Philippa Kaur

1.Elser, J. J. et al. Global analysis of nitrogen and phosphorus limitation of primary producers in freshwater, marine and terrestrial ecosystems. Ecol. Lett. 10, 1135–1142 (2007).Article 

Google Scholar 
2.Mengel, K. & Kirkby, E. A. Principles of Plant Nutrition (Kluwer Academic Publishers, 2001).Book 

Google Scholar 
3.Reich, M., Aghajanzadeh, T. & De Kok, L. J. Physiological basis of plant nutrient use efficiency—Concepts, opportunities and challenges for its improvement. In Nutrient Use Efficiency in Plants: Concepts and Approaches (eds Hawkesford, M. J. et al.) (Springer, 2014).
Google Scholar 
4.Agren, G. I. Ideal nutrient productivities and nutrient proportions in plant growth. Plant Cell Environ. 11, 613–620 (1988).Article 

Google Scholar 
5.Weih, M., Hamner, K. & Pourazari, F. Analyzing plant nutrient uptake and utilization efficiencies: Comparison between crops and approaches. Plant Soil 430, 7–21 (2018).CAS 
Article 

Google Scholar 
6.Sterner, R. W. & Elser, J. J. Ecological stoichiometry: The biology of elements from molecules to the biosphere (2002).7.Reich, P. B. et al. Evidence of a general 2/3-power law of scaling leaf nitrogen to phosphorus among major plant groups and biomes. Proc. R. Soc. B Biol. Sci. 277, 877–883 (2010).CAS 
Article 

Google Scholar 
8.Hutchinson, G. E. Population studies—Animal ecology and demography—Concluding remarks. Cold Spring Harbor. Symp. Quant. Biol. 22, 415–427 (1957).Article 

Google Scholar 
9.Agren, G. I. & Weih, M. Multi-dimensional plant element stoichiometry-looking beyond carbon, nitrogen, and phosphorus. Front. Plant Sci. 11, 23 (2020).Article 

Google Scholar 
10.Niklas, K. J. Plant allometry, leaf nitrogen and phosphorus stoichiometry, and interspecific trends in annual growth rates. Ann. Bot. 97, 155–163 (2006).CAS 
Article 

Google Scholar 
11.Hou, E. et al. Global meta-analysis shows pervasive phosphorus limitation of aboveground plant production in natural terrestrial ecosystems. Nat. Commun. 11, 637 (2020).ADS 
CAS 
Article 

Google Scholar 
12.Ryan, P. R. et al. Early vigour improves phosphate uptake in wheat. J. Exp. Bot. 66, 7089–7100 (2015).CAS 
Article 

Google Scholar 
13.Wiel, CCMvd., Linden, CGvd & Scholten, O. E. Improving phosphorus use efficiency in agriculture: Opportunities for breeding. Euphytica 207, 1–22 (2016).Article 

Google Scholar 
14.Bilal, H. M., Aziz, T., Maqsood, M. A., Farooq, M. & Yan, G. Categorization of wheat genotypes for phosphorus efficiency. PLoS ONE 13, e0205471 (2018).Article 

Google Scholar 
15.Wang, Z. et al. Magnesium fertilization improves crop yield in most production systems: A meta-analysis. Front. Plant Sci. 10, 1727 (2020).Article 

Google Scholar 
16.Hauer-Jakli, M. & Traenkner, M. Critical leaf magnesium thresholds and the impact of magnesium on plant growth and photo-oxidative defense: a systematic review and meta-analysis from 70 years of research. Front. Plant Sci. 10, 766 (2019).Article 

Google Scholar 
17.Chawade, A. et al. A transnational and holistic breeding approach is needed for sustainable wheat production in the Baltic Sea region. Physiol. Plant. 164, 442–451 (2018).CAS 
Article 

Google Scholar 
18.Weih, M., Pourazari, F. & Vico, G. Nutrient stoichiometry in winter wheat: Element concentration pattern reflects developmental stage and weather. Sci. Rep. 6, 35958–35958 (2016).ADS 
CAS 
Article 

Google Scholar 
19.Hamner, K., Weih, M., Eriksson, J. & Kirchmann, H. Influence of nitrogen supply on macro- and micronutrient accumulation during growth of winter wheat. Field Crop Res. 213, 118–129 (2017).Article 

Google Scholar 
20.Jia, X., Liu, P. & Lynch, J. P. Greater lateral root branching density in maize improves phosphorus acquisition from low phosphorus soil. J. Exp. Bot. 69, 4961–4970 (2018).CAS 
Article 

Google Scholar 
21.Kumar, A. et al. Root trait plasticity and plant nutrient acquisition in phosphorus limited soil. J. Plant Nutr. Soil Sci. 182, 945–952 (2019).CAS 
Article 

Google Scholar 
22.Lynch, J. P. Root phenes for enhanced soil exploration and phosphorus acquisition: Tools for future crops. Plant Physiol. 156, 1041–1049 (2011).CAS 
Article 

Google Scholar 
23.Lynch, J. P. Steep, cheap and deep: An ideotype to optimize water and N acquisition by maize root systems. Ann. Bot. 112, 347–357 (2013).CAS 
Article 

Google Scholar 
24.Lambers, H., Shane, M., Cramer, M., Pearse, S. & Veneklaas, E. Root structure and functioning for efficient acquisition of phosphorus: Matching morphological and physiological traits. Ann. Bot. 98, 693–713 (2006).Article 

Google Scholar 
25.Trachsel, S., Kaeppler, S. M., Brown, K. M. & Lynch, J. P. Maize root growth angles become steeper under low N conditions. Field Crop Res 140, 18–31 (2013).Article 

Google Scholar 
26.Jobbagy, E. G. & Jackson, R. B. The distribution of soil nutrients with depth: Global patterns and the imprint of plants. Biogeochemistry 53, 51–77 (2001).CAS 
Article 

Google Scholar 
27.Sun, B. R., Gao, Y. Z. & Lynch, J. P. Large crown root number improves topsoil foraging and phosphorus acquisition. Plant Physiol. 177, 90–104 (2018).CAS 
Article 

Google Scholar 
28.Weih, M., Asplund, L. & Bergkvist, G. Assessment of nutrient use in annual and perennial crops: A functional concept for analyzing nitrogen use efficiency. Plant Soil 339, 513–520 (2011).CAS 
Article 

Google Scholar 
29.Malhi, S. S., Johnston, A. M., Schoenau, J. J., Wang, Z. H. & Vera, C. L. Seasonal biomass accumulation and nutrient uptake of wheat, barley and oat on a Black Chernozern soil in Saskatchewan. Can. J. Plant Sci. 86, 1005–1014 (2006).Article 

Google Scholar 
30.Maeoka, R. E. et al. Changes in the phenotype of winter wheat varieties released between 1920 and 2016 in response to in-furrow fertilizer: Biomass allocation, yield, and grain protein concentration. Front. Plant Sci. 10, 1786 (2020).Article 

Google Scholar 
31.Pourazari, F., Vico, G., Ehsanzadeh, P. & Weih, M. Contrasting growth pattern and nitrogen economy in ancient and modern wheat varieties. Can. J. Plant Sci. 95, 851–860 (2015).Article 

Google Scholar 
32.Rietra, R. P. J. J., Heinen, M., Dimkpa, C. O. & Bindraban, P. S. Effects of nutrient antagonism and synergism on yield and fertilizer use efficiency. Commun. Soil Sci. Plant Anal. 48, 1895–1920 (2017).CAS 
Article 

Google Scholar 
33.Pedro, A., Savin, R. & Slafer, G. A. Crop productivity as related to single-plant traits at key phenological stages in durum wheat. Field Crop Res. 138, 42–51 (2012).Article 

Google Scholar 
34.Cakmak, I. & Yazici, A. M. Magnesium: A forgotten element in crop production. Better Crops Plant Food 94, 23–25 (2010).
Google Scholar 
35.Lancashire, P. D. et al. A uniform decimal code for growth-stages of crops and weeds. Ann. Appl. Biol. 119, 561–601 (1991).Article 

Google Scholar 
36.Trachsel, S., Kaeppler, S. M., Brown, K. M. & Lynch, J. P. Shovelomics: High throughput phenotyping of maize (Zea mays L.) root architecture in the field. Plant Soil 341, 75–87 (2011).CAS 
Article 

Google Scholar 
37.Colombi, T. & Walter, A. Root responses of triticale and soybean to soil compaction in the field are reproducible under controlled conditions. Funct. Plant Biol. 43, 114–128 (2016).Article 

Google Scholar  More

We asked whether the mating of male and female fruit flies would be affected by the presence of parasitoid wasps. We placed a pair of D. melanogaster flies in a small Petri dish, either with or without parasitoid wasps (Fig. 1a). In an initial experiment we used the wasp Leptopilina boulardi, which specializes on D. melanogaster and on closely related fly species14.Fig. 1: Exposure of Drosophila to wasps accelerates sexual behavior.a Courtship arena containing a male and virgin female fly with (left) and without (right) two wasps, one male and one female. b Copulation latency of D. melanogaster. p  More

Now that China has finally updated its List of Wildlife under Special State Protection, a more nimble and responsive approach is needed to aid conservation. The list should be reviewed every year, as well as subjected to the planned five-yearly updates. Species can quickly become endangered in times of rapid development.The latest additions are the first in more than 30 years (see go.nature.com/2q7sfga). During that time, China has changed profoundly, but the list of protected species has not kept pace. This lag has been disastrous for some animals that were not given the protection they needed.At least 33 species became extinct in China and many more are critically endangered (Y. Xie & W. Sung Integr. Zool. 2, 26–35; 2007; Z. Jiang et al. Biodivers. Sci. 24, 500–551; 2016).An independent government committee should be created to oversee amendments. When making decisions, it could refer to appendices of the Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES) and the ‘red lists’ of threatened species curated by the Chinese Academy of Sciences and the International Union for Conservation of Nature (IUCN). These steps would build on the more forceful approach to managing wildlife that China has taken since the start of the COVID-19 pandemic. More

1.Whyte, R. O. Grassland and Fodder Resources of India Revised. (Indian Council of Agricultural Research, 1964).
Google Scholar 
2.Misra, R. The vegetation of the Indian Savannas. In Tropical Savannas (ed. Bourliere, F.) 151–166 (Elsevier, 1983).3.Behrensmeyer, A. K. et al. The structure and rate of late Miocene expansion of C4 plants: evidence from lateral variation in stable isotopes in paleosols of the Siwalik Group, northern Pakistan. GSA Bull. 119, 1486–1505 (2007).CAS 
Article 

Google Scholar 
4.Champion, H. G. & Seth, S. K. A Revised Survey of the Forest Types of India (Government of India Press, 1968).
Google Scholar 
5.Mani, M. S. The Flora. In Ecology and Biogeography in India (ed. Mani, M. S.) 159–177 (Dr. W. Junk b.v. Publishers, 1974).6.Ratnam, J., Tomlinson, K. W., Rasquinha, D. N. & Sankaran, M. Savannahs of Asia: antiquity, biogeography, and an uncertain future. Philos. Trans. R. Soc. B 371, 20150305 (2016).Article 
CAS 

Google Scholar 
7.Blasco, F. The transition from open forest to Savanna in continental Southeast Asia. In Tropical Savannas (ed. Bourliere, F.) 167–182 (Elsevier, 1983).8.Puri, G. S., Meher Homji, V. M., Gupta, R. K. & Puri, S. Forest Ecology. Phytogeography and Conservation Vol. 1 (Oxford & IBH Publishing, 1983).
Google Scholar 
9.Fuller, D. Q. & Korisettar, R. The vegetational context of early agriculture in South India. Man Environ. 29, 7–27 (2004).
Google Scholar 
10.Fuller, D. Q. Finding plant domestication in the Indian subcontinent. Curr. Anthropol. 52, S347–S362 (2011).Article 

Google Scholar 
11.Lehmann, C. E. R., Archibald, S. A., Hoffmann, W. A. & Bond, W. J. Deciphering the distribution of the savanna biome. New Phytol. 191, 197–209 (2011).PubMed 
Article 
PubMed Central 

Google Scholar 
12.Staver, A. C., Archibald, S. & Levin, S. A. Tree-cover in sub-Saharan Africa: rainfall and fire constrain forest and savanna as alternative stable states. Ecology 92, 1063–1072 (2011).PubMed 
Article 
PubMed Central 

Google Scholar 
13.Bond, W. J. What limits trees in C4 grasslands and savannas?. Annu. Rev. Ecol. Evol. Syst. 39, 641–659 (2008).Article 

Google Scholar 
14.Hirota, M., Holmgren, M., Van Nes, E. & Scheffer, M. Global resilience of tropical forest and savanna to critical transitions. Science 334, 232–235 (2011).ADS 
CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
15.Staver, A. C., Archibald, S. & Levin, S. A. The global extent and determinants of savanna and forest as alternative biome states. Science 334, 230–232 (2011).ADS 
CAS 
PubMed 
MATH 
Article 
PubMed Central 

Google Scholar 
16.Mayle, F. E. & Power, M. J. Impact of a drier early–mid-Holocene climate upon Amazonian forests. Philos. Trans. R. Soc. Lond. B Biol. Sci. 363, 1829–1838 (2008).PubMed 
PubMed Central 
Article 

Google Scholar 
17.Ngomanda, A. et al. Western equatorial African forest-savanna mosaics: a legacy of late Holocene climatic change?. Clim. Past 5, 647–659 (2009).Article 

Google Scholar 
18.Metwally, A. A., Scott, L., Neumann, F. H., Bamford, M. K. & Oberhänsli, H. Holocene palynology and palaeoenvironments in the Savanna Biome at Tswaing Crater, central South Africa. Palaeogeogr. Palaeoclimatol. Palaeoecol. 402, 125–135 (2014).Article 

Google Scholar 
19.Kuper, R. & Kröpelin, S. Climate-controlled Holocene occupation in the Sahara: motor of Africa’s evolution. Science 313, 803–807 (2006).ADS 
CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
20.Mayewski, P. A. et al. Holocene climate variability. Quat. Res. 62, 243–255 (2004).Article 

Google Scholar 
21.Wanner, H. et al. Mid- to late Holocene climate change: an overview. Quat. Sci. Rev. 27, 1791–1828 (2008).ADS 
Article 

Google Scholar 
22.Kathayat, G. et al. The Indian monsoon variability and civilization changes in the Indian subcontinent. Sci. Adv. 3, e1701296 (2017).ADS 
PubMed 
PubMed Central 
Article 

Google Scholar 
23.Shinde, V. The origin and development of the Chalcolithic in Central India. Indo-Pac. Prehist. Assoc. Bull. 19, 125–136 (2000).
Google Scholar 
24.Fuller, D. Q. Agricultural origins and frontiers in South Asia: a working synthesis. J. World Prehist. 20, 1–86 (2006).Article 

Google Scholar 
25.Fuller, D. Q., Boivin, N. & Korisettar, R. Dating the Neolithic of South India: new radiometric evidence for key economic, social and ritual transformations. Antiquity 81, 755–778 (2007).Article 

Google Scholar 
26.Johansen, P. G. Landscape, monumental architecture, and ritual: a reconsideration of the South Indian ashmounds. J. Anthropol. Archaeol. 23, 309–330 (2004).Article 

Google Scholar 
27.Fuller, D. Q. Asia, South: Neolithic cultures. In Encyclopedia of Archaeology (ed. Pearsall, D.) 756–768 (Springer, 2008).
Google Scholar 
28.Asouti, E. & Fuller, D. Q. Trees and Woodlands of South India: Archaeological Perspectives (Left Coast Press, 2008).
Google Scholar 
29.Singh, G., Joshi, R. D., Chopra, S. K. & Singh, A. B. Late quaternary history of vegetation and climate of the Rajasthan desert, India. Philos. Trans. R. Soc. Lond. B Biol. Sci. 267, 467–501 (1974).ADS 
Article 

Google Scholar 
30.Singh, I. B. Quaternary palaeoenvironments of the Ganga plain and anthropogenic activity. Man Environ. 30, 1–35 (2005).
Google Scholar 
31.Clarkson, C. et al. The oldest and longest enduring microlithic sequence in India: 35 000 years of modern human occupation and change at the Jwalapuram locality 9 rockshelter. Antiquity 83, 326–348 (2009).Article 

Google Scholar 
32.Riedel, N. et al. Modern pollen vegetation relationships in a dry deciduous monsoon forest: a case study from Lonar Crater Lake, central India. Quat. Int. 371 (2015).33.Sarkar, S. et al. Monsoon source shifts during the drying mid-Holocene: biomarker isotope based evidence from the core ‘monsoon zone’ (CMZ) of India. Quat. Sci. Rev. 123, 144–157 (2015).ADS 
Article 

