Philippa Kaur

Pan, Y. et al. A large and persistent carbon sink in the world’s forests. Science 333, 988–993 (2011).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Tarnocai, C. et al. Soil organic carbon pools in the northern circumpolar permafrost region. Glob. Biogeochem. Cycles 23, 1–11 (2009).Article 
CAS 

Google Scholar 
Davidson, E. A. & Janssens, I. A. Temperature sensitivity of soil carbon decomposition and feedbacks to climate change. Nature 440, 165–173 (2006).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Wardle, D. A., Nilsson, M. C., Zackrisson, O. & Gallet, C. Determinants of litter mixing effects in a Swedish boreal forest. Soil Biol. Biochem. 35, 827–835 (2003).CAS 
Article 

Google Scholar 
Moen, J., Cairns, D. M. & Lafon, C. W. Factors structuring the treeline ecotone in Fennoscandia. Plant Ecol. Divers. 1, 77–87 (2008).Article 

Google Scholar 
Sjögersten, S. & Wookey, P. A. Climatic and resource quality controls on soil respiration across a forest-tundra ecotone in Swedish Lapland. Soil Biol. Biochem. 34, 1633–1646 (2002).Article 

Google Scholar 
Sjögersten, S., Turner, B. L., Mahieu, N., Condron, L. M. & Wookey, P. A. Soil organic matter biochemistry and potential susceptibility to climatic change across the forest-tundra ecotone in the Fennoscandian mountains. Glob. Change Biol. 9, 759–772 (2003).ADS 
Article 

Google Scholar 
IPCC. IPCC report global warming of 1.5 °C. Ipcc Sr15. 2, 17–20 (2018).
Google Scholar 
Hobbie, S. E., Nadelhoffer, K. J. & Högberg, P. A synthesis: The role of nutrients as constraints on carbon balances in boreal and arctic regions. Plant Soil 242, 163–170 (2002).CAS 
Article 

Google Scholar 
DeLuca, T. H. & Boisvenue, C. Boreal forest soil carbon: Distribution, function and modelling. Forestry 85, 161–184 (2012).Article 

Google Scholar 
Hansson, A., Dargusch, P. & Shulmeister, J. A review of modern treeline migration, the factors controlling it and the implications for carbon storage. J. Mt. Sci. 18, 291–306 (2021).Article 

Google Scholar 
Sjögersten, S. & Wookey, P. A. The impact of climate change on ecosystem carbon dynamics at the Scandinavian mountain birch forest-tundra heath ecotone. Ambio 38, 2–10 (2009).PubMed 
Article 

Google Scholar 
Rustad, L. E. et al. A meta-analysis of the response of soil respiration, net nitrogen mineralization, and aboveground plant growth to experimental ecosystem warming. Oecologia 126, 543–562 (2001).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Kullman, L. Rapid recent range-margin rise of tree and shrub species in the Swedish Scandes. J. Ecol. 90, 68–77 (2002).Article 

Google Scholar 
Lloyd, A. H. & Fastie, C. L. Recent changes in treeline forest distribution and structure in interior Alaska. Ecoscience 10, 176–185 (2003).Article 

Google Scholar 
Truong, C., Palmé, A. E. & Felber, F. Recent invasion of the mountain birch Betula pubescens ssp. tortuosa above the treeline due to climate change: Genetic and ecological study in northern Sweden. J. Evol. Biol. 20, 369–380 (2007).CAS 
PubMed 
Article 

Google Scholar 
Danby, R. K. & Hik, D. S. Variability, contingency and rapid change in recent subarctic alpine tree line dynamics. J. Ecol. 95, 352–363 (2007).Article 

Google Scholar 
Harsch, M. A., Hulme, P. E., McGlone, M. S. & Duncan, R. P. Are treelines advancing? A global meta-analysis of treeline response to climate warming. Ecol. Lett. 12, 1040–1049 (2009).PubMed 
Article 

Google Scholar 
Tingstad, L., Olsen, S. L., Klanderud, K., Vandvik, V. & Ohlson, M. Temperature, precipitation and biotic interactions as determinants of tree seedling recruitment across the tree line ecotone. Oecologia 179, 599–608 (2015).ADS 
PubMed 
Article 

Google Scholar 
Hofgaard, A. Inter-Relationships between treeline position, species diversity, land use and climate change in the Central Scandes Mountains of Norway. Annika Hofgaard Source Glob. Ecol. Biogeogr. Lett. 6(6), 419–429 (1997).Article 

Google Scholar 
Olsson, E. G. A., Austrheim, G. & Grenne, S. N. Landscape change patterns in mountains, land use and environmental diversity, Mid-Norway 1960–1993. Landsc. Ecol. 15, 155–170 (2000).Article 

Google Scholar 
Weintraub, M. N. & Schimel, J. P. Interactions between carbon and nitrogen mineralization and soil organic matter chemistry in arctic tundra soils. Ecosystems 6, 129–143 (2003).CAS 
Article 

Google Scholar 
Melillo, J. M. et al. Soil warming and carbon-cycle feedbacks to the climate system. Science 298, 2173–2176 (2002).Kammer, A. et al. Treeline shifts in the Ural mountains affect soil organic matter dynamics. Glob. Change Biol. 15, 1570–1583 (2009).ADS 
Article 

Google Scholar 
Parker, T. C., Subke, J. A. & Wookey, P. A. Rapid carbon turnover beneath shrub and tree vegetation is associated with low soil carbon stocks at a subarctic treeline. Glob. Change Biol. 21, 2070–2081 (2015).ADS 
Article 

Google Scholar 
Speed, J. D. M. et al. Continuous and discontinuous variation in ecosystem carbon stocks with elevation across a treeline ecotone. Biogeosciences 12, 1615–1627 (2015).ADS 
Article 

Google Scholar 
Hartley, I. P. et al. A potential loss of carbon associated with greater plant growth in the European Arctic. Nat. Clim. Chang. 2, 875–879 (2012).ADS 
CAS 
Article 

Google Scholar 
Yoo, K., Amundson, R., Heimsath, A. M. & Dietrich, W. E. Spatial patterns of soil organic carbon on hillslopes: Integrating geomorphic processes and the biological C cycle. Geoderma 130, 47–65 (2006).ADS 
CAS 
Article 

Google Scholar 
Zhu, M. et al. Soil organic carbon as functions of slope aspects and soil depths in a semiarid alpine region of Northwest China. CATENA 152, 94–102 (2017).CAS 
Article 

Google Scholar 
Hilli, S., Stark, S. & Derome, J. Litter decomposition rates in relation to litter stocks in boreal coniferous forests along climatic and soil fertility gradients. Appl. Soil Ecol. 46, 200–208 (2010).Article 

Google Scholar 
Parker, T. C. et al. Exploring drivers of litter decomposition in a greening Arctic: Results from a transplant experiment across a treeline. Ecology 99, 2284–2294 (2018).PubMed 
Article 

Google Scholar 
Strand, L. T., Callesen, I., Dalsgaard, L. & de Wit, H. A. Carbon and nitrogen stocks in Norwegian forest soils—The importance of soil formation, climate, and vegetation type for organic matter accumulation. Can. J. For. Res. 46, 1459–1473 (2016).CAS 
Article 

Google Scholar 
Thieme, N., Bollandsås, O. M., Gobakken, T. & Næsset, E. Detection of small single trees in the forest-tundra ecotone using height values from airborne laser scanning. Can. J. Remote Sens. 37, 264–274 (2011).ADS 
Article 

Google Scholar 
Mienna, I. M., Klanderud, K., Ørka, H. O., Bryn, A. & Bollandsås, O. M. Land cover classification of treeline ecotones along a 1100 km latitudinal transect using spectral- and three-dimensional information from UAV -based aerial imagery. Remote Sens. Ecol. Conserv. https://doi.org/10.1002/rse2.260 (2022).Article 

Google Scholar 
Tveito, O. E., Bjørdal, I., Skjelvåg, A. O. & Aune, B. A GIS-based agro-ecological decision system based on gridded climatology. Meteorol. Appl. 12, 57–68 (2005).ADS 
Article 

Google Scholar 
Carter, T. R. Changes in the thermal growing season in Nordic countries during the past century and prospects for the future. Agric. Food Sci. Finl. 7, 161–179 (1998).Article 

Google Scholar 
Abdi, H. Partial least square regression PLS-regression. Encyclopedia Res. Methods Social Sci. 792.295 (2003).Wold, S., Sjöström, M. & Eriksson, L. PLS-regression: A basic tool of chemometrics. Chemom. Intell. Lab. Syst. 58, 109–130 (2001).CAS 
Article 

Google Scholar 
Liland, K. H., Mevik, B.-H., Wehrens, R. & Hiemstra, P. Package ‘ pls ’. (2021).Mevik, B.-H. & Wehrens, R. Introduction to the pls Package. Help Sect. ‘pls’ Packag. RStudio Softw. 1–23 (2015).Huang, X. et al. Soil moisture dynamics within soil profiles and associated environmental controls. CATENA 136, 189–196 (2016).Article 

Google Scholar 
Trap, J., Hättenschwiler, S., Gattin, I. & Aubert, M. Forest ageing: An unexpected driver of beech leaf litter quality variability in European forests with strong consequences on soil processes. For. Ecol. Manage. 302, 338–345 (2013).Article 

Google Scholar 
Sørensen, M. V. et al. Draining the pool? Carbon storage and fluxes in three alpine plant communities. Ecosystems 21, 316–330 (2018).Article 
CAS 

Google Scholar 
Qian, H., Joseph, R. & Zeng, N. Enhanced terrestrial carbon uptake in the Northern High Latitudes in the 21st century from the Coupled Carbon Cycle Climate Model Intercomparison Project model projections. Glob. Chang. Biol. 16, 641–656 (2010).ADS 
Article 

Google Scholar 
Sturm, M. et al. Snow—Shrub interactions in Arctic Tundra : A hypothesis with climatic implications. J. Clim. 14, 336–344 (2001).ADS 
Article 

Google Scholar 
Grogan, P. & Jonasse, S. Ecosystem CO2 production during winter in a Swedish subarctic region: The relative importance of climate and vegetation type. Glob. Change Biol. 12, 1479–1495 (2006).ADS 
Article 

Google Scholar 
Sistla, S. A. et al. Long-term warming restructures Arctic tundra without changing net soil carbon storage. Nature 497, 615–617 (2013).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Wiesmeier, M. et al. Soil organic carbon storage as a key function of soils—A review of drivers and indicators at various scales. Geoderma 333, 149–162 (2019).ADS 
CAS 
Article 

Google Scholar 
Brooks, P. D. & Williams, M. W. Snowpack controls on nitrogen cycling and export in seasonally snow-covered catchments. Hydrological processes 13, 2177–2190 (1999).Broll, G. et al. Landscape mosaic in the treeline ecotone on Mt. Rodjanoaivi, Subarctic Finland. Fenn. J. Geogr. 185, 89–105 (2007).
Google Scholar 
Turetsky, M. R. The role of bryophytes in carbon and nitrogen cycling. Bryologist 106, 395–409 (2003).Article 

