Philippa Kaur

Ceballos, G. & Ehrlich, P. R. Mammal population losses and the extinction crisis. Science 296, 904–907 (2002).ADS 
CAS 
PubMed 
Article 

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

Google Scholar 
Ripple, W. J. et al. Status and ecological effects of the world’s largest carnivores. Science 343, 1241484 (2014).PubMed 
Article 
CAS 

Google Scholar 
Carbone, C. & Gittleman, J. L. A common rule for the scaling of carnivore density. Science 295, 2273–2276 (2014).ADS 
Article 

Google Scholar 
Durant, S. M. et al. The global decline of cheetah Acinonyx jubatus and what it means for conservation. Proc. Natl. Acad. Sci. 114, 528–533 (2017).CAS 
PubMed 
Article 

Google Scholar 
Jowkar, H. et al. Acinonyx jubatus ssp. venaticus. The IUCN Red List of Threatened Species 2008: e.T220A13035342. (2008).Khalatbari, L., Yusefi, G. H., Martínez-Freiría, F., Jowkar, H. & Brito, J. C. Availability of prey and natural habitats are related with temporal dynamics in range and habitat suitability for Asiatic Cheetah. Hystrix 29, 145–151 (2018).
Google Scholar 
Asadi, H. The Environmental Limitations and Future of the Asiatic Cheetah in Iran. (1997).CACP. Annual Report. (2014).Khalatbari, L., Jowkar, H., Yusefi, G. H., Brito, J. C. & Ostrowski, S. The current status of Asiatic cheetah in Iran. Cat News 66, 10–13 (2017).
Google Scholar 
Marker, L. L. et al. Ecology of free-ranging cheetahs. in Cheetahs: Biology and Conservation (eds. Marker, L. L., Boast, L. K. & Schmidt-Kuntzel, A.) 107–119 (Elsevier, 2017). doi:https://doi.org/10.1016/B978-0-12-804088-1.00008-3Hayward, M. W., Hofmeyr, M., O’Brian, J. & Kerley, G. I. H. Prey preferences of the cheetah (Acinonyx jubatus) (Felidae: Carnivora): morphological limitations or the need to capture rapidly consumable prey before kleptoparasites arrive?. J. Zool. 270, 615–627 (2006).Article 

Google Scholar 
Mills, M. G. L., Broomhall, L. S. & Toit, J. T. Cheetah Acinonyx jubatus feeding ecology in the Kruger National Park and a comparison across African savanna habitats: is the cheetah only a successful hunter on open grassland plains?. Wildlife Biol. 10, 177–186 (2004).Article 

Google Scholar 
Wachter, B., Jauernig, O. & Breitenmoser, U. Determination of prey hair in faeces of free-ranging Namibian cheetahs with a simple method. Cat News 44, 8–9 (2006).
Google Scholar 
Marker, L. L., Muntifering, J. R., Dickman, A. J., Mills, M. G. L. & Macdonald, D. W. Quantifying prey preferences of free-ranging Namibian cheetahs. South Afr. J. Wildl. Res. 33, 43–53 (2003).
Google Scholar 
Wacher, T. et al. Sahelo-Saharan Interest Group Wildlife Surveys, Part 4: Ahaggar Mountains, Algeria (March 2005). (2005).Thuo, D. et al. An insight into the prey spectra and livestock predation by cheetahs in Kenya using faecal DNA metabarcoding. Zoology 143, 125853 (2020).PubMed 
Article 

Google Scholar 
Broekhuis, F., Thuo, D. & Hayward, M. W. Feeding ecology of cheetahs in the Maasai Mara, Kenya and the potential for intra- and interspecific competition. J. Zool. 304, 65–72 (2018).Article 

Google Scholar 
Cooper, A. B., Pettorelli, N. & Durant, S. M. Large carnivore menus: factors affecting hunting decisions by cheetahs in the Serengeti. Anim. Behav. 73, 651–659 (2007).Article 

Google Scholar 
Mills, M. G. L. Living near the edge: A review of the ecological relationships between large carnivores in the arid Kalahari. African J. Wildl. Res. 45, 127–137 (2015).Article 

Google Scholar 
Rostro-García, S., Kamler, J. F. & Hunter, L. T. B. To kill, stay or flee: The effects of lions and landscape factors on habitat and kill site selection of cheetahs in South Africa. PLoS ONE 10, e0117743 (2015).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Laurenson, M. K. Behavioural costs and constraints of lactation in free-living cheetahs. Anim. Behav. 50, 815–826 (1995).Article 

Google Scholar 
Farhadinia, M. S. & Hemami, M.-R. Prey selection by the critically endangered Asiatic cheetah in central Iran. J. Nat. Hist. 44, 1239–1249 (2010).Article 

Google Scholar 
Farhadinia, M. S. et al. Feeding ecology of the Asiatic cheetah Acinonyx jubatus venaticus in low prey habitats in northeastern Iran: Implications for effective conservation. J. Arid Environ. 87, 206–211 (2012).ADS 
Article 

Google Scholar 
Zahedian, B. & Nezami, B. Cheetah (Acinonyx jubatus venaticus) (Felidae: Carnivora) feeding ecology in Central Plateau of Iran and effects of prey poor management. J. Wildl. Biodivers. 3, 22–30 (2019).
Google Scholar 
Zamani, N. et al. Predation of montane deserts ungulates by Asiatic cheetah Acinonyx jubatus venaticus in Central Iran. Folia Zool. 66, 50–57 (2017).Article 

Google Scholar 
Monterroso, P. et al. Factors affecting the (in)accuracy of mammalian mesocarnivore scat identification in South-western Europe. J. Zool. 289, 243–250 (2013).Article 

Google Scholar 
Morin, D. J. et al. Bias in carnivore diet analysis resulting from misclassification of predator scats based on field identification. Wildl. Soc. Bull. 40, 669–677 (2016).Article 

Google Scholar 
Caro, T. M. Cheetahs of the Serengeti Plains: Group Living in an Asocial Species (University of Chicago Press, 1994).
Google Scholar 
Floyd, T. J., Mech, L. D. & Jordan, P. A. Relating wolf scat content to prey consumed. J. Wildl. Manage. 42, 528–532 (1978).Article 

Google Scholar 
Jethva, B. D. & Jhala, Y. V. Computing biomass consumption from prey occurrences in Indian wolf scats. Zoo Biol. 23, 513–520 (2004).Article 

Google Scholar 
Pompanon, F. et al. Who is eating what: diet assessment using next generation sequencing. Mol. Ecol. 21, 1931–1950 (2012).CAS 
PubMed 
Article 

Google Scholar 
Taberlet, P., Coissac, E., Pompanon, F., Brochmann, C. & Willerslev, E. Towards next-generation biodiversity assessment using DNA metabarcoding. Mol. Ecol. 21, 2045–2050 (2012).CAS 
PubMed 
Article 

Google Scholar 
Mata, V. A. et al. How much is enough? Effects of technical and biological replication on metabarcoding dietary analysis. Mol. Ecol. 28, 165–175 (2019).CAS 
PubMed 
Article 

Google Scholar 
Shehzad, W. et al. Prey preference of Snow Leopard (Panthera uncia) in South Gobi Mongolia. PLoS ONE 7, e32104 (2012).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Monterroso, P. et al. Feeding ecological knowledge: the underutilised power of faecal DNA approaches for carnivore diet analysis. Mamm. Rev. 49, 97–112 (2019).Article 

Google Scholar 
Shehzad, W. et al. Carnivore diet analysis based on next-generation sequencing: Application to the leopard cat (Prionailurus bengalensis) in Pakistan. Mol. Ecol. 21, 1951–1965 (2012).CAS 
PubMed 
Article 

Google Scholar 
Thuo, D. et al. Food from faeces: Evaluating the efficacy of scat DNA metabarcoding in dietary analyses. PLoS ONE 14, e0225805 (2019).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Araujo, M. S., Bolnick, D. I. & Layman, C. A. The ecological causes of individual specialisation. Ecol. Lett. 14, 948–958 (2011).PubMed 
Article 

Google Scholar 
Balme, G. A., Roex, N., Rogan, M. S. & Hunter, L. T. B. Ecological opportunity drives individual dietary specialization in leopards. J. Anim. Ecol. 89, 589–600 (2020).PubMed 
Article 

Google Scholar 
Bolnick, D. I. et al. The ecology of individuals: incidence and implications of individual specialization. Am. Nat. 161, 1–28 (2003).MathSciNet 
PubMed 
Article 

Google Scholar 
Harrington, L. A., Harrington, A. L., Hughes, J., Stirling, D. & Macdonald, D. W. The accuracy of scat identification in distribution surveys: American mink, Neovison vison, in the northern highlands of Scotland. Eur. J. Wildl. Res. 56, 377–384 (2010).Article 

Google Scholar 
Weiskopf, S. R., Kachel, S. M. & McCarthy, K. P. What are snow leopards really eating? Identifying bias in food-habit studies. Wildl. Soc. Bull. 40, 233–240 (2016).Article 

Google Scholar 
Durant, S. M., Caro, T. M., Collins, D. A., Alawi, R. M. & Fitzgibbon, C. D. Migration patterns of Thomson’s gazelles and cheetahs on the Serengeti Plains. Afr. J. Ecol. 26, 257–268 (1988).Article 

Google Scholar 
Lindsey, P. A. et al. Minimum prey and area requirements of the vulnerable cheetah Acinonyx jubatus: implications for reintroduction and management of the species in South Africa. Oryx 45, 587–599 (2011).Article 

Google Scholar 
Farhadinia, M. S., Akbari, H., Eslami, M. & Adibi, M. A. A review of ecology and conservation status of Asiatic cheetah in Iran. Cat News Spec. Issue 18–26 (2016).Asadi, H. Some Observation on Hunting Behaviours of the Iranian Cheetah in Captivity. (1997).Heptner, V. G. & Sludskii, A. A. Mammals ofthe Soviet Union volume II part 2 Carnivora (hyaenas and cats). (Vysshaya Shkola Publishers, 1974).Ziaie, H. A Field Guide to the Mammals of Iran. (Iran Wildlife Center, 2008).Wilson, J. W. et al. Cheetahs, Acinonyx jubatus, balance turn capacity with pace when chasing prey. Biol. Lett. 9, 20130620 (2013).PubMed 
PubMed Central 
Article 

Google Scholar 
Grohé, C., Lee, B. & Flynn, J. J. Recent inner ear specialization for high-speed hunting in cheetahs. Sci. Rep. 8, 2301 (2018).ADS 
PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Cheraghi, F. et al. Inter-dependent movements of Asiatic Cheetahs Acinonyx jubatus venaticus and a Persian Leopard Panthera pardus saxicolor in a desert environment in Iran (Mammalia: Felidae). Zool. Middle East 65, 283–292 (2019).Article 

Google Scholar 
Ghoddousi, A., Soofi, M., Hamidi, A. K. & Lumetsberger, T. Assessing the role of livestock in big cat prey choice using spatiotemporal availability patterns. PLoS ONE 11, e0153439 (2016).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Khorozyan, I., Ghoddousi, A., Soofi, M. & Waltert, M. Big cats kill more livestock when wild prey reaches a minimum threshold. Biol. Conserv. 192, 268–275 (2015).Article 

Google Scholar 
Zeder, M. A. Domestication and early agriculture in the Mediterranean Basin: Origins, diffusion, and impact. Proc. Natl. Acad. Sci. 105, 11597–11604 (2008).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Daberger, M. Systematic prioritization of livestock grazing rights buyout in the last viable population of Asiatic cheetah (Acinonyx jubatus venaticus) in Iran. (Humboldt University Berlin, 2021).Wolf, C. & Ripple, W. J. Prey depletion as a threat to the world’s large carnivores. R. Soc. Open Sci. 3, 160252 (2016).ADS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Melzheimer, J. et al. Communication hubs of an asocial cat are the source of a human—carnivore conflict and key to its solution. Proc. Natl. Acad. Sci. 117, 33325–33333 (2020).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Malakoutikhah, S., Fakheran, S., Tarkesh, M. & Senn, J. Assessing future distribution, suitability of corridors and efficiency of protected areas to conserve vulnerable ungulates under climate change. Divers. Distrib. 26, 1383–1396 (2020).Article 

Google Scholar 
Long, R. A., Donovan, T. M., Mackay, P., Zielinski, W. J. & Buzas, J. S. Comparing scat detection dogs, cameras, and hair snares for surveying carnivores. J. Wildl. Manage. 71, 2018–2025 (2007).Article 

Google Scholar 
Becker, M. S. et al. Using dogs to find cats: Detection dogs as a survey method for wide-ranging cheetah. J. Zool. 302, 184–192 (2017).Article 

Google Scholar 
Johnson, W. E. & O’Brien, S. J. Phylogenetic reconstruction of the Felidae using 16S rRNA and NADH-5 mitochondrial genes. J. Mol. Evol. 44, S98–S116 (1997).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Reese, E. M., Winters, M., Booth, R. K. & Wasser, S. K. Development of a mitochondrial DNA marker that distinguishes domestic dogs from Washington state gray wolves. Conserv. Genet. Resour. 12, 497–501 (2020).Article 

Google Scholar 
Ormerod, S. J. Applied issues with predators and predation: Editor’s introduction. J. Appl. Ecol. 39, 181–188 (2002).Article 

Google Scholar 
Boast, L. K., Good, K. & Klein, R. Translocation of problem predators: Is it an effective way to mitigate conflict between farmers and cheetahs Acinonyx jubatus in Botswana?. Oryx 50, 537–544 (2016).Article 

Google Scholar 
Darvish Sefat, A. A. Atlas of Protected Areas of Iran (University of Tehran, 2006).
Google Scholar 
Yusefi, G. H., Faizolahi, K., Darvish, J., Safi, K. & Brito, J. C. The species diversity, distribution, and conservation status of the terrestrial mammals of Iran. J. Mammal. 100, 55–71 (2019).Article 

Google Scholar 
Karami, M., Ghadirian, T. & Faizolahi, K. The Atlas of the Mammals of Iran. (Iran Department of the Environment, 2016).Abangah Consulting Engineer Company. Reconvene expanded Livestock Control Committee (LCC) in Touran and establish the LCC for Miandasht with participation of all stakeholders. (2017).Mills, M. G. L. & Hofer, H. Hyaenas. Status Survey and Conservation Action Plan. (IUCN/SSC Hyaena Specualist Group, 1998).Maudet, C., Luikart, G., Dubray, D., Von Hardenberg, A. & Taberlet, P. Low genotyping error rates in wild ungulate faeces sampled in winter. Mol. Ecol. Notes 4, 772–775 (2004).CAS 
Article 

Google Scholar 
Deagle, B. E., Kirkwood, R. & Jarman, S. N. Analysis of Australian fur seal diet by pyrosequencing prey DNA in faeces. Mol. Ecol. 18, 2022–2038 (2009).CAS 
PubMed 
Article 

Google Scholar 
Frantz, A. C. et al. Reliable microsatellite genotyping of the Eurasian badger (Meles meles) using faecal DNA. Mol. Ecol. 12, 1649–1661 (2003).CAS 
PubMed 
Article 

Google Scholar 
Boom, R. et al. Rapid and simple method for purification of nucleic acids. J. Clin. Microbiol. 28, 495–503 (1990).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Rosel, P. E. & Kocher, T. D. DNA-based identification of larval cod in stomach contents of predatory fishes. J. Exp. Mar. Bio. Ecol. 267, 75–88 (2002).Article 

Google Scholar 
Deagle, B. E. et al. Molecular scatology as a tool to study diet: analysis of prey DNA in scats from captive Steller sea lions. Mol. Ecol. 14, 1831–1842 (2005).CAS 
PubMed 
Article 

Google Scholar 
Riaz, T. et al. ecoPrimers: inference of new DNA barcode markers from whole genome sequence analysis. Nucleic Acids Res. 39, e145 (2011).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Luikart, G. et al. Multiple maternal origins and weak phylogeographic structure in domestic goats. Proc. Natl. Acad. Sci. 98, 5927–5932 (2001).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Menotti-Raymond, M. et al. A genetic linkage map of microsatellites in the domestic cat (Felis catus). Genomics 57, 9–23 (1999).CAS 
PubMed 
Article 

Google Scholar 
Charruau, P. et al. Phylogeography, genetic structure and population divergence time of cheetahs in Africa and Asia: Evidence for long-term geographic isolates. Mol. Ecol. 20, 706–724 (2011).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Driscoll, C. A., Menotti-Raymond, M., Nelson, G., Goldstein, D. & O’Brien, S. J. Genomic microsatellites as evolutionary chronometers: A test in wild cats. Genome Res. 12, 414–423 (2002).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Kotze, A., Ehlers, K., Cilliers, D. C. & Grobler, J. P. The power of resolution of microsatellite markers and assignment tests to determine the geographic origin of cheetah (Acinonyx jubatus) in Southern Africa. Mamm. Biol. 73, 457–462 (2008).Article 

Google Scholar 
Marker, L. L. et al. Molecular genetic insights on cheetah (Acinonyx jubatus) ecology and conservation in Namibia. J. Hered. 99, 2–13 (2008).CAS 
PubMed 
Article 

Google Scholar 
Taberlet, P. et al. Reliable genotyping of samples with very low DNA quantities using PCR. Nucleic Acids Res. 24, 3189–3194 (1996).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Egeter, B. et al. Challenges for assessing vertebrate diversity in turbid Saharan water-bodies using environmental DNA. Genome 61, 807–814 (2018).CAS 
PubMed 
Article 

Google Scholar 
Magoc, T. & Salzberg, S. L. FLASH: Fast length adjustment of short reads to improve genome assemblies. Bioinformatics 27, 2957–2963 (2011).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Rognes, T., Flouri, T., Nichols, B., Quince, C. & Mahé, F. VSEARCH: A versatile open source tool for metagenomics. PeerJ 4, e2584 (2016).PubMed 
PubMed Central 
Article 

Google Scholar 
Godinho, R. et al. Real-time assessment of hybridization between wolves and dogs: Combining noninvasive samples with ancestry informative markers. Mol. Ecol. Resour. 15, 317–328 (2015).CAS 
PubMed 
Article 

Google Scholar 
Valière, N. GIMLET: A computer program for analysing individual identification data. Mol. Ecol. 2, 377–379 (2002).
Google Scholar 
Wachter, B. et al. An advanced method to assess the diet of free-ranging large carnivores based on scats. PLoS ONE 7, e38066 (2012).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Breuer, T. Diet choice of large carnivores in northern Cameroon. Afr. J. Ecol. 43, 181–190 (2005).Article 

Google Scholar 
Wilson, M. F. J., O’Connell, B., Brown, C., Guinan, J. C. & Grehan, A. J. Multiscale terrain analysis of multibeam bathymetry data for habitat mapping on the continental slope. Mar. Geodesy 30, 2 (2007).Article 

Google Scholar 
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  More

Pachauri, R. K. et al. Climate change 2014: synthesis report. Contribution of Working Groups I, II and III to the fifth assessment report of the Intergovernmental Panel on Climate Change. (IPCC, 2014).Thackeray, S. J. et al. Phenological sensitivity to climate across taxa and trophic levels. Nature 535, 241–245 (2016).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Walther, G.-R. et al. Ecological responses to recent climate change. Nature 416, 389–395 (2002).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Root, T. L., MacMynowski, D. P., Mastrandrea, M. D. & Schneider, S. H. Human-modified temperatures induce species changes: Joint attribution. Proc. Natl. Acad. Sci. USA 102, 7465–7469 (2005).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Menzel, A. et al. European phenological response to climate change matches the warming pattern. Glob. Change Biol. 12, 1969–1976 (2006).ADS 
Article 

Google Scholar 
Rosenzweig, C. et al. Attributing physical and biological impacts to anthropogenic climate change. Nature 453, 353–357 (2008).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Myneni, R. B., Keeling, C. D., Tucker, C. J., Asrar, G. & Nemani, R. R. Increased plant growth in the northern high latitudes from 1981 to 1991. Nature 386, 698–702 (1997).ADS 
CAS 
Article 

Google Scholar 
Walkovszky, A. Changes in phenology of the locust tree (Robinia pseudoacacia L.) in Hungary. Int. J. Biometeorol. 41, 155–160 (1998).ADS 
Article 

Google Scholar 
Crick, H. Q. P. & Sparks, T. H. Climate change related to egg-laying trends [8]. Nature 399, 423–424 (1999).ADS 
CAS 
Article 

Google Scholar 
Both, C., Van Asch, M., Bijlsma, R. G., Van Den Burg, A. B. & Visser, M. E. Climate change and unequal phenological changes across four trophic levels: Constraints or adaptations?. J. Anim. Ecol. 78, 73–83 (2009).PubMed 
Article 

Google Scholar 
Brown, J. L., Li, S. H. & Bhagabati, N. Long-term trend toward earlier breeding in an American bird: A response to global warming?. Proc. Natl. Acad. Sci. USA. 96, 5565–5569 (1999).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Miller-Rushing, A. J., Lloyd-Evans, T. L., Primack, R. B. & Satzinger, P. Bird migration times, climate change, and changing population sizes. Glob. Chang. Biol. 14, 1959–1972 (2008).ADS 
Article 

Google Scholar 
Hughes, L. Biological consequences of global warming: Is the signal already apparent?. Trends Ecol. Evol. 15, 56–61 (2000).CAS 
PubMed 
Article 

Google Scholar 
Kudo, G., Nishikawa, Y., Kasagi, T. & Kosuge, S. Does seed production of spring ephemerals decrease when spring comes early?. Ecol. Res. 19, 255–259 (2004).Article 

Google Scholar 
Doi, H., Gordo, O. & Katano, I. Heterogeneous intra-annual climatic changes drive different phenological responses at two trophic levels. Clim. Res. 36, 181–190 (2008).Article 

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).ADS 
CAS 
PubMed 
Article 

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

Google Scholar 
Thackeray, S. J. et al. Trophic level asynchrony in rates of phenological change for marine, freshwater and terrestrial environments. Glob. Chang. Biol. 16, 3304–3313 (2010).ADS 
Article 

Google Scholar 
Visser, M. E. & Both, C. Shifts in phenology due to global climate change: The need for a yardstick. Proc. R. Soc. B Biol. Sci. 272, 2561–2569 (2005).Article 

Google Scholar 
Hegland, S. J., Nielsen, A., Lázaro, A., Bjerknes, A. L. & Totland, Ø. How does climate warming affect plant-pollinator interactions?. Ecol. Lett. 12, 184–195 (2009).PubMed 
Article 

Google Scholar 
Brown, C. J. et al. Quantitative approaches in climate change ecology. Glob. Chang. Biol. 17, 3697–3713 (2011).ADS 
PubMed Central 
Article 

Google Scholar 
Parmesan, C., Duarte, C., Poloczanska, E., Richardson, A. J. & Singer, M. C. Overstretching attribution. Nat. Clim. Chang. 1, 2–4 (2011).ADS 
Article 

Google Scholar 
Damos, P. & Savopoulou-Soultani, M. Temperature-driven models for insect development and vital thermal requirements. Psyche (London) 2012, (2012).Osawa, T. et al. Climate-mediated population dynamics enhance distribution range expansion in a rice pest insect. Basic Appl. Ecol. 30, 41–51 (2018).Article 

Google Scholar 
Kiritani, K. Predicting impacts of global warming on population dynamics and distribution of arthropods in Japan. Popul. Ecol. 48, 5–12 (2006).Article 

Google Scholar 
Ozawa, A., Uchiyama, T. & Kasai, A. Estimating the day on which the numbers of adult tea spiny whiteflies (Aleurocanthus camelliae Kanmiya and Kasai) peaked and the number of generations produced in a year based on the effective cumulative temperature in tea fields. Annu. Rep. Kansai Plant Prot. Soc. 58, 57–64 (2016) (in Japanese).Article 

Google Scholar 
Ozawa, A., Saito, T. & Ikeda, F. Effect of host plant and temperature on reproduction of American Serpentine Leafminer, Liriomyza trifolii (Burgess). Japan. J. Appl. Entomol. Zool. 43, 41–48 (1999) (in Japanese).Article 

Google Scholar 
Baier, P., Pennerstorfer, J. & Schopf, A. PHENIPS—A comprehensive phenology model of Ips typographus (L.) (Col., Scolytinae) as a tool for hazard rating of bark beetle infestation. For. Ecol. Manage. 249, 171–186 (2007).Article 

Google Scholar 
Karuppaiah, V. & Sujayanad, G. K. Impact of climate change on population dynamics of insect pests. (2012).Lipper, L. et al. Climate-smart agriculture for food security. Nat. Clim. Chang. 4, 1068–1072 (2014).ADS 
Article 

Google Scholar 
Campbell, B. M. et al. Reducing risks to food security from climate change. Glob. Food Sec. 11, 34–43 (2016).Article 

Google Scholar 
Kiritani, K. The low development threshold temperature and the thermal constant in insects and mites in Japan (2nd edition). Bull. Nationai Instirute Agro-Environmental Sci. 31, 1–74 (2012) (in Japanese).
Google Scholar 
Nagasawa, A., Takahashi, A. & Higuchi, H. Host plant use for oviposition by Trigonotylus caelestialium (Hemiptera: Miridae) and Stenotus rubrovittatus (Hemiptera: Miridae). Appl. Entomol. Zool. 47, 331–339 (2012).Article 

Google Scholar 
Higuchi, H. Ecology and management of rice bugs causing pecky rice. Japan. J. Appl. Entomol. Zool. 54, 171–188 (2010) (in Japanese).Article 

Google Scholar 
Ohtomo, R. Occurrence and control of Stenotus rubrovittatus (Hemiptera: Miridae) in Touhoku area in Japan. Japan. J. Appl. Entomol. Zool. 57, 137–149 (2013) (in Japanese).Article 

Google Scholar 
Kiritani, K. The impact of global warming and land-use change on the pest status of rice and fruit bugs (Heteroptera) in Japan. Glob. Chang. Biol. 13, 1586–1595 (2007).ADS 
Article 

Google Scholar 
Nagasawa, A. & Higuchi, H. Suitability of poaceous plants for nymphal growth of the pecky rice bugs Trigonotylus caelestialium and Stenotus rubrovittatus (Hemiptera: Miridae) in Niigata, Japan. Appl. Entomol. Zool. 47, 421–427 (2012).Article 

Google Scholar 
Gordo, O. & Sanz, J. J. Temporal trends in phenology of the honey bee Apis mellifera (L.) and the small white Pieris rapae (L.) in the Iberian Peninsula (1952–2004). Ecol. Entomol. 31, 261–268 (2006).Article 

Google Scholar 
Sparks, T. H. & Yates, T. J. The effect of spring temperature on the appearance dates of British butterflies 1883–1993. Ecography (Cop.) 20, 368–374 (1997).Article 

Google Scholar 
Stefanescu, C., Penuelas, J. & Filella, I. Effects of climatic change on the phenology of butterflies in the northwest Mediterranean Basin. Glob. Chang. Biol. 9, 1494–1506 (2003).ADS 
Article 

Google Scholar 
Dell, D., Sparks, T. H. & Dennis, R. L. H. Climate change and the effect of increasing spring temperatures on emergence dates of the butterfly Apatura iris (Lepidoptera: Nymphalidae). Eur. J. Entomol. 102, 161–167 (2005).Article 

Google Scholar 
Tabuchi, K. et al. Rice bugs in the Tohoku Region: Their occurrence and damage from 2003 to 2013. Bull. Natl. Agric. Res. Cent. Tohoku Reg. 117, 63–115 (2015) (in Japanese).
Google Scholar 
Jolly, W. M. & Running, S. W. Effects of precipitation and soil water potential on drought deciduous phenology in the Kalahari. Glob. Chang. Biol. 10, 303–308 (2004).ADS 
Article 

Google Scholar 
Kriticos, D. J. et al. CliMond: Global high-resolution historical and future scenario climate surfaces for bioclimatic modelling. Methods Ecol. Evol. 3, 53–64 (2012).Article 

Google Scholar 
Takeda, A. & Shimizu, K. Characteristics of the damaged grain caused by the sorghum plant bug, Stenotus rubrovittatus (Hemiptera: Miridae) at different infection periods. Annu. Rep. Kanto-Tosan Plant Prot. Soc. 2009, 85–87 (2009) (in Japanese).
Google Scholar 
Ishimoto, M. Seasonal Prevalence of Occurrence of the Rice Leaf Bug, Trigonotylus caelestialium (Kirkaldy) (Heteroptera: Miridae) on Paddy Rice Plants. Jpn. J. Appl. Entomol. Zool. 48, 79–85 (2004) (in Japanese).
Katase, M., Shimizu, K., Siina, S., Hagiwara, K. & Iwai, H. Seasonal occurrence of rice bugs in the northern part of Chiba Prefecture. Annu. Rep. Kanto-Tosan Plant Prot. Soc. 2007, 99–104 (2007) (in Japanese).
Google Scholar 
Shintani, Y. Effect of seasonal variation in host–plant quality on the rice leaf bug, Trigonotylus caelestialium. Entomol. Exp. Appl. 133, 128–135 (2009).Article 

Google Scholar 
Takada, M. B., Yoshioka, A., Takagi, S., Iwabuchi, S. & Washitani, I. Multiple spatial scale factors affecting mirid bug abundance and damage level in organic rice paddies. Biol. Control 60, 169–174 (2012).Article 

Google Scholar 
Yoshioka, A., Takada, M. B. & Washitani, I. Landscape effects of a non-native grass facilitate source populations of a native generalist bug, Stenotus rubrovittatus, in a heterogeneous agricultural landscape. J. Insect Sci. 14, 1–14 (2014).Article 

Google Scholar 
Watanabe, T. & Higuchi, H. Recent occurrence and problem of rice bugs. Plant Prot. 60, 201–203 (2006) (in Japanese).
Google Scholar 
Seino, H. An estimation of distribution of meteorological elements using GIS and AMeDAS data. J. Agric. Meteorol. 48, 379–383 (1993) (in Japanese).Article 

Google Scholar 
Ishigooka, Y., Tsuneo, K., Nishimori, M., Hasegawa, T. & Ohno, H. Spatial characterization of recent hot summers in Japan with agro-climatic indices related to rice production. J. Agric. Meteorol. 67, 209–224 (2011).Article 

Google Scholar 
Yamasaki, K. et al. Intraspecific variations in life history traits of two pecky rice bug species from Japan: Mapping emergence dates and number of annual generations. Ecol. Evol. (2021).Sakagami, Y. & Korenaga, R. Triangle method—A simple method for the estimation of total effective temperature. Japan. J. Appl. Entomol. Zool. 25, 52–54 (1981) (in Japanese).Article 

Google Scholar 
Shigehisa, S. Seasonal changes in egg diapause induction and effects of photoperiod and temperature on egg diapause in the sorghum plant bug, Stenotus rubrovittatus (Matsumura) (Heteroptera: Miridae). Japan. J. Appl. Entomol. Zool. 52, 229–232 (2008) (in Japanese).Article 

Google Scholar 
Ishimoto, M. Oviposition of sorghum plant bug, Stenotus rubrovittatus (Matsumura) (Heteroptera: Miridae) on rice plants. Japan. J. Appl. Entomol. Zool. 55, 193–197 (2011) (in Japanese).Article 

Google Scholar 
Ogata, M. et al. Fecundity and longevity in adults of the sorghum plant bug, Stenotus rubrovittatus (Matsumura) (Heteroptera: Miridae) under laboratory conditions. Japan. J. Entomol. 13, 129–132 (2010) (in Japanese).
Google Scholar 
Niiyama, T. & Iitomi, A. Optimal control timing of the rice leaf bug, Trigonotylus caelestialium (Heteroptera: Miridae). Annu. Rep. Soc. Plant Prot. North Japan. (in Japanese) (2003).Takeda, A., Shimizu, K., Shiina, S., Hagiwara, K. & Katase, M. Seasonal prevalence of Stenotus rubrovittatus (Hemiptera: Miridae) in a gramineous weed field and a rice field. Annu. Rep. Kanto-Tosan Plant Prot. Soc. 2008, 97–102 (2008) (in Japanese).
Google Scholar 
Niiyama, T. Studies on the ecology of Trigonotylus caelestialium and establishment of pesticide control techniques. Annu. Rep. Akita Prefect. Agric. Inst. 49, 147–180 (2009) (in Japanese).
Google Scholar 
Sato, M. Latest infestation period of Miridae causing pecky rice damage in Aomori Prefecture. Annu. Rep. Soc. Plant Prot. North Japan 2014, 129–134 (2014) (in Japanese).
Google Scholar 
Johnson, J. B. & Omland, K. S. Model selection in ecology and evolution. Trends Ecol. Evol. 19, 101–108 (2004).PubMed 
Article 

Google Scholar 
Kuznetsova, A., Brockhoff, P. B. & Christensen, R. H. B. lmerTest package: tests in linear mixed effects models. J. Stat. Softw. 82, 1–26 (2017).Article 

Google Scholar  More

Model descriptionThe system dynamics model divided an urban dog population into the following subpopulations: (i) free-roaming dogs (both owned and unowned free-roaming, i.e. unrestricted dogs found on streets), (ii) shelter dogs (unowned restricted dogs living in shelters), and (iii) owned dogs (owned home-dwelling restricted dogs) (Fig. 1). The subpopulations change in size by individuals flowing between the different subpopulations or from flows extrinsically modelled (i.e. flows from subpopulations not included in the systems model; the acquisition of dogs from breeders and friends to the owned dog population, and the immigration/emigration of dogs from other neighbourhoods).Ordinary differential equations were used to describe the dog population dynamics. The models were written in R version 3.6.128, and numerically solved using the Runge–Kutta fourth order integration scheme with a 0.01 step sizes using the package “deSolve”29,30. For the baseline model, Eqs. (1–3) were used to describe the rates of change of dog subpopulations in the absence of management.Baseline free-roaming dog population (S):$$frac{dS}{dt}={r}_{s}times Stimes left(1-frac{S}{{K}_{s}}right)+alpha times O-delta times S$$
(1)
In the baseline model, the free-roaming dog population (Eq. 1) increases through the free-roaming dog intrinsic growth rate (rs), and the abandonment and roaming of dogs from the owned dog population (α) and decreases through adoption to the owned dog population (δ). The intrinsic growth rate is the sum of the effects of births, deaths, immigration, and emigration, which are not modelled separately. In this model, the growth rate of the free-roaming dog population is reduced depending on the population size in relation to the carrying capacity, through the logistic equation (rreal = rmax(1 − S/Ks))31. In the baseline simulation, the free-roaming dog population rises over time, until it stabilises at an equilibrium size.Baseline shelter dog population (H):$$frac{dH}{dt}=gamma times O-beta times H- {mu }_{h}times H$$
(2)
The shelter dog population (Eq. 2) increases through relinquishment of owned dogs (γ) and decreases through the adoption of shelter dogs to the owned dog population (β), and through the shelter dog death rate (µh). There is no carrying capacity for the shelter dog population as we assumed that more housing would be created as the population increases. This allowed calculation of the resources required to house shelter dogs.Baseline owned dog population (O),$$frac{dO}{dt}={r}_{o} times Otimes (1-frac{O}{{K}_{o}})+beta times H+delta times S-alpha times O-gamma times O$$
(3)
The owned dog population (Eq. 3) increases through the owned dog growth rate (ro), adoption of shelter dogs (β), and adoption of free-roaming dogs (δ); and decreases through abandonment/roaming (α) and relinquishment (γ) of owned dogs to the shelter dog population. The growth rate of the owned dog population (ro) combines the birth, death, and acquisition rates from sources other than the street or shelters (e.g. breeders, friends) and was modelled as density dependent by the limit to growth logistic formula (1 − O/Ko).Parameter estimatesDetailed descriptions of parameter estimates are provided in the supplementary information. The simulated environment was based on the city of Lviv, Ukraine. This city has an area of 182 km2 and a human population size of 717,803. Parameters were estimated from literature, where possible, and converted to monthly rates (Table 1). Initial sizes of the dog populations were estimated for the baseline simulation, based on our previous research in Lviv32. The carrying capacity depends on the availability of resources (i.e. food, shelter, water, and human attitudes and behaviour33) and is challenging to estimate. We assumed the initial free-roaming and owned dog populations were at carrying capacity. Initial population sizes for simulations including interventions were determined by the equilibrium population sizes from the baseline simulation (i.e. the stable population size, the points at which the populations were no longer increasing/decreasing).Table 1 Parameter description, parameter value, and minimum and maximum values used in the sensitivity analysis for the systems model.Full size tableEstimating the rate at which owned dogs are abandoned is difficult, as abandonment rates are often reported per dog-owning lifetime32,34 and owners are likely to under-report abandonment of dogs. Similarly, it is challenging to estimate the rate that owned dogs move from restricted to unrestricted (i.e. free-roaming). For simplicity, we modelled a combined abandonment/roaming rate (α) of 0.003 per month, estimated based on our previous research in Lviv and from literature34,35,36. We derive the owned dog relinquishment rate (γ) from New et al.37. We estimated shelter (β) and free-roaming adoption rates (δ) from shelter data in Lviv. We set the maximum intrinsic growth rate for the free-roaming dogs (rs) at 0.03 per month, similar to that reported in literature17,19,38. We assumed that demand for dogs was met quickly through a supply of dogs from births, breeders and friends and set a higher growth rate for the owned dog population (ro) at 0.07 per month.We assumed shelters operated with a “no-kill” policy (i.e. dogs were not killed in shelters as part of population management) and included a shelter dog death rate (µh) of 0.008 per month to incorporate deaths due to euthanasia for behavioural problems or health problems, or natural mortality. We modelled neutered free-roaming dog death rate (µn) explicitly for the CNR intervention at a minimum death rate of 0.02 per month38,39,40,41.InterventionsSix intervention scenarios were modelled (Table 2): sheltering; culling; CNR; responsible ownership; combined CNR and responsible ownership; and combined CNR and sheltering, representing interventions feasibly applied and often reported27. Table 2 outlines the equations describing each intervention. To simulate a sheltering intervention, a proportion of the free-roaming dog population was removed and added to the shelter dog population at sheltering rate (σ). In culling interventions, a proportion of the free-roaming dog population was removed through culling (χ).Table 2 Description of intervention parameters and coverages for simulations applied at continuous and annual periodicities.Full size tableFree-roaming dog population with sheltering intervention:$$frac{dS}{dt}={r}_{s}times Stimes left(1-frac{S}{{K}_{s}}right)+alpha times O-delta times S-sigma times S$$
(4)
Shelter dog population with sheltering intervention:$$frac{dH}{dt}=gamma times O-beta times H- {mu }_{h}times H+sigma times S$$
(5)
Free-roaming dog population with a culling intervention:$$frac{dS}{dt}={r}_{s}times Stimes left(1-frac{S}{{K}_{s}}right)+alpha times O-delta times S-chi times S$$
(6)
To simulate a CNR intervention, an additional subpopulation was added to the system (Eq. 7): (iv) the neutered free-roaming dog population (N; neutered, free-roaming). In this simulation, a proportion of the intact (I) free-roaming dog population was removed and added to the neutered free-roaming dog population. A neutering rate (φ) was added to the differential equations describing the intact free-roaming and the neutered free-roaming dog populations. Neutering was assumed to be lifelong (e.g. gonadectomy); a neutered free-roaming dog could not re-enter the intact free-roaming dog subpopulation. Neutered free-roaming dogs were removed from the population through the density dependent neutered dog death rate (µn); death rate increased when the population was closer to the carrying capacity. The death rate was a non-linear function of population size and carrying capacity modelled using a table lookup function (Fig. S1). Neutered free-roaming dogs were also removed through adoption to the owned dog population, and we assumed that adoption rates did not vary between neutered and intact free-roaming dogs.Neutered free-roaming dog population:$$frac{dN}{dt}=varphi times I-{mu }_{n}times N-delta times N$$
(7)
Intact free-roaming dog population with neutering intervention.$$frac{dI}{dt}={r}_{s}times Itimes left(1-frac{(I+N)}{{K}_{s}}right)+alpha times O-delta times I-varphi times I$$
(8)
To simulate a responsible ownership intervention, the baseline model was applied with decreased rate of abandonment/roaming (α) and increased rate of shelter adoption (β). To simulate combined CNR and responsible ownership, a proportion of the intact free-roaming dog population was removed through the neutering rate (φ), abandonments/roaming decreased (α) and shelter adoptions increased (β). In combined CNR and sheltering interventions, a proportion of the intact free-roaming dog population (I) was removed through neutering (φ) and added to the neutered free-roaming dog population (N), and a proportion was removed through sheltering (σ) and added to the shelter dog population (H).Intact free-roaming dog population with combined CNR and sheltering interventions:$$frac{dI}{dt}={r}_{s}times Stimes left(1-frac{(I+N)}{{K}_{s}}right)+alpha times O-delta times I-varphi times I- sigma times I$$
(9)
Intervention length, periodicity, and coverageAll simulations were run for 70 years to allow populations to reach equilibrium. It is important to note that this is a theoretical model; running the simulations for 70 years allows us to compare the interventions, but does not accurately predict the size of the dog subpopulations over this long time period. Interventions were applied for two lengths of time: (i) the full 70-year duration of the simulation; and (ii) a five-year period followed by no further intervention, to simulate a single period of investment in population management. In each of these simulations, we modelled the interventions as (i) continuous (i.e. a constant rate of e.g. neutering) and (ii) annual (i.e. intervention applied once per year). Interventions were run at low, medium, and high coverages (Table 2). As the processes are not equivalent, we apply different percentages for the intervention coverage (culling/neutering/sheltering) and the percent increase/decrease in parameter rates for the responsible ownership intervention. Intervention coverage refers to the proportion of dogs that are culled/neutered/sheltered per year (i.e. 20%, 40% and 70% annually) and, for responsible ownership interventions, the decrease in abandonment/roaming rate and increase in the adoption rate of shelter dogs (30%, 60% and 90% increase/decrease from baseline values). To model a low (20%), medium (40%) and high (70%) proportion of free-roaming dogs caught, but where half of the dogs were sheltered and half were neutered-and-returned, combined CNR and sheltering interventions were simulated at half-coverage (e.g. intervention rate of 0.7 was simulated by 0.35 neutered and 0.35 sheltered). For continuous interventions, sheltering (σ), culling (χ), and CNR (φ) were applied continuously during the length of the intervention. For annual interventions, σ, χ, and φ were applied to the ordinary differential equations using a forcing function applied at 12-month intervals. In simulations that included responsible ownership interventions, the decrease in owned dog abandonment/roaming (α) and the increase in shelter adoption (β) was assumed instantaneous and continuous (i.e. rates did not change throughout the intervention).Model outputsThe primary outcome of interest was the impact of interventions on free-roaming dog population size. For interventions applied for the duration of the simulation, we calculated: (i) equilibrium population size for each population; (ii) percent decrease in free-roaming dog population; (iii) costs of intervention in terms of staff-time; and (iv) an overall welfare score. For interventions applied for a five-year period, we also calculated: (v) minimum free-roaming dog population size and percent reduction from initial population size; and (vi) the length of time between the end of the intervention and time-point at which the free-roaming dog population reached above 20,000 dogs (the assumed initial free-roaming dog population size of Lviv, based on our previous research32, see Supplementary Information for detail).The costs of population management interventions vary by country (e.g. staff salaries vary between countries) and by the method of application (e.g. method of culling, or resources provided in a shelter). To enable a comparison of the resources required for each intervention, the staff time (staff working-months) required to achieve the intervention coverage was calculated. While this does not incorporate the full costs of an intervention, as equipment (e.g. surgical equipment), advertising campaigns, travel costs for the animal care team, and facilities (e.g. clinic or shelter costs) are not included, it can be used as a proxy for intervention cost. Using data provided from VIER PFOTEN International, we estimated the average number of staff required to catch and neuter the free-roaming dog population and to house the shelter dog population in each intervention, using this data as a proxy for catching and sheltering/culling. The number of dogs that can be cared for per shelter staff varies by shelter. To account for this, we estimated two staff-to-dog ratios (low and high). Table 3 describes the staff requirements for the different interventions.Table 3 Staff required for interventions and the number of dogs processed per staff per day.Full size tableUsing the projected population sizes, the staff time required for each staff type (e.g. number of veterinarian-months of work required) was calculated for each intervention. Relative salaries for the different staff types were estimated (Table 3). The relative salaries were used to calculate the cost of the interventions by:[Staff time required × relative salary ] × €20,000.Where €20,000 was the estimated annual salary of a European veterinarian, allowing relative staff-time costs to be compared between the different interventions. Average annual costs were reported.To provide overall welfare scores for each of the interventions, we apply the estimated welfare scores on a one to five scale, for each of the dog subpopulations, as determined by Hogasen et al. (2013)22. This scale is based on the Five Freedoms (freedom from hunger and thirst; freedom from discomfort; freedom from pain, injury, or disease; freedom to express normal behaviour; freedom from fear and distress42,43) and was calculated using expert opinions from 60 veterinarians in Italy22. The scores were weighted by the participants’ self-reported knowledge of different dog subpopulations, which resulted in the following scores: 2.8 for shelter dogs (WH); 3.5 for owned dogs (WO); 3.1 for neutered free-roaming dogs (WN); and 2.3 for intact free-roaming dogs (WI)22.Using these estimated welfare scores, we calculated an average welfare score for the total dog population based on the model’s projected population sizes for each subpopulation (Eq. 10). For interventions running for the duration of the simulation, the welfare score was calculated at the time point (t) when the population reached an equilibrium size. For interventions running for five years, the welfare score was calculated at the end of the five-year intervention. The percentage change in welfare scores from the baseline simulation were reported.$$Welfare score= frac{{H}_{t}times {W}_{H}+{O}_{t}times {W}_{O}+{N}_{t}times {W}_{N}+{I}_{t}times {W}_{I}}{{H}_{t}+{O}_{t}+{N}_{t}+{I}_{t}}$$
(10)
Model validation and sensitivity analysisA global sensitivity analysis was conducted on all parameters described in the baseline simulation and all interventions applied continuously, at high coverage, for the full duration of the simulation. A Latin square design algorithm was used in package “FME”44 to sample the parameters within their range of values (Table 1). For the global sensitivity analysis on interventions, all parameter values were varied, apart from the parameters involved in the intervention (e.g. culling, neutering, abandonment/roaming rates). The effects of altering individual parameters (local sensitivity analysis) on the population equilibrium was also examined for the baseline simulation using the Latin square design algorithm to sample each parameter, individually, within their range of values. Sensitivity analyses were run for 100 simulations over 50 years solved with 0.01 step sizes. More

Lehtonen12 presents three simple models with the same broad structure: a single mutant individual with divergent mating behaviour arises in a population of ‘residents’ that all play the same strategy, and the success of that mutant is then followed (Figs. 1, 2). Specifically, Lehtonen investigates the fitness benefits of increased mating for mutant males in comparison to mutant females. Two important parameters can be varied: (i) the degree of anisogamy (defined here as the ratio of sperm number to egg number), which captures how divergent males and females are in the size (and thus number) of gametes they produce, and (ii) the efficiency of fertilisation, which determines how easily gametes can find and fuse with each other. If fertilisation is highly efficient, then gametes of the less numerous type will achieve nearly full fertilisation; on the other hand, inefficient fertilisation can result in gametes of both sexes going unfertilised.Fig. 2: Structure of the three models of Lehtonen12, showing differences in mating behaviour between resident males (green), resident females (blue) and mutant males and females (both yellow).For illustration, we suppose that females produce four eggs each and males produce eight sperm (the anisogamy ratio in nature is typically much higher). In Model 1, resident individuals spawn monogamously in a ‘nest’ (black outline), whereas mutant males and females can bring additional partners to their nest to spawn in a group. In Model 2, resident individuals divide their gametes equally among m spawning groups, each consisting of m individuals of each sex (shown here with m = 2). Mutant males and females instead divide their gametes among a larger or smaller number of groups, mmutant (shown here with mmutant = 4). In Model 3, there is a further sex asymmetry in addition to anisogamy: Fertilisation takes place inside the female’s body. Resident individuals mate with m partners (shown here with m = 2), whereas mutant males and females mate with a larger or smaller number of partners, mmutant (shown here with mmutant = 4).Full size imageIn the first two models, fertilisation is external and no assumptions are made about pre-existing differences between the sexes apart from the number of gametes they produce. In other words, males and females are identical except that males produce sperm in greater numbers than females produce eggs. In Model 1, resident individuals are assumed to mate monogamously, whereas a mutant can monopolise multiple partners of the opposite sex (Fig. 2). Importantly, both male and female mutants can bring additional partners back to their ‘nest’ to spawn in a group. When fertilisation is highly efficient, females can fertilise all of their eggs by bringing back a single male, and there is simply no benefit (in this model) of seeking further partners (Fig. 1A). In contrast, anisogamy means that males always produce at least some gametes in excess, and thus can benefit from seeking additional mates. When fertilisation is inefficient, however, both sexes benefit from increasing the concentration of opposite-sex gametes at their ‘nest’ (Fig. 1B). This latter benefit is sex-symmetric, whereas the former continues to apply only to males. As a consequence, the Bateman gradients are always steeper for males than for females (Fig. 1A, B), confirming Bateman’s argument.Model 2 similarly assumes external fertilisation, but in this case the resident males and females meet in groups consisting of m individuals of each sex (Fig. 2). Fertilisