Ecology

Study areaWe conducted the study in the best-preserved stands of the Białowieża Forest, strictly protected within the Białowieża National Park (hereafter BNP; coordinates of Białowieża village: 52°42′N, 23°52′E). The extensive Białowieża Forest (c. 1500 km2) straddles the Polish-Belarusian border, where the climate is subcontinental with annual mean temperatures during May–July of 13–18 °C, and mean annual precipitation of 426–940 mm66,67.The forest provides a unique opportunity to observe animals under conditions that likely prevailed across European lowlands before widespread deforestation and forest exploitation by humans66,68,69. The stands have retained a primeval character distinguished by a multi-layered structure, frequent fallen and standing dead trees, and a high species richness66,70. The stands are composed of about a dozen tree species of various ages, up to several hundred years old. The interspecific interactions and natural processes have been little affected by direct human activity.We conducted observations mostly within the three permanent study plots (MS, N, W), totalling c. 130 ha, and in other nearby fragments of primeval oak-lime-hornbeam Tilio-Carpinetum or mixed deciduous-coniferous Pino-Quercetum stands. However, a small number of observations from adjacent managed deciduous forest stands were also included. For details of the study area see71,72,73.Study speciesOur study system focused on ground-nesting Wood Warblers Phylloscopus sibilatrix, blowflies Protocalliphora azurea, and Myrmica or Lasius ants, which occurred in the birds’ nests.The Wood Warbler is a small (c. 10 g) insectivorous songbird that winters in equatorial Africa and breeds in temperate European forests, typically rearing one or two broods each year74. Wood Warblers build dome-shaped nests for each breeding attempt, composed of woven grass, leaves and moss, and lined with animal hair73. The nests are situated on the ground among moderately sparse vegetation, often under a tussock of vegetation or near a fallen tree-branch or log (see examples in Supplementary Fig. S2)53,75. The breeding season of Wood Warblers begins in late April–early May and ends in July–August, when nestlings from replacement clutches (after initial loss) or second broods leave the nest. The typical clutch size in BNP is 5–7 eggs, and the nestling stage lasts 12–13 days74,76.Wood Warbler nests are inhabited by various arthropods, including Myrmica ruginodis or M. rubra ants, and less often Lasius platythorax, L. niger or L. brunneus. The ants foraged and/or raised their own broods within the Wood Warbler nests52. The Myrmica and Lasius ant species are common in Europe77,78. Their colonies contain from tens to thousands of workers, and can be found on the forest floor, e.g. in soil, within or under fallen dead wood, in patches of moss, or among fallen tree-leaves53,77,78. All of the ant species found in the Wood Warbler nests are predators of other arthropods77,79,80.Blowflies, Protocalliphora spp., are obligatory blood-sucking (hematophagous) ectoparasites that reproduce within bird nests. The occurrence, abundance, and impact of blowflies on Wood Warbler offspring is largely unknown, similar to many other European songbirds that build dome-shaped nests. Adult blowflies emerge in late spring and summer to lay eggs on the birds’ nesting material or directly onto the skin of typically newly hatched nestlings14,26. The blowfly larvae hatch within two–three days, and develop in the structure of warm bird nests for another 6–15 days, during which they emerge intermittently to feed on host blood, before finally pupating within the nests14,25,26,27.Data collectionNest monitoring and measurements of nestlingsWe searched for Wood Warbler nests daily from late April until mid-July in 2018–2020, by following birds mainly during nest-building. Nests were assigned to a deciduous or mixed deciduous-coniferous habitat type, depending on the tree stand where they were found. We inspected nests systematically, according to the protocol described in Wesołowski and Maziarz76. The number of observer visits was kept to a minimum to reduce disruptions for birds or potential risks of nest predation.We aimed to establish the dates of hatching (day 0 ± 1 day), nestlings vacating the nest (fledging; ± 1 day) or nest failure (± 1–2 days). When nestlings hatched asynchronously, the hatching date corresponded to the earliest record of nestling hatching. The dates of fledging or nest failure were the mid-dates between the last visit when the nestlings were present in the nest, and the following visit, when the nest was found empty. Nest failure was primarily due to predation, which is the main cause of the Wood Warbler nest losses in BNP76,81 and elsewhere in Europe82,83.To assess fitness consequences for birds of variable weather conditions, blowfly abundance and/or ant presence, we measured nestling growth and determined brood reduction (i.e. the mortality of chicks in the nest) from hatching until fledging. To define brood reduction, we assessed the number of hatchlings (nestlings up to 4 days old) and the number of fledglings leaving the nests. To ensure accurate counting and avoid premature fledging of nestlings, we established the number of fledglings on the day of measurement, when all nestlings were temporarily extracted from the nest.We measured nestling growth on a single occasion when they were 6–9 days old (median 8 days), almost fully developed but too young to leave the nest. The measurements lasted for less than 10–15 min at each nest to minimise any potential risk of attracting predators. For each nestling we measured (using a ruler) the emerged length of the longest (3rd) primary feather vane (± 0.5 mm) on the left wing84,85, and body mass to the nearest 0.1 g using an electronic balance. The length of the feather vane is closely linked to feather growth86 and is one of the characteristics of nestling growth85,87. We treated the length of the primary feather vane and body mass as indices of nestling growth rate under varying conditions of weather, blood-sucking ectoparasites, or ant presence.Extraction of arthropods from bird nestsTo assess the number of blowflies and to establish the presence of ants, we checked the contents of 129 nests (including 11 nests from the managed forest stands) at which Wood Warbler nestlings had been measured. The sample included 86 successful breeding attempts (where a minimum of one nestling successfully left the nest), 27 failed (predated) nests (remnants of nestlings were found, but the nest structure remained intact), and 16 nests with an unknown fate (nestlings were large, so were capable of leaving the nest, but no family were located or other signs indicating fledging).Due to ethical reasons, we were unable to collect the Wood Warbler nests and extract the ectoparasites and ants from them while they were in use by the birds. Removing the nests and replacing them with dummy nests would cause unacceptable nest desertion by adults. Therefore, we assessed the occurrence and number of blowflies or ant presence after Wood Warbler nestlings fledged or the breeding attempts failed naturally. We retrospectively explored the changes in blowfly infestation14, including the effect of ant presence53 in the same nests.We collected nests from the field as soon as a breeding attempt ended, within approximately five days (median 1 day) following fledging or nest failure (nest structure remained intact). The delay of nest collection would not bias the ectoparasite infestation, as blowfly larvae pupate within bird nests and stay there after the hosts abandon their nests; puparia can be still found in nests collected in autumn or winter14. As the likelihood of finding ant broods (larvae or pupae associated with workers) was rather stable with the delay of nest collection53, the method seemed reliable also for assessing the presence of ant broods (35 of all 71 Wood Warbler nests containing ants). Only the number of nests with lone foraging ant workers could be underestimated, potentially inflating the uncertainty of tested relationships. However, as ants usually re-use rich food resources88, foraging Myrmica or Lasius ant workers might regularly exploit warbler nests, increasing the chances of finding the insects in the collected nests.Wood Warbler nests were collected in one piece, with each placed into a separate sealed and labelled plastic bag. We carefully inspected the leaf litter around the nests, and the soil surface under them, to make sure that all blowfly larvae or pupae were collected. We transported the collected nests to a laboratory, where we stored them in a fridge for up to 5–6 days before the arthropod extraction.To establish the number of blowflies and the presence of ants, in 2018, we carefully pulled apart the nesting material and searched for the arthropods amongst it 52. We gathered all blowfly pupae or larvae and a sample of ant specimens into separate tubes, labelled and filled with 70–80% alcohol, for later species identification. For nests collected in 2019–2020, we extracted the arthropods with a Berlese-Tullgren funnel. During the extraction, which usually lasted for 72 h, each nest was covered with fine metal mesh and placed c. 15 cm under the heat of a 40 W electric lamp. The arthropods were caught in 100 ml plastic bottles containing 30 ml of 70–80% ethanol, installed under each funnel. After the arthropod extraction, we carefully inspected the nesting material in the same way as in 2018, to collect any blowflies that remained within the nests. The quality of information collected on the number of ectoparasites and ant presence should be comparable each year.Weather dataWe obtained the mean daily temperatures and rainfall sums from a meteorological station, operated by the Meteorology and Water Management National Research Institute in the Białowieża village, 1–7 km from the study areas.Data analysesWeather conditions affecting blowfly ectoparasitesTo explore the impact of weather on blowfly ectoparasites, for each Wood Warbler nest we calculated average temperatures from daily means, and total sums of rainfall from daily sums, for the two time-windows in which we assumed the impact of weather would be of greatest importance:

i.

the early nestling stage, when Wood Warbler nestlings were 1–4 days old. During this stage, female blowflies require a minimum temperature of c. 16 °C to become active and oviposit in bird nests27. Thus, cool and wet weather in the early nestling stage should reduce the activity of ovipositing blowflies, leading to less frequent ectoparasite infestation of Wood Warbler nests.

ii.

The late nestling stage, when the warbler nestlings were aged between over four days old and until fledging or nest failure. During this stage, blowfly larvae grow and develop in bird nests after hatching a few days after oviposition14,25,26,27. As the temperature of bird nests strongly depends on ambient temperatures21, mortality of blowfly larvae should increase in cool weather, resulting in fewer ectoparasites in nests collected shortly after the fledging of birds29.

Weather conditions affecting Wood Warbler nestling growthTo explore the impact of weather on nestling growth, for each nest we calculated the average temperatures and total sums of rainfall for the period when nestlings were over four days old and until their measurement, usually on day 8 from hatching (see above). During this stage, nestlings are no longer brooded by a parent74, so must balance their energetic expenditure between growth (feather length and body mass) or thermoregulation89. Thus, we expected that the gain in body mass and the growth of flight feathers would be reduced in nestlings during cool and wet weather, when maintaining a stable body temperature would be costly90.Statistical analysesAll statistical tests were two-tailed and performed in R version 4.1.091.The changes in blowfly infestation of the Wood Warbler nestsTo test the changes in blowfly infestation of warbler nests, we used zero-augmented negative binomial models (package pscl in R;92,93), which deal with the problem of overdispersion and excess of zeros92. In this study, hurdle and zero-inflated models fitted with the same covariates had an almost identical Akaike Information Criterion (AIC). Therefore, we presented only the results of hurdle models, which are easier to interpret than zero-inflated models. Hurdle models consisted of two parts: a left-truncated count with a negative binomial distribution representing the number of blowflies in infested nests, and a zero hurdle binomial estimating the probability of blowfly presence. We used models with a negative binomial distribution, which had a much lower AIC than with a Poisson distribution on a count part.We designed the most complex (global) model that contained a response variable of the number of blowflies in each of the 129 Wood Warbler nests. The covariates were: mean ambient temperature, total sum of rainfall, presence (or absence) of ants in the same nests, habitat type (deciduous vs mixed deciduous-coniferous forest), study year (2018–2020), the number of nestlings hatched (brood size), and nest phenology (the relative hatching date of Wood Warbler nestlings, as days from the median hatching date in a season: 23 May in 2018, 25 May in 2019 and 29 May in 2020). The initial global model also contained the two-way interaction terms that we suspected to be important: between temperature and rainfall, temperature and presence of ants, and rainfall and presence of ants.To explore all potentially meaningful subsets of models, we used the same covariates on both parts (count and binomial) of the global model. We performed automated model selection with the MuMIn package94, starting from the most complex (global) model and using all possible simpler models (i.e. all subsets)95. To attain the minimum sample size of c. 20 data points for each parameter96, we limited the maximum number of parameters to six in each part (count or binomial) of the candidate models.As some of the interaction terms appeared insignificant in the initial model selection, to minimise the risk of over-parametrisation, we included only the significant interaction term on a count part of the final global model. As described above, we performed model selection again. We tested linear relationships, as the quadratic effects of weather variables (presuming temperature or rainfall optima) appeared insignificant.To test whether blowfly infestation changed with weather in the early or late nestling stages, we twice repeated the procedure described above. The first global model included the mean ambient temperature and the total sum of rainfall for the early nestling stage, and the second global model contained weather variables for the late nestling stage. The remaining covariates were the same.A practice of including the same sets of covariates on count and binomial parts has been previously questioned97. However, our approach allowed us to comply with these objections97, as we presented only the most parsimonious models (with ΔAICc  More

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Lal, R. Soil carbon sequestration impacts on global climate change and food security. Science 304, 1623–1627 (2004).ADS 
PubMed 

