The Strathprints institutional repository (https://strathprints.strath.ac.uk) is a digital archive of University of Strathclyde research outputs. It has been developed to disseminate open access research outputs, expose data about those outputs, and enable the management and persistent access to Strathclyde's intellectual output.

In this short note we present comparable loss rates of honey bee colonies during winter 2015/16 from 29 countries, obtained with the COLOSS questionnaire. Altogether, we received valid answers from 19,952 beekeepers. These beekeepers collectively wintered 421,238 colonies, and reported 18,587 colonies with unsolvable queen problems and 32,048 dead colonies after winter. This gives an overall loss rate of 12.0% (95% confidence interval 11.8%-12.2%) during winter 2015/16, with marked differences among countries. Beekeepers in the present study assessed 7.6% (95% CI 7.4%-7.8%) of their colonies as dead or empty, and 4.4% (95% CI 4.3%-4.5%) as having unsolvable queen problems after winter. The overall analysis showed that small operations suffered higher losses than larger ones. A table with detailed results and a map showing response and relative risks at regional level are presented

This short article presents loss rates of honey bee colonies over winter 2017/18 from 36 countries, including 33 in Europe, from data collected using the standardized COLOSS questionnaire. The 25,363 beekeepers supplying data passing consistency checks in total wintered 544,879 colonies, and reported 26,379 (4.8%, 95% CI 4.7-5.0%) colonies with unsolvable queen problems, 54,525 (10.0%, 95% CI 9.8-10.2%) dead colonies after winter and another 8,220 colonies (1.5%, 95% CI 1.4-1.6%) lost through natural disaster. This gave an overall loss rate of 16.4% (95% CI 16.1-16.6%) of honey bee colonies during winter 2017/18, but this varied greatly from 2.0 to 32.8% between countries. The included map shows relative risks of winter loss at regional level. The analysis using the total data-set confirmed findings from earlier surveys that smaller beekeeping operations with at most 50 colonies suffer significantly higher losses than larger operations (p < .001). Beekeepers migrating their colonies had significantly lower losses than those not migrating (p < .001), a different finding from previous research. Evaluation of six different forage sources as potential risk factors for colony loss indicated that intensive foraging on any of five of these plant sources (Orchards, Oilseed Rape, Maize, Heather and Autumn Forage Crops) was associated with significantly higher winter losses. This finding requires further study and explanation. A table is included giving detailed results of loss rates and the impact of the tested forage sources for each country and overall.

This article presents managed honey bee colony loss rates over winter 2018/19 resulting from using the standardised COLOSS questionnaire in 35 countries (31 in Europe). In total, 28,629 beekeepers supplying valid loss data wintered 738,233 colonies, and reported 29,912 (4.1%, 95% confidence interval (CI) 4.0-4.1%) colonies with unsolvable queen problems, 79,146 (10.7%, 95% CI 10.5-10.9%) dead colonies after winter and 13,895 colonies (1.9%, 95% CI 1.8-2.0%) lost through natural disaster. This gave an overall colony winter loss rate of 16.7% (95% CI 16.4-16.9%), varying greatly between countries, from 5.8% to 32.0%. We modelled the risk of loss as a dead/empty colony or from unresolvable queen problems, and found that, overall, larger beekeeping operations with more than 150 colonies experienced significantly lower losses (p < 0.001), consistent with earlier studies. Additionally, beekeepers included in this survey who did not migrate their colonies at least once in 2018 had significantly lower losses than those migrating (p < 0.001). The percentage of new queens from 2018 in wintered colonies was also examined as a potential risk factor. The percentage of colonies going into winter with a new queen was estimated as 55.0% over all countries. Higher percentages of young queens corresponded to lower overall losses (excluding losses from natural disaster), but also lower losses from unresolvable queen problems, and lower losses from winter mortality (p < 0.001). Detailed results for each country and overall are given in a table, and a map shows relative risks of winter loss at regional level.

Context Place-based transdisciplinary research involves multiple academic disciplines and non-academic actors. Long-Term Socio-Ecological Research (LTSER) platform is one concept with * 80 initiatives globally.

Context Maintaining functional green infrastructures (GIs) require evidence-based knowledge about historic and current states and trends of representative land cover types. Objectives We address: (1) the long-term loss and transformation of potential natural forest vegetation; (2) the effects of site productivity on permanent forest loss and emergence of traditional cultural landscapes; (3) the current management intensity; and (4) the social-ecological contexts conducive to GI maintenance . Methods We selected 16 case study regions, each with a local hotspot landscape, ranging from intact forest landscapes, via contiguous and fragmented forest covers, to severe forest loss. Quantitative open access data were used to estimate (i) the historic change and (ii) transformation of land covers, and (iii) compare the forest canopy loss from 2000 to 2018. Qualitative narratives about each hotspot landscape were analysed for similarities (iv). Results While the potential natural forest vegetation cover in the 16 case study regions had a mean of 86%, historically it has been reduced to 34%. Higher site productivity coincided with transformation to non-forest land covers. The mean annual forest canopy loss for 2000–2018 ranged from 0.01 to 1.08%. The 16 case studies represented five distinct social-ecological contexts (1) radical transformation of landscapes, (2) abuse of protected area concepts, (3) ancient cultural landscapes (4) multi-functional forests, and (5) intensive even-aged forest management, of which 1 and 4 was most common. Conclusions GIs encompass both forest naturalness and traditional cultural landscapes. Our review of Pan-European regions and landscapes revealed similarities in seemingly different contexts, which can support knowledge production and learning about how to sustain GIs.

This article presents managed honey bee colony loss rates over winter 2019/20 resulting from using the standardised COLOSS questionnaire in 37 countries. Six countries were from outside Europe, including, for the first time in this series of articles, New Zealand. The 30,491 beekeepers outside New Zealand reported 4.5% of colonies with unsolvable queen problems, 11.1% of colonies dead after winter and 2.6% lost through natural disaster. This gave an overall colony winter loss rate of 18.1%, higher than in the previous year. The winter loss rates varied greatly between countries, from 7.4% to 36.5%. 3216 beekeepers from New Zealand managing 297,345 colonies reported 10.5% losses for their 2019 winter (six months earlier than for other, Northern Hemisphere, countries). We modelled the risk of loss as a dead/empty colony or from unresolvable queen problems, for all countries except New Zealand. Overall, larger beekeeping operations with more than 50 colonies experienced significantly lower losses (p < 0.001). Migration was also highly significant (p < 0.001), with lower loss rates for operations migrating their colonies in the previous season. A higher proportion of new queens reduced the risk of colony winter loss (p < 0.001), suggesting that more queen replacement is better. All three factors, operation size, migration and proportion of young queens, were also included in a multivariable main effects quasi-binomial GLM and all three remained highly significant (p < 0.001). Detailed results for each country and overall are given in a table, and a map shows relative risks of winter loss at the regional level.

Exploitation of natural forests forms expanding frontiers. Simultaneously, protected area frontiers aim at maintaining functional habitat networks. To assess net effects of these frontiers, we examined 16 case study areas on five continents. We (1) mapped protected area instruments, (2) assessed their effectiveness, (3) mapped policy implementation tools, and (4) effects on protected areas originating from their surroundings. Results are given as follows: (1) conservation instruments covered 3–77%, (2) effectiveness of habitat networks depended on representativeness, habitat quality, functional connectivity, resource extraction in protected areas, time for landscape restoration, “paper parks”, “fortress conservation”, and data access, (3) regulatory policy instruments dominated over economic and informational, (4) negative matrix effects dominated over positive ones (protective forests, buffer zones, inaccessibility), which were restricted to former USSR and Costa Rica. Despite evidence-based knowledge about conservation targets, the importance of spatial segregation of conservation and use, and traditional knowledge, the trajectories for biodiversity conservation were generally negative.