Google Scholar 
34.Chakraborty, A., Joshi, P. K., Ghosh, A. & Areendran, G. Assessing biome boundary shifts under climate change scenarios in India. Ecol. Indic. 34, 536–547 (2013).Article 

Google Scholar 
35.Rasquinha, D. N. & Sankaran, M. Modelling biome shifts in the Indian subcontinent under scenarios of future climate change. Curr. Sci. 111, 147–156 (2016).Article 

Google Scholar 
36.Berkelhammer, M. et al. An abrupt shift in the Indian monsoon 4000 years ago in Climates, Landscapes, and Civilizations (eds. Giosan, L. et al.) 75–88 (American Geophysical Union, 2013).37.Fleitmann, D. et al. Holocene ITCZ and Indian monsoon dynamics recorded in stalagmites from Oman and Yemen (Socotra). Quat. Sci. Rev. 26, 170–188 (2007).ADS 
Article 

Google Scholar 
38.Sinha, A. et al. A global context for megadroughts in monsoon Asia during the past millennium. Quat. Sci. Rev. 30, 47–62 (2011).ADS 
Article 

Google Scholar 
39.Berkelhammer, M. et al. Persistent multidecadal power of the Indian Summer Monsoon. Earth Planet. Sci. Lett. 290, 166–172 (2010).ADS 
CAS 
Article 

Google Scholar 
40.Laskar, A. H., Yadava, M. G., Ramesh, R., Polyak, V. J. & Asmerom, Y. A 4 kyr stalagmite oxygen isotopic record of the past Indian Summer Monsoon in the Andaman Islands. Geochem. Geophys. Geosyst. 14, 3555–3566 (2013).ADS 
CAS 
Article 

Google Scholar 
41.Thamban, M., Kawahata, H. & Rao, V. P. Indian summer monsoon variability during the Holocene as recorded in sediments of the Arabian Sea: timing and implications. J. Oceanogr. 63, 1009–1020 (2007).Article 

Google Scholar 
42.Ponton, C. et al. Holocene aridification of India. Geophys. Res. Lett. 39, L03704 (2012).ADS 
Article 

Google Scholar 
43.Deblauwe, V. et al. Remotely sensed temperature and precipitation data improve species distribution modelling in the tropics. Glob. Ecol. Biogeogr. 25, 443–454 (2016).Article 

Google Scholar 
44.Gaussen, H. et al. International Map of the Vegetation at Scale 1:1.000.000 (French Institute of Pondycherry, 1964).
Google Scholar 
45.ESRI Inc. ArcGIS Pro (ESRI Inc., 2019).
Google Scholar 
46.Saha, K. Tropical Circulation Systems and Monsoons (Springer, 2010).Book 

Google Scholar 
47.Goswami, B. N. South Asian monsoon. In Intraseasonal Variability in the Atmosphere–Ocean Climate System (eds. Lau, W. K. M. & Waliser, D. E.) 19–61 (Springer, 2005).48.Dabadghao, P. M. & Shankarnarayan, K. A. The Grass Cover of India (Indian Council of Agricultural Research, 1973).
Google Scholar 
49.Prasad, S. & Enzel, Y. Holocene paleoclimates of India. Quat. Res. 66, 442–453 (2006).Article 

Google Scholar 
50.Fleitmann, D. et al. Palaeoclimatic interpretation of high-resolution oxygen isotope profiles derived from annually laminated speleothems from Southern Oman. Quat. Sci. Rev. 23, 935–945 (2004).ADS 
Article 

Google Scholar 
51.Kale, V. S. Fluvio–sedimentary response of the monsoon-fed Indian rivers to Late Pleistocene–Holocene changes in monsoon strength: reconstruction based on existing 14C dates. Quat. Sci. Rev. 26, 1610–1620 (2007).ADS 
MathSciNet 
Article 

Google Scholar 
52.Prasad, S. et al. Prolonged monsoon droughts and links to Indo-Pacific warm pool: a Holocene record from Lonar Lake, central India. Earth Planet. Sci. Lett. 391, 171–182 (2014).ADS 
CAS 
Article 

Google Scholar 
53.Dixit, Y., Hodell, D. A. & Petrie, C. A. Abrupt weakening of the summer monsoon in northwest India ∼ 4100 yr ago. Geology https://doi.org/10.1130/G35236.1 (2014).Article 

Google Scholar 
54.Laskar, J. et al. A long-term numerical solution for the insolation quantities of the Earth. Astron. Astrophys. 428, 261–285 (2004).ADS 
Article 

Google Scholar 
55.Marzin, C. & Braconnot, P. Variations of Indian and African monsoons induced by insolation changes at 6 and 9.5 kyr BP. Clim. Dyn. 33, 215–231 (2009).Article 

Google Scholar 
56.Bush, R. T. & McInerney, F. A. Leaf wax n-alkane distributions in and across modern plants: implications for paleoecology and chemotaxonomy. Geochim. Cosmochim. Acta 117, 161–179 (2013).ADS 
CAS 
Article 

Google Scholar 
57.Murphy, C. & Fuller, D. Q. The agriculture of early India. In Oxford Research Encyclopedia of Environmental Science (ed. Shugart, H.) (Oxford University Press, 2017).
Google Scholar 
58.Kumaran, N. K. P. et al. Vegetation response and landscape dynamics of Indian Summer Monsoon variations during Holocene: an eco-geomorphological appraisal of tropical evergreen forest subfossil logs. PLoS ONE 9, e93596 (2014).ADS 
PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
59.Singh, G., Wasson, R. J. & Agrawal, D. P. Vegetational and seasonal climatic changes since the last full glacial in the Thar Desert, northwestern India. Rev. Palaeobot. Palynol. 64, 351–358 (1990).Article 

Google Scholar 
60.Cole, M. M. The Savannas, Biogeography and Geobotany (Academic Press, 1986).61.Sankaran, M. et al. Determinants of woody cover in African savannas. Nature 438, 846–849 (2005).ADS 
CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
62.Kodandapani, N., Cochrane, M. A. & Sukumar, R. A comparative analysis of spatial, temporal, and ecological characteristics of forest fires in seasonally dry tropical ecosystems in the Western Ghats, India. For. Ecol. Manag. 256, 607–617 (2008).Article 

Google Scholar 
63.Hegde, V., Chandran, M. D. S. & Gadgil, M. Variation in bark thickness in a tropical forest community of Western Ghats in India. Funct. Ecol. 12, 313–318 (1998).Article 

Google Scholar 
64.Stott, P. A., Goldammer, J. G. & Werner, W. L. The role of fire in the tropical lowland deciduous forests of Asia. In Fire in the Tropical Biota. Ecosystem Processes and Global Challenges (ed. Goldammer, J. G.) 32–44 (Springer, 1990).65.Murphy, C. & Fuller, D. Q. Seed coat thinning during horsegram (Macrotyloma uniflorum) domestication documented through synchrotron tomography of archaeological seeds. Sci. Rep. 7, 5369 (2017).ADS 
PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
66.Kingwell-Banham, E. & Fuller, D. Q. Shifting cultivators in South Asia: expansion, marginalisation and specialisation over the long term. Quat. Int. 249, 84–95 (2012).Article 

Google Scholar 
67.Kajale, M. Excavation at Inamgaon (Deccan College Postgraduate and Research Institute, 1988).
Google Scholar 
68.Shirvalkar, P. & Prasad, E. The archaeology of the Late Holocene on the Deccan Plateau (The Deccan Chalcolithic). In A Companion to South Asia in the Past (eds. Schug, G. R. & Walimbe, S. R.) 240-254 (John Wiley & Sons, 2016).69.Roberts, P. et al. Local diversity in settlement, demography and subsistence across the southern Indian Neolithic-Iron Age transition: site growth and abandonment at Sanganakallu-Kupgal. Archaeol. Anthropol. Sci. 8, 575–599 (2016).Article 

Google Scholar 
70.Nayar, T. S. Pollen Flora of Maharashtra State, India (Today & Tomorrow Printers and Publishers, 1990).
Google Scholar 
71.APSA Members. The Australasian Pollen and Spore Atlas V1.0 (Australian National University, 2007).
Google Scholar 
72.Tinner, W. & Hu, F. S. Size parameters, size-class distribution and area-number relationship of microscopic charcoal: relevance for fire reconstruction. Holocene 13, 499–505 (2003).ADS 
Article 

Google Scholar 
73.Conedera, M. et al. Reconstructing past fire regimes: methods, applications, and relevance to fire management and conservation. Quat. Sci. Rev. 28, 555–576 (2009).ADS 
Article 

Google Scholar 
74.Higuera, P., Peters, M., Brubaker, L. & Gavin, D. Understanding the origin and analysis of sediment-charcoal records with a simulation model. Quat. Sci. Rev. 26, 1790–1809 (2007).ADS 
Article 

Google Scholar 
75.McDermott, F. Palaeo-climate reconstruction from stable isotope variations in speleothems: a review. Quat. Sci. Rev. 23, 901–918 (2004).ADS 
Article 

Google Scholar 
76.Baldini, J., McDermott, F. & Fairchild, I. Spatial variability in cave drip water hydrochemistry: implications for stalagmite paleoclimate records. Chem. Geol. 235, 390–404 (2006).ADS 
CAS 
Article 

Google Scholar 
77.Allchin, B. & Allchin, F. R. The Rise of Civilization in India and Pakistan (Cambridge University Press, 1982).
Google Scholar 
78.Shinde, V. S. New light on the origin, settlement system and decline of the Jorwe culture in the Deccan India. South Asian Stud. 5, 59–72 (1989).Article 

Google Scholar 
79.Shinde, V. S. Settlement pattern of the Savalda culture—the first farming community of Maharashtra. Bull. Deccan Coll. Res. Inst. 49–50, 417–426 (1990).
Google Scholar 
80.Paddayya, K. Investigations Into the Neolithic Culture of the Shorapur Doab, South India Vol. 3 (Brill, 1973).
Google Scholar  More

For each case study area, a search query was executed (Table 1). Query terms were based on the hashtags of the geographical name of the study areas; therefore, the post download was related to the name of the study area (e.g., Galapagos), with all downloaded posts including this name as query. Query search was limited to English, the most common language amongst tourists. This might have overlooked posts where the name of the place was in a different language. For most marine areas, this was considered irrelevant as the name of the place is not translated to other languages (e.g., Tayrona, Vamizi, Skomer). In some of the cases, the name of the place could appear in a variety of languages (e.g., Great Barrier Reef), however, the use of non-English place hashtags as queries generally retrieved a significantly lower number of posts (e.g., Gran Barrera de Coral in Spanish with 1900 posts, or Grand Barrière de Corail in French with 14 posts, while Great Barrier Reef had over 10,000 posts). In the specific case of Easter Island, we observed that the use of three particular queries was linked to a high number of posts: Easter Island and the local name Rapanui had over 10,000 posts each, and Isla de Pascua in Spanish had 8700 posts. In this case, three separate posts’ downloads were performed, and data were merged for subsequent analysis. The above, rather than a limitation of the methodological approach, demonstrates its flexibility to adapt to different data acquisition requirements.To illustrate the most relevant information contained as part of the posts downloaded for each of the 14 areas, we selected the 150 most frequent hashtags from each dataset in order to create the network graph and represent the dominant discourse in relation to the area in question. Network graphs were delineated using eigenvector, betweenness and edge betweenness as centrality measures. Eigenvector centrality measure (hereafter Eigenvector) allows identifying those hashtags that are frequently posted with other hashtags also frequently posted, and it can be interpreted as the pairs or groups of features more frequently related to the case study by the users. Betweenness centrality (hereafter betweenness) and edge betweenness centrality (hereafter edge betweenness) provide information about clusters of hashtags that describe users’ experiences or perceptions and that connect (by means of a hashtag) to other clusters representing other types of experiences or perceptions. These high betweenness hashtags structure the general discourse about an area and their removal would fragment the network and disconnect distant concepts. Therefore, hashtags and links with high betweenness can show the discourse parallel or additional to the main discourse and their relations, allowing to identify less frequent activities or perceptions but that are equally important to understand the network as a whole.Network centrality measuresResults indicated that network graphs captured information on distinct types of ecosystem services, for example, those based on wildlife and nature, heritage, or beach tourism. In areas such as Galapagos, central hashtags were nature, wildlife, photography, travel and adventure, evidencing a preference for wildlife and nature-based tourism. In this area, betweenness evidenced the connections between the most frequent hashtags group with other peripheric hashtags and provided a complete picture on the discourse of Galapagos’ visitors (Fig. 2). As such, nature and wildlife-based travel and photography is related with natural science concepts like evolution and endemism, and specific biotic and abiotic components like crabs and waves, altogether related with positive feelings (i.e., happy). Other areas emerging for their wildlife and nature were Skomer nature reserve, characterised by the hashtags birds (including the species Puffin), nature and wildlife photography; and Península Valdés, characterized by many locality names and by fauna, with the frequently posted hashtags’ wildlife, whales and nature funnelling most connections to other less frequent hashtags (e.g., wind, hiking, relax) and providing a full picture of the social perception on nature recreation activities, iconic fauna and positive feelings. Three networks, Sandwich Harbour, Glacier Bay and Macquarie Island also included popular hashtags related with nature, wildlife and photography; however, most hashtags had low betweenness and edge betweenness limiting the diversity of the posts (all network graphs are available at the Figshare repository, https://doi.org/10.6084/m9.figshare.13325627.v2).Figure 2Example of network graphs in Galapagos case study. In plot (A) node size represents the Eigenvector centrality and edges represent normalized strength (weighted degree). In plot (B) node size represents normalized Betweenness centrality and edges represent normalized Edge betweenness.Full size imageRegarding cultural heritage, Easter Island was characterised by popular hashtags related with Easter Island stone statues (moais) and with travel; and edge betweenness evidenced a diversity of peripherical nodes that describe other cultural elements, like design, music and food, and evidence social preferences for different cultural elements of the island, beyond the moais. Other areas reflected cultural identity by the frequent post of local names (e.g., Ytrehvaler), words related with the country’s identity (e.g., Isole Egadi) and positive feelings about this identity (e.g., Tawharanui). In Tayrona National Park network, the full discourse identified cultural identity like Kogui (indigenous culture) linked with the popular posts related with nature and summer holidays. Similarly, in Tawharanui and Isole Egadi, beach, nature and summer where the most frequent posts that, in some cases, where connected with places and activities. In these cases, and particularly in Isole Egadi and Ytrehvaler, edge betweenness allows to identify connections between places and activities, wildlife or natural structures, providing relevant information for area management and conservation.A group of areas were appreciated by their underwater ecosystems. For Great Barrier Reef, popular hashtags were related with the coral reef: ocean, diving, underwater photography, travel, nature, coral and reef; whereas betweenness highlighted a set of hashtags related with conservation: science, sustainability, save the reef, 4 ocean (Fig. 3) and evidenced the presence of a conservationist discourse in the social media. In Toguean Island network, the frequent hashtags beach, wonderful and charming are connected to peripherical hashtags related with the sea (e.g., sea life, diving), while in Vamizi, popular hashtags were related with high-income tourism, private island, travel, luxury travel, and were connected to less frequent hashtags linked to the sea, including recreational fisheries. These last two examples illustrate differences in the benefits, and beneficiaries, provided by two popular touristic destinations.Figure 3Example of network graphs in Great Barrier Reef case study. In plot (A) node size represents the Eigenvector centrality and edges represent normalized strength (weighted degree). In plot (B) node size represents normalized Betweenness centrality and edges represent normalized Edge betweenness.Full size imageNetwork communitiesThe division of hashtags in communities allows for a more detailed exploration of the words included in the 150 most frequent hashtags selection, independently of their centrality measures, and allowed a categorisation of hashtags within cultural ecosystem services classes in each area (Table 2). Hashtags were grouped in 3 to 5 communities, with some communities relatively constant across case studies, e.g., aesthetics, wildlife and nature appreciation (Fig. 4) (all other network graphs are available at the Figshare repository, https://doi.org/10.6084/m9.figshare.13325627.v2).Table 2 Cultural Ecosystem Services’ types (CES) depicted from the community analysis (Fast Greedy algorithm). The order of the CES class does not imply a priority rank.Full size tableFigure 4Communities assessed through Fast-Greedy algorithm for the case studies Glacier Bay (A) and Tayrona (C). The node size represents the normalized Eigenvector and the colour represents the community. The colour and width of the edges represents the normalized edge strength (weighted degree).Full size imageIn some of the areas, the communities were diverse in hashtag composition, for example, in Galapagos, wildlife (and related words) was distinctive of several communities, but other communities were characterised by different concepts: beach, holidays, happiness, snorkelling and diving. In Easter Island, the hashtags related with the stone statues and cultural heritage characterise one community, while the other communities include a diversity of hashtags classified under adventure, nature, underwater recreational activities; therefore, it widens the information provided by the centrality metrics. Tayrona (Fig. 4) is also a diverse network with one community characterised by hashtags like beach, summer, happiness (wellbeing), but other communities contain a diversity of hashtags like forest, hiking, indigenous and wildlife (classified in recreational, cultural heritage, nature and aesthetics; Table 2).In some areas, the communities were not so diverse, but provided additional information on the posts. For example, in MacQuarie Island the communities highlighted iconic fauna, including several penguin species, and biodiversity conservation. In several areas, network communities informed of the iconic fauna and specific places: puffins and other bird species in Skomer; southern right whale, sealions and penguins in Península Valdés; glaciers and mountains in Glacier bay (Fig. 4); desert and dunes in Sandwich harbour. Finally, Ytrehvaler is a network characterised by many local names (in Norwegian), evidencing a national tourism, and hashtags related with scenery.Merged network of the 14 case studiesThe merged network highlighted several hashtags that act as bridges between communities of hashtags (Fig. 5). Nature, travel, photo and travel photography are key to structure the global network. However, several low eigenvector hashtags connect smaller groups: sunset and island connect the subgroups from Easter Island, Isole Egadi and Vamizi.Figure 5Global network graph including the fourteen case studies where the node size represents the Eigenvector centrality. The coloured clusters arrange the case studies to facilitate the visual identification of areas connected in the network.Full size imageFrom the hashtag travel photography diverges a branch that connects 7 areas through adventure; a small group of hashtags deriving from this node represent Sandwich harbour and Vamizi, connected through Africa. The hashtag ocean, connected to adventure, relates Great Barrier Reef with Tawharanui, and to wanderlust (a German expression for the desire to explore the world) that connects Península Valdés, Skomer and Macquairie Island. These three areas and Tayrona are also connected through the central hashtag travel photography, and Skomer and Macquairie Island through wildlife photography. The hashtag adventure is also connected to a group of hashtags from Galapagos that also derive to the high eigenvector hashtag nature.The hashtag nature is key to include the fragile sub-network Ytrehvaler, and also derives to other high eigenvector hashtag, travel, that in turn, connects to the small sub-network from Glacier bay. Photo, a central hashtag related with travel, connects to paradise, that is key to integrate Toguean Island, a few hashtags from Tayrona related with the Caribbean and beach, and a group of hashtags from Peninsula Valdez related with whale watching. Some other small hashtags, that are connected to high eigenvector hashtags but are not included in any particular area are shared by many of the areas, e.g., sun, relax, landscape photography, nature lovers, sunset, sky. More