Google Scholar 
Torn, M. S., Vitousek, P. M. & Trumbore, S. E. The influence of nutrient availability on soil organic matter turnover estimated by incubations and radiocarbon modeling. Ecosystems 8, 352–372 (2005).
Google Scholar 
Schimel, J. P. & Schaeffer, S. M. Microbial control over carbon cycling in soil. Front. Microbiol. 3, 348 (2012).PubMed 
PubMed Central 

Google Scholar 
Ding, X., Liang, C., Zhang, B., Yuan, Y. & Han, X. Higher rates of manure application lead to greater accumulation of both fungal and bacterial residues in macroaggregates of a clay soil. Soil Biol. Biochem. 84, 137–146 (2015).
Google Scholar 
Liang, C., Schimel, J. P. & Jastrow, J. D. The importance of anabolism in microbial control over soil carbon storage. Nat. Microbiol. 2, 17105 (2017).PubMed 

Google Scholar 
Kögel-Knabner, I. The macromolecular organic composition of plant and microbial residues as inputs to soil organic matter: fourteen years on. Soil Biol. Biochem. 105, A3–A8 (2017).
Google Scholar 
Miltner, A., Bombach, P., Schmidt-Brücken, B. & Kästner, M. SOM genesis: microbial biomass as a significant source. Biogeochemistry 111, 41–55 (2012).
Google Scholar 
Cotrufo, M. F., Wallenstein, M. D., Boot, C. M., Denef, K. & Paul, E. The Microbial Efficiency-Matrix Stabilization (MEMS) framework integrates plant litter decomposition with soil organic matter stabilization: Do labile plant inputs form stable soil organic matter?. Global Change Biol. 19, 988–995 (2013).ADS 

Google Scholar 
Sokol, N. W. & Bradford, M. A. Microbial formation of stable soil carbon is more efficient from belowground than aboveground input. Nat. Geosci. 12, 46–53 (2019).ADS 

Google Scholar 
Six, J., Frey, S. D., Thiet, R. K. & Batten, K. M. Bacterial and fungal contributions to carbon sequestration in agroecosystems. Soil Sci. Soc. Am. J. 70, 555–569 (2006).ADS 

Google Scholar 
Simpson, A. J., Simpson, M. J., Smith, E. & Kelleher, B. P. Microbially derived inputs to soil organic matter: Are current estimates too low?. Environ. Sci. Technol. 41, 8070–8076 (2007).ADS 
PubMed 

Google Scholar 
Liang, C., Fujinuma, R. & Balser, T. C. Comparing PLFA and amino sugars for microbial analysis in an Upper Michigan old growth forest. Soil Biol. Biochem. 40, 2063–2065 (2008).
Google Scholar 
Shao, P., Liang, C., Lynch, L., Xie, H. & Bao, X. Reforestation accelerates soil organic carbon accumulation: Evidence from microbial biomarkers. Soil Biol. Biochem. 131, 182–190 (2019).
Google Scholar 
Ma, S. et al. Effects of seven-year nitrogen and phosphorus additions on soil microbial community structures and residues in a tropical forest in Hainan Island, China. Geoderma 361, 114034 (2020).ADS 

Google Scholar 
Zelles, L. Fatty acid patterns of phospholipids and lipopolysaccharides in the characterisation of microbial communities in soil: A review. Biol. Fertil. Soils 29, 111–129 (1999).
Google Scholar 
Kong, A. Y. Y. et al. Microbial community composition and carbon cycling within soil microenvironments of conventional, low-input, and organic cropping systems. Soil Biol. Biochem. 43, 20–30 (2011).PubMed 
PubMed Central 

Google Scholar 
Müller, K., Marhan, S., Kandeler, E. & Poll, C. Carbon flow from litter through soil microorganisms: From incorporation rates to mean residence times in bacteria and fungi. Soil Biol. Biochem. 115, 187–196 (2017).
Google Scholar 
Amelung, W. Syntax of Referencing in Assessment Methods for Soil Carbon (Lewis Publishers, 2001).
Google Scholar 
Joergensen, R. & Wichern, F. Quantitative assessment of the fungal contribution to microbial tissue in soil. Soil Biol. Biochem. 40, 2977–2991 (2008).
Google Scholar 
Joergensen, R. G. Amino sugars as specific indices for fungal and bacterial residues in soil. Biol. Fert. Soils 54, 559–568 (2018).
Google Scholar 
Wang, X. et al. Distinct regulation of microbial processes in the immobilization of labile carbon in different soils. Soil Biol. Biochem. 142, 107723 (2020).
Google Scholar 
Wang, J., Chapman, S. J. & Yao, H. Incorporation of 13C-labelled rice rhizodeposition into soil microbial communities under different fertilizer applications. Appl. Soil Ecol. 101, 11–19 (2016).ADS 

Google Scholar 
Cui, S. et al. Long-term fertilization management affects the C utilization from crop residues by the soil micro-food web. Plant Soil 429, 335–348 (2018).
Google Scholar 
Liu, X., Zhang, X. & Herbert, S. Feeding China’s growing needs for grain. Nature 465, 420 (2010).ADS 
PubMed 

Google Scholar 
Edmeades, D. C. The long-term effects of manures and fertilisers on soil productivity and quality: A review. Nutr. Cycl. Agroecosys. 66, 165–180 (2003).
Google Scholar 
Chaparro, J., Sheflin, A., Manter, D. & Vivanco, J. Manipulating the soil microbiome to increase soil health and plant fertility. Biol. Fertil. Soils 48, 489–499 (2012).
Google Scholar 
Jin, X. et al. Enhanced conversion of newly-added maize straw to soil microbial biomass C under plastic film mulching and organic manure management. Geoderma 313, 154–162 (2018).ADS 

Google Scholar 
Chen, X., Li, Z., Liu, M., Jiang, C. & Che, Y. Microbial community and functional diversity associated with different aggregate fractions of a paddy soil fertilized with organic manure and/or NPK fertilizer for 20 years. J. Soil Sediment. 15, 292–301 (2014).
Google Scholar 
Wang, Y. et al. Soil aggregation regulates distributions of carbon, microbial community and enzyme activities after 23-year manure amendment. Appl. Soil Ecol. 111, 65–72 (2017).
Google Scholar 
Joergensen, R. G., Mäder, P. & Fließbach, A. Long-term effects of organic farming on fungal and bacterial residues in relation to microbial energy metabolism. Biol. Fert. Soils 46, 303–307 (2010).
Google Scholar 
Sun, H. et al. Soil microbial community and microbial residues respond positively to minimum tillage under organic farming in Southern Germany. Appl. Soil Ecol. 108, 16–24 (2016).
Google Scholar 
Heijboer, A. et al. Plant biomass, soil microbial community structure and nitrogen cycling under different organic amendment regimes; A 15N tracer-based approach. Appl. Soil Ecol. 107, 251–260 (2016).
Google Scholar 
Six, J., Elliott, E. T. & Paustian, K. Soil macroaggregate turnover and microaggregate formation: A mechanism for C sequestration under no-tillage agriculture. Soil Biol. Biochem. 32, 2099–2103 (2000).
Google Scholar 
Wall, D. et al. Soil Ecology and Ecosystem Services (Oxford University Press, 2012).
Google Scholar 
Helgason, B. L., Walley, F. L. & Germida, J. J. No-till soil management increases microbial biomass and alters community profiles in soil aggregates. Appl. Soil Ecol. 46, 390–397 (2010).
Google Scholar 
Blaud, A. et al. Dynamics of bacterial communities in relation to soil aggregate formation during the decomposition of 13C-labelled rice straw. Appl. Soil Ecol. 53, 1–9 (2012).
Google Scholar 
Tisdall, J. M. & Oades, J. M. Organic matter and water stable aggregates in soils. Eur. J. Soil Sci. 33, 141–163 (1982).
Google Scholar 
Bronick, C. J. & Lal, R. Soil structure and management: A review. Geoderma 124, 3–22 (2005).ADS 

Google Scholar 
Li, N. et al. Separation of soil microbial community structure by aggregate size to a large extent under agricultural practices during early pedogenesis of a Mollisol. Appl. Soil Ecol. 88, 9–20 (2015).
Google Scholar 
Bidisha, M., Joerg, R. & Yakov, K. Effects of aggregation processes on distribution of aggregate size fractions and organic C content of a long-term fertilized soil. Eur. J. Soil Biol. 46, 365–370 (2010).
Google Scholar 
Xiang, X. et al. Divergence in fungal abundance and community structure between soils under long-term mineral and organic fertilization. Soil Till. Res. 196, 104491 (2020).
Google Scholar 
Jin, X. et al. Long-term plastic film mulching and fertilization treatments changed the annual distribution of residual maize straw C in soil aggregates under field conditions: Characterization by 13C tracing. J. Soils Sediment. 18, 169–178 (2018).
Google Scholar 
Kemper, W. & Rosenau, R. Syntax of referencing. In Methods of Soil Analysis (ed. Klute, A.) (ASA and SSSA, 1986).
Google Scholar 
Bossio, D. A. & Scow, K. M. Impact of carbon and flooding on the metabolic diversity of microbial communities in soils. Appl. Environ. Microbiol. 61, 4043–4050 (1995).ADS 
PubMed 
PubMed Central 

Google Scholar 
Denef, K. et al. Community shifts and carbon translocation within metabolically-active rhizosphere microorganisms in grasslands under elevated CO2. Biogeosciences 4, 769–779 (2007).ADS 

Google Scholar 
Tavi, N. M. et al. Linking microbial community structure and allocation of plant-derived carbon in an organic agricultural soil using 13CO2 pulse-chase labelling combined with 13C-PLFA profiling. Soil Biol. Biochem. 58, 207–215 (2013).
Google Scholar 
Bach, E. M., Baer, S. G., Meyer, C. K. & Six, J. Soil texture affects soil microbial and structural recovery during grassland restoration. Soil Biol. Biochem. 42, 2182–2191 (2010).
Google Scholar 
Pan, F., Li, Y., Chapman, S. J., Khan, S. & Yao, H. Microbial utilization of rice straw and its derived biochar in a paddy soil. Sci. Total Environ. 559, 15–23 (2016).ADS 
PubMed 

Google Scholar 
Olsson, P. A. Signature fatty acids provide tools for determination of the distribution and interactions of mycorrhizal fungi in soil. FEMS Microbial Ecol. 29, 303–310 (1999).
Google Scholar 
Zhang, X. & Amelung, W. Gas Chromatographic determination of muramic acid, glucosamine, mannosamine, and galactosamine in soils. Soil Biol. Biochem. 28, 1201–1206 (1996).
Google Scholar 
Zhang, X. et al. Land-use effects on amino sugars in particle size fractions of an Argiudoll. Appl. Soil Ecol. 11, 271–275 (1999).
Google Scholar 
van Groenigen, K.-J. et al. Abundance, production and stabilization of microbial biomass under conventional and reduced tillage. Soil Biol. Biochem. 42, 48–55 (2010).
Google Scholar 
Liang, C., Amelung, W., Lehmann, J. & Kastner, M. Quantitative assessment of microbial necromass contribution to soil organic matter. Global Change Biol. 25, 3578–3590 (2019).ADS 

Google Scholar 
Engelking, B., Flessa, H. & Joergensen, R. G. Shifts in amino sugar and ergosterol contents after addition of sucrose and cellulose to soil. Soil Biol. Biochem. 39, 2111–2118 (2007).
Google Scholar 
Chander, K. & Joergensen, R. G. Decomposition of 14C glucose in two soils with different amounts of heavy metal contamination. Soil Biol. Biochem. 33, 1811–1816 (2001).
Google Scholar 
Zhu, Z. et al. Fate of rice shoot and root residues, rhizodeposits, and microbial assimilated carbon in paddy soil – part 2: turnover and microbial utilization. Plant Soil. 416, 243–257 (2017).
Google Scholar 
Appuhn, A. & Joergensen, R. Microbial colonisation of roots as a function of plant species. Soil Biol. Biochem. 38, 1040–1051 (2006).
Google Scholar 
Huang, Y., Liang, C., Duan, X., Chen, H. & Li, D. Variation of microbial residue contribution to soil organic carbon sequestration following land use change in a subtropical karst region. Geoderma 353, 340–346 (2019).ADS 