Google Scholar  More

Study designWe used a food systems framing to conceptually position our research to investigate how small-scale fisheries shape two key aspects of food environments – physical access to food via living in proximity to small-scale fisheries (fish as food pathway), and economic access to food via small-scale fisheries livelihoods (fish as income pathway).We examined food system components of supply chains (small-scale fisheries livelihoods related to harvesting, processing and trade), food environments (proximity to small-scale fisheries and livelihoods), income poverty status, and household diets (fish consumption and annual food security) (Supplementary Fig 7)40,41. Small-scale fisheries are notably recognised for their safety net function during times of shocks and extreme events, increasing the ability of households to recover, exit poverty and afford food over the longer-term42.Country selection and household survey dataWe selected Malawi, Tanzania and Uganda, given these countries represent a region where small-scale fisheries provides the main supply of fish and are important for rural inland and coastal livelihoods24,43, and yet substantial data gaps remain in valuing small-scale fisheries in the regional food system. Small-scale fisheries, particularly inland fisheries, in this region are known to be highly productive with a linear increasing trend in catches over the last three decades25,35. On average 70% of the total catches consist of small pelagic species, which are largely driven by climate, and are highly productive, resilient, and under-exploited34. However, challenges do exist in fisheries governance and signs of over-exploitation of some few fish stocks44, as well as high post-harvest fish waste and loss across value-chains undermine the potential benefits from the sector23. We analysed the World Bank’s Living Standards Measurement Surveys and its Integrated Surveys on Agriculture (LSMS-ISA) from Malawi, Tanzania and Uganda. The LSMS-ISA surveys conducted in these countries collected georeferenced household-level data and had been designed and implemented with a dedicated fishery module39 which contained questions on household fish consumption (frequency, quantity, and form of fresh or dried fish) and small-scale fisheries livelihoods across value chains (harvesting, processing and trading). The fishery module was collected across different years in Malawi (2016–17), Tanzania (2014–15) and Uganda (2010–11), and accordingly these are the years analysed in this study. The LSMS-ISA surveys collects consumption data over a period of 12 months so that the indicator captures the intrinsic variability due to seasonality, such as low and high periods of food consumption.Geospatial data and distance to fishing groundsGeoreferenced household data from LSMS-ISA surveys were matched with geospatial data on the location of inland water bodies and coastlines (Supplementary Table 11) to investigate geographic correlates (e.g., distance to fishing grounds – water bodies where fisheries occur) of poverty and food security. Data on inland water bodies were from the Global Lakes and Wetlands Database (GLWD)45, and the European Space Agency GlobCover databases for coastlines46. Inland water bodies from the GLWD database include permanent, open water bodies (e.g., lakes, reservoirs, rivers) with a surface area ≥0.1 km2 for each country, including cross-border water bodies. We selected water bodies to represent types of water bodies known to support fisheries, based on catch data24,43. We assume the entire coastline of Tanzania was accessible and used for marine small-scale fisheries. We use the term ‘water body’ to mean either freshwater or marine waters.Distance between water bodies and households was calculated as the shortest, straight line, distance from the household location (identified through the GPS coordinates of the households) to any point of the nearest water body. The distance was expressed in km.In our descriptive statistics, a cut-off threshold of 5 km from fishing grounds was used to compare the key indicators presented in this study (e.g., percent of poor and food insecure households, frequency and quantity of fish consumption, etc), for households proximate and distant (≤5 km was considered close and >5 km was considered far) from fished water bodies, as well as between fishing and non-fishing households. The choice of the cut-off threshold used for our descriptive statistics was guided by other studies16,17, in addition to reflecting the distribution of households by quintile of distance to water bodies. Concerning the latter, we found that the average distance from fishing ground of the first quintile was always lower than 5 km in all countries.In the regression analyses, the distance to water bodies was included as a continuous variable (in km). This choice reflects the need to better understand dynamics for households that tend to live more distant from fishing grounds. These dynamics were captured by measuring the marginal increase in the probability of being poor or food insecure for a one-unit increase (1 km) from the mean distance to fishing grounds.We acknowledge two limitations behind the calculation of the straight-line distance to water bodies. First, using the straight-line distance to water bodies may introduce biases in the statistical analyses presented, especially for households located in any particular landscapes within the country. The walking or travel time distance over a road network would provide a better alternative, however there is lack of data on road networks. Despite the straight-line distance to water bodies encompasses some limitations, we still believe that this method of calculation provides a good proxy to categorize household in relation to their distance to water bodies, and the results from the analyses should not deviate substantially from other method of calculation. For example, a study51 found that the straight-line distance tends to be highly correlated (R  > 0.91) with both walking and travel time distance.Second, an additional bias in the presented analyses may be introduced due to the modification strategy of the households GPS coordinates. This strategy was implemented before dissemination of household level data to avoid the risk of disclosure of sampled households. In its essence, the modification strategy relies on random offset of cluster center-point within a specified range. For urban areas a range of 0–2 km is used. In rural areas, where risk of disclosure may be higher due to more dispersed communities, a range of 0–5 km offset was used. While we had no control over this modification strategy, we believe that the modification of the GPS coordinates does not affect the way households are classified in relation to their distance to fishing grounds: considering that the modification strategy was applied to both distant and proximate households, we expect that the distribution between households close and distant to water bodies has remained unchanged and, hence, the presented statistics are still valid for the analysis.Variable constructionWe used a range of socio-economic indicators across food system components (Supplementary Table 11). As a measure of physical and economic access to food we used two indicators of small-scale fisheries: proximity to fishing grounds and fishing households. Household livelihoods were assigned according to whether households primarily, but not exclusively, engaged in small-scale fisheries (fishing, harvesting, processing and/or trading which varied by survey), agriculture (e.g., crop or livestock), or neither fisheries or agriculture. For each country survey, households were categorised according to their engagement in fishing and/or agriculture activities in the prior 12 months. Households in which one or more member engaged in fish-related activities were defined as ‘fishing households’. Fish-related livelihood activities were defined as fish harvesting, processing, and trading in Malawi and Tanzania, whilst in Uganda they were defined only as fishing. Households with one or more member engaged in agriculture, but not in fish-related activities, were defined as ‘agriculture households’. Through data exploration of livelihood categories, we found that 96% of all fishing households in our study combine fish-related and agricultural activities, with only 4% engaging exclusively in small-scale fisheries. Examination of diverse livelihood typologies within fishing household category (e.g., fisher-farmer, which is common in the region or exclusive fisher) was deemed out of the scope of this study and not feasible due to the small number of observations of exclusive fishers.Household poverty was measured using the per-capita monthly expenditure (equivalized using the adult equivalent scale). Poor households were defined as those households with a per-capita monthly expenditure below the national poverty line. The national poverty line –which was defined by national authorities in the three countries analysed–is a country-specific monetary threshold below which a household (and its members) cannot meet their basic needs. The poverty metric, as defined above, was used across physical, natural and human capital: asset wealth, distance to markets, access to land and education level of head of household. Since the asset wealth captures the typologies and number of assets owned by the household (durable goods – radio, bicycle, TV; utilities and infrastructure – access to protected water source and electricity), we developed an index for assets using the principal component analysis. This technique reduced the multi-dimensionality of the asset’s variables, and it allowed the data to identify the linear combinations of the assets components that explain the greatest share of the variation in wealth. As the final wealth index was standardised across households, this index allowed providing a ranking of households which reflected their ownership of assets.Food security was measured using two indicators; household-level food consumption profile – using the Food Consumption Score (FCS) index20, and subjective food insecurity defined as the number of months during a year that a household reported not having enough food to feed the household. Together, these indicators provide a more comprehensive understanding of household food security over a longer period than other surveys (e.g. Demographic and Health)47,48,49. The LSMS-ISA surveys collects food consumption data over a 7-day recall period. To capture seasonal variation in the food consumption indicators, sampled households were interviewed over a 12-month period: for each month of the year, a different portion of sampled households was interviewed so that the derived indicators reflect the intrinsic variability in food consumption, which may be due to seasonality. We used the FCS index as a food security indicator as it is akin to the data collected via the LSMS-ISA surveys, and that there was a need for comparison across select countries. The FCS index measures the frequency (number of days) and diversity of food groups consumed over a 7-day recall period, with weights given to groups based on nutritional value. The FCS index is validated as a proxy for energy sufficiency (quantity of food) and food access, and is associated with other household-level diet diversity measures (e.g. household dietary diversity score (HDDS))20,48. The difference between FCS and other indicators such as HDDS is the recall period (7-days versus 24 h), diversity of groups, weights assigned based on nutrition, and use of frequency together with diversity of groups consumed. The FCS with a longer recall period can show more habitual consumption but can also have limitations with people’s recall reliability. Although it has not been validated yet as an indicator for micronutrient intake, it does provide weights to nutrient-rich food groups and accounts for frequency of consumption, which other indicators do not. Fish consumption was described in terms of the (i) quantity (kg of wet weight equivalent per household per week), (ii) form (fresh, dried, smoked, other) and (iii) source (purchased, own consumption, gift) of fish consumed. The share of households reporting consumption of other animal source foods was also calculated to examine the relative role of fish in overall diets.We also examined the prices of foods consumed to investigate the accessibility of fish as food in terms of affordability compared to animal source foods. The LSMS-ISA survey collects data on the value and volume of food that were purchased and consumed. Those two variables were further used to construct the average price for each food item. To control for price level differences between countries, food prices data calculated from the survey were converted from local currency unit to international USD, using the Purchase power parity conversion factor corresponding to the year of the survey (Source: World Development Indicators database, World Bank). Moreover, since the surveys were conducted in different years, nominal prices corresponding to the years of the surveys were converted into real, inflation-adjusted prices using the Consumer Price Index (CPI, base year: 2010). This allowed to control for potential inflation patterns within countries and provide a better comparison of food prices per Kg. across the three countries analyzed (Source: World Development Indicators database, World Bank).Finally, we drew upon nutritional databases (food composition tables, FishBase and Illuminating Hidden Harvest Initiative) to understand the relative nutritional value of fish; by species, size (small or large) and form (e.g., fresh or dried), compared to other animal source foods (Supplementary Table 12). This enables us to contextualise the nutritional importance of consumption patterns.Descriptive statisticsWe created a harmonized multi-country dataset for Malawi, Tanzania and Uganda with 18,715 nationally representative household-level observations. The sample included in this study represents more than 19 million households corresponding to a population of 93.8 million people across the three countries (Supplementary Information).Descriptive statistics were calculated to compare poverty and food security indicators among households proximate and distant from fished water bodies, and between fishing and non-fishing households (see full details in Supplementary Information). For this analysis, households distant and proximate from fished water bodies were clustered into two groups based on a cut-off threshold of 5 km (distant  > 5 km; proximate ≤5 km). The Welch’s t-test was then used throughout to assess the statistical significance of mean statistics between these two groups.Econometric modelThe estimated probabilities of being poor (household living below the national poverty line) and food insecure (household with a poor food consumption profile) were modelled through two separate probit regression models, where the outcome variable was equal to 1 for poor and food insecure households and 0 otherwise. The independent variables in both models included the household’s distance to water bodies and the distance to food market. Both variables are expressed as continuous variables (in km), reflecting the need to measure the marginal increase in the probability of being poor or food insecure (i.e., the estimated β coefficients) given a one-unit change (1 km) in the distance to fishing ground (or food markets) from its mean. Both models also included an interaction variable which measured the household’s distance to water bodies but restricted to only those households who were unable to reach the food market. We tested this interaction as we expected that living in proximity to water bodies could mitigate the negative effects on poverty and food insecurity when households are unable to access food markets. In order to measure the conditional difference in the average probability to be poor and food insecure between households who engaged in fisheries and households who engaged in other non-fishing activities, we constructed a categorical variable that classified households according to their main livelihood activity, namely (1) neither fishing, nor agriculture households (i.e., the reference baseline household category), (2) fishing households and (3) agriculture households. This categorical variable was further restricted to only households living in proximity to water bodies to better measure for which typology of household the proximity to fishing grounds is most beneficial. Both models were controlled for the age, sex and the highest level of education attained by the head of the household, as well as the total number of household members employed (over total household members) and the wealth index of the household.For each model (poverty and food insecurity), we examined associations at the cross-country, national and rural levels (Tables 1 and 2, also available as Supplementary Data 1 and 2). Stata 15 was used for all statistical analyses. Both descriptive statistics and the regression coefficients were estimated using the household probability weight, the latter instrumental to make the derived indicators from the surveys representative of the population of interest thus allowing general inference for the three countries.Reporting summaryFurther information on research design is available in the Nature Research Reporting Summary linked to this article. More