1.Péres, J. M. & Picard, J. New manual for benthic bionomics in the Mediterranean Sea. Trav. Stn. Marittime Endoume 31, 137 (1964).
Google Scholar 
2.Moschino, V. & Marin, M. G. Seasonal changes in physiological responses and evaluation of “well-being” in the Venus clam Chamelea gallina from the Northern Adriatic Sea. Comp. Biochem. Physiol. Part A Mol. Integr. Physiol. 145, 433–440 (2006).Article 

Google Scholar 
3.Barillari, A., Boldrin, A., Mozzi, C. & Rabitti, S. Some relationships between the nature of the sediments and the presence of the clam Chamelea (Venus) gallina in the upper Adriatic sea, near Venice. Atti dell’istituto Veneto di Sci. Lett. ed Arti. Cl. di Sci. Mat. Fis. e Nat. 137, 19–34 (1979).4.Froglia, C. Clam fisheries with hydraulic dredges in the Adriatic Sea. In Marine Invertebrates Fisheries: Their Assessment and Management (ed. Caddy, J. F.) 507–524 (Wiley, 1989).
Google Scholar 
5.Orban, E. et al. Nutritional and commercial quality of the striped venus clam, Chamelea gallina, from the Adriatic sea. Food Chem. 101, 1063–1070 (2007).CAS 
Article 

Google Scholar 
6.Marini, M., Jones, B. H., Campanelli, A., Grilli, F. & Lee, C. M. Seasonal variability and Po River plume influence on biochemical properties along western Adriatic coast. J. Geophys. Res. Ocean 113, 1–18 (2008).7.Italian National Management Plan for hydraulic dredges. National management plan for fishing activities with the hydraulic dredger system and rakes for boats as identified in the designation of fishing gear in mechanical dredgers including hydraulic mechanized dredger (HMD) and mechanized dredger. Public Law No. 9913 of Italian Ministry for Agricultural, Food and Forestry Policies (2019).8.Morello, E. B., Froglia, C., Atkinson, R. J. A. & Moore, P. G. Impacts of hydraulic dredging on a macrobenthic community of the Adriatic Sea, Italy. Can. J. Fish. Aquat. Sci. 62, 2076–2087 (2005).Article 

Google Scholar 
9.Froglia, C. The contribution of scientific research to the management of bivalve mollusc fishing with hydraulic dredgers. Biol. Mar. Mediterr. 7, 71–82 (2000).
Google Scholar 
10.STECF. Commission Decision of 25 February 2016 setting up a Scientific, Technical and Economic Committee for Fisheries, C(2016) 1084, OJ C 74, 26.2.2016, 4–10 (2016).11.Gaspar, M. B., Pereira, A. M., Vasconcelos, P. & Monteiro, C. C. Age and growth of Chamelea gallina from the Algarve coast (southern Portugal): influence of seawater temperature and gametogenic cycle on growth rate. J. Molluscan Stud. 70, 371–377 (2004).Article 

Google Scholar 
12.Deval, M. C. Shell growth and biometry of the striped venus Chamelea gallina (L) in the Marmara Sea, Turkey. J. Shellfish Res. 20, 155–159 (2001).
Google Scholar 
13.Polenta, R. Observations on Growth of the Striped Venus Clam Chamelea gallina L. in the Middle Adriatic (Università di Bologna, 1993).
Google Scholar 
14.European Council. Council Regulation (EC) No 1967/2006 of 21 December 2006 concerning management measures for the sustainable exploitation of fishery resources in the Mediterranean Sea, amending Regulation (EEC) No 2847/93 and repealing Regulation (EC) No 1626/94. Off. J. Eur. Union, L 409/11 75 (2006).15.European Council. Commission Delegated Regulation (EU) 2016/2376 of 13 October 2016 establishing a rejection plan for bivalve molluscs Venus spp. in Italian territorial waters. Off. J. Eur. Union, L 352/48 2 (2016).16.European Council. Commission Delegated Regulation (EU) 2020/3 of 28 August 2019 establishing a discard plan for Venus shells (Venus spp.) in certain Italian territorial waters. Off. J. Eur. Union, L2/1 4 (2020).17.European Council. Commission Delegated Regulation (EU) 2020/2237 amending the Delegated Reg. (EU) 2020/3 concerning the waiver for the minimum conservation reference size for the conservation of the striped venus clam (Venus spp.) in certain Italian territorial waters. Off. J. Eur. Union, L436/1 3 (2020).18.European Council. Regulation (EU) No 1380/2013 of the European Parliament and of the Council of 11 December 2013 on the Common Fisheries Policy, amending Council Regulations (EC) No 1954/2003 and (EC) No 1224/2009 and repealing Council Regulations (EC) No 2371/2002 etc. Off. J. Eur. Union, L 354/22 40 (2013).19.Petetta, A. et al. Dredge selectivity in a Mediterranean striped venus clam (Chamelea gallina) fishery. Fish. Res. 238, 105895 (2021).Article 

Google Scholar 
20.Sala, A., Brčić, J., Herrmann, B., Lucchetti, A. & Virgili, M. Assessment of size selectivity in hydraulic clam dredge fisheries. Can. J. Fish. Aquat. Sci. 74, 339–348 (2017).Article 

Google Scholar 
21.Marin, M. G. et al. Effects of hydraulic dredging on target species Chamelea gallina from the northern Adriatic Sea: physiological responses and shell damage. J. Mar. Biol. Assoc. U. K. 83, 1281–1285 (2003).Article 

Google Scholar 
22.Moschino, V., Chícharo, L. & Marin, M. G. Effects of hydraulic dredging on the physiological responses of the target species Chamelea gallina (Mollusca: Bivalvia): laboratory experiments and field surveys. Sci. Mar. 72, 493–501 (2008).
Google Scholar 
23.Morello, E. B., Froglia, C., Atkinson, R. J. A. & Moore, P. G. Hydraulic dredge discards of the clam (Chamelea gallina) fishery in the western Adriatic Sea, Italy. Fish. Res. 76, 430–444 (2005).Article 

Google Scholar 
24.Moschino, V., Deppieri, M. & Marin, M. G. Evaluation of shell damage to the clam Chamelea gallina captured by hydraulic dredging in the Northern Adriatic Sea. ICES J. Mar. Sci. 60, 393–401 (2003).Article 

Google Scholar 
25.Brooks, S. P. J. et al. Differential survival of Venus gallina and Scapharca inaequivalvis during anoxic stress: covalent modification of phosphofructokinase and glycogen phosphorylase during anoxia. J. Comp. Physiol. B 161, 207–212 (1991).CAS 
Article 

Google Scholar 
26.Eertman, R. H. M., Wagenvoort, A. J., Hummel, H. & Smaal, A. C. “Survival in air” of the blue mussel Mytilus edulis L. as a sensitive response to pollution-induced environmental stress. J. Exp. Mar. Biol. Ecol. 170, 179–195 (1993).Article 

Google Scholar 
27.Crawley, M. J. The R book 2nd edn. (Wiley, 2013).MATH 

Google Scholar 
28.Zuur, A., Ieno, E. N., Walker, N., Saveliev, A. A. & Smith, G. M. Mixed Effects Models and Extensions in Ecology with R (Springer, 2009).Book 

Google Scholar 
29.Pinheiro, J., Bates, D., DebRoy, S., Sarkar, D. & R Core Team. nlme: linear and nonlinear mixed effects models. R package version 3.1-137 (2018).30.Morello, E. B., Froglia, C., Atkinson, R. J. A. & Moore, P. G. The effects of hydraulic dredging on the reburial of several molluscan species. Biol. Mar. Mediterr. 13, 610–613 (2006).
Google Scholar 
31.Henderson, S. M. & Richardson, C. A. A comparison of the age, growth rate and burrowing behaviour of the razor clams, Ensis siliqua and E. ensis. J. Mar. Biol. Assoc. U. K. 74, 939–954 (1994).Article 

Google Scholar 
32.Chıcharo, L., Chıcharo, M., Gaspar, M., Regala, J. & Alves, F. Reburial time and indirect mortality of Spisula solida clams caused by dredging. Fish. Res. 59, 247–257 (2002).Article 

Google Scholar 
33.Leitão, F. M. & Gaspar, M. B. Comparison of the burrowing response of undersized cockles (Cerastoderma edule) after fishing disturbance caused by hand dredge and harvesting knife. Mar. Biol. Res. 7, 509–514 (2011).Article 

Google Scholar 
34.Gaspar, M. B. et al. The influence of dredge design on the catch of Callista chione (Linnaeus, 1758). In Coastal Shellfish—A Sustainable Resource (ed. Burnell, G.) 153–167 (Springer, 2001).
Google Scholar 
35.Chícharo, M. A. et al. Adenylic-derived indices and reburying time as indicators of the effects of dredging-induced stress on the clam Spisula solida. Mar. Biol. 142, 1113–1117 (2003).Article 

Google Scholar 
36.Broadhurst, M. K., Suuronen, P. & Hulme, A. Estimating collateral mortality from towed fishing gear. Fish Fish. 7, 180–218 (2006).Article 

Google Scholar 
37.Uhlmann, S. S. & Broadhurst, M. K. Mitigating unaccounted fishing mortality from gillnets and traps. Fish Fish. 16, 183–229 (2015).Article 

Google Scholar 
38.ICES. Report of the Workshop on Methods for Estimating Discard Survival (WKMEDS) (2015).39.Breen, M., Huse, I., Ingolfsson, I., Madsen, N. & Soldal, A. V. SURVIVAL: an assessment of mortality in fish escaping from trawl codends and its use in fisheries management. EU Final Report (2007).40.Boscolo, R., Cornello, M. & Giovanardi, O. Condition index and air survival time to compare three kinds of Manila clam Tapes philippinarum (Adams & Reeve) farming systems. Aquac. Int. 11, 243–254 (2003).Article 

Google Scholar 
41.Ahrens, M. J., Nieuwenhuis, R. & Hickey, C. W. Sensitivity of juvenile Macomona liliana (bivalvia) to UV-photoactivated fluoranthene toxicity. Environ. Toxicol. 17, 567–577 (2002).ADS 
CAS 
Article 

Google Scholar 
42.Hutchins, C. M., Teasdale, P. R., Lee, S. Y. & Simpson, S. L. Influence of sediment metal spiking procedures on copper bioavailability and toxicity in the estuarine bivalve Indoaustriella lamprelli. Environ. Toxicol. Chem. Int. J. 28, 1885–1892 (2009).CAS 
Article 

Google Scholar 
43.Ballarin, L., Pampanin, D. M. & Marin, M. G. Mechanical disturbance affects haemocyte functionality in the Venus clam Chamelea gallina. Comp. Biochem. Physiol. Part A Mol. Integr. Physiol. 136, 631–640 (2003).Article 

Google Scholar 
44.Lucchetti, A. & Sala, A. Impact and performance of Mediterranean fishing gear by side-scan sonar technology. Can. J. Fish. Aquat. Sci. 69, 1806–1816 (2012).Article 

Google Scholar 
45.Italian Ministry Decree (DM) 22/12/2000. Ministerial Decree of 22 December 2000 Subject: discipline for fishing for bivalve molluscs. Changes to the Ministerial Decree 21.7.98 Being Registered At The Central Budget Office (2000).46.Anjos, M. et al. Bycatch and discard survival rate in a small-scale bivalve dredge fishery along the Algarve coast (southern Portugal). Sci. Mar. 82, 75–90 (2018).Article 

Google Scholar 
47.Bargione, G. et al. Age and growth of striped Venus Clam Chamelea gallina (Linnaeus, 1758) in the Mid-Western Adriatic Sea: a comparison of three laboratory techniques. Front. Mar. Sci. 7, 807 (2020).Article 

Google Scholar  More

Figure 4 illustrates the length of fertile internodes 20–40 within the various treatments of: FC, FN, F45, T45, N45, and B90. The FC, FN, and F45 treatments grew lengthier internodes from node 20–40 than the T45, N45, and B45 treatments (Fig. 4). Internode width, however, was greater in T45, N45, and B90 as compared to the undisturbed FC, FN, and F45 treatments (Table 1). The T45 and N45 treatments had a 27.9% and 26.6% reduction in internode elongation compared to the FC, FN, and F45 treatments. Of the treatments, B90 had the shortest internodes and widest internode thickness between node 20–40 (Tables 1, 2). Due to the shorter internode lengths in the mechanically affected treatments, the density of nodes per unit area was ~ 25% greater in T45 and N45 from node 20–40 and an additional 28% shorter in B90. In other words, B90 internodes were ~ 54% shorter between nodes 20–40 as compared to the untouched treatments and had the densest node concentration (cf Fig. 4 and Table 2). Both touched and bent bines were significantly reduced in elongation (Table 1; P  12–25. Thus, amassing many fertile nodes per vertical distance within a high sidewall greenhouse (e.g. ≥ 6 m) would be one viable means to increase the yield potential of hop in controlled environment production as long as plant resources did not become limiting. What’s more the 15.25 cm rise over run staircase created by the B90 internode bending treatment would allow for approximately double the bine length from the container to the top of a high sidewall greenhouse as compared to a vertically trellised bine (an additional direct step toward increasing node quantity per unit vertical production area). Secondly, the time and resource investment in overcoming the hop cultivar specific 11–24 infertile juvenile phase adds approximately three weeks to a single hop crop cycle e.g.11,36. Thus, it would be more time and space efficient to grow fewer crop cycles per annum that contain larger amounts of fertile nodes within a cycle as compared to additional cycles that contain the unfertile juvenile phase.In conclusion, repeated touch and/or bine bending within the active elongation zone of hop bines resulted in shortened internode length with higher cone production per given area. Mechanical stimuli did not reduce cone yield or flower quality. The results demonstrate that successive local internode strain can aid the control of internode elongation. Moreover, the study provides evidence that thigmomorphogenic cues can be used as a management tool to increase bine compactness and increase node density per unit area. This finding is especially important for growth control when production space is limiting and/or of high-value (e.g. greenhouse production)1. Hence, mechanical perturbation was an effective non-chemical means to control hop internode length. Nonetheless, models aimed at predicting internode length of hop bines in response to strain should still take into account a cultivar parameter. The results are practical on a commercial scale because the methods of touch and bending used in this study are easy to apply with minimal investment in labor, have a short time interval of application (approximately 5–10 s−1 per bine per 24 h), and the application duration is relatively short ~ 30 days out of the 90–120 day crop cycle, making this a practical endeavor when one considers that high value vine crops are already repeatedly handled by humans throughout their production cycle (e.g. viticulture grape and controlled environment cucumber production). More

1.Ceballos, G. Mammal population losses and the extinction crisis. Science 296, 904–907 (2002).ADS 
CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
2.Meyer, C. F. J., Struebig, M. J. & Willig, M. R. Responses of tropical bats to habitat fragmentation, logging, and deforestation. In Bats in the Anthropocene: Conservation of Bats in a Changing World (eds Voigt, C. C. & Kingston, T.) 63–103 (Springer, 2016). https://doi.org/10.1007/978-3-319-25220-9_4.
Google Scholar 
3.Torres-Romero, E. J., Giordano, A. J., Ceballos, G. & López-Bao, J. V. Reducing the sixth mass extinction: understanding the value of human-altered landscapes to the conservation of the world’s largest terrestrial mammals. Biol. Conserv. 249, 108706 (2020).Article 

Google Scholar 
4.Mittermeier, R. A., Turner, W. R., Larsen, F. W., Brooks, T. M. & Gascon, C. Global biodiversity conservation: the critical role of hotspots BT—biodiversity hotspots: distribution and protection of conservation priority areas. In (eds Zachos, F. E. & Habel, J. C.) 3–22 (Springer, Berlin, 2011). https://doi.org/10.1007/978-3-642-20992-5_1.5.Bosso, L., Mucedda, M., Fichera, G., Kiefer, A. & Russo, D. A gap analysis for threatened bat populations on Sardinia. Hystrix Ital. J. Mammal. 27, 212–214 (2016).
Google Scholar 
6.Upham, N. S. Past and present of insular Caribbean mammals: understanding Holocene extinctions to inform modern biodiversity conservation. J. Mammal. 98, 913–917 (2017).Article 

Google Scholar 
7.Gould, W. A., Castro-Prieto, J. & Álvarez-Berríos, N. L. Climate change and biodiversity conservation in the Caribbean islands. In Encyclopedia of the World’s Biomes (eds Goldstein, M. & DellaSala, D.) 114–125 (Elsevier, 2020). https://doi.org/10.1016/B978-0-12-409548-9.12091-3.
Google Scholar 
8.Schoener, T. W., Spiller, D. A. & Losos, J. B. Variable ecological effects of hurricanes: the importance of seasonal timing for survival of lizards on Bahamian islands. Proc. Natl. Acad. Sci. 101, 177 LP – 181 (2004).ADS 
Article 
CAS 

Google Scholar 
9.Barnosky, A. D. et al. Has the Earth’s sixth mass extinction already arrived?. Nature 471, 51–57 (2011).ADS 
CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
10.Pimm, S. L. et al. The biodiversity of species and their rates of extinction, distribution, and protection. Science 344, 1246752–1246752 (2014).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
11.Turvey, S. T., Kennerley, R. J., Nuñez-Miño, J. M. & Young, R. P. The Last Survivors: current status and conservation of the non-volant land mammals of the insular Caribbean. J. Mammal. 98, 918–936 (2017).Article 

Google Scholar 
12.Andermann, T., Faurby, S., Turvey, S. T., Antonelli, A. & Silvestro, D. The past and future human impact on mammalian diversity. Sci. Adv. 6, eabb313 (2020).Article 

Google Scholar 
13.Turvey, S. T. & Crees, J. J. Extinction in the anthropocene. Curr. Biol. 29, R982–R986 (2019).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
14.Donihue, C. M. et al. Hurricane effects on neotropical lizards span geographic and phylogenetic scales. Proc. Natl. Acad. Sci. 117, 10429 LP – 10434 (2020).Article 
CAS 

Google Scholar 
15.Gannon, M. R., Kurta, A., Rodríguez-Durán, A. & Willig, M. R. Bats of Puerto Rico: An Island Focus and a Caribbean Perspective (Texas Tech University Press, 2005).
Google Scholar 
16.Miller, G. L. & Lugo, A. E. Guide to the ecological systems of Puerto Rico. IITF-GTR-35. (2009).17.Guzmán-Colón, D. K., Pidgeon, A. M., Martinuzzi, S. & Radeloff, V. C. Conservation planning for island nations: using a network analysis model to find novel opportunities for landscape connectivity in Puerto Rico. Glob. Ecol. Conserv. 23, e01075 (2020).Article 

Google Scholar 
18.Gould, W. A. et al. The Puerto Rico Gap Analysis Project Volume 1: Land Cover, Vertebrate Species Distributions, and Land Stewardship. General technical reports IITF-39 vol. 1 https://www.fs.usda.gov/treesearch/pubs/38430 (2008).19.Gould, W. A. Puerto Rico gap analysis project. GAP Anal. Bull. 16, 71–79 (2009).
Google Scholar 
20.Gould, W. A., Quiñones, M., Solorzano, M., Alcobas, W. & Alarcon, C. Protected Natural Areas of Puerto Rico. Res. Map IITF-RMAP-02. Rio Piedras, PR US Dep. Agric. For. Serv. Int. Inst. Trop. For. (2011).21.Junta de Planificación. Plan de Uso de Terrenos, Guías de Ordenación del Territorio. 220 (2015).22.Gould, W. A., Wadsworth, F. H., Quiñones, M., Fain, S. J. & Álvarez-Berríos, N. L. Land use, conservation, forestry, and agriculture in Puerto Rico. Forests 8, 242–263 (2017).Article 

Google Scholar 
23.QGIS.org. QGIS Geographic Information System (2016).24.Martinuzzi, S., Gould, W. A., González, O. M. R., Quiñones, M. & Jiménez, M. E. Urban and rural land use in Puerto Rico. Res. Map IITF-RMAP-01. Rio Piedras, PR US Dep. Agric. For. Serv. Int. Inst. Trop. For. (2008).25.Gould, W. A., Martinuzzi, S. & González, O. M. R. High and low density development in Puerto Rico. Res. Map IITF-RMAP-11. Rio Piedras, PR US Dep. Agric. For. Serv. Int. Inst. Trop. For. (2008).26.Gannon, M. R. & Willig, M. R. The effects of Hurricane Hugo on bats of the Luquillo experimental forest of Puerto Rico. Biotropica 26, 320 (1994).Article 

Google Scholar 
27.Gannon, M. R. & Willig, M. R. Long-term monitoring protocol for bats: lessons from the Luquillo Experimental Forest of Puerto Rico. For. Biodivers. North Cent. South Am. Caribbean. Res. Monit. Man Biosph. Ser. 21, 271–291 (1998).
Google Scholar 
28.Gannon, M. R. & Willig, M. R. Island in the storm: disturbance ecology of plant-visiting bats on the hurricane-prone island of Puerto Rico. In Island Bats: Evolution, Ecology, and Conservation (eds Fleming, T. H. & Racey, P.) 281–301 (University of Chicago Press, 2009).
Google Scholar 
29.Jones, K. E., Barlow, K. E., Vaughan, N., Rodríguez-Durán, A. & Gannon, M. R. Short-term impacts of extreme environmental disturbance on the bats of Puerto Rico. Anim. Conserv. 4, 59–66 (2001).Article 

Google Scholar 
30.Rodríguez-Durán, A. & Vázquez, R. The bat Artibeus jamaicensis in Puerto Rico (West Indies): seasonality of diet, activity, and effect of a hurricane. Acta Chiropterologica 3, 53–61 (2001).
Google Scholar 
31.Rodríguez-Durán, A., Nieves, N. A. & Avilés-Ruiz, Y. Hurricane-mediated extirpation of a bat from an Antillean Island. Caribb. Nat. 78, 1–7 (2020).
Google Scholar 
32.Genoways, H. H. & Baker, R. J. Stenoderma rufum. Mamm. Species https://doi.org/10.2307/3503991 (1972).Article 

Google Scholar 
33.Kwiecinski, G. G. & Coles, W. C. Presence of Stenoderma rufum beyond the Puerto Rican bank. Occas. Pap. Museum Texas Tech Univ. https://doi.org/10.5962/bhl.title.156896 (2007).Article 

Google Scholar 
34.Liu, X. et al. Litterfall production prior to and during Hurricanes Irma and Maria in four Puerto Rican forests. Forests 9, 367 (2018).Article 

Google Scholar 
35.Rodríguez-Durán, A. Stenoderma rufum. IUCN Red List Threat. Species e.T20743A22065638 https://doi.org/10.2305/IUCN.UK.2016-1.RLTS.T20743A22065638.en (2016).Article 

Google Scholar 
36.Gannon, M. R. Foraging Ecology, Reproductive Biology, and Systematics of the Red Fig-Eating Bat (Stenoderma rufum) in the Tabonuco Rain Forest of Puerto Rico (Texas Tech University, 1991).
Google Scholar 
37.Meyer, C. F. J. & Kalko, E. K. V. Assemblage-level responses of phyllostomid bats to tropical forest fragmentation: land-bridge islands as a model system. J. Biogeogr. 35, 1711–1726 (2008).Article 

Google Scholar 
38.Estrada-Villegas, S., Meyer, C. F. J. & Kalko, E. K. V. Effects of tropical forest fragmentation on aerial insectivorous bats in a land-bridge island system. Biol. Conserv. 143, 597–608 (2010).Article 

Google Scholar 
39.Feng, Y., Negrón-Juárez, R. I. & Chambers, J. Q. Remote sensing and statistical analysis of the effects of hurricane María on the forests of Puerto Rico. Remote Sens. Environ. 247, 111940 (2020).ADS 
Article 

Google Scholar 
40.Soto-Centeno, J. A. & Steadman, D. W. Fossils reject climate change as the cause of extinction of Caribbean bats. Sci. Rep. 5, 7971 (2015).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
41.Razgour, O. Beyond species distribution modeling: a landscape genetics approach to investigating range shifts under future climate change. Ecol. Inform. 30, 250–256 (2015).Article 

Google Scholar 
42.Rodríguez-Durán, A. Bat assemblages in the West Indies: the role of caves. In Island Bats: Evolution, Ecology and Conservation (eds Fleming, T. H. & Racey, P.) 265–280 (University of Chicago Press, 2009).
Google Scholar 
43.Nassar, J. M., Aguirre, L. F., Rodríguez-Herrera, B. & Medellín, R. A. Threats, status, and conservation perspectives for leaf-nosed bats. In Phyllostomid Bats: A Unique Mammalian Radiation (eds Fleming, T. H. et al.) 470 (University of Chicago Press, 2020).
Google Scholar 
44.Rodríguez-Durán, A. Nonrandom aggregations and distribution of cave-dwelling bats in Puerto Rico. J. Mammal. 79, 141–146 (1998).Article 

Google Scholar 
45.Rodríguez-Durán, A. & Padilla-Rodríguez, E. New records for the bat fauna of Mona Island, Puerto Rico, with notes on their natural history. Caribb. J. Sci. 46, 102–105 (2010).Article 

Google Scholar 
46.Rodríguez-Durán, A. & Feliciano-Robles, W. Conservation value of remnant habitat for neotropical bats on islands. Caribb. Nat. 35, 1–10 (2016).
Google Scholar 
47.Gómez-Ruiz, E. P. & Lacher, T. E. Modelling the potential geographic distribution of an endangered pollination corridor in Mexico and the United States. Divers. Distrib. 23, 67–78 (2017).Article 

Google Scholar 
48.Shah, V. B. & McRae, B. H. Circuitscape: a tool for landscape ecology. In Proceedings of the 7th Python in Science Conference, vol. 7, 62–66 (SciPy Conference California, 2008).49.McRae, B. H., Dickson, B. G., Keitt, T. H. & Shah, V. B. Using circuit theory to model connectivity in ecology, evolution, and conservation. Ecology 89, 2712–2724 (2008).PubMed 
Article 
PubMed Central 

Google Scholar 
50.Carroll, C., McRae, B. H. & Brookes, A. Use of linkage mapping and centrality analysis across habitat gradients to conserve connectivity of Gray wolf populations in Western North America. Conserv. Biol. 26, 78–87 (2012).PubMed 
Article 
PubMed Central 

Google Scholar 
51.Theobald, D. M., Reed, S. E., Fields, K. & Soulé, M. Connecting natural landscapes using a landscape permeability model to prioritize conservation activities in the United States. Conserv. Lett. 5, 123–133 (2012).Article 

Google Scholar 
52.Dutta, T., Sharma, S., McRae, B. H., Roy, P. S. & DeFries, R. Connecting the dots: mapping habitat connectivity for tigers in central India. Reg. Environ. Change 16, 53–67 (2016).Article 

Google Scholar 
53.Mallory, C. D. & Boyce, M. S. Prioritization of landscape connectivity for the conservation of Peary caribou. Ecol. Evol. 9, 2189–2205 (2019).PubMed 
PubMed Central 
Article 

Google Scholar 
54.Osipova, L. et al. Using step-selection functions to model landscape connectivity for African elephants: accounting for variability across individuals and seasons. Anim. Conserv. 22, 35–48 (2019).Article 

Google Scholar 
55.GBIF.org. GBIF Occurrence Download (2019). https://doi.org/10.15468/dl.atjvik56.Fick, S. E. & Hijmans, R. J. WorldClim 2: new 1-km spatial resolution climate surfaces for global land areas. Int. J. Climatol. 37, 4302–4315 (2017).Article 

Google Scholar 
57.Vermote, E. & NOAA CDR Program. NOAA Climate Data Record (CDR) of AVHRR Normalized Difference Vegetation Index (NDVI), Version 5 (2019). https://doi.org/10.7289/V5ZG6QH9.58.de Moraes, W. M. & Viveiros Grelle, C. E. Does environmental suitability explain the relative abundance of the tailed tailless bat, Anoura caudifer. Nat. Conserv. 10, 221–227 (2012).Article 

Google Scholar 
59.Gutiérrez, E. E., Boria, R. A. & Anderson, R. P. Can biotic interactions cause allopatry? Niche models, competition, and distributions of South American mouse opossums. Ecography 37, 741–753 (2014).Article 

Google Scholar 
60.Gutiérrez, E. E. et al. The taxonomic status of Mazama bricenii and the significance of the Táchira depression for mammalian endemism in the Cordillera de Mérida, Venezuela. PLoS ONE 10, 1–24 (2015).
Google Scholar 
61.Ancillotto, L., Mori, E., Bosso, L., Agnelli, P. & Russo, D. The Balkan long-eared bat (Plecotus kolombatovici) occurs in Italy—first confirmed record and potential distribution. Mamm. Biol. 96, 61–67 (2019).Article 

Google Scholar 
62.Alberdi, A., Aizpurua, O., Aihartza, J. & Garin, I. Unveiling the factors shaping the distribution of widely distributed alpine vertebrates, using multi-scale ecological niche modelling of the bat Plecotus macrobullaris. Front. Zool. 11, 77 (2014).PubMed 
PubMed Central 
Article 

Google Scholar 
63.Phillips, S. J., Anderson, R. P. & Schapire, R. E. Maximum entropy modeling of species geographic distributions. Ecol. Model. 190, 231–259 (2006).Article 

Google Scholar 
64.Phillips, S. J. & Dudík, M. Modeling of species distributions with Maxent: new extensions and a comprehensive evaluation. Ecography (Cop.) 31, 161–175 (2008).Article 

Google Scholar 
65.R Core Team. R: A Language and Environment for Statistical Computing (2018).66.Muscarella, R. et al. ENMeval: an R package for conducting spatially independent evaluations and estimating optimal model complexity for Maxent ecological niche models. Methods Ecol. Evol. 5, 1198–1205 (2014).Article 

Google Scholar 
67.Hirzel, A. H., Le Lay, G., Helfer, V., Randin, C. & Guisan, A. Evaluating the ability of habitat suitability models to predict species presences. Ecol. Model. 199, 142–152 (2006).Article 

Google Scholar  More