Google Scholar 
Liang, C. et al. Microorganisms and their residues under restored perennial grassland communities of varying diversity. Soil Biol. Biochem. 103, 192–200 (2016).
Google Scholar 
Kallenbach, C. M., Frey, S. D. & Grandy, A. S. Direct evidence for microbial-derived soil organic matter formation and its ecophysiological controls. Nat. Commun. 7, 13630 (2016).ADS 
PubMed 
PubMed Central 

Google Scholar 
Veresoglou, S. D., Chen, B. & Rillig, M. C. Arbuscular mycorrhiza and soil nitrogen cycling. Soil Biol. Biochem. 46, 53–62 (2012).
Google Scholar 
Treseder, K. K. A meta-analysis of mycorrhizal responses to nitrogen, phosphorus, and atmospheric CO2 in field studies. New Phytol. 164, 347–355 (2004).PubMed 

Google Scholar 
Xu, Y. et al. Microbial assimilation dynamics differs but total mineralization from added root and shoot residues is similar in agricultural Alfsols. Soil Biol. Biochem. 148, 107901 (2020).
Google Scholar 
Chenu, C. & Stotzky, G. Syntax of referencing in Interactions between soil particles and microorganisms (eds. Huang, P., Bollag, J. & Senesi, N.) 3–39 (Wiley-VCH, 2002).Chantigny, M., Angers, D., Prévost, D., Vézina, L.-P. & Chalifour, F. Soil aggregation and fungal and bacterial biomass under annual and perennial cropping systems. Soil Sci. Soc. Am. J. 61, 262–267 (1997).ADS 

Google Scholar 
Liang, C., Duncan, D., Balser, T., Tiedje, J. & Jackson, R. Soil microbial residue storage linked to soil legacy under biofuel cropping systems in southern Wisconsin, USA. Soil Biol. Biochem. 57, 939–942 (2013).
Google Scholar 
Feng, Y. et al. Temperature thresholds drive the global distribution of soil fungal decomposers. Glaobal Change Biol. 28, 2779–2789 (2022).
Google Scholar 
An, T. et al. Carbon fluxes from plants to soil and dynamics of microbial immobilization under plastic film mulching and fertilizer application using 13C pulse-labeling. Soil Biol. Biochem. 80, 53–61 (2015).
Google Scholar 
Lauer, F., Kösters, R., du Preez, C. C. & Amelung, W. Microbial residues as indicators of soil restoration in South African secondary pastures. Soil Biol. Biochem. 43, 787–794 (2011).
Google Scholar  More

Bolliger, J., Kienast, F. & Zimmermann, N. E. Risk of global warming on montane and subalpine forests in Switzerland—A modeling study. Reg. Environ. Change 1, 99–111 (2000).
Google Scholar 
Bugmann, H. & Pfister, Ch. Impacts of interannual climate variability on past and future forest composition. Reg. Environ. Change 1, 112–125 (2000).
Google Scholar 
Becker, A. & Bugmann, H. (eds.) Global change and mountain regions: The Mountain Research Initiative. IHDP Report 13, GTOS Report 28 and IGBP Report 49, Stockholm (2001).Kullman, L. 20th Century climate warming and tree-limit rise in the southern Scandes of Sweden. Ambio 30, 72–80. https://doi.org/10.1579/0044-7447-30.2.72 (2001).CAS 
PubMed 

Google Scholar 
Körner, Ch. & Paulsen, J. A world-wide study of high altitude treeline temperatures. J. Biogeogr. 31, 713–732. https://doi.org/10.1111/j.1365-2699.2003.01043.x (2004).
Google Scholar 
Harsch, M. A. & Bader, M. Y. Treeline form—A potential key to understanding treeline dynamics. Global Ecol. Biogeogr. 20, 582–596. https://doi.org/10.1111/j.1466-8238.2010.00622.x (2011).
Google Scholar 
Tokarczyk, N. Forest encroachment on temperate mountain meadows: scale, drivers, and current research directions. Geogr. Pol. 90, 463–480 (2017).
Google Scholar 
Vitali, A. et al. Pine recolonization dynamics in Mediterranean human-disturbed treeline ecotones. For. Ecol. Manag. 435, 28–37. https://doi.org/10.1016/j.foreco.2018.12.039 (2019).
Google Scholar 
Heikkinen, O., Obrębska-Starkel, B. & Tuhkanen, S. Introduction: the timberline—A changing battlefront. Prace Geograficzne UJ 98, 7–16 (1995).
Google Scholar 
Mattson, J. Human impact on the timberline in the far North of Europe. Zeszyty Naukowe UJ, Prace Geogr. 98, 41–56 (1995).
Google Scholar 
Stanisci, A., Lavieri, D., Acosta, A. & Blasi, C. Structure and diversity trends at Fagus timberline in central Italy. Community Ecol. 1, 133–138 (2000).
Google Scholar 
Gehrig-Fasel, J., Guisan, A. & Zimmermann, N. E. Tree line shifts in the Swiss Alps: Climate change or land abandonment?. J. Veg. Sci. 18, 571–582 (2007).
Google Scholar 
Feurdean, A. et al. Long-term land-cover/use change in a traditional farming landscape in Romania inferred from pollen data, historical maps and satellite images. Reg. Environ. Change 17, 2193–2207. https://doi.org/10.1007/s10113-016-1063-7 (2017).
Google Scholar 
Burga, C. A., Bührer, S. & Klötzli, F. Mountain ash (Sorbus aucuparia) forests of the Central and Southern Alps (Grisons and Ticino, Switzerland-Prov. Verbano-Cusio-Ossola, N-Italy): Plant ecological and phytosociological aspects. Tuexenia 39, 121–138 (2019).
Google Scholar 
Slayter, R. O. & Noble, I. R. Dynamics of Montane Treelines. In Landscape Boundaries, Consequences for Biotic Diversity and Ecological Flows. Ecological Studies Vol. 92 (eds Hansen, A. J. & di Castri, F.) 346–359 (Springer-Verlag, 1992).
Google Scholar 
Bryn, A. Recent forest limit changes in south-east Norway: Effects of climate change or regrowth after abandoned utilisation?. Nor. Geogr. Tidsskr. 62(4), 251–270. https://doi.org/10.1080/00291950802517551 (2008).
Google Scholar 
Lu, X., Liang, E., Wang, Y., Babst, F. & Camarero, J. J. Mountain treelines climb slowly despite rapid climate warming. Glob. Ecol. Biogeogr. 30(1), 305–315. https://doi.org/10.1111/geb.13214 (2021).
Google Scholar 
Armand, A. D. Sharp and Gradual Mountain Timberlines as Result of species Interaction. Landscape Boundaries, Consequences for Biotic Diversity and Ecological Flows. In Ecological Studies Vol. 92 (eds Hansen, A. J. & di Castri, F.) 360–377 (Springer-Verlag, 1992).
Google Scholar 
Kucharzyk, S. Ekologiczne znaczenie drzewostanów w strefie górnej granicy lasu w Karpatach Wschodnich i ich wrażliwość na zmiany antropogeniczne [Ecological importance of stands at the upper forest limit in the Eastern Carpathians and their sensibility to anthropogenic changes]. Roczn. Bieszcz. 14, 15–43 (2006) (in Polish with English summary).
Google Scholar 
Surina, B. & Rakaj, M. Subalpine beech forest with Hairy alpenrose (Polysticho lonchitis-Fagetum Rhododendretosum hirsuti subass. nova) on Mt. Snežnik (Liburnian Karst, Dinaric Mts). Hacquetia 6, 195–208 (2007).
Google Scholar 
Kucharzyk, S. Zmiany przebiegu górnej granicy lasu w pasmie Szerokiego Wierchu w Bieszczadzkim Parku Narodowym [Changes of upper forest limit in the Szeroki Wierch range (Bieszczady National Park)]. Roczn. Bieszcz. 12, 81–102 (2004) (in Polish with English summary).
Google Scholar 
Kucharzyk, S. & Augustyn, M. Dynamika górnej granicy lasu w Bieszczadach Zachodnich – zmiany w ciągu półtora wieku [The upper forest limit dynamics in the Western Bieszczady Mts.—Changes over a century and a half]. Stud. Nat. 54, 133–156 (2008) (in Polish with English summary).
Google Scholar 
Kubijowicz, W. Życie pasterskie w Beskidach Wschodnich [La Vie Pastorale dans les Beskides Orientales]. Prace Instytutu Geograficznego UJ 5, 3–30 (1926) (in Polish).
Google Scholar 
Zarzycki, K. Lasy Bieszczadów Zachodnich [The forests of the Western Bieszczady Mts (Polish Eastern Carpathians)]. Acta Agr. et Silv. Ser. Leśna 3, 1–131 (1963) (in Polish with English summary).
Google Scholar 
Augustyn, M. Połoniny w Bieszczadach Zachodnich [Almen im westlichen Bieszczady-Gebirge]. Materiały Muzeum Budownictwa Ludowego w Sanoku 31, 88–98 (1993) (in Polish with German summary).
Google Scholar 
Winnicki, T. Zbiorowiska roślinne połonin Bieszczadzkiego Parku Narodowego (Bieszczady Zachodnie, Karpaty Wschodnie) [Plant communities of subalpine poloninas in the Bieszczady National Park (Western Bieszczady Mts, Eastern Carpathians)]. Monogr. Bieszczadzkie 4, 1–215 (1999) (in Polish with English summary).
Google Scholar 
Mróz, W. Zróżnicowanie szaty roślinnej przy górnej granicy lasu w Bieszczadach Wschodnich i Zachodnich [The diversity of vegetation near the upper timberline in the Eastern and the Western Bieszczady Mts]. Roczn. Bieszcz. 14, 45–62 (2006) (in Polish with English summary).
Google Scholar 
Augustyn, M. & Kucharzyk, S. Górna granica lasu na terenie wsi Ustrzyki Górne i Wołosate w końcu XVIII wieku [Timberline in the Western Bieszczady Mts.]. Roczn. Bieszcz. 20, 15–27 (2012) (in Polish with English summary).
Google Scholar 
Jeník, J. Succession on the Połonina Balds in the Western Bieszczady, the Eastern Carpathians. Tuexenia 3, 207–216 (1983).
Google Scholar 
Michalik, S. & Szary, A. Zbiorowiska leśne Bieszczadzkiego Parku Narodowego [The forest communities of the Bieszczady National Park]. Monogr. Bieszcz. 1, 1–175 (1997).
Google Scholar 
Zemanek, B. & Winnicki, T. Rośliny naczyniowe Bieszczadzkiego Parku Narodowego [Vascular plants of the Bieszczady National Park]. Monogr. Bieszcz. 3, 1–249 (1999) (in Polish with English summary).
Google Scholar 
Kucharzyk, S. & Augustyn, M. Trwałość polan reglowych w Bieszczadzkim Parku Narodowym [Stability of mountain glades in the Bieszczady National Park]. Roczn. Bieszcz. 18, 45–58 (2010) (in Polish with English summary).
Google Scholar 
Durak, T., Żywiec, M. & Ortyl, B. Rozprzestrzenianie się zarośli drzewiastych w piętrze połonin Bieszczad Zachodnich [Expansion of brushwood in the subalpine zone of the Western Bieszczady Mts]. Sylwan 157, 130–138 (2013) (in Polish with English summary).
Google Scholar 
Durak, T., Żywiec, M., Kapusta, P. & Holeksa, J. Impact of land use and climate changes on expansion of woody species on subalpine meadows in the Eastern Carpathians. For. Ecol. Manag. 339, 127–135. https://doi.org/10.1016/j.foreco.2014.12.014 (2015).
Google Scholar 
Durak, T., Żywiec, M., Kapusta, P. & Holeksa, J. Rapid spread of a fleshy-fruited species in abandoned subalpine meadows—Formation of an unusual forest belt in the eastern Carpathians. iForest – Biogeosci. For. 9, 337–343. https://doi.org/10.3832/ifor1470-008 (2015).
Google Scholar 
Wężyk, P. & Hawryło, P. Analiza struktury 3D drzewostanów Bieszczadzkiego PN na podstawie danych lotniczego skanowania laserowego oraz ortofotomap lotniczych CIR [3D structure analysis of stands of the Bieszczady National Park on the basis of airborne laser scanning data and CIR aerial ortho-photomaps] (ProGea Consulting, 2015) (in Polish).Anselin, L. Local indicators of spatial association—LISA. Geogr. Anal. 27, 93–115. https://doi.org/10.1111/j.1538-4632.1995.tb00338.x (1995).
Google Scholar 
Scott, L. M. & Janikas, M. V. Spatial Statistics in ArcGIS. In Handbook of Applied Spatial Analysis (eds Fischer, M. M. & Getis, A.) 27–41 (Springer, 2010).
Google Scholar 
Cui, H., Wu, L., Hu, S., Lu, R. & Wang, S. Research on the driving forces of urban hot spots based on exploratory analysis and binary logistic regression model. Trans. GIS 25(3), 1522–1541. https://doi.org/10.1111/tgis.12739 (2021).
Google Scholar 
Pierce, K. B., Lookingbill, T. & Urban, D. A simple method for estimating potential relative radiation (PRR) for landscape-scale vegetation analysis. Landsc. Ecol. 20, 137–147 (2005).
Google Scholar 
Riley, S. J., DeGloria, S. D. & Elliot, R. A terrain ruggedness index that quantifies topographic heterogeneity. Int. J. Sc. 5, 23–27 (1999).
Google Scholar 
Böhner, J. & Antonić, O. Land-surface parameters specific to topo-climatology. Geomorphometry – Concepts, Softw. Appl. Dev. Soil Sci. 33, 195–226. https://doi.org/10.1016/S0166-2481(08)00008-1 (2009).
Google Scholar 
R Core Team. R: A Language and Environment for Statistical Computing (R Core Team, 2021).
Google Scholar 
Agresti, A. An Introduction to Categorical Data Analysis 2nd edn. (Wiley & Sons Inc., 2007).MATH 

