uncertain, even under the most optimistic levels of fossil fuel replacement, and will not offset initial carbon losses over the coming 50 yr. The growth of intensive agriculture required to satisfy the demand for bioenergy and food will have negative impacts on crucial ecosystem services. Overall, we identify substantial disadvantages to increasing bioenergy production relative to freeing land for natural succession. At best, large-scale bioenergy production is likely to be irrelevant to time-sensitive climate targets.</p

Crop selection under price and yield fluctuation : Analysis of agro-economic time series from South Korea

Temporal fluctuations of crop price and yield can have a strong inuence on farmers\u27 revenue. Under uncertainty, farmers\u27 crop selection on { what to cultivate and how much of their land to allocate to different crops{ is of crucial importance to secure their revenue as well as related ecosystem services. Multi-crop farming can be seen as a strategy to mitigate uncertainties that farmers face. In this study, we used Singular Spectrum Analysis (SSA) to quantify the fluuctuations of crop price and yield for single and multiple crop selections in South Korea. Furthermore, risk adjusted revenue of each crop selection was analysed using the Sharpe ratio. We constructed three empirical crop portfolios containing one, three and five crops. For the single crop farming, six main crops in South Korea were analysed, and household data were used to build empirical crop portfolios. Our results showed that revenue from rice farming was the most stable, whereas it fluctuated strongly for pepper. However, growing rice provided the lowest revenue and farmers who cultivate multiple crops might as much as double their revenue compared to rice farming. Diversified crop farming can be a means of enhancing revenue. The biggest part of fluctuations in portfolios with several crops was seasonal, which might be mitigated by planning in advance. The artificial stability of rice price was due to policy intervention. However, it should be noted that the rice policy has been reformed and a high protection for domestic rice farming would no longer last in the future in South Korea. These results might have practical consequences for farmers\u27 decision making on crop selection as well as for agricultural policy

An open‐source image classifier for characterizing recreational activities across landscapes

Environmental management increasingly relies on information about ecosystem services for decision-making. Compared with regulating and provisioning services, cultural ecosystem services (CES) are particularly challenging to characterize and measure at management-relevant spatial scales, which has hindered their consideration in practice. Social media are one source of spatially explicit data on where environments support various types of CES, including physical activity. As tools for automating social media content analysis with artificial intelligence (AI) become more commonplace, studies are promoting the potential for AI and social media to provide new insights into CES. Few studies, however, have evaluated what biases are inherent to this approach and whether it is truly reproducible. This study introduces and applies a novel and open-source convolutional neural network model that uses computer vision to recognize recreational activities in the content of photographs shared as social media. We train a model to recognize 12 common recreational activities to map one aspect of recreation in a national forest in Washington, USA, based on images uploaded to Flickr. The image classifier performs well, overall, but varies by activity type. The model, which is trained with data from one region, performs nearly as well in a novel region of the same national forest, suggesting that it is broadly applicable across similar public lands. By comparing the results from our CNN model with an on-site survey, we find that there are apparent biases in which activities visitors choose to photograph and post to social media. After considering potential issues with underlying data and models, we map activity diversity and find that natural features (such as rivers, lakes and higher elevations) and some built infrastructure (campgrounds, trails, roads) support a greater diversity of activities in this region. We make our model and training weights available in open-source software, to facilitate reproducibility and further model development by researchers who seek to understand recreational values at management-relevant scales—and more broadly provide an example of how to build, test and apply AI to understand recreation and other types of CESs

Three billion new trees in the EU’s biodiversity strategy:low ambition, but better environmental outcomes?

The EU Biodiversity strategy aims to plant 3 billion trees by 2030, in order to improve ecosystem restoration and biodiversity. Here, we compute the land area that would be required to support this number of newly planted trees by taking account of different tree species and planting regimes across the EU member states. We find that 3 billion trees would require a total land area of between 0.81 and 1.37 Mha (avg. 1.02 Mha). The historic forest expansion in the EU since 2010 was 2.44 Mha, meaning that despite 3 billion trees sounding like a large number this target is considerably lower than historic afforestation rates within the EU, i.e. only 40% of the past trend. Abandoned agricultural land is often proposed as providing capacity for afforestation. We estimate agricultural abandoned land areas from the HIstoric Land Dynamics Assessment+ database using two time thresholds (abandonment since 2009 or 2014) to identify potential areas for tree planting. The area of agricultural abandoned land was 2.6 Mha (potentially accommodating 7.2 billion trees) since 2009 and 0.2 Mha (potentially accommodating 741 million trees) since 2014. Our study highlights that sufficient space could be available to meet the 3 billion tree planting target from abandoned land. However, large-scale afforestation beyond abandoned land could have displacement effects elsewhere in the world because of the embodied deforestation in the import of agricultural crops and livestock. This would negate the expected benefits of EU afforestation. Hence, the EU’s relatively low ambition on tree planting may actually be better in terms of avoiding such displacement effects. We suggest that tree planting targets should be set at a level that considers physical ecosystem dynamics as well as socio-economic conditions.</p

Implementing land-based mitigation to achieve the Paris Agreement in Europe requires food system transformation

Land-based mitigation, particularly through afforestation, reforestation and avoided deforestation, is an important component of the 'Paris Agreement' to limit average global temperature increases to between 1.5 and 2 ◦C. However, the specific actions that would ensure sufficient carbon sequestration in forests remain unclear, as do their trade-offs against other land-based objectives. We use a regional integrated assessment model to identify the conditions under which European forests reach the extent required by mitigation targets. We compare stylised scenarios of changes in meat demand, bioenergy crop production, irrigation efficiency, and crop yield improvement. Only 42 out of 972 model simulations achieved minimum levels of food provision and forest extent without the need to change dietary preferences, but relied on crop yield improvements within Europe of at least 30%. Maintaining food imports at today's levels to avoid the potential displacement of food production and deforestation required at least a 15 % yield improvement, or a drastic reduction in meat consumption (avg. 57 %). The results suggest that the large-scale afforestation/reforestation planned in European targets is virtually impossible to achieve without transformation of the food system, making it unlikely that Europe will play its required role in global efforts to limit climate change without utilising land beyond its borders

Three billion new trees in the EU’s biodiversity strategy: low ambition, but better environmental outcomes?

The EU Biodiversity strategy aims to plant 3 billion trees by 2030, in order to improve ecosystem restoration and biodiversity. Here, we compute the land area that would be required to support this number of newly planted trees by taking account of different tree species and planting regimes across the EU member states. We find that 3 billion trees would require a total land area of between 0.81 and 1.37 Mha (avg. 1.02 Mha). The historic forest expansion in the EU since 2010 was 2.44 Mha, meaning that despite 3 billion trees sounding like a large number this target is considerably lower than historic afforestation rates within the EU, i.e. only 40% of the past trend. Abandoned agricultural land is often proposed as providing capacity for afforestation. We estimate agricultural abandoned land areas from the HIstoric Land Dynamics Assessment+ database using two time thresholds (abandonment since 2009 or 2014) to identify potential areas for tree planting. The area of agricultural abandoned land was 2.6 Mha (potentially accommodating 7.2 billion trees) since 2009 and 0.2 Mha (potentially accommodating 741 million trees) since 2014. Our study highlights that sufficient space could be available to meet the 3 billion tree planting target from abandoned land. However, large-scale afforestation beyond abandoned land could have displacement effects elsewhere in the world because of the embodied deforestation in the import of agricultural crops and livestock. This would negate the expected benefits of EU afforestation. Hence, the EU\u27s relatively low ambition on tree planting may actually be better in terms of avoiding such displacement effects. We suggest that tree planting targets should be set at a level that considers physical ecosystem dynamics as well as socio-economic conditions

Efficient extraction of small and large RNAs in bacteria for excellent total RNA sequencing and comprehensive transcriptome analysis.

BACKGROUND: Next-generation transcriptome sequencing (RNA-Seq) has become the standard practice for studying gene splicing, mutations and changes in gene expression to obtain valuable, accurate biological conclusions. However, obtaining good sequencing coverage and depth to study these is impeded by the difficulties of obtaining high quality total RNA with minimal genomic DNA contamination. With this in mind, we evaluated the performance of Phenol-free total RNA purification kit (Amresco) in comparison with TRI Reagent (MRC) and RNeasy Mini (Qiagen) for the extraction of total RNA of Pseudomonas aeruginosa which was grown in glucose-supplemented (control) and polyethylene-supplemented (growth-limiting condition) minimal medium. All three extraction methods were coupled with an in-house DNase I treatment before the yield, integrity and size distribution of the purified RNA were assessed. RNA samples extracted with the best extraction kit were then sequenced using the Illumina HiSeq 2000 platform. RESULTS: TRI Reagent gave the lowest yield enriched with small RNAs (sRNAs), while RNeasy gave moderate yield of good quality RNA with trace amounts of sRNAs. The Phenol-free kit, on the other hand, gave the highest yield and the best quality RNA (RIN value of 9.85&nbsp;&plusmn;&nbsp;0.3) with good amounts of sRNAs. Subsequent bioinformatic analysis of the sequencing data revealed that 5435 coding genes, 452 sRNAs and 7 potential novel intergenic sRNAs were detected, indicating excellent sequencing coverage across RNA size ranges. In addition, detection of low abundance transcripts and consistency of their expression profiles across replicates from the same conditions demonstrated the reproducibility of the RNA extraction technique. CONCLUSIONS: Amresco\u27s Phenol-free Total RNA purification kit coupled with DNase I treatment yielded the highest quality RNAs containing good ratios of high and low molecular weight transcripts with minimal genomic DNA. These RNA extracts gave excellent non-biased sequencing coverage useful for comprehensive total transcriptome sequencing and analysis. Furthermore, our findings would be useful for those interested in studying both coding and non-coding RNAs from precious bacterial samples cultivated in growth-limiting condition, in a single sequencing run

Five steps towards transformative valuation of nature

The Values Assessment (VA) of the Intergovernmental Science Policy Platform on Biodiversity and Ecosystem Services shows that while a wide range of valuation methods exist to include nature's values in diverse decision-making contexts, uptake of these methods remains limited. Building on the VA, this paper reviews five critical steps in the evaluation of project or policy proposals that can improve the inclusion of nature's values in decisions. Furthermore, improving valuation practice requires guidelines that utilise quality criteria for valuation of nature and ensure a balance between them. This paper proposes three such quality criteria: relevance, robustness and resource efficiency. The paper argues that the five steps and three Rs can generate a practical checklist to support commissioning, evaluation and performance of more plural valuations. Such guidelines can provide the next steps needed to improve uptake of nature valuation in decision-making