Larvae display conserved gene expression response to heat stressLarval gene expression (GE) was quantified to assess if plastic responses in gene expression to heat stress varied depending on site of origin or parental identity. Larval survival under heat stress varied between crosses, with larvae produced from dams sourced from far Northern GBR sites exhibiting higher thermal tolerance (Fig. 1b). The cross with the lowest thermal tolerance (LSxSB) did not have any larvae survive the heat treatment (Fig. 1b, Supplementary Fig. 2). GE was examined in aposymbiotic larvae experiencing ambient conditions prior to the heat treatment (“pre”), larvae after exposure to simulated heat stress (35.5 °C for 56 hours, “post heat”), and a simultaneous control temperature of 27 °C (“post ambient”). Therefore, the “pre” larval treatment provided transcriptomic baselines of GE between genetic crosses while “post heat” and “post ambient” comparisons show a baseline for cross-specific heat responses without the confounding effect of symbiosis found in the post-metamorphic phase. Using a principal coordinates analysis (PCoA), we find that GE patterns in larvae were driven by treatment (“pre”, “post ambient”, “post heat”), explaining 29.2% of the variation in survival (padonis  More

Chen, I. C., Hill, J. K., Ohlemuller, R., Roy, D. B. & Thomas, C. D. Rapid range shifts of species associated with high levels of climate warming. Science 333, 1024–1026. https://doi.org/10.1126/science.1206432 (2011).ADS 
CAS 
Article 
PubMed 

Google Scholar 
Gottfried, M. et al. Continent-wide response of mountain vegetation to climate change. Nat. Clim. Change 2, 111–115. https://doi.org/10.1038/nclimate1329 (2012).ADS 
Article 

Google Scholar 
Rumpf, S. B. et al. Range dynamics of mountain plants decrease with elevation. Proc. Natl. Acad. Sci. 115, 201713936. https://doi.org/10.1073/pnas.1713936115 (2018).CAS 
Article 

Google Scholar 
Gigauri, K., Akhalkatsi, M., Abdaladze, O. & Nakhutsrishvili, G. Alpine plant distribution and thermic vegetation indicator on GLORIA summits in the Central Greater Caucasus. Pak. J. Bot. 48, 1893–1902 (2016).
Google Scholar 
Gritsch, A., Dirnböck, T. & Dullinger, S. Recent changes in alpine vegetation differ among plant communities. J. Veg. Sci. 27, 1177–1186. https://doi.org/10.1111/jvs.12447 (2016).Article 

Google Scholar 
Speed, J. D. M., Austrheim, G., Hester, A. J. & Mysterud, A. Elevational advance of alpine plant communities is buffered by herbivory. J. Veg. Sci. 23, 617–625. https://doi.org/10.1111/j.1654-1103.2012.01391.x (2012).Article 

Google Scholar 
Grytnes, J. A. et al. Identifying the driving factors behind observed elevational range shifts on European mountains. Global Ecol. Biogeogr. 23, 876–884. https://doi.org/10.1111/geb.12170 (2014).Article 

Google Scholar 
Johnson, D. R., Ebert-May, D., Webber, P. J. & Tweedie, C. E. Forecasting alpine vegetation change using repeat sampling and a novel modeling approach. Ambio 40, 693. https://doi.org/10.1007/s13280-011-0175-z (2011).Article 
PubMed 
PubMed Central 

Google Scholar 
Amagai, Y., Kudo, G. & Sato, K. Changes in alpine plant communities under climate change: Dynamics of snow-meadow vegetation in northern Japan over the last 40 years. Appl. Veg. Sci. 21, 561–571. https://doi.org/10.1111/avsc.12387 (2018).Article 

Google Scholar 
Crimmins, S. M., Dobrowski, S. Z., Greenberg, J. A., Abatzoglou, J. T. & Mynsberge, A. R. Changes in climatic water balance drive downhill shifts in plant species’ optimum elevations. Science 331, 324–327. https://doi.org/10.1126/science.1199040 (2011).ADS 
CAS 
Article 
PubMed 

Google Scholar 
Engler, R. et al. 21st century climate change threatens mountain flora unequally across Europe. Global Change Biol. 17, 2330–2341. https://doi.org/10.1111/j.1365-2486.2010.02393.x (2011).ADS 
Article 

Google Scholar 
Matteodo, M., Ammann, K., Verrecchia, E. P. & Vittoz, P. Snowbeds are more affected than other subalpine–alpine plant communities by climate change in the Swiss Alps. Ecol. Evol. 6, 6969–6982. https://doi.org/10.1002/ece3.2354 (2016).Article 
PubMed 
PubMed Central 

Google Scholar 
Tingley, M. W., Monahan, W. B., Beissinger, S. R. & Moritz, C. Birds track their Grinnellian niche through a century of climate change. Proc. Natl. Acad. Sci. 106, 19637–19643. https://doi.org/10.1073/pnas.0901562106 (2009).ADS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Cuesta, F. et al. Thermal niche traits of high alpine plant species and communities across the tropical Andes and their vulnerability to global warming. J. Biogeogr. 47, 408–420. https://doi.org/10.1111/jbi.13759 (2020).Article 

Google Scholar 
Hamid, M., Khuroo, A. A., Malik, A. H., Ahmad, R. & Singh, C. P. Assessment of alpine summit flora in Kashmir Himalaya and its implications for long-term monitoring of climate change impacts. J. Mt. Sci. 17, 1974–1988. https://doi.org/10.1007/s11629-019-5924-7 (2020).Article 

Google Scholar 
Steinbauer, K., Lamprecht, A., Semenchuk, P., Winkler, M. & Pauli, H. Dieback and expansions: Species-specific responses during 20 years of amplified warming in the high Alps. Alpine Bot. 130, 1–11. https://doi.org/10.1007/s00035-019-00230-6 (2019).Article 

Google Scholar 
Noroozi, J. et al. Hotspots within a global biodiversity hotspot-areas of endemism are associated with high mountain ranges. Sci. Rep. 8, 10345. https://doi.org/10.1038/s41598-018-28504-9 (2018).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Testolin, R. et al. Global patterns and drivers of alpine plant species richness. Global Ecol. Biogeogr. 30, 12181–12231. https://doi.org/10.1111/geb.13297 (2021).Article 

Google Scholar 
Körner, C. in Alpine Plant Life Ch. 1. Plant ecology at high elevations, 1–22 (Springer, 2021).Smith, J. G., Sconiers, W., Spasojevic, M. J., Ashton, I. W. & Suding, K. N. Phenological changes in alpine plants in response to increased snowpack, temperature, and nitrogen. Arct. Antarct. Alp. Res. 44, 135–142. https://doi.org/10.1657/1938-4246-44.1.135 (2012).Article 

Google Scholar 
Körner, C. Alpine Plant Life. (Springer, 2021).Pauli, H. et al. The GLORIA field manual–standard Multi-Summit approach, supplementary methods and extra approaches. 5th edn, (GLORIA-Coordination, Austrian Academy of Sciences & University of Natural Resources and Life Sciences, 2015).Kuo, C.-C., Su, Y., Liu, H.-Y. & Lin, C.-T. Assessment of climate change effects on alpine summit vegetation in the transition of tropical to subtropical humid climate. Plant Ecol. 222, 933–951. https://doi.org/10.1007/s11258-021-01152-2 (2021).Article 

Google Scholar 
Suonan, J., Classen, A. T., Zhang, Z. & He, J. S. Asymmetric winter warming advanced plant phenology to a greater extent than symmetric warming in an alpine meadow. Funct. Ecol. 31, 2147–2156. https://doi.org/10.1111/1365-2435.12909 (2017).Article 

Google Scholar 
Lamprecht, A. et al. Changes in plant diversity in a water-limited and isolated high-mountain range (Sierra Nevada, Spain). Alpine Bot. 131, 27–39. https://doi.org/10.1007/s00035-021-00246-x (2021).Article 

Google Scholar 
Barthlott, W., Mutke, J., Rafiqpoor, D., Kier, G. & Kreft, H. Global centers of vascular plant diversity. Nova Acta Leopold. 92, 61–83 (2005).
Google Scholar 
Kier, G. et al. A global assessment of endemism and species richness across island and mainland regions. Proc. Natl. Acad. Sci. 106, 9322–9327. https://doi.org/10.1073/pnas.0810306106 (2009).ADS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Huang, S.-F. Historical biogeography of the flora of Taiwan. J. Natl. Taiwan Museum 64, 33–63. https://doi.org/10.1111/j.1756-1051.1995.tb02123.x (2011).Article 

Google Scholar 
Beck, H. E. et al. Present and future Köppen-Geiger climate classification maps at 1-km resolution. Sci. Data 5, 180214. https://doi.org/10.1038/sdata.2018.214 (2018).Article 
PubMed 
PubMed Central 

Google Scholar 
TCCIP. The past and future of climate in Taiwan. 1–31 (National Science and Technology Center for Disaster Reduction & Research Center for Environmental Change, Academia Sinica, New Taipei City, 2018).Central Weather Bureau. in The Typhoon Database (ed Central Weather Bureau;) (https://rdc28.cwb.gov.tw/TDB/, 2021).Henny, L., Thorncroft, C. D., Hsu, H.-H. & Bosart, L. F. Extreme rainfall in Taiwan: Seasonal statistics and trends. J. Climate https://doi.org/10.1175/jcli-d-20-0999.1 (2021).Article 

Google Scholar 
Tu, J.-Y. & Chou, C. Changes in precipitation frequency and intensity in the vicinity of Taiwan: Typhoon versus non-typhoon events. Environ. Res. Lett. 8, 014023. https://doi.org/10.1088/1748-9326/8/1/014023 (2013).ADS 
Article 