Google Scholar 
Cottrell, A. Gnu Regression, Econometrics and Time-series Library gretl. http://gretl.sourceforge.net/(2020).Hellevik, O. Linear versus logistic regression when the dependent variable is a dichotomy. Qual. Quant. 43, 59–74 (2009).
Google Scholar 
Azen, R. & Traxel, N. Using dominance analysis to determine predictor importance in logistic regression. J. Educ. Behav. Stat. 34, 319–347. https://doi.org/10.3102/1076998609332754 (2009).
Google Scholar 
Borcard, P., Legendre, P. & Drapeau, P. Partialling out the spatial component of ecological variation. Ecology 73, 1045–1055 (1992).
Google Scholar 
Przybylska, K. & Kucharzyk, S. Skład gatunkowy i struktura lasów Bieszczadzkiego Parku Narodowego [Species composition and structure of forest of the Bieszczady National Park. Monogr. Bieszcz. 6, 1–159 (1999) (in Polish with English summary).
Google Scholar 
Bader, M. Y. et al. A global framework for linking alpine-treeline ecotone patterns to underlying processes. Ecography 44(2), 265–292. https://doi.org/10.1111/ecog.05285 (2021).
Google Scholar 
Nowosad, M. Zarys klimatu Bieszczadzkiego Parku Narodowego i jego otuliny w świetle dotychczasowych badań [Outlines of climate of the Bieszczady National Park and its bufferzone in the light of previous studies]. Roczn. Bieszcz. 4, 163–183 (1995) (in Polish with English summary).
Google Scholar 
Nowosad, M. & Wereski, S. Warunki klimatyczne. Bieszczadzki Park Narodowy–40 lat ochrony [Climatic conditions. Bieszczady National Park–40 years of protection]. In Bieszczadzki Park Narodowy [The Bieszczady National Park] (eds Górecki, A. & Zemanek, B.) 31–38 (Wyd. Bieszczadzki Park Narodowy, 2016) (in Polish with English summary).
Google Scholar 
Kukulak, J. Neotectonics and planation surfaces in the High Bieszczady Mountains (Outer Carpathians, Poland). Ann. Soc. Geol. Pol. 74, 339–350 (2004).
Google Scholar 
Haczewski, G., Kukulak, J. & Bąk, K. Budowa geologiczna i rzeźba Bieszczadzkiego Parku Narodowego [Geology and relief of the Bieszczady National Park]. Prace monograficzne (Akademia Pedagogiczna im. Komisji Edukacji Narodowej w Krakowie) 468, 1–156 (2007) (in Polish with English summary).
Google Scholar 
Skiba, S., Drewnik, M., Kacprzak, A. & Kołodziejczyk, M. Gleby litogeniczne Bieszczadów i Beskidu Niskiego [Lithogenous soils of the Bieszczady and Beskid Niski Mts (Polish Carpathians)]. Roczn. Bieszcz. 7, 387–396 (1998) (in Polish with English summary).
Google Scholar 
Skiba, S. & Winnicki, T. Gleby zbiorowisk roślinnych bieszczadzkich połonin [Soils of the subalpine meadows plant communities in the Bieszczady Mts]. Roczn. Bieszcz. 4, 97–109 (1995) (in Polish with English summary).
Google Scholar 
Musielok, Ł, Drewnik, M., Szymański, W. & Stolarczyk, M. Classification of mountain soils in a subalpine zone—A case study from the Bieszczady Mountains (SE Poland). Soil Sci. Annu. 70, 170–177. https://doi.org/10.2478/ssa-2019-0015 (2019).CAS 

Google Scholar 
Spatz, G. Succession patterns on mountain pastures. Vegetatio 43, 39–41 (1980).
Google Scholar 
Kozak, J. Zmiany powierzchni lasów w Karpatach Polskich na tle innych gór świata [Changes in the Land Cover in the Polish Carpathians at the Turn of the 20th and 21st Century in Relation to Local Development Level]. Wydawnictwo Uniwersytetu Jagiellońskiego, Kraków (2005) (in Polish with English summary).Vitali, A., Urbinati, C., Weisberg, P. J., Urza, A. K. & Garbarino, M. Effects of natural and anthropogenic drivers on land-cover change and treeline dynamics in the Apennines (Italy). J. Veg. Sci. 29(2), 189–199. https://doi.org/10.1111/jvs.12598 (2018).
Google Scholar 
Micu, D. M., Dumitrescu, A., Cheval, S., Nita, I.-A. & Birsan, M.-V. Temperature changes and elevation-warming relationships in the Carpathian Mountains. Int. J. Climatol. 41, 2154–2172. https://doi.org/10.1002/joc.6952 (2020).
Google Scholar 
Rehman, A. Ziemie dawnej Polski. Cz. I. Karpaty [The lands of ancient Poland. Part I. The Carpathians]. (Gubrynowicz i Schmidt, Lwów) (1895) (in Polish).Frey, W. The influence of snow on growth and survival of planted trees. Arct. Alp. Res. 15, 241–251 (1983).
Google Scholar 
Malanson, G. P. et al. Alpine treeline of Western North America: Linking organism-to-landscape dynamics. Phys. Geogr. 28, 378–396. https://doi.org/10.2747/0272-3646.28.5.378 (2007).
Google Scholar 
Holtmeier, F. K. & Broll, G. Wind as an ecological agent at treelines in North America, the Alps, and the European Subarctic. Phys. Geogr. 31, 203–233. https://doi.org/10.2747/0272-3646.31.3.203 (2010).
Google Scholar 
Barclay, A. M. & Crawford, R. M. M. Winter desiccation stress and resting bud viability in relation to high altitude survival in Sorbus aucuparia L. Flora 172, 21–34 (1982).
Google Scholar 
Raspé, O., Findlay, C. & Jacquemart, A. L. Sorbus aucuparia L. J. Ecol. 88, 910–930 (2000).
Google Scholar 
Zerbe, S. On the ecology of Sorbus aucuparia (Rosaceae) with special regard to germination, establishment and growth. Pol. Bot. J. 46, 229–239 (2001).
Google Scholar 
Smith, W. K., Germino, M. J., Hancock, T. E. & Johnson, D. M. Another perspective on altitudinal limits of alpine timberlines. Tree Physiol. 23, 1101–1112 (2003).PubMed 

Google Scholar 
Trant, A., Higgs, E. & Starzomski, B. M. A century of high elevation ecosystem change in the Canadian Rocky Mountains. Sci. Rep. 10, 9698. https://doi.org/10.1038/s41598-020-66277-2 (2020).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Barbeito, I., Dawes, M. A., Rixen, C., Senn, J. & Bebi, P. Factors driving mortality and growth at treeline: A 30-year experiment of 92 000 conifers. Ecology 93(2), 389–401 (2012).PubMed 

Google Scholar 
Kullman, L. A 25-year survey of geoecological change in the scandes mountains of Sweden. Geogr. Ann. Ser. B 79, 139–165 (1997).
Google Scholar 
Pękala, K. Rzeźba Bieszczadzkiego Parku Narodowego [Relief of the Bieszczady National Park]. Roczn. Bieszcz. 6, 19–38 (1997) (in Polish with English summary).
Google Scholar 
Kullman, L. Temporal and spatial aspects of subalpine populations of Sorbus aucuparia in Sweden. Ann. Bot. Fenn. 23, 267–275 (1986).
Google Scholar 
Hoersch, B. Modelling the spatial distribution of montane and subalpine forests in the Central Alps using digital elevation models. Ecol. Model. 168, 267–282 (2003).
Google Scholar 
Resler, L. M., Butler, D. R. & Malanson, G. P. Topographic shelter and conifer establishment and mortality in an alpine environment, Glacier National Park, Montana. Phys. Geogr. 26, 112–125 (2005).
Google Scholar 
Kollmann, J. Regeneration window for fleshy-fruited plants during scrub development on abandoned grassland. Ecoscience 2, 213–222 (1995).
Google Scholar 
Lediuk, K. D., Damascos, M. A., Puntieri, J. G. & de Torres Curth, M. I. Population dynamics of an invasive tree, Sorbus aucuparia, in the understory of a Patagonian forest. Plant Ecol. 217, 899–911 (2016).
Google Scholar 
McCutchan, M. H. & Fox, D. G. Effect of elevation and aspect on wind, temperature and humidity. J. Appl. Meteorol. Climatol. 25(12), 1996–2013 (1986).ADS 

Google Scholar 
Stage, A. R. & Salas, C. Interactions of elevation, aspect, and slope in models of forest species composition and productivity. For. Sci. 53, 486–492 (2007).
Google Scholar 
Pocewicz, A. L., Gessler, P. & Robinson, A. P. The relationship between effective plant area index and Landsat spectral response across elevation, solar insolation, and spatial scales in a northern Idaho forest. Can. J. For. Res. 34, 465–480 (2004).
Google Scholar 
Kucharzyk, S. & Sugiero, D. Zróżnicowanie dynamiki procesów lasotwórczych w buczynach bieszczadzkich w zależności od wystawy i wzniesienia [Variability of the dynamics of forest development processes in the Bieszczady beech forests in relation to exposition and altitude]. Sylwan 7, 29–38 (2007) (in Polish with English summary).
Google Scholar 
Drewnik, M., Musielok, Ł, Stolarczyk, M., Mitka, J. & Gus, M. Effects of exposure and vegetation type on organic matter stock in the soils of subalpine meadows in the Eastern Carpathians. CATENA 147, 167–176. https://doi.org/10.1016/j.catena.2016.07.014 (2016).CAS 

Google Scholar 
Zheng, L. et al. Tree regeneration patterns on contrasting slopes at treeline ecotones in Eastern Tibet. Forests 12, 1605. https://doi.org/10.3390/f12111605 (2021).
Google Scholar  More

The studied viviparous clausiliids developed four types of morphological adaptations that facilitate the delivery of embryos through the shell aperture: (1) reduction of the clausiliar apparatus, (2) decrease of embryonic shell width, (3) widening of the shell canal, and (4) development of a flexible embryonic shell.Reduction of the clausiliar apparatusMembers of the Reinia genus, arboreal species from Japan (Fig. 1), show the most advanced adaptations to live-bearing compared to hypothetical ancestral Phaedusinae. The shell shape in these species is more conical than fusiform, the number of whorls decreases, and the aperture widens. One of the species, R. variegata, features almost full reduction of the clausiliar apparatus that consists of only vestigial folds (Fig. 1F). This species also lacks the clausilium, so the entrance through the aperture is unprotected.Figure 1Different stages of reduction of apertural barriers in members of genus Reinia: R. ashizuriensis (A–C; upper row) and R. variegata (D–F; lower row). (A,D) Adult shells; (B,C,E,F) adult shells with body whorl cut open dorsally in microCT visualisation. cp clausilium plate, il inferior lamella, pr principal plica, sc subcolumellar lamella, sl superior lamella, sp spiral lamella, upp upper palatal plica.Full size imageDecrease of embryonic shell widthAnother adaptation concerns the shape of the embryonic shell (“protoconch”), which becomes very narrow in some viviparous species. This feature is conspicuous because embryonic whorls remain in the adult shell as apical whorls. For instance in S. addisoni (Fig. 2A–D), the apical part being much narrower than the first whorls of the teleoconch is a clear evidence that the growth trajectory has changed abruptly after birth. Other examples include E. cylindrella and E. steetzneri, in which both the protoconch and the teleoconch are very narrow, yet at the borderline between these parts, the shell axis is slightly bent (Fig. 2E–L). We suppose that this feature develops as a result of obstruction during birth.Figure 2Width difference between protoconch and teleoconch in Stereophaedusa addisoni (A–D, upper row), Euphaedusa cylindrella (E–H, middle row), Euphaedusa steetzneri (I–L, lower row). (A,C,E,G,I,K) Adult shells with very narrow apical whorls; (B,F,J) X-rayed adults; (F,J) with retained embryos inside; (D,H,L) X-rays of apical part of adult shell with schematic drawings of a neonate.Full size imageWidening of the shell canalThe third type of adaptation is the widening of the shell canal in the body whorl, allowing for easier passage of the embryo between the lamellae and plicae of the apertural barriers. In this case, the outline of the shell changes only slightly giving the body whorl a more convex appearance. A substantial difference to egg-laying species concerns the apertural barriers: the clausiliar includes a broad clausilium plate and a spirally ascending inferior lamella (Fig. 3A–D). These modifications result in a spacious shell canal in the body whorl, for example in S. addisoni and E. sheridani, that can accommodate the transfer of a large embryo. Table 1 presents neonatal size in these species (shell width ca. 1.2 mm), which is very similar to their clausilium width (ca. 1.1–1.2 mm).Figure 3Two types of clausiliar apparatus occurring in Phaedusinae in microCT visualisation: with spirally ascending inferior lamella and wide clausilium plate (upper row), and with straight ascending inferior lamella and narrow clausilium plate (lower row). (A) T. sheridani adult shell with the body whorl cut open dorsally; (B) clausilium of T. sheridani; (C) clausilium of S. addisoni; (D) clausilium of R. ashizuriensis; (E) Zaptyx ventriosa adult shell with body whorl cut open dorsally; (F) clausilium of Z. ventriosa; (G,H) clausilia of O. miranda. Note, that all depicted species are viviparous.Full size imageTable 1 Shell size of studied Phaedusinae species.Full size tableMost viviparid clausiliids develop one of these three types of modification; some adaptations co-occur within a single species, for example a wide clausilium accompanies a narrow apex. Interestingly, the Reinia genus includes taxa with a gradual escalation of viviparity-related adaptations: R. ashizurensis, with a stout shell shape and a low number of whorls, has fully developed apertural barriers with a broad clausilium plate (Fig. 1A–C), while its congener, R. variegata, has reduced apertural barriers (Fig. 1D–F).Development of a flexible embryonic shellThe fourth type of adaptation found in Phaedusinae concerns the structure of the embryonic shells. We report this adaptation in O. miranda and Z. ventriosa.Oospira miranda is a dextral, often decollated, ground-dwelling species from Vietnam (Fig. 4A). The species is viviparous: during microCT scanning of museum specimens, we found embryos within a parental shell (Fig. 4B); in laboratory culture, we observed neonates immediately after live birth (Fig. 4C,D). Morphological characters recognized in the adult shell, i.e., a wide apex (= wide embryonic shell), straightly ascending inferior lamella, and a narrow clausilium plate (Fig. 3G,H), seemed to exclude the possibility of live-bearing reproduction, as embryos are too large to pass through the shell canal at the narrowest point. The height and width of the neonatal shell (mean values: 5.19 mm, 3.59 mm) evidently exceeds the width of the clausilium plate in this species (1.97 mm) (Table 1). However, under closer examination, we found the shell to be thin and delicate, which we refer to as a ‘soft shell’. In direct examination, the neonatal shell of O. miranda resembles cellophane, which may keep a given shape for a long time but becomes distorted already under slight pressure.Figure 4Viviparous clausiliids and their ‘soft-shelled’ neonates born in laboratory culture. (A–D) O. miranda: adult shell, X-rayed shell with embryo visible inside, neonates; (E–H) Z. ventriosa: adult shell, X-rayed shell with eggs visible inside, neonates.Full size imageA similar adaptation exists in Z. ventriosa, a Taiwanese species with a very wide apex, never decollated, a straight ascending inferior lamella, and a narrow clausilium plate (Figs. 3E,F, 4E,F). This species produces neonates in laboratory culture (Fig. 4G–H). The dimensions of the neonates (mean values: height 3.37 mm, width 2.51 mm) exceed at last twofold the width of the clausilium plate (1.08 mm). The shells of such freshly delivered juveniles, when gently touched with laboratory tweezers, became dented, but not fractured. More intense and stronger pressing can break this dentation.These initial observations, that we made during the maintenance of the laboratory culture, suggested that the neonatal shells of O. miranda and Z. ventriosa have flexible walls. These ‘soft-shells’ seem to be highly malleable during the entire embryonic development period and delivery through apertural barriers, hardening shortly after birth. We further investigated the physical properties of the embryonic shell by means of microcomputed tomography and scanning electron microscopy.Microcomputed tomographyWe scanned ‘soft-shelled’ neonates of O. miranda and Z. ventriosa, together with ‘hard-shelled’ embryos and neonates of S. addisoni and T. sheridani, in order to compare the density and thickness of the shells (Fig. 5).Figure 5Comparison of embryonic shell thickness in clausiliids: ‘soft-shelled’ neonates of Z. ventriosa (A,B,G,H) and O. miranda (C,D,I,J); “hard-shelled” neonate of S. addisoni (E,K) and embryo of T. sheridani (F,L) scanned inside a parental shell. Upper row—microCT visualisation of shell surface; middle row—microCT sections of those specimens; (M–O) X-ray photographs of S. addisoni (embryo from dissected adult) and Z. ventriosa (neonate) enlarged in (N,O), respectively, showing the difference in shell density and thickness; (P) microCT based volume rendering of O. miranda (left) and S. addisoni (right) neonates, showing difference between relative density of their shells.Full size imagePreliminary observations using the two-dimensional X-ray photographs showed a difference in thickness and density between S. addisoni and Z. ventriosa (Fig. 5M, enlarged in N and O, respectively). The 3D visualization of O. miranda and S. addisoni (the same microCT scanning and reconstruction parameters) confirmed the difference between density and shell thickness of these two species (Fig. 5P).Due to variations in wall thickness within the neonatal shell (e.g., between the first and the second whorls), it is not possible to precisely determine the thickness of the shell wall. The accuracy of the measurement is also limited by the resolution of the microCT scans, especially in the case of the relatively large neonates of O. miranda and Z. ventriosa. When scanning the whole embryonic shell of Z. ventriosa (approximately 3.5 mm in height), the size of the voxel was approximately 1 µm. Thus, we cannot determine the shell thickness down to the nearest micron, but we can estimate it from a few to a dozen microns. A direct comparison between virtual microCT sections of specimens scanned under the same conditions shows a clear difference between the ‘soft-shelled’ and ‘hard-shelled’ taxa (Fig. 5G–L). The ’hard-shelled’ neonates have a shell wall of 30–40 µm thick. We examined the sequence of three ’soft-shelled’ O. miranda specimens that differed in size (the exact time of birth of each of the cultured neonates is unknown, ca. 1–2 days). The larger (older) the neonate was, the thicker the shell. The shell of the largest of the studied O. miranda was up to 20 µm thick. However, the shell wall of this relatively large juvenile (several millimeters in height) still did not reach the thickness of the small ’hard-shelled’ T. sheridani embryo, which was already about 30–40 µm thick, stiff and rigid during the retention in the genital tract. The neonates of O. miranda and Z. ventriosa were much larger than the embryos and neonates of S. addisoni and R. variegata (Table 1), however, the former taxa has much thinner shells.Scanning electron microscopyAfter the non-invasive microCT scan, we scanned embryos and neonates using SEM (Fig. 6). The different properties of the shells of Z. ventriosa and O. miranda vs. S. addisoni and R. variegata were already visible during the preparation of the analysis. Under vacuum conditions, the soft shells of Z. ventriosa and O. miranda shrank and crumpled, creating a cellophane-like surface (Fig. 6A). Embryos and neonates of S. addisoni and R. variegata did not require any special preparation and their shell shape remained unchanged under the vacuum conditions applied during the SEM examination (Fig. 6D,E). To reduce the shell deformations, we freeze-dried the next group of thin-shelled neonates prior to SEM analyses (Fig. 6B,C).Figure 6Neonates of O. miranda (A,B,F,I,L,M,O) and Z. ventriosa (C,G,J,P) in direct comparison with hard-shelled embryos and neonates of R. variegata (D,N,Q) and S. addisoni (E,H,K); SEM microphotographs. The vacuum conditions in SEM led to the shrinkage of the thin O. miranda shell (A); freeze-drying of ‘soft-shelled’ neonates prior to SEM imaging reduced the level of deformity (B,C). Contrastingly, R. variegata and S. addisoni shells do not require special preparation and retain their shape (D,E). (F) The dented surface of O. miranda neonate and SEM-close-up (I) on a cross-section of the shell just a few micrometers thick (arrow in F indicates the region enlarged in I). (G,J) Shell of Z. ventriosa in comparison with similarly ornamented fragment of S. addisoni (H,K); note several times thicker shell in the latter (arrows in G,H indicate the regions enlarged in J,K, respectively). (L,M) Inner surface of intact periostracum which still connects two fragments of broken aragonite shell of O. miranda (the arrow in M indicates the region enlarged in L); note the difference between shell thickness in O. miranda (L,M) and R. variegata (N). All observed specimens have similar crossed-lamellar microstructure (L–Q). However, just as shell thickness, also the number of lamellar layers of alternate orientation within the shell differs (L,M,O,P vs N,Q).Full size imageThe SEM studies allowed for complementary measurements of the shells. In the broken fragments of Z. ventriosa and O. miranda, the thickness of the shell wall ranged from 2–3 µm (Fig. 6F,G,I,J,L,M) to 18 µm in the largest neonate of O. miranda (Fig. 6O). The shells of S. addisoni (Fig. 6H,K) and R. variegata (Fig. 6N) are several times thicker.All analyzed samples have a thin ( More

replying to Y. Cheng et al. Nature Communications https://doi.org/10.1038/s41467-022-33958-7 (2022)We welcome the comment from Matters arising from Cheng Y et al.1, which provides us an opportunity for further clarification of some of our points2. The Comment raised interesting and important issues about our paper, that undoubtably could enhance our understanding for the Holocene vegetation evolution in the northern China and its relationship with East Asian Summer Monsoon (EASM). In particular, the results from Dali lake pose the questions on the timing of the peak of tree cover, that invokes the further investigation to understand this complex tree changes over Holocene period. However, these comments do not impact the key result in our original study2, that is the periodical asynchronous evolutions between EASM and northern China ecosystem under specific conditions.Main points of our paper are: First, we propose that the EASM and its rainfall over northern China mainly followed the variation of the summer insolation and peaked in the early Holocene, while the relative tree cover of temperate deciduous broadleaf tree peaked in the mid-Holocene; the delayed tree cover peak is caused by the winter warming, and peak soil moisture also in the mid-Holocene, which could be related to a hydrological impact from vegetation shift from grass to tree and the positive feedback between this vegetation shift and soil wetting.Second, this asynchronous evolution between the EASM rainfall, which peaks in the early Holocene, and the northern China ecosystem, which peaks in the mid-Holocene, is caused mainly by the opposing effect of residual ice sheet retreat on the decreasing summer insolation. The declining summer insolation does cause a substantial decrease of EASM rainfall from the early to mid-Holocene. However, 2/3 of this rainfall decrease is canceled by the rainfall increase forced by the retreat of residual Laurentide ice sheet, resulting in a weak decreasing trend of rainfall over this period.Third, under this background of weak rainfall changes, winter warming, induced by increased winter insolation and ice sheet retreat, raised the coldest temperature to above −17 °C, the threshold for the survival of temperate deciduous broadleaf tree3, and then favored an increase in tree, meanwhile induced a decrease in grass for reasons of its lower competitiveness than that of tree. This vegetation shift then supported the wetting of northern China through its hydrological effect2. The vegetation shift and soil wetting could reinforce each other. Furthermore, the dominant effect of winter warming on vegetation from the early to mid-Holocene is supported by our sensitive experiments with an off-line land-vegetation model.As stated in Cheng Y’s Comment1, the land cover in northern China includes forests, grass and bare land. In our interpretation, the process of “the vegetation feedback to climate” is mentioned as a possible feedback that enhances this asynchronous response, but is not critically involved in the mechanism. As such, whether the absolute or relative vegetation cover is not a major issue in our discussion. It’s sure that the reconstructed absolute tree cover, which based on pollen concentration, could enrich our understanding of the vegetation changes over the Holocene period in northern China. Indeed, the hydrological impact of bare land (evaporation) had been considered in our hydrological analysis of northern China soil moisture, and the results indicated its impact is important but not critical to the Holocene long-term changes of soil moisture over this region. The relative tree cover, the percentage of cool mixed tree (COMX4) in fossil pollen which is consistent with that of temperate deciduous broadleaf tree in simulation2, that we cited4 is a synthesis of 31 records, which represented the general evolution of vegetation over a large part of northern China, and its main result is consistent with records from other part of northern China such as the 6 ka peak in Gonghai Lake5. In spite of its low time resolution, the general trend over the millennium scale seems to us clear.It’s true that the −17 °C of the coldest month temperature is the survival threshold for the temperate deciduous broadleaved tree. While, the temperature threshold for C3 grass and C3 arctic grass are complex, its direct impact on the changes of grass proposed in our paper is somewhat not strict. However, considering the different competitiveness between tree and grass, increased temperate deciduous broadleaved tree, which derived by the winter warming, could induce a decrease in the grass from the early to mid-Holocene. Indeed, summer temperature, annual rainfall and fire incidents are all the important factors determining the Holocene changes of vegetation over northern China, but series of sensitivity experiment proposed the key impact of winter temperature on the vegetation shift and soil moisture evolution, which is consistent with the results of transient coupled climate simulation and geological records. This grass-to-tree shift for this period is evidenced in the pollen percentages and well simulated by the climate model shown in our paper2.Fire is an important factor for the long-term changes of vegetation cover over semi-arid regions, and its emergence and impact on vegetation are already incorporated into our model6, then, in turn, the simulation. Future works could assess the impact of fire on the long-term changes of semi-arid vegetation through the combination of reconstruction and process-based simulation of fire7.Focusing on the contrary views of Holocene EASM within proxy records, we proposed an asynchronous evolution of EASM rainfall and northern China ecosystem for the period of early to mid-Holocene. Our proposal is based on a state-of-the-art transient climate simulation, which reproduced the diverse evolution of EASM proxies reasonably well. The mechanisms proposed for this asynchronous evolution appear to us consistent with the current evidences available. There are, however, uncertainties in models and proxies. Meanwhile, the northern China is a broad region with large gradient in rainfall and ecosystem, that could induce the possible diverse evolutions in climate and ecosystem under Holocene climate change. Therefore, we believe further studies using other models and new proxies are important to further improve our understanding of this issue. More

Alerstam, T., Hedenström, A. & Åkesson, S. Long-distance migration: evolution and determinants. Oikos 103, 247–260 (2003).Article 

Google Scholar 
Bauer, S., Lisovski, S. & Hahn, S. Timing is crucial for consequences of migratory connectivity. Oikos 125, 605–612 (2016).Article 

Google Scholar 
Bauer, S. & Hoye, B. J. Migratory animals couple biodiversity and ecosystem functioning worldwide. Science 344, 1242552 (2014).Article 
CAS 
PubMed 

Google Scholar 
Fricke, E. C., Ordonez, A., Rogers, H. S. & Svenning, J. C. The effects of defaunation on plants’ capacity to track climate change. Science 214, 210–214 (2022).Article 

Google Scholar 
Tucker, M. A. et al. Moving in the Anthropocene: global reductions in terrestrial mammalian movements. Science 359, 466–469 (2018).Article 
CAS 
PubMed 

Google Scholar 
Wilcove, D. S. & Wikelski, M. Going, going, gone: is animal migration disappearing? PLoS Biol. 6, e188 (2008).Article 
PubMed 
PubMed Central 

Google Scholar 
Parmesan, C. & Yohe, G. A globally coherent fingerprint of climate change. Nature 421, 37–42 (2003).Article 
CAS 
PubMed 

Google Scholar 
Walther, G. et al. Ecological responses to recent climate change. Nature 4126, 389–395 (2002).Article 

Google Scholar 
Teitelbaum, C. S. et al. Experience drives innovation of new migration patterns of whooping cranes in response to global change. Nat. Commun. 7, 12793 (2016).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Oestreich, W. K., Chapman, M. S. & Crowder, L. B. A comparative analysis of dynamic management in marine and terrestrial systems. Front. Ecol. Environ. 18, 496–504 (2020).Article 

Google Scholar 
Senzaki, M. et al. Sensory pollutants alter bird phenology and fitness across a continent. Nature 587, 605–609 (2020).Article 
CAS 
PubMed 

Google Scholar 
Guerra, A. S. Wolves of the sea: managing human–wildlife conflict in an increasingly tense ocean. Mar. Policy 99, 369–373 (2019).Article 

Google Scholar 
Abrahms, B. Human–wildlife conflict under climate change. Science 373, 484–485 (2021).Article 
CAS 
PubMed 

Google Scholar 
Both, C., Bouwhuis, S., Lessells, C. M. & Visser, M. E. Climate change and population declines in a long-distance migratory bird. Nature 441, 81–83 (2006).Article 
CAS 
PubMed 

Google Scholar 
Post, E. & Forchhammer, M. C. Climate change reduces reproductive success of an Arctic herbivore through trophic mismatch. Phil. Trans. R. Soc. B Biol. Sci. 363, 2369–2375 (2008).Article 

Google Scholar 
Winkler, D. W. et al. Cues, strategies, and outcomes: how migrating vertebrates track environmental change. Mov. Ecol. 2, 10 (2014).Article 

Google Scholar 
Xu, W. et al. The plasticity of ungulate migration in a changing world. Ecology 102, e03293 (2021).Article 
PubMed 

Google Scholar 
McNamara, J. M., Barta, Z., Klaassen, M. & Bauer, S. Cues and the optimal timing of activities under environmental change. Ecol. Lett. 14, 1183–1190 (2011).Article 
PubMed 
PubMed Central 

Google Scholar 
Bauer, S., McNamara, J. M. & Barta, Z. Environmental variability, reliability of information and the timing of migration. Proc. R. Soc. B Biol. Sci. 287, 20200622 (2020).Article 

Google Scholar 
Abrahms, B. et al. Emerging perspectives on resource tracking and animal movement ecology. Trends Ecol. Evol. 36, 308–320 (2020).Article 
PubMed 

Google Scholar 
Visser, M. E., Holleman, L. J. M. & Gienapp, P. Shifts in caterpillar biomass phenology due to climate change and its impact on the breeding biology of an insectivorous bird. Oecologia 147, 164–172 (2006).Article 
PubMed 

Google Scholar 
Aikens, E. O. et al. Wave-like patterns of plant phenology determine ungulate movement tactics. Curr. Biol. 30, 3444–3449 (2020).Article 
CAS 
PubMed 

Google Scholar 
Abrahms, B. et al. Memory and resource tracking drive blue whale migrations. Proc. Natl Acad. Sci. USA 116, 5582–5587 (2019).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Lank, D. B., Butler, R. W., Ireland, J. & Ydenberg, R. C. Effects of predation danger on migration strategies of sandpipers. Oikos 103, 303–319 (2003).Article 

Google Scholar 
Sabal, M. C. et al. Predation landscapes influence migratory prey ecology and evolution. Trends Ecol. Evol. 36, 737–749 (2021).Article 
PubMed 

Google Scholar 
Furey, N. B., Armstrong, J. B., Beauchamp, D. A. & Hinch, S. G. Migratory coupling between predators and prey. Nat. Ecol. Evol. 2, 1846–1853 (2018).Article 
PubMed 

Google Scholar 
Altizer, S., Bartel, R. & Han, B. A. Animal migration and infectious disease risk. Science 331, 296–302 (2011).Article 
CAS 
PubMed 

Google Scholar 
Gunnarsson, T., Gill, J., Sigurbjörnsson, T. & Sutherland, W. Arrival synchrony in migratory birds. Nature 431, 646 (2004).Article 
CAS 
PubMed 

Google Scholar 
Beltran, R. S. et al. Elephant seals time their long-distance migration using a map sense. Curr. Biol. 32, R156–R157 (2022).Article 
CAS 
PubMed 

Google Scholar 
Yang, L. H. & Rudolf, V. H. W. Phenology, ontogeny and the effects of climate change on the timing of species interactions. Ecol. Lett. 13, 1–10 (2010).Article 
CAS 
PubMed 

Google Scholar 
Visser, M. E. & Gienapp, P. Evolutionary and demographic consequences of phenological mismatches. Nat. Ecol. Evol. 3, 879–885 (2019).Article 
PubMed 
PubMed Central 

Google Scholar 
Furey, N. B. et al. Predator swamping reduces predation risk during nocturnal migration of juvenile salmon in a high-mortality landscape. J. Anim. Ecol. 85, 948–959 (2016).Article 
PubMed 

Google Scholar 
Rickbeil, G. J. M. et al. Plasticity in elk migration timing is a response to changing environmental conditions. Glob. Change Biol. 25, 2368–2381 (2019).Article 

Google Scholar 
Schmaljohann, H. & Both, C. The limits of modifying migration speed to adjust to climate change. Nat. Clim. Change 7, 573–576 (2017).Article 

Google Scholar 
Gwinner, E. Circadian and circannual programmes in avian migration. J. Exp. Biol. 199, 39–48 (1996).Article 
CAS 
PubMed 

Google Scholar 
Liedvogel, M., Åkesson, S. & Bensch, S. The genetics of migration on the move. Trends Ecol. Evol. 26, 561–569 (2011).Article 
PubMed 

Google Scholar 
Hauser, D. D. W. et al. Decadal shifts in autumn migration timing by Pacific Arctic beluga whales are related to delayed annual sea ice formation. Glob. Change Biol. 23, 2206–2217 (2017).Article 

Google Scholar 
Palacín, C., Alonso, J. C., Alonso, J. A., Magaña, M. & Martín, C. A. Cultural transmission and flexibility of partial migration patterns in a long-lived bird, the great bustard Otis tarda. J. Avian Biol. 42, 301–308 (2011).Article 

Google Scholar 
Couzin, I. D. Collective animal migration. Curr. Biol. 28, R976–R980 (2018).Article 
CAS 
PubMed 

Google Scholar 
Guttal, V. & Couzin, I. D. Social interactions, information use, and the evolution of collective migration. Proc. Natl Acad. Sci. USA 107, 16172–16177 (2010).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Berdahl, A. M. et al. Collective animal navigation and migratory culture: from theoretical models to empirical evidence. Phil. Trans. R. Soc. B Biol. Sci. 373, 20170009 (2018).Article 

Google Scholar 
Cohen, E. B. & Satterfield, D. A. ‘Chancing on a spectacle:’ co-occurring animal migrations and interspecific interactions. Ecography 43, 1657–1671 (2020).Article 

Google Scholar 
Berdahl, A., Torney, C. J., Ioannou, C. C., Faria, J. J. & Couzin, I. D. Emergent sensing of complex environments by mobile animal groups. Science 339, 574–576 (2013).Article 
CAS 
PubMed 

Google Scholar 
Abrahms, B., Teitelbaum, C. S., Mueller, T. & Converse, S. J. Ontogenetic shifts from social to experiential learning drive avian migration timing. Nat. Commun. 12, 7326 (2021).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Sasaki, T. & Biro, D. Cumulative culture can emerge from collective intelligence in animal groups. Nat. Commun. 8, 15049 (2017).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Helm, B., Piersma, T. & van der Jeugd, H. Sociable schedules: interplay between avian seasonal and social behaviour. Anim. Behav. 72, 245–262 (2006).Article 

Google Scholar 
Piersma, T., Zwarts, L. & Bruggemann, J. H. Behavioural aspects of the departure of waders before long-distance flights: flocking, vocalizations, flight paths and diurnal timing. Ardea 78, 157–184 (1990).
Google Scholar 
Dingle, H. & Drake, V. A. What is migration? BioScience 57, 113–121 (2007).Article 

Google Scholar 
Oestreich, W. K. & Aiu, K. M. Code and data from: The influence of social cues on timing of animal migrations. Zenodo https://zenodo.org/record/6574762 (2022).Furey, N. B., Martins, E. G. & Hinch, S. G. Migratory salmon smolts exhibit consistent interannual depensatory predator swamping: effects on telemetry-based survival estimates. Ecol. Freshw. Fish 30, 18–30 (2021).Article 

Google Scholar 
Berdahl, A., Westley, P. A. H. & Quinn, T. P. Social interactions shape the timing of spawning migrations in an anadromous fish. Anim. Behav. 126, 221–229 (2017).Article 

Google Scholar 
Louca, V., Lindsay, S. W. & Lucas, M. C. Factors triggering floodplain fish emigration: importance of fish density and food availability. Ecol. Freshw. Fish 18, 60–64 (2009).Article 
PubMed 
PubMed Central 

Google Scholar 
Bastille-Rousseau, G. et al. Migration triggers in a large herbivore: Galápagos giant tortoises navigating resource gradients on volcanoes. Ecology 100, e02658 (2019).Article 
PubMed 

Google Scholar 
Bracis, C. & Mueller, T. Memory, not just perception, plays an important role in terrestrial mammalian migration. Proc. R. Soc. B Biol. Sci. 284, 20170449 (2017).Article 

Google Scholar 
Barrett, B., Zepeda, E., Pollack, L., Munson, A. & Sih, A. Counter-culture: does social learning help or hinder adaptive response to human-induced rapid environmental change? Front. Ecol. Evol. 7, 183 (2019).Article 

Google Scholar 
Merkle, J. A. et al. Site fidelity as a maladaptive behavior in the Anthropocene. Front. Ecol. Environ. 20, 187–194 (2022).Article 

Google Scholar 
Teske, P. R. et al. The sardine run in southeastern Africa is a mass migration into an ecological trap. Sci. Adv. 7, eabf4514 (2021).Article 
PubMed 
PubMed Central 

Google Scholar 
Corten, A. The role of ‘conservatism’ in herring migrations. Rev. Fish Biol. Fish. 11, 339–361 (2002).Article 

Google Scholar 
Mukhin, A., Chernetsov, N. & Kishkinev, D. Acoustic information as a distant cue for habitat recognition by nocturnally migrating passerines during landfall. Behav. Ecol. 19, 716–723 (2008).Article 

Google Scholar 
Barker, K. J. et al. Toward a new framework for restoring lost wildlife migrations. Conserv. Lett. 15, e12850 (2022).Article 

Google Scholar 
Teitelbaum, C. S., Converse, S. J. & Mueller, T. The importance of early life experience and animal cultures in reintroductions. Conserv. Lett. 12, e12599 (2019).Article 

Google Scholar 
Hughey, L. F., Hein, A. M., Strandburg-Peshkin, A., Jensen, F. H. & Hughey, L. F. Challenges and solutions for studying collective animal behaviour in the wild. Phil. Trans. R. Soc. B 373, 20170005 (2018).Article 
PubMed 
PubMed Central 

Google Scholar 
Calabrese, J. M. et al. Disentangling social interactions and environmental drivers in multi-individual wildlife tracking data. Phil. Trans. R. Soc. B 373, 20170007 (2018).Article 
PubMed 
PubMed Central 

Google Scholar 
Jesmer, B. R. et al. Is ungulate migration culturally transmitted? Evidence of social learning from translocated animals. Science 361, 1023–1025 (2018).Article 
CAS 
PubMed 

Google Scholar 
Bousquet, C. A. H., Sumpter, D. J. T. & Manser, M. B. Moving calls: a vocal mechanism underlying quorum decisions in cohesive groups. Proc. R. Soc. B Biol. Sci. 278, 1482–1488 (2011).Article 

Google Scholar 
Dibnah, A. J. et al. Vocally mediated consensus decisions govern mass departures from jackdaw roosts. Curr. Biol. 32, R455–R456 (2022).Article 
CAS 
PubMed 

Google Scholar 
Robart, A. R., Zuñiga, H. X., Navarro, G. & Watts, H. E. Social environment influences termination of nomadic migration. Biol. Lett. 18, 20220006 (2022).Article 
PubMed 

Google Scholar 
Dodson, S., Abrahms, B., Bograd, S. J., Fiechter, J. & Hazen, E. L. Disentangling the biotic and abiotic drivers of emergent migratory behavior using individual-based models. Ecol. Modell. 432, 109225 (2020).Article 

Google Scholar 
Kays, R., Crofoot, M. C., Jetz, W. & Wikelski, M. Terrestrial animal tracking as an eye on life and planet. Science 348, aaa2478 (2015).Article 
PubMed 

Google Scholar 
Hussey, N. E. et al. Aquatic animal telemetry: a panoramic window into the underwater world. Science 348, 1255642 (2015).Article 
PubMed 

Google Scholar 
Oestreich, W. K. et al. Acoustic signature reveals blue whale tune life history transitions to oceanographic conditions. Funct. Ecol. 36, 882–895 (2022).Article 
CAS 

Google Scholar 
Chapman, J. W., Reynolds, D. R. & Smith, A. D. Vertical-looking radar: a new tool for monitoring high-altitude insect migration. BioScience 53, 503–511 (2003).Article 

Google Scholar 
Oestreich, W. K. et al. Animal-borne metrics enable acoustic detection of blue whale migration. Curr. Biol. 30, 4773–4779 (2020).Article 
CAS 
PubMed 

Google Scholar 
Fraser, K. C., Shave, A., de Greef, E., Siegrist, J. & Garroway, C. J. Individual variability in migration timing can explain long-term, population-level advances in a songbird. Front. Ecol. Evol. 7, 324 (2019).Article 

Google Scholar 
Byholm, P., Beal, M., Isaksson, N., Lötberg, U. & Åkesson, S. Paternal transmission of migration knowledge in a long-distance bird migrant. Nat. Commun. 13, 1566 (2022).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Schneider, S. S. & McNally, L. C. Waggle dance behavior associated with seasonal absconding in colonies of the African honey bee, Apis mellifera scutellata. Insectes Soc. 41, 115–127 (1994).Article 

Google Scholar 
Raveling, D. G. Preflight and flight behavior of Canada geese. Auk 86, 671–681 (1969).Article 

Google Scholar 
Tennessen, J. B., Parks, S. E. & Langkilde, T. Traffic noise causes physiological stress and impairs breeding migration behaviour in frogs. Conserv. Physiol. 2, cou032 (2014).Article 
PubMed 
PubMed Central 

Google Scholar 
Lagarde, A., Lagarde, F. & Piersma, T. Vocal signalling by Eurasian spoonbills Platalea leucorodia in flocks before migratory departure. Ardea 109, 243–250 (2021).Article 

Google Scholar 
Rees, E. C. Conflict of choice within pairs of Bewick’s swans regarding their migratory movement to and from the wintering grounds. Anim. Behav. 35, 1685–1693 (1987).Article 

Google Scholar 
Mazeroll, A. I. & Montgomery, W. L. Daily migrations of a coral reef fish in the Red Sea (Gulf of Aqaba, Israel). Copiea 1998, 893–905 (1998).Article 

Google Scholar 
Méndez, V. et al. Paternal effects in the initiation of migratory behaviour in birds. Sci. Rep. 11, 2782 (2021).Article 
PubMed 
PubMed Central 

Google Scholar 
Nelson, M. E. Development of migratory behavior in northern white-tailed deer. Can. J. Zool. 76, 426–432 (1998).Article 

Google Scholar 
Sweanor, P. Y. & Sandgren, F. Winter-range philopatry of seasonally migratory moose. J. Appl. Ecol. 26, 25–33 (1989).Article 

Google Scholar 
Rees, E. C. Consistency in the timing of migration for individual Bewick’s swans. Anim. Behav. 38, 384–393 (1989).Article 

Google Scholar 
Corten, A. A possible adaptation of herring feeding migrations to a change in timing of the Calanus finmarchicus season in the eastern North Sea. ICES J. Mar. Sci. 57, 1261–1270 (2000).Article 

Google Scholar 
Loonstra, A. J. et al. Individual black-tailed godwits do not stick to single routes: a hypothesis on how low population densities might decrease social conformity. Ardea 107, 251–261 (2020).Article 

Google Scholar 
Hake, M., Kjellén, N. & Alerstam, T. Age‐dependent migration strategy in honey buzzards Pernis apivorus tracked by satellite. Oikos 103, 385–396 (2003).Article 

Google Scholar 
Gupte, P. R., Koffijberg, K., Müskens, G. J. D. M., Wikelski, M. & Kölzsch, A. Family size dynamics in wintering geese. J. Ornithol. 160, 363–375 (2019).Article 

Google Scholar 
Gonçalves, M. I. C. et al. Movement patterns of humpback whales (Megaptera novaeangliae) reoccupying a Brazilian breeding ground. Biota Neotrop. 18, e20180567 (2018).Article 

Google Scholar 
Trudelle, L. et al. First insights on spatial and temporal distribution patterns of humpback whales in the breeding ground at Sainte Marie Channel, Madagascar. Afr. J. Mar. Sci. 40, 75–86 (2018).Article 

Google Scholar 
De La Gala-Hernández, S. R., Heckel, G. & Sumich, J. L. Comparative swimming effort of migrating gray whales (Eschrichtius robustus) and calf cost of transport along Costa Azul, Baja California, Mexico. Can. J. Zool. 86, 307–313 (2008).Article 

Google Scholar 
Sword, G. A. Local population density and the activation of movement in migratory band-forming Mormon crickets. Anim. Behav. 69, 437–444 (2005).Article 

Google Scholar 
Buhl, J. et al. From disorder to order in marching locusts. Science 312, 1402–1406 (2006).Article 
CAS 
PubMed 

Google Scholar 
Mysterud, A., Loe, L. E., Zimmermann, B., Bischof, R. & Meisingset, E. Partial migration in expanding red deer populations at northern latitudes—a role for density dependence? Oikos 120, 1817–1825 (2011).Article 

Google Scholar 
Bukreeva, O. M. & Lidzhi-garyaeva, G. V. Mass migration of social voles (Microtus socialis Pallas, 1773) in the Northwestern Caspian region. Arid Ecosyst. 8, 147–151 (2018).Article 

Google Scholar 
Eggeman, S. L., Hebblewhite, M., Bohm, H., Whittington, J. & Merrill, E. H. Behavioural flexibility in migratory behaviour in a long-lived large herbivore. J. Anim. Ecol. 85, 785–797 (2016).Article 
PubMed 

Google Scholar 
Weithman, C. et al. Senescence and carryover effects of reproductive performance influence migration, condition, and breeding propensity in a small shorebird. Ecol. Evol. 7, 11044–11056 (2017).Article 
PubMed 
PubMed Central 

Google Scholar 
Rappole, J. H. & Warner, D. W. Relationships between behavior, physiology and weather in avian transients at a migration stopover site. Oecologia 212, 193–212 (1976).Article 

Google Scholar 
Fauchald, P., Mauritzen, M. & Gjøsæter, H. Density‐dependent migratory waves in the marine pelagic ecosystem. Ecology 87, 2915–2924 (2006).Article 
PubMed 

Google Scholar 
Makris, N. C. et al. Critical population density triggers rapid formation of vast oceanic fish shoals. Science 323, 1734–1737 (2009).Article 
CAS 
PubMed 

Google Scholar 
Tøttrup, A. P. & Thorup, K. Sex-differentiated migration patterns, protandry and phenology in North European songbird populations. J. Ornithol. 149, 161–167 (2008).Article 

Google Scholar 
Francis, C. M. & Cooke, C. F. Differential timing of spring migration in rose-breasted grosbeaks. J. Field Ornithol. 61, 404–412 (1990).
Google Scholar 
Corgos, A., Verísimo, P. & Freire, J. Timing and seasonality of the terminal molt and mating migration in the spider crab, Maja brachydactyla: evidence of alternative mating strategies. J. Shellfish Res. 25, 577–587 (2006).Article 

Google Scholar 
Gordo, O., Sanz, J. J. & Lobo, J. M. Spatial patterns of white stork (Ciconia ciconia) migratory phenology in the Iberian Peninsula. J. Ornithol. 148, 293–308 (2007).Article 

Google Scholar 
Sergio, F. et al. Individual improvements and selective mortality shape lifelong migratory performance. Nature 515, 410–413 (2014).Article 
CAS 
PubMed 