Google Scholar 
Liang, A., Oey, L., Huang, S. & Chou, S. Long-term trends of typhoon-induced rainfall over Taiwan: In situ evidence of poleward shift of typhoons in western North Pacific in recent decades. J. Geophys. Res. Atmos. 122, 2750–2765. https://doi.org/10.1002/2017jd026446 (2017).ADS 
Article 

Google Scholar 
Lee, Y.-C., Wang, C.-C., Weng, S.-P., Chen, C.-T. & Cheng, C.-T. Future projections of meteorological drought characteristics in Taiwan. Atmos. Sci. https://doi.org/10.3966/025400022019034701003 (2019).Article 

Google Scholar 
Kudo, G., Kawai, Y., Amagai, Y. & Winkler, D. E. Degradation and recovery of an alpine plant community: Experimental removal of an encroaching dwarf bamboo. Alpine Bot. 127, 75–83. https://doi.org/10.1007/s00035-016-0178-2 (2017).Article 

Google Scholar 
Richman, S. K., Levine, J. M., Stefan, L. & Johnson, C. A. Asynchronous range shifts drive alpine plant–pollinator interactions and reduce plant fitness. Global Change Biol. 26, 3052–3064. https://doi.org/10.1111/gcb.15041 (2020).ADS 
Article 

Google Scholar 
Spasojevic, M. J., Bowman, W. D., Humphries, H. C., Seastedt, T. R. & Suding, K. N. Changes in alpine vegetation over 21 years: Are patterns across a heterogeneous landscape consistent with predictions? Ecosphere 4, 1–18. https://doi.org/10.1890/es13-00133.1 (2013).Article 

Google Scholar 
Rogora, M. et al. Assessment of climate change effects on mountain ecosystems through a cross-site analysis in the Alps and Apennines. Sci. Total Environ. 624, 1429–1442. https://doi.org/10.1016/j.scitotenv.2017.12.155 (2018).ADS 
CAS 
Article 
PubMed 

Google Scholar 
Malanson, G. P., Resler, L. M., Butler, D. R. & Fagre, D. B. Mountain plant communities: Uncertain sentinels? Prog. Phys. Geogr. Earth Environ. 43, 521–543. https://doi.org/10.1177/0309133319843873 (2019).Article 

Google Scholar 
Berauer, B. J. et al. Low resistance of montane and alpine grasslands to abrupt changes in temperature and precipitation regimes. Arct Antarct. Alp. Res. 51, 215–231. https://doi.org/10.1080/15230430.2019.1618116 (2019).Article 

Google Scholar 
Körner, C. in Alpine Plant Life Ch. 9. Water relations, 333–383 (Springer, 2021).Cai, Y. et al. Photosynthetic response of an alpine plant, rhododendron delavayi Franch, to water stress and recovery: The role of Mesophyll conductance. Front. Plant Sci. 6, 1089. https://doi.org/10.3389/fpls.2015.01089 (2015).Article 
PubMed 
PubMed Central 

Google Scholar 
Farooq, M., Wahid, A., Kobayashi, N., Fujita, D. & Basra, S. M. A. in Sustainable Agriculture (eds E. Lichtfouse et al.) 153–188 (Springer, 2009).Greenwood, S., Chen, J. C., Chen, C. T. & Jump, A. S. Temperature and sheltering determine patterns of seedling establishment in an advancing subtropical treeline. J. Veg. Sci. 26, 711–721. https://doi.org/10.1111/jvs.12269 (2015).Article 

Google Scholar 
Morley, P. J., Donoghue, D. N. M., Chen, J. C. & Jump, A. S. Montane forest expansion at high elevations drives rapid reduction in non-forest area, despite no change in mean forest elevation. J. Biogeogr. 47, 2405–2416. https://doi.org/10.1111/jbi.13951 (2020).Article 

Google Scholar 
Salick, J., Ghimire, S. K., Fang, Z., Dema, S. & Konchar, K. M. Himalayan alpine vegetation, climate change and mitigation. J. Ethnobiol. 34, 276–293. https://doi.org/10.2993/0278-0771-34.3.276 (2014).Article 

Google Scholar 
Winkler, M. et al. The rich sides of mountain summits–a pan-European view on aspect preferences of alpine plants. J. Biogeogr. 43, 2261–2273. https://doi.org/10.1111/jbi.12835 (2016).Article 

Google Scholar 
Verheyen, K. et al. Combining biodiversity resurveys across regions to advance global change research. Bioscience 67, 73–83. https://doi.org/10.1093/biosci/biw150 (2016).Article 
PubMed 

Google Scholar 
Ganjurjav, H. et al. Complex responses of spring vegetation growth to climate in a moisture-limited alpine meadow. Sci. Rep. 6, 1–10. https://doi.org/10.1038/srep23356 (2016).CAS 
Article 

Google Scholar 
Nagy, L., Kreyling, J., Gellesch, E., Beierkuhnlein, C. & Jentsch, A. Recurring weather extremes alter the flowering phenology of two common temperate shrubs. Int. J. Biometeorol. 57, 579–588. https://doi.org/10.1007/s00484-012-0585-z (2013).ADS 
CAS 
Article 
PubMed 

Google Scholar 
Jump, A. S., Huang, T.-J. & Chou, C.-H. Rapid altitudinal migration of mountain plants in Taiwan and its implications for high altitude biodiversity. Ecography 35, 204–210. https://doi.org/10.1111/j.1600-0587.2011.06984.x (2012).Article 

Google Scholar 
Cowles, J., Boldgiv, B., Liancourt, P., Petraitis, P. S. & Casper, B. B. Effects of increased temperature on plant communities depend on landscape location and precipitation. Ecol. Evol. 8, 5267–5278. https://doi.org/10.1002/ece3.3995 (2018).Article 
PubMed 
PubMed Central 

Google Scholar 
Oldfather, M. F. & Ackerly, D. D. Increases in thermophilus plants in an arid alpine community in response to experimental warming. Arct. Antarct. Alp. Res. 51, 201–214. https://doi.org/10.1080/15230430.2019.1618148 (2019).Article 

Google Scholar 
Shao, K.-T. Taiwan’s biodiversity research achievements over the past 10 years (2001–2011). Biodivers. Sci. https://doi.org/10.3724/sp.j.1003.2012.06123 (2012).Article 

Google Scholar 
Chen, J.-M., Lu, F.-C., Kuo, S.-L. & Shih, C.-F. Summer climate variability in Taiwan and associated large-scale processes. J. Meteorol. Soc. Japan 83, 499–516. https://doi.org/10.2151/jmsj.83.499 (2005).ADS 
Article 

Google Scholar 
Chen, T.-C., Wang, S.-Y., Huang, W.-R. & Yen, M.-C. Variation of the East Asian summer monsoon rainfall. J. Climate 17, 744–762. https://doi.org/10.1175/1520-0442(2004)017%3c0744:voteas%3e2.0.co;2 (2004).ADS 
Article 

Google Scholar 
Thornthwaite, C. W. An approach toward a rational classification of climate. Geogr. Rev. 38, 55. https://doi.org/10.2307/210739 (1948).Article 

Google Scholar 
Kambach, S. et al. Of niches and distributions: Range size increases with niche breadth both globally and regionally but regional estimates poorly relate to global estimates. Ecography 42, 467–477. https://doi.org/10.1111/ecog.03495 (2019).Article 

Google Scholar 
Luna, B. & Moreno, J. M. Range-size, local abundance and germination niche-breadth in Mediterranean plants of two life-forms. Plant Ecol. 210, 85–95. https://doi.org/10.1007/s11258-010-9740-y (2010).Article 

Google Scholar 
Newbold, T. Applications and limitations of museum data for conservation and ecology, with particular attention to species distribution models. Prog. Phys. Geog. 34, 3–22. https://doi.org/10.1177/0309133309355630 (2010).Article 

Google Scholar 
Karger, D. N., Wilson, A. M., Mahony, C., Zimmermann, N. E. & Jetz, W. Global daily 1 km land surface precipitation based on cloud cover-informed downscaling. Sci. Data 8, 307. https://doi.org/10.1038/s41597-021-01084-6 (2021).Article 
PubMed 
PubMed Central 

Google Scholar 
Welham, S. J., Gezan, S. A., Clark, S. J. & Mead, A. Statistical Methods in Biology: Design and Analysis of Experiments and Regression. (Chapman and Hall/CRC, 2014).R: A Language and Environment for Statistical Computing v. 4.0.3 (2021).Beguería, S., Vicente-Serrano, S. M., Reig, F. & Latorre, B. Standardized precipitation evapotranspiration index (SPEI) revisited: Parameter fitting, evapotranspiration models, tools, datasets and drought monitoring. Int. J. Climatol. 34, 3001–3023. https://doi.org/10.1002/joc.3887 (2014).Article 

Google Scholar 
rgbif: Interface to the Global Biodiversity Information Facility API v. 3.7.1 (2022). More

Matthews, E. G., Lawrence, J. F., Bouchard, P., Steiner, W. E. Jr. & Ślipiński, S. A. Tenebrionidae Latreille, 1802. In Handbook of Zoology. A Natural History of the Phyla of the Animal Kingdom. Vol. IV—Arthropoda: Insecta. Part 38 Coleoptera, Beetles. Vol. 2: Systematics (Part 2) (eds Leschen, R. A. B. et al.) 574–659 (Walter de Gruyter GmbH & Co, 2010).
Google Scholar 
Kergoat, G. J. et al. Higher-level molecular phylogeny of darkling beetles (Coleoptera: Tenebrionidae). Syst. Entomol. 39, 486–499. https://doi.org/10.1111/syen.12065 (2014).Article 

Google Scholar 
Bouchard, P. et al. Review of genus-group names in the family Tenebrionidae (Insecta, Coleoptera). Zookeys 26, 1–633. https://doi.org/10.3897/zookeys.1050.64217 (2021).Article 

Google Scholar 
Matthews, E. G. & Bouchard, P. Tenebrionid Beetles of Australia 398 (Australian Biological Resources Study, 2008).
Google Scholar 
Thomas, D. B. J. R. Patterns in the abundance of some tenebrionid beetles in the Mojave Desert. Environ. Entomol. 8, 568–657 (1979).Article 

Google Scholar 
Seely, M. K. & Louw, G. N. First approximation of the effects of rainfall on the ecology and energetics of a Namib Desert dune ecosystem. J. Arid Environ. 3, 25–54 (1980).ADS 
Article 

Google Scholar 
Crawford, C. S. The community ecology of macroarthropod detritivores. In The Ecology of Desert Communities (ed. Polis, G. A.) 89–112 (The University of Arizona Press, 1991).
Google Scholar 
Mordkovich, V. G. Species richness, population structure and functional significance of black-beetles (Coleoptera: Tenebrionidae) in steppes of Northern Asia. Russ. Entomol. J. 11, 57–68 (2002).
Google Scholar 
Bartholomew, A. & El Moghrabi, J. Seasonal preference of darkling beetles (Tenebrionidae) for shrub vegetation due to high temperatures, not predation or food availability. J. Arid Environ. 156, 34–40 (2018).ADS 
Article 

Google Scholar 
Cheli, G. H., Bosco, T. & Flores, G. The role of Nyctelia dorsata Fairmaire, 1905 (Coleoptera: Tenebrionidae) on litter fragmentation processes and soil biogeochemical cycles in arid Patagonia. Ann. Zool. 72, 129–134. https://doi.org/10.3161/00034541ANZ2022.72.1.011 (2022).Article 

Google Scholar 
Nørgaard, T. & Dacke, M. Fog-basking behaviour and water collection efficiency in Namib Desert Darkling beetles. Front. Zool. 7, 23. https://doi.org/10.1186/1742-9994-7-23 (2010).Article 
PubMed 
PubMed Central 

Google Scholar 
Comanns, P. Passive water collection with the integument: Mechanisms and their biomimetic potential. J. Exp. Biol. 221, jeb153130. https://doi.org/10.1242/jeb.153130 (2018).Article 
PubMed 

Google Scholar 
Doyen, J. T. Familial and subfamilial classification of the Tenebrionoidea (Coleoptera) and a revised generic classification of the Coniontini (Tentyriidae). Quest. Entomol. 8, 357–376 (1972).
Google Scholar 
Schulze, L. The Tenebrionidae of Southern Africa. XLII. Description of the early stages of Carchares macer Pascoe and Herpiscus sommeri Solier with a discussion of some phylogenetic aspects arising from the incongruities of adult and larval systematics. Sci. Pap. Namib Desert Res. Stn. 53, 139–149 (1969).
Google Scholar 
Kamiński, M. J. et al. Reevaluation of Blapimorpha and Opatrinae: Addressing a major phylogeny-classification gap in darkling beetles (Coleoptera: Tenebrionidae: Blaptinae). Syst. Entomol. 46, 140–156. https://doi.org/10.1111/syen.12453 (2021).Article 

Google Scholar 
Skopin, N. G. [Larvae of the subfamily Pimeliinae (Coleoptera, Tenebrionidae)]. Lichinki podsemeystva Pimeliinae (Coleoptera, Tenebrionidae). Trudy Nauchno-Issledovatelskogo Instituta Zashchity Rastenii Kazakhstanskoy Akademii Selskokhozyastvennykh Nauk 7, 191–298 (1962).
Google Scholar 
Skopin, N. G. Die Larven der Tenebrioniden des Tribus Pycnocerini (Coleoptera, Heteromera). Ann. Museé R. l’Afrique Centrale 127, 1–35 (1964).
Google Scholar 
Iwan, D. & Bečvář, S. Description of the early stages of Anomalipus plebejus plebejulus (Coleoptera: Tenebrionidae) from Zimbabwe with notes on the classifcation of the Opatrinae. Eur. J. Entomol. 97, 403–412 (2000).Article 

Google Scholar 
Koch, C. Monograph of the Tenebrionidae of southern Africa Vol I (Tentyriinae, Molurini Trachynotina: Somaticus Hope). Transvaal Mus. Mem. 7, 242 (1955).
Google Scholar 
Kergoat, G. J. Cretaceous environmental changes led to high extinction rates in a hyperdiverse beetle family. BMC Evol. Biol. 14, 220. https://doi.org/10.1186/s12862-014-0220-1 (2014).Article 
PubMed 
PubMed Central 

Google Scholar 
Smith, A. D., Dornburg, R. & Wheeler, Q. D. Larvae of the genus Eleodes (Coleoptera, Tenebrionidae): Matrix-based descriptions, cladistic analysis, and key to late instars. Zookeys 415, 217–268 (2014).Article 

Google Scholar 
Kamiński, M. J. et al. Immature stages of beetles representing the ‘Opatrinoid’ clade (Coleoptera: Tenebrionidae): An overview of current knowledge of the larval morphology and some resulting taxonomic notes on Blapstinina. Zoomorphology 138, 349–370. https://doi.org/10.1007/s00435-019-00443-7 (2019).Article 

Google Scholar 
Rasa, O. A. E. Bechavioural adaptations to moisture as an environmental constraint in a nocturnal burrow-linhabiting Kalahari detritivore Parastizopus amraticpes Peringuey (Coleoptera: Tenebrionidae). Koedoe 37(1), 57–66 (1994).Article 

Google Scholar 
Rasa, O. A. E. Ecological factors influencing burrow location, group size and mortality in a nocturnal fossorial Kalahari detritivore, Parastizopus armaticeps Peringuey (Coleoptera: Tenebrionidae). J. Arid Environ. 29, 353–365 (1995).ADS 
Article 

Google Scholar 
Fabricius, J. C. Supplementum Entomologia Systematica. (Impensis CG Proft, 1978).Péringuey, L. Fourth contribution to the South African coleopterous fauna. Description of new Coleoptera in the South African Museum. Trans. S. Afr. Philos. Soc. 6, 95–136 (1892).Article 

Google Scholar 
Endrody-Younga, S. A revision of the subtribe Gonopina (Coleoptera: Tenebrionidae: Opatrinae: Platynotini). Ann. Transvaal Mus. 37, 1–54 (2000).
Google Scholar 
Kamiński, M. J. Notes on species diversity patterns in Stizopina (Coleoptera: Tenebrionidae), with description of a new genus from Nama Karoo. Ann. Zool. 65, 131–148. https://doi.org/10.3161/00034541ANZ2015.65.2.002 (2015).Article 

Google Scholar 
Schulze, L. The Tenebrionidae of Southern Africa. XXXVIII. On the morphology of the larvae of some Stizopina (Coleoptera: Opatrini). Sci. Pap. Namib Desert Res. Stn. 19, 1–23 (1963).
Google Scholar 
Schulze, L. A review of silk production and spinning activities in Arthropoda with special reference to spinning in Tenebrionid larvae (Coleoptera) and Brown, J. M. M.: A chromatographic analysis of Tenebrionid silk. Mem. Transvaal Mus. 51, 409–410 (1975).
Google Scholar 
Rasa, O. A. E. & Endrödy-Younga, S. Intergeneric associations of stizopinid tenebrionids relative to their geographical distribution (Coleoptera: Tenebrionidae: Opatrini: Stitzopina). Afr. Entomol. 5, 231–239 (1997).
Google Scholar 
Kamiński, M. J., Raś, M., Steiner, W. E. & Iwan, D. Immature stages of beetles representing the ‘Opatrinoid’ clade (Coleoptera: Tenebrionidae): An overview of current knowledge of the pupal morphology. Ann. Zool. 68, 825–836. https://doi.org/10.3161/00034541ANZ2018.68.4.006 (2018).Article 

Google Scholar 
Doyen, J. T. The skeletal anatomy of Tenebrio molitor (Coleoptera: Tenebrionidae). Ann. Entomol. Soc. Am. 5, 103–150 (1966).
Google Scholar 
Ohde, T., Yaginuma, T. & Niimi, T. Insect morphological diversification through the modification of wing serial homologs. Science 340, 495 (2013).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Zhu, J. Y., Yang, P., Zhang, Z., Wu, G. X. & Yang, B. Transcriptomic immune response of Tenebrio molitor pupae to parasitization by Scleroderma guani. PLoS ONE 8, e54411 (2013).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Raś, M., Iwan, D. & Kamiński, M. J. Tracheal system in post-embryonic development of holometabolous insects: A case study using mealworm beetle. J. Anat. 232, 997–1015. https://doi.org/10.1111/joa.12808 (2018).Article 
PubMed 
PubMed Central 

Google Scholar 
Kwon, G. T. et al. Mealworm larvae (Tenebrio molitor L.) exuviae as a novel prebiotic material for BALB/c mouse gut microbiota. Food Sci. Biotechnol. 29(4), 531–537. https://doi.org/10.1007/s10068-019-00699-1 (2019).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Machona, O., Chidzwondo, F. & Mangoyi, R. Tenebrio molitor: Possible source of polystyrene-degrading bacteria. BMC Biotechnol. 22, 2. https://doi.org/10.1186/s12896-021-00733-3 (2022).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Jösting, E. A. Die Innervierung des Skelettmuskelsystems des Mehlwurms (Tenebrio molitor L., Larve). Zool. Jb. Anat. 67, 381–460 (1942).
Google Scholar 
Burakowski, B., Mroczkowski, M. & Stefańska, J. Chrząszcze: Coleoptera. Cucujoidea, Część 3. Katalog Fauny Polski, XXIII, 14 (1987).Schulze, L. The Tenebrionidae of southern Africa. XXXIII. Description of the larvae of Gonopus tibialis Fabricius and Gonopus agrestis Fahraeus (Gonopina, sensu Koch 1956). Cimbebasia 5, 1–12 (1962).
Google Scholar 
Lawrence, J. F., Pollock, D. A. & Ślipiński, A. Tenebrionoidea. In Handbook of Zoology. A Natural History of the Phyla of the Animal kingdom, Vol. IV. Arthropoda: Insecta (eds Leschen, R. A. B. et al.) 487–659 (Walter de Gruyter, 2010).
Google Scholar 
Lawrence, J. F. et al. Phylogeny of the Coleoptera based on morphological characters of adults and larvae. Ann. Zool. 61(1), 1–217 (2011).Article 

Google Scholar 
Beutel, R. G. & Friedrich, F. Comparative study of larvae of Tenebrionoidea (Coleoptera: Cucujiformia). Eur. J. Entomol. 102, 241–264 (2005).Article 

Google Scholar 
Fredrich, F. & Beutel, R. G. The thorax of Zorotypus (Hexapoda, Zoraptera) and a new nomenclature for the musculature of Neoptera. Arthropod Struct. Dev. 37, 29–54 (2008).Article 

Google Scholar 
Beutel, R. G., Friedrich, F., Yang, X.-K. & Ge, S.-Q. Insect Morphology and Phylogeny: A Textbook for Students of Entomology 515 (Walter de Gruyter, 2014).
Google Scholar 
Aibekova, L. et al. The skeletomuscular system of the mesosoma of Formica rufa workers (Hymenoptera: Formicidae). Insect Syst. Divers. 6(2), 1–26. https://doi.org/10.1093/isd/ixac002 (2022).Article 

Google Scholar 
Raś, M. Digging adaptations in psammophilous beetle larvae. Harvard Dataverse https://doi.org/10.7910/DVN/NNAETE (2022).SkyScan. Method Notes, Skyscan 1172 Desktop Micro-CT (Skyscan, 2008).
Google Scholar 
R Core Team. 2020. R: A Language and Environment for Statistical Computing. (R Foundation for Statistical Computing, 2020) https://www.R-project.org/.Sokal, R. R. & Rohlf, F. J. Biometry 937 (W.H. Freeman, 2011).
Google Scholar 
Cloudsley-Thompson, J. L. Terrestrial animals in dry heat: Arthropods. In Handbook of Physiology. Section 4: Adaptation to the Environment 414–436 (American Physiological Society, 1964).
Google Scholar 
Cloudsley-Thompson, J. L. Adaptations of Arthropoda to arid environments. Annu. Rev. Entomol. 20, 261–283. https://doi.org/10.1146/annurev.en.20.010175.001401 (1975).CAS 
Article 
PubMed 

Google Scholar 
Draney, M. L. The subelytral cavity of desert tenebrionids. Fla. Entomol. 76, 539–549 (1993).Article 

Google Scholar 
Duncan, F. D. The role of the subelytral cavity in water loss in the flightless dung beetle, Circellium bacchus (Coleoptera: Scarabaeinae). Eur. J. Entomol. 99(2), 253–258. https://doi.org/10.14411/eje.2002.034 (2002).Article 

Google Scholar 
Endrödy-Younga, S. & Tschinkel, W. Estimation of population size and dispersal in Anomalipus mastodon Fåhraeus, 1870 (Coleoptera: Tenebrionidae: Platynotini). Ann. Transvaal Mus. 36(4), 21–30 (1993).
Google Scholar 
Iwan, D. Insecta Coleoptera Tenebrionidae Pedinini Platynotina. Vol. 93 of Faune de Madagascar 178 (Editions Quae, 2010).
Google Scholar 
Wallwork, J. A. Desert Soil Fauna 296 (Praeger Publication, 1982).
Google Scholar 
Iwan, D. Oviviparity in tenebrionid beetles of the melanocratoid Platynotina (Coleoptera: Tenebrionidae: Platynotini) from Madagascar with notes on the viviparous beetles. Ann. Zool. 50, 15–25 (2000).
Google Scholar 
Kaufmann, T. Observations on some factors which influence aggregated by Blaps sulcata in Israel. Ann. Entomol. Soc. Am. 59, 660–664 (1966).Article 

Google Scholar 
Kiihnelt, G. On the biology and temperature accommodation of Lepidochora argentogrisea Koch. Sci. Pap. Namib Desert Res. Stn. 51, 121–122 (1969).
Google Scholar 
Hamilton, W. J. Competition and thermoregulatory behaviour of the Namib desert tenebrionid beetle genus Cardiosis. Ecology 52, 810–822 (1971).Article 

Google Scholar 
Watt, J. A revised subfamily classifcation of Tenebrionidae (Coleoptera). N. Z. J. Zool. 11, 381–452 (1974).Article 

Google Scholar 
Burakowski, B. Laboratory methods for rearing soil beetles (Coleoptera). Memorab. Zool. 46, 1–66 (1993).
Google Scholar 
De Block, M. & Stoks, R. Fitness effects from egg to reproduction: Bridging the life history transition. Ecology 86, 185–197 (2005).Article 

Google Scholar 
Pechenik, J. A. Larval experience and latent effects: Metamorphosis is not a new beginning. Integr. Comp. Biol. 46, 323–333 (2006).PubMed 
Article 

Google Scholar 
Doyen, J. T. Reconstitution of Coelometopini, Tenebrionini and related tribes of America north of Colombia (Coleoptera: Tenebrionidae). J. N. Y. Entomol. Soc. 97, 277–304 (1989).
Google Scholar 
St. George, R. A. Studies on the larvae on North American beetles of the subfamily Tenebrioninae with a description of the larva and pupa of Merinus laevis (Olivier). Proc. U.S. Natl. Mus. 65, 1–22. https://doi.org/10.5479/si.00963801.65-2514.1 (1924).Article 

Google Scholar 
Purchart, L. & Nabozhenko, M. V. First description of larva and pupa of the genus Deretus (Coleoptera: Tenebrionidae) with key to the larvae of the tribe Helopini. Acta Entomol. Musei Natl. Pragae 52, 295–302 (2012).
Google Scholar 
Steiner, W. Larvae and pupae of two North American darkling beetles (Coleoptera, Tenebrionidae, Stenochiinae), Glyptotus cribratus LeConte and Cibdelis blaschkei Mannerheim, with notes on ecological and behavioural similarities. ZooKeys 415, 311–327. https://doi.org/10.3897/zookeys.415.6891 (2014).Article 

Google Scholar 
Wagner, G. & Gosik, R. Comparative morphology of immature stages of two sympatric Tenebrionidae species, with comments on their biology. Zootaxa 4111, 201–222 (2017).Article 

Google Scholar  More

Lehmkuhl, F. et al. Loess landscapes of Europe-mapping, geomorphology, and zonal differentiation. Earth-Sci. Rev. 215, 103496 (2021).Article 

Google Scholar 
Li, Y., Shi, W., Aydin, A., Beroya-Eitner, M. A. & Gao, G. Loess genesis and worldwide distribution. Earth Sci. Rev. 201, 102947 (2020).Article 

Google Scholar 
Moine, O. et al. The impact of last Glacial climate variability in west-European loess revealed by radiocarbon dating of fossil earthworm granules. PNAS 114, 6209–6214 (2017).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Újvári, G. et al. Coupled European and Greenland last glacial dust activity driven by North Atlantic climate. PNAS 114, E10632–E10638 (2017).ADS 
PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Rousseau, D.-D. et al. Link between European and North Atlantic abrupt climate changes over the last glaciation. Geophys. Res. Lett. 34, L22713 (2007).ADS 
Article 

Google Scholar 
Rousseau, D.-D. et al. Eurasian contribution to the last glacial dust cycle: how are loess sequences built?. Clim. Past. 13, 1181–1197 (2017).Article 

Google Scholar 
Fischer, P. et al. Millennial-scale terrestrial ecosystem responses to Upper Pleistocene climatic changes: 4D-reconstruction of the Schwalbenberg Loess-Palaeosol-Sequence (Middle Rhine Valley, Germany). CATENA 196, 104913 (2021).Article 

Google Scholar 
Wolf, D. et al. Evidence for strong relations between the Upper Tagus Loess Formation (Central Iberia) and the marine atmosphere off the Iberian Margin during the Last Glacial Period. Quat. Res. 101, 84–113 (2021).Article 

Google Scholar 
Porter, S. & An, Z. Correlation between climate events in the North Atlantic and China during the last glaciation. Nature 375, 305–308 (1995).ADS 
CAS 
Article 

Google Scholar 
Sun, Y. et al. Influence of Atlantic meridional overturning circulation on the East Asian winter monsoon. Nat. Geosci. 5, 46–49 (2012).ADS 
CAS 
Article 

Google Scholar 
Zeeden, C. et al. Patterns and timing of loess-palaeosol transitions in Eurasia: Constraints for palaeoclimate studies. Glob. Planet. Change 162, 1–7 (2018).ADS 
Article 

Google Scholar 
Cheng, H. et al. The climatic cyclicity in semiarid-arid central Asia over the past 500,000 years. Geophys. Res. Lett. 39, L01705 (2012).ADS 
Article 

Google Scholar 
Cheng, H. et al. The Asian monsoon over the past 640,000 years and ice age terminations. Nature 534, 640–646 (2016).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Chiang, J. C. H. et al. Role of seasonal transitions and westerly jets in East Asian paleoclimate. Quat. Sci. Rev. 108, 111–129 (2015).ADS 
Article 

Google Scholar 
Youn, J. H., Seong, Y. B., Choi, J. H., Abdrakhmatov, K. & Ormukov, C. Loess deposits in the northern Kyrgyz Tien Shan: Implications for the paleoclimate reconstruction during the Late Quaternary. CATENA 117, 81–93 (2014).Article 

Google Scholar 
Li, Y. et al. Eolian dust dispersal patterns since the last glacial period in eastern Central Asia: Insights from a loess-paleosol sequence in the Ili Basin. Clim. Past 14, 271–286 (2018).Article 

Google Scholar 
Frechen, M., Oches, E. A. & Kohfeld, K. E. Loess in Europe—Mass accumulation rates during the Last Glacial Period. Quat. Sci. Rev. 22, 1835–1857 (2003).ADS 
Article 

Google Scholar 
Antoine, P. et al. High resolution record of the last climatic cycle in the southern carpathian basin at Surduk (vojvodina, Serbia). Quat. Int. 198, 19–36 (2009).MathSciNet 
Article 

Google Scholar 
Antoine, P. et al. Upper Pleistocene loess-palaeosols records from Northern France in the European context: Environmental background and dating of the Middle Palaeolithic. Quat. Int. 411, 4–24 (2016).Article 

Google Scholar 
Kang, S., Roberts, H. M., Wang, X., An, Z. S. & Wang, M. Mass accumulation rate changes in Chinese loess during MIS 2, and asynchrony with records from Greenland ice cores and North Pacific Ocean sediments during the last glacial maximum. Aeol. Res. 19, 251–258 (2015).Article 

Google Scholar 
Fitzsimmons, K. E. et al. Loess accumulation in the Tian Shan piedmont: Implications for palaeoenvironmental change in arid Central Asia. Quat. Int. 469, 30–43 (2018).Article 

Google Scholar 
Li, Y., Song, Y., Qiang, M., Miao, Y. & Zeng, M. Atmospheric dust variations in the Ili Basin, northwest China, during the last glacial period as revealed by a high mountain loess-paleosol sequence. J. Geophys. Res. Atmos. 124, 8449–8466 (2019).ADS 
Article 

Google Scholar 
Pinto, J. G. & Ludwig, P. Extratropical cyclones over the North Atlantic and western Europe during the last glacial maximum and implications for proxy interpretation. Clim. Past 16, 611–626 (2020).Article 

Google Scholar 
Cheng, L. et al. Drivers for asynchronous patterns of dust accumulation in central and eastern Asia and in Greenland during the Last Glacial Maximum. Geophys. Res. Lett. 48, e2020GL01194 (2021).
Google Scholar 
Fenn, K. et al. A tale of two signals: Global and local influences on the Late Pleistocene loess sequences in Bulgarian Lower Danube. Quat. Sci. Rev. 274, 107264 (2021).Article 

Google Scholar 
Song, Y. et al. Spatio-temporal distribution of Quaternary loess across Central Asia. Palaeogeogr. Palaeoclim. Palaeoecol. 567, 110279 (2021).ADS 
Article 

Google Scholar 
Hughes, P. D. & Gibbard, P. L. A stratigraphical basis for the Last Glacial Maximum (LGM). Quat. Int. 383, 174–185 (2015).Article 

Google Scholar 
Baykal, Y. et al. Detrital zircon U-Pb age analysis of last glacial loess sources and proglacial sediment dynamics in the Northern European Plain. Quat. Sci. Rev. 274, 107265 (2021).Article 

Google Scholar 
Pötter, S. et al. Disentangling sedimentary pathways for the Pleniglacial Lower Danube loess based on geochemical signatures. Front. Earth Sci. 9, 150 (2021).ADS 
Article 

Google Scholar 
Prud’homme, C. et al. δ13C signal of earthworm calcite granules: A new proxy for palaeoprecipitation reconstructions during the Last Glacial in western Europe. Quat. Sci. Rev. 179, 158–166 (2018).ADS 
Article 

Google Scholar 
Obreht, I. et al. A critical reevaluation of palaeoclimate proxy records from loess in the Carpathian Basin. Earth-Sci. Rev. 190, 498–520 (2019).ADS 
CAS 
Article 

Google Scholar 
Joannin, S. et al. Vegetation, fire and climate history of the Lesser Caucasus: A new Holocene record from Zarishat fen (Armenia). J. Quat. Sci. 29, 70–82 (2014).Article 

Google Scholar 
Brittingham, A. et al. Influence of the north atlantic oscillation on δD and δ18O in meteoric water in the Armenian highland. J. Hydrol. 575, 513–522 (2019).ADS 
CAS 
Article 

Google Scholar 
Bohn, U., Zazanashvili, N. & Nakhutsrishvili, G. The map of the natural vegetation of Europe and its application in the caucasus ecoregion. Bull. Georgian Natl. Acad. Sci. 175, 112–121 (2007).
Google Scholar 
Trigui, Y. et al. First calibration and application of leaf wax n-alkane biomarkers in Loess-Paleosol sequences and modern plants and soils in Armenia. Geosciences 9, 263 (2019).ADS 
CAS 
Article 

Google Scholar 
Richter, C. et al. New insights into southern Caucasian glacial-interglacial climate conditions inferred from Quaternary Gastropod Fauna. J. Quat. Sci. 35, 634–649 (2020).Article 

Google Scholar 
Kharzyan, E. Geological Map of Republic of Armenia (Ministry of Nature Protection of Republic of Armenia, 2005).
Google Scholar 
Sosson, M. et al. Subductions, obduction and collision in the Lesser Caucasus (Armenia, Azerbaijan, Georgia), new insights. Geol. Soc. Spec. Publ. 340, 329–352 (2010).ADS 
Article 

Google Scholar 
Lomax, J. et al. Testing post-IR-IRSL dating on Armenian loess palaeosol sections against independent age control. Quat. Geochron. 69, 101265 (2021).Article 

Google Scholar 
Újvári, G., Kovács, J., Varga, G., Raucsik, B. & Markovic, S. B. Dust flux estimates for the Last Glacial Period in East Central Europe based on terrestrial records of loess deposits: A review. Quat. Sci. Rev. 29, 3157–3166 (2010).ADS 
Article 

Google Scholar 
Rudnick, R. L. & Gao, S. Composition of the continental crust. In The Crust (ed. Rudnick, R. L.) 1–64 (Elsevier-Pergamon, 2003).
Google Scholar 
Újvári, G., Varga, A. & Balogh-Brunstad, Z. Origin, weathering, and geochemical composition of loess in southwestern Hungary. Quat. Res. 69, 421–437 (2008).Article 
CAS 

Google Scholar 
Galoyan, G. et al. Geology, geochemistry and 40Ar/39Ar dating of Sevan ophiolites (Lesser Caucasus, Armenia): Evidence for Jurassic Back-arc opening and hot spot event between the South Armenian Block and Eurasia. J. Asian Earth Sci. 34, 135–153 (2009).ADS 
Article 

Google Scholar 
Hässig, M. et al. New structural and petrological data on the Amasia ophiolites (NW Sevan-Akera suture zone, Lesser Caucasus): Insights for a large-scale obduction in Armenia and NE Turkey. Tectonophysics 588, 135–153 (2013).ADS 
Article 
CAS 

Google Scholar 
Sahakyan, L. et al. Geochemistry of the Eocene magmatic rocks from the Lesser Caucasus area (Armenia): Evidence of a subduction geodynamic environment. in Tectonic Evolution of the Eastern Black Sea and Caucasus (eds. Sosson, M., Stephenson, R. A., Adamia, S. A.). Geological Society Special Publication. Vol. 428. (2016).Obreht, I. et al. Tracing the influence of Mediterranean climate on Southeastern Europe during the past 350,000 years. Sci. Rep. 6, 36334 (2016).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Profe, J., Wacha, L., Frechen, M., Ohlendorf, C. & Zolitschka, B. XRF scanning of discrete samples—A chemostratigraphic approach exemplified for loess-paleosol sequences from the Island of Susak, Croatia. Quat. Int. 494, 34–51 (2018).Article 

Google Scholar 
Profe, J., Zolitschka, B., Schirmer, W., Frechen, M. & Ohlendorf, C. Geochemistry unravels MIS3/2 paleoenvironmental dynamics at the loess-paleosol sequence Schwalbenberg II, Germany. Palaeogeogr. Palaeoclim. Palaeoecol. 459, 537–551 (2016).ADS 
Article 

Google Scholar 
Zeeden, C. et al. Three climatic cycles recorded in a loess-palaeosol sequence at Semlac (Romania)—Implications for dust accumulation in south-eastern Europe. Quat. Sci. Rev. 154, 130–142 (2016).ADS 
Article 

Google Scholar 
Song, Y. et al. Magnetic stratigraphy of the Danube loess: A composite Titel-Stari Slankamen loess section over the last one million years in Vojvodina, Serbia. J. Asian Earth Sci. 155, 68–80 (2018).ADS 
Article 

Google Scholar 
Rouzaut, S. & Orgeira, M. J. Influence of volcanic glass on the magnetic signal of different paleosols in Córdoba, Argentina. Stud. Geophys. Geod. 61, 361–384 (2017).ADS 
Article 

Google Scholar 
Campodonico, V. A., Rouzaut, S. & Pasquini, A. I. Geochemistry of a Late Quaternary loess-paleosol sequence in central Argentina: Implications for weathering, sedimentary recycling and provenance. Geoderma 351, 235–249 (2019).ADS 
CAS 
Article 

Google Scholar 
Wolf, D. et al. Loess in Armenia—Stratigraphic findings and palaeoenvironmental indications. Proc. Geol. Assoc. 127, 29–39 (2016).Article 

Google Scholar 
Buggle, B. et al. Iron mineralogical proxies and Quaternary climate change in SE-European Loess–Paleosol sequences. CATENA 117, 4–22 (2014).CAS 
Article 

Google Scholar 
Bradák, B. et al. Magnetic susceptibility in the European Loess Belt: New and existing models of magnetic enhancement in Loess. Palaeogeogr. Palaeoclim. Palaeoecol. 569, 110329 (2021).ADS 
Article 

Google Scholar 
Laag, C. et al. A detailed paleoclimate proxy record for the Middle Danube Basin over the Last 430 kyr: A rock magnetic and colorimetric study of the Zemun loess-paleosol sequence. Front. Earth Sci. 9, 600086 (2021).ADS 
Article 

Google Scholar 
Baumgart, P., Hambach, U., Meszner, S. & Faust, D. An environmental magnetic fingerprint of periglacial loess: Records of Late Pleistocene loess–palaeosol sequences from eastern Germany. Quat. Int. 296, 82–93 (2013).Article 

Google Scholar 
Boers, N., Ghil, M. & Rousseau, D.-D. Ocean circulation, ice shelf, and sea ice interactions explain Dansgaard-Oeschger cycles. PNAS 115, E11005–E11014 (2018).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Menviel, L. C., Skinner, L. C., Tarasov, L. & Tzedakis, P. C. An ice–climate oscillatory framework for Dansgaard-Oeschger cycles. Nat. Rev. Earth Environ. 1, 677–693 (2020).ADS 
Article 

Google Scholar 
Rasmussen, S. O. et al. A stratigraphic framework for abrupt climatic changes during the Last Glacial period based on three synchronized Greenland ice-core records: refining and extending the INTIMATE event stratigraphy. Quat. Sci. Rev. 106, 14–28 (2014).ADS 
Article 

Google Scholar 
Martrat, B. et al. Four climate cycles ofrecurring deep and surface water destabilizations on the Iberian margin. Science 317, 502–507 (2007).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Broecker, W. S. Massive iceberg discharges as triggers for global climate change. Nature 372, 421–424 (1994).ADS 
CAS 
Article 

Google Scholar 
Jin, L., Chen, F., Ganopolski, A. & Claussen, M. Response of East Asian climate to Dansgaard/Oeschger and Heinrich events in a coupled model of intermediate complexity. J. Geophys. Res. 112, D06117 (2007).ADS 

Google Scholar 
Sun, Y., Wang, X., Liu, Q. & Clemens, S. C. Impacts of post-depositional processes on rapid monsoon signals recorded by the last glacial loess deposits of northern China. Earth Planet. Sci. Lett. 289, 171–179 (2010).ADS 
CAS 
Article 

Google Scholar 
Yang, S. & Ding, Z. A 249 kyr stack of eight loess grain size records from northern China documenting millennial-scale climate variability. Geochem. Geophys. Geosyst. 15, 798–814 (2014).ADS 
Article 

Google Scholar 
Obreht, I. et al. Shift of large-scale atmospheric systems over Europe during late MIS 3 and implications for modern human dispersal. Sci. Rep. 7, 5848 (2017).ADS 
PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Antoine, P. et al. Evidence of rapid and cyclic eolian deposition during the Last Glacial in European loess series (Loess events): The high-resolution records from Nussloch (Germany). Quat. Sci. Rev. 28, 2955–2973 (2009).ADS 
Article 

Google Scholar 
Rousseau, D. D. et al. North Atlantic abrupt climatic events of the last glacial period recorded in Ukrainian loess deposits. Clim. Past 7, 221–234 (2011).Article 

Google Scholar 
Machalett, B. et al. Aeolian dust dynamics in Central Asia during the Pleistocene: driven by the long-term migration, seasonality and permanency of the Asiatic polar front. Geophys. Geochem. Geosyst. 9, Q08Q09 (2008).Article 
CAS 

Google Scholar 
Berger, A. & Loutre, M. F. Insolation values for the climate of the last 10 million years. Quat. Sci. Rev. 10, 297–317 (1991).ADS 
Article 

Google Scholar 
Kutzbach, J., Chen, G., Cheng, H., Edwards, R. & Liu, Z. Potential role of winter rainfall in explaining increased moisture in the Mediterranean and Middle East during periods of maximum orbitally-forced insolation seasonality. Clim. Dynam. 42, 1079–1095 (2014).ADS 
Article 

Google Scholar 
Marković, S. B. et al. Danube loess stratigraphy—Towards a pan-European loess stratigraphic model. Earth Sci. Rev. 148, 228–258 (2015).ADS 
Article 

Google Scholar 
Li, G. et al. Paleoenvironmental changes recorded in a luminescence dated loess/paleosol sequence from the Tianshan Mountains, arid central Asia, since the penultimate glaciation. Earth Planet. Sci. Lett. 448, 1–12 (2016).ADS 
CAS 
Article 

Google Scholar 
Lomax, J. et al. A luminescence-based chronology for the Harletz Loess sequence, Bulgaria. Boreas 48, 179–194 (2019).Article 

Google Scholar 
Kehl, M. et al. Pleistocene dynamics of dust accumulation and soil formation in the southern Caspian Lowlands—New insights from the loess-paleosol sequence at Neka-Abelou, northern Iran. Quat. Sci. Rev. 253, 106774 (2021).Article 

Google Scholar 
Ganopolski, A., Calov, R. & Claussen, M. Simulation of the last glacial cycle with a coupled climate ice-sheet model of intermediate complexity. Clim. Past 6, 229–244 (2010).Article 

Google Scholar 
Malinsky-Buller, A. et al. Evidence for Middle Palaeolithic occupation and landscape change in central Armenia at the open-air site of Alapars-1. Quat. Res. 99, 223–247 (2021).Article 

Google Scholar 
Rao, Z. et al. High-resolution summer precipitation variations in the western Chinese Loess Plateau during the last glacial. Sci. Rep. 3, 2785 (2013).PubMed 
PubMed Central 
Article 

Google Scholar 
Stevens, T., Marković, S. B., Zech, M., Hambach, U. & Sümegi, P. Dust deposition and climate in the Carpathian Basin over an independently dated last glacial-interglacial cycle. Quat. Sci. Rev. 30, 662–681 (2011).ADS 
Article 

Google Scholar 
Torfstein, A., Goldstein, S. L., Stein, M. & Enzel, Y. Impacts of abrupt climate changes in the Levant from Last Glacial Dead Sea levels. Quat. Sci. Rev. 69, 1–7 (2013).ADS 
Article 

Google Scholar 
Pickarski, N., Kwiecien, O., Langgut, D. & Litt, T. Abrupt climate and vegetation variability of eastern Anatolia during the last glacial. Clim. Past 11, 1491–1505 (2015).Article 

Google Scholar 
Wegwerth, A. et al. Northern hemisphere climate control on the environmental dynamics in the glacial Black Sea “Lake”. Quat. Sci. Rev. 135, 41–53 (2016).ADS 
Article 

Google Scholar 
Ollivier, V., Fontugne, M. & Lyonnet, B. Geomorphic response and 14C chronology of base-level changes induced by Late Quaternary Caspian Sea mobility (middle Kura Valley, Azerbaijan). Geomorphology 230, 109–124 (2015).ADS 
Article 

Google Scholar 
Egeland, C. P. et al. Bagratashen 1, a stratified open-air Middle Paleolithic site in the Debed river valley of northeastern Armenia: A preliminary report. Archaeol. Res. Asia 8, 1–20 (2016).Article 

Google Scholar 
von Suchodoletz, H., Gärtner, A., Zielhofer, C. & Faust, D. Eemian and post-Eemian fluvial dynamics in the Lesser Caucasus. Quat. Sci. Rev. 191, 189–203 (2018).ADS 
Article 

Google Scholar 
Langbein, W. B. & Schumm, S. A. Yield of sediment in relation to mean annual precipitation. Trans. Am. Geophys. Union 39, 1076–1084 (1958).ADS 
Article 

Google Scholar 
Wolman, M. G. & Miller, J. P. Magnitude and frequency of forces in geomorphic processes. J. Geol. 68, 54–74 (1960).ADS 
Article 

Google Scholar 
Svirčev, Z. et al. Importance of biological loess crusts for loess formation in semi-arid environments. Quat. Int. 296, 206–215 (2013).Article 

Google Scholar 
Reber, R. et al. Glacier advances in northeastern Turkey before and during the global Last Glacial Maximum. Quat. Sci. Rev. 101, 177–192 (2014).ADS 
Article 

Google Scholar 
Ammann, C., Jenny, B., Kammer, K. & Messerli, B. Late Quaternary glacier response to humidity changes in the arid Andes of Chile (18–29 °S). Palaeogeogr. Palaeoclim. Palaeoecol. 172, 313–326 (2001).ADS 
Article 

Google Scholar 
Domínguez-Villar, D. et al. Early maximum extent of paleoglaciers from Mediterranean mountains during the last glaciation. Sci. Rep. 3, 2034 (2013).PubMed 
PubMed Central 
Article 

Google Scholar 
Spötl, C. et al. Increased autumn and winter precipitation during the Last Glacial Maximum in the European Alps. Nat. Commun. 12, 1839 (2021).ADS 
PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Shumilovskikh, L. S. et al. Orbital and millennial-scale environmental changes between 64 and 20 ka BP recorded in Black Sea sediments. Clim. Past 10, 939–954 (2014).Article 

Google Scholar 
Wegwerth, A. et al. Black Sea temperature response to glacial millennial-scale climate variability. Geophys. Res. Lett. 42, 8147–8154 (2015).ADS 
Article 

Google Scholar 
Sarıkaya, M. A., Zreda, M., Çiner, A. & Zweck, C. Cold and wet Last Glacial Maximum on Mount Sandıras, SW Turkey, inferred from cosmogenic dating and glacier modeling. Quat. Sci. Rev. 27, 769–780 (2008).ADS 
Article 

Google Scholar 
Lézine, A.-M. et al. Lake Ohrid, Albania, provides an exceptional multi-proxy record of environmental changes during the last glacial–interglacial cycle. Palaeogeogr. Palaeoclim. Palaeoecol. 287, 116–127 (2010).ADS 
Article 

Google Scholar 
Tecsa, V. et al. Revisiting the chronostratigraphy of late Pleistocene loess-paleosol sequences in southwestern Ukraine: OSL dating of Kurortne section. Quat. Int. 542, 65–79 (2020).Article 

Google Scholar 
Luetscher, M. et al. North Atlantic storm track changes during the Last Glacial Maximum recorded by Alpine speleothems. Nat. Commun. 6, 6344 (2015).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Ludwig, P., Schaffernicht, E. J., Shao, Y. & Pinto, J. G. Regional atmospheric circulation over Europe during the Last Glacial Maximum and its links to precipitation. J. Geophys. Res.-Atmos. 121, 2130–2145 (2016).ADS 
Article 

Google Scholar 
Schaffernicht, E. J., Ludwig, P. & Shao, Y. Linkage between dust cycle and loess of the last glacial maximum in Europe. Atmos. Chem. Phys. 20, 4969–4986 (2020).ADS 
CAS 
Article 

Google Scholar 
Beghin, P. et al. What drives LGM precipitation over the western Mediterranean? A study focused on the Iberian Peninsula and northern Morocco. Clim. Dyn. 46, 2611–2631 (2016).Article 

Google Scholar 
Sümegi, P. et al. Vegetation and land snail-based reconstruction of the palaeocological changes in the forest steppe eco-region of the Carpathian Basin during last glacial warming. Glob. Ecol. Conserv. 33, e01976 (2022).Article 

Google Scholar 
Chen, J. et al. Revisiting Late Pleistocene Loess-Paleosol sequences in the Azov Sea Region of Russia: Chronostratigraphy and paleoenvironmental record. Front. Earth Sci. 9, 808157 (2022).Article 

Google Scholar 
Xepos, S. Analysis of trace elements in geological materials, soils and sludges. Spectro XRF Rep. 193, 1–5 (2007).
Google Scholar 
Buggle, B. et al. Geochemical characterization and origin of Southeastern and Eastern European loesses (Serbia, Romania, Ukraine). Quat. Sci. Rev. 27, 1058–1075 (2008).ADS 
Article 

Google Scholar 
Weltje, G. J. & Tjallingii, R. Calibration of XRF core scanners for quantitative geochemical logging of sediment cores: Theory and application. Earth Planet. Sci. Lett. 274, 423–438 (2008).ADS 
CAS 
Article 

Google Scholar 
Dearing, J. Environmental Magnetic Susceptibility: Using the Bartington MS2 System (Chi Publishing, 1999).
Google Scholar 
Buylaert, J., Murray, A. S., Thomsen, K. J. & Jain, M. Testing the potential of an elevated temperature IRSL signal from K-feldspar. Radiat. Meas. 44, 560–565 (2009).CAS 
Article 

Google Scholar 
Lomax, J. et al. Establishing a luminescence-based chronostratigraphy for the Last Glacial-interglacial cycle of the Loess-Palaeosol sequence Achajur (Armenia). Front. Earth Sci. 9, 755084 (2021).Article 

Google Scholar 
Lamothe, M., Auclair, M., Hamzaoui, C. & Huot, S. Towards a prediction of long-term anomalous fading of feldspar IRSL. Radiat. Meas. 37, 493–498 (2003).CAS 
Article 

Google Scholar 
Tudyka, K. et al. Increased dose rate precision in combined α and β counting in the μDose system—A probabilistic approach to data analysis. Radiat. Meas. 134, 106310 (2020).CAS 
Article 

Google Scholar 
Kolb, T. et al. The µDose-system: Determination of environmental dose rates by combined alpha and beta counting—Performance tests and practical experiences. GChron 4, 1–31 (2021).ADS 

Google Scholar 
Durcan, J. A., King, G. & Duller, G. DRAC: Dose rate and age calculator for trapped charge dating. Quat. Geochron. 28, 54–61 (2015).Article 

Google Scholar 
von Suchodoletz, H. & Faust, D. Late Quaternary fluvial dynamics and landscape evolution at the lower Shulaveris Ghele River (southern Caucasus). Quat. Res. 89, 254–269 (2018).Article 

Google Scholar 
von Suchodoletz, H. et al. Late Pleistocene river migrations in response to thrust belt advance and sediment-flux steering e the Kura River (southern Caucasus). Geomorphology 266, 53–65 (2016).ADS 
Article 

Google Scholar 
Ryan, W. B. F. et al. Global multi-resolution topography (GMRT) synthesis data set. Geochem. Geophys. Geosyst. 10, Q03014 (2009).ADS 
Article 

Google Scholar 
Nalivkin, D. V. et al. Geologicheskaya Karta Kavkaza, Mashtav 1:500.000 (Geological Map of the Caucasus, Scale 1:500,000). (Ministry of Geology of the USSR, 1976). More

Share this articleAnyone you share the following link with will be able to read this content:Get shareable linkSorry, a shareable link is not currently available for this article.Copy to clipboard
Provided by the Springer Nature SharedIt content-sharing initiative More

Diverse oviposition rates of Drosophila females after long exposure to waspsTo investigate whether D. melanogaster change oviposition behavior when they cohabit with Lb female wasps, we designed an experimental procedure and monitored egg laying for a much longer time than in previous experiments – approximately 20 days. Specifically, twenty 3-day-old female and five 3-day-old male D. melanogaster adults were placed in standard fly bottles containing fly food dishes. Flies were housed with twenty 2-day-old Lb female wasps (exposed) or without any female wasps (unexposed). The fly food dishes were replaced daily, and fly eggs were counted daily (Fig. 1a). Consistent with previous observations24, the exposed Drosophila females had significantly reduced oviposition numbers compared to the unexposed flies (Fig. 1b). This response lasted approximately 6 days in the presence of Lb females. After that, we surprisingly found that the number of eggs laid by the exposed flies did not differ from the numbers laid by the unexposed controls (Fig. 1b). This variation led us to speculate that this decreased oviposition may have been induced by the diverse life-threatening pressure when D. melanogaster females encounter different aged wasps, as old ones present less danger to their offspring28,29, or simply indicate that the flies become habituated to the constant presence of wasps.Fig. 1: D. melanogaster oviposition rates are altered in the presence of young Lb females.a Standard oviposition assay design. Each bottle contained twenty Canton-S (CS) female flies and five CS male flies, either with twenty female Lb wasps (exposed) or with no wasps (unexposed). Flies aged 3 days post-eclosion and wasps aged 2 days post-emergence were used. The food dishes were replaced daily, and the eggs laid each day were counted. b The daily number of eggs laid by the unexposed and exposed CS flies. Flies were exposed to wasps for 20 days. The experiment was performed eighteen times. Data represent the mean ± SEM. Significance was determined by two-way ANOVA with Sidak’s multiple comparisons test, p values are indicated in Source Data file (***p  More