Google Scholar 
Manica, L. T., Graves, J. A., Podos, J. & Macedo, R. H. Hidden leks in a migratory songbird: mating advantages for earlier and more attractive males. Behav. Ecol. 31, 1180–1191 (2020).Article 

Google Scholar 
Cade, D. E. et al. Social exploitation of extensive, ephemeral, environmentally controlled prey patches by supergroups of rorqual whales. Anim. Behav. 182, 251–266 (2021).Article 

Google Scholar 
Urbanek, R. P., Fondow, L. E. A., Zimorski, S. E., Wellington, M. A. & Nipper, M. A. Winter release and management of reintroduced migratory whooping cranes Grus americana. Bird Conserv. Int. 20, 43–54 (2010).Article 

Google Scholar 
Németh, Z. & Moore, F. R. Information acquisition during migration: a social perspective. Auk 131, 186–194 (2014).Article 

Google Scholar  More

Pascual, U. et al. Biodiversity and the challenge of pluralism. Nat. Sustain. 4, 567–572 (2021).Article 

Google Scholar 
Cumming, G. S. The relevance and resilience of protected areas in the Anthropocene. Anthropocene 13, 46–56 (2016).Article 

Google Scholar 
Cumming, G. S. et al. Understanding protected area resilience: a multi-scale, social-ecological approach. Ecol. Appl. 25, 299–319 (2015).Article 

Google Scholar 
Ellis, E. C. & Mehrabi, Z. Half Earth: promises, pitfalls, and prospects of dedicating half of Earth’s land to conservation. Curr. Opin. Environ. Sustain. 38, 22–30 (2019).Article 

Google Scholar 
Golden Kroner, R. E. et al. The uncertain future of protected lands and waters. Science 364, 881–886 (2019).Article 
CAS 

Google Scholar 
Palfrey, R., Oldekop, J. & Holmes, G. Conservation and social outcomes of private protected areas. Conserv. Biol. 35, 1098–1110 (2021).Article 

Google Scholar 
Gurney, G. G. et al. Biodiversity needs every tool in the box: use OECMs. Nature 595, 646–649 (2021).Article 
CAS 

Google Scholar 
Kremen, C. & Merenlender, A. M. Landscapes that work for biodiversity and people. Science 362, eaau6020 (2018).Article 

Google Scholar 
Taylor, W. A. et al. South Africa’s private wildlife ranches protect globally significant populations of wild ungulates. Biodivers. Conserv. 30, 4111–4135 (2021).Article 

Google Scholar 
Child, B. A., Musengezi, J., Parent, G. D. & Child, G. F. T. The economics and institutional economics of wildlife on private land in Africa. Pastoralism 2, 18 (2012).Article 

Google Scholar 
Kiffner, C. et al. Community-based wildlife management area supports similar mammal species richness and densities compared to a national park. Ecol. Evol. 10, 480–492 (2020).Article 

Google Scholar 
Naidoo, R. et al. Complementary benefits of tourism and hunting to communal conservancies in Namibia. Conserv. Biol. 30, 628–638 (2016).Article 

Google Scholar 
Cousins, J., Sadler, J. & Evans, J. Exploring the role of private wildlife ranching as a conservation tool in South Africa: stakeholder perspectives. Ecol. Soc. 13, 43 (2008).Article 

Google Scholar 
Kamal, S., Grodzińska-Jurczak, M. & Brown, G. Conservation on private land: a review of global strategies with a proposed classification system. J. Environ. Plann. Manage. 58, 576–597 (2015).Article 

Google Scholar 
Ogar, E., Pecl, G. & Mustonen, T. Science must embrace traditional and indigenous knowledge to solve our biodiversity crisis. One Earth 3, 162–165 (2020).Article 

Google Scholar 
De Vos, A. & Cumming, G. S. The contribution of land tenure diversity to the spatial resilience of protected area networks. People Nat. 1, 331–346 (2019).Article 

Google Scholar 
Biggs, R. et al. Toward principles for enhancing the resilience of ecosystem services. Annu. Rev. Environ. Resour. 37, 421–448 (2012).Article 

Google Scholar 
Cumming, G. & Collier, J. Change and identity in complex systems. Ecol. Soc. 10, 29 (2005).Article 

Google Scholar 
Oliver, T. H. et al. Biodiversity and resilience of ecosystem functions. Trends Ecol. Evol. 30, 673–684 (2015).Article 

Google Scholar 
Leslie, P. & McCabe, J. T. Response diversity and resilience in social–ecological systems. Curr. Anthropol. 54, 114–143 (2013).Article 

Google Scholar 
Clements, H. S., Knight, M., Jones, P. & Balfour, D. Private rhino conservation: diverse strategies adopted in response to the poaching crisis. Conserv. Lett. 13, e12741 (2020).Article 

Google Scholar 
Carpenter, S., Walker, B., Anderies, J. M. & Abel, N. From metaphor to measurement: resilience of what to what? Ecosystems 4, 765–781 (2001).Article 

Google Scholar 
Parker, K., De Vos, A., Clements, H. S., Biggs, D. & Biggs, R. Impacts of a trophy hunting ban on private land conservation in South African biodiversity hotspots. Conserv. Sci. Pract. 2, e214 (2020).
Google Scholar 
World Travel & Tourism Council. The Economic Impact of Global Wildlife Tourism (WTTC, 2019).Lindsey, P. et al. Conserving Africa’s wildlife and wildlands through the COVID-19 crisis and beyond. Nat. Ecol. Evol. 4, 1300–1310 (2020).Article 

Google Scholar 
Hambira, W. L., Stone, L. S. & Pagiwa, V. Botswana nature-based tourism and COVID-19: transformational implications for the future. Dev. South. Afr. 39, 51–67 (2021).Article 

Google Scholar 
Mudzengi, B. K., Gandiwa, E., Muboko, N. & Mutanga, C. N. Innovative community ecotourism coping and recovery strategies to COVID-19 pandemic shocks: the case of Mahenye. Dev. South. Afr. 39, 68–83 (2021).Article 

Google Scholar 
Waithaka, J. et al. Impacts of COVID-19 on protected and conserved areas: a global overview and regional perspectives. Parks 27, 41–56 (2021).Article 

Google Scholar 
Smith, M. K. S. et al. Sustainability of protected areas: vulnerabilities and opportunities as revealed by COVID-19 in a national park management agency. Biol. Conserv. 255, 108985 (2021).Article 

Google Scholar 
Miller-Rushing, A. J. et al. COVID-19 pandemic impacts on conservation research, management, and public engagement in US national parks. Biol. Conserv. 257, 109038 (2021).Article 

Google Scholar 
Thurstan, R. H. et al. Envisioning a resilient future for biodiversity conservation in the wake of the COVID‐19 pandemic. People Nat. 3, 990–1013 (2021).Article 

Google Scholar 
Taylor, W. A., Lindsey, P. A., Nicholson, S. K., Relton, C. & Davies-Mostert, H. T. Jobs, game meat and profits: the benefits of wildlife ranching on marginal lands in South Africa. Biol. Conserv. 245, 108561 (2020).Article 

Google Scholar 
Chidakel, A., Eb, C. & Child, B. The comparative financial and economic performance of protected areas in the Greater Kruger National Park, South Africa: functional diversity and resilience in the socio-economics of a landscape-scale reserve network.J. Sustain. Tour. 28, 1100–1119 (2020).Article 

Google Scholar 
Saayman, M., van der Merwe, P. & Saayman, A. The economic impact of trophy hunting in the South African wildlife industry. Glob. Ecol. Conserv. 16, e00510 (2018).Article 

Google Scholar 
Hall, R. A political economy of land reform in South Africa. Rev. Afr. Polit. Econ. 31, 213–227 (2004).Article 

Google Scholar 
Mkhize, N. Game farm conversions and the land question: unpacking present contradictions and historical continuities in farm dwellers’ tenure insecurity in Cradock. J. Contemp. Afr. Stud. 32, 207–219 (2014).Article 

Google Scholar 
Thakholi, L. Conservation labour geographies: subsuming regional labour into private conservation spaces in South Africa. Geoforum 123, 1–11 (2021).Article 

Google Scholar 
Brandt, F. Power battles on South African trophy-hunting farms: farm workers, resistance and mobility in the Karoo. J. Contemp. Afr. Stud. 34, 165–181 (2016).Article 

Google Scholar 
Child, B. & Barnes, G. The conceptual evolution and practice of community-based natural resource management in southern Africa: past, present and future. Environ. Conserv. 37, 283–295 (2010).Article 

Google Scholar 
Clements, H. S., Baum, J. & Cumming, G. S. Money and motives: an organizational ecology perspective on private land conservation. Biol. Conserv. 197, 108–115 (2016).Article 

Google Scholar 
van der Merwe, P., Saayman, A. & Jacobs, C. Assessing the economic impact of COVID-19 on the private wildlife industry of South Africa. Glob. Ecol. Conserv. 28, e01633 (2021).Article 

Google Scholar 
Clements, H. S. & Cumming, G. S. Traps and transformations influencing the financial viability of tourism on private-land conservation areas. Conserv. Biol. 32, 424–436 (2018).Article 

Google Scholar 
Winterbach, C. W., Whitesell, C. & Somers, M. J. Wildlife abundance and diversity as indicators of tourism potential in northern Botswana. PLoS ONE 10, e0135595 (2015).Article 

Google Scholar 
Di Minin, E., Fraser, I., Slotow, R. & MacMillan, D. C. Understanding heterogeneous preference of tourists for big game species: implications for conservation and management. Anim. Conserv. 16, 249–258 (2013).Article 

Google Scholar 
Clements, H. S., Biggs, R. & Cumming, G. S. Cross-scale and social–ecological changes constitute main threats to private land conservation in South Africa. J. Environ. Manag. 274, 111235 (2020).Article 

Google Scholar 
Breen, C. et al. Integrating cultural and natural heritage approaches to marine protected areas in the MENA region. Mar. Policy 132, 104676 (2021).Article 

Google Scholar 
Munasinghe, H. The politics of the past: constructing a national identity through heritage conservation. Int. J. Herit. Stud. 11, 251–260 (2005).Article 

Google Scholar 
MacKinnon, K. et al. Strengthening the global system of protected areas post-2020: a perspective from the IUCN World Commission on Protected Areas. Parks 36, 281–296 (2020).
Google Scholar 
van Kerkhoff, L. et al. Towards future-oriented conservation: managing protected areas in an era of climate change. Ambio 48, 699–713 (2019).Article 

Google Scholar 
De Vos, A. et al. Pathogens, disease, and the social–ecological resilience of protected areas. Ecol. Soc. 21, 20 (2016).Article 

Google Scholar 
Bengtsson, J. et al. Reserves, resilience and dynamic landscapes. Ambio 32, 389–396 (2003).Article 

Google Scholar 
Broom, D. M., Galindo, F. A. & Murgueitio, E. Sustainable, efficient livestock production with high biodiversity and good welfare for animals. Proc. R. Soc. B 280, 20132025 (2013).Article 
CAS 

Google Scholar 
IPBES Global Assessment Report on Biodiversity and Ecosystem Services of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES Secretariat, 2019).Marnewick, D., Jonas, H. & Stevens, C. Site-level Methodology for Identifying Other Effective Area-based Conservation Measures (OECMs) Draft Version 1.0 (IUCN: Gland, Switzerland; 2020).Nalau, J., Becken, S. & Mackey, B. Ecosystem-based adaptation: a review of the constraints. Environ. Sci. Policy 89, 357–364 (2018).Article 

Google Scholar 
Hartung, C. et al. Open Data Kit: tools to build information services for developing regions. In Proc. 4th ACM/IEEE International Conference on Information and Communication Technologies and Development (ed Unwin, T.) pp 1–12 (Association for Computing Machinery, New York, NY, United States; 2010).Oksanen, A. J. et al. Vegan: Community Ecology Package. R version 2.6–2 (2022). https://cran.r-project.org/web/packages/vegan/vegan.pdfWard, J. Hierarchical grouping to optimize an objective function. J. Am. Stat. Assoc. 58, 236–244 (1963).Article 

Google Scholar 
Maechler, M. et al. Cluster: Finding Groups in Data. R version 2.0.3 (2015). https://cran.microsoft.com/snapshot/2015-11-17/web/packages/cluster/cluster.pdfR Core Team R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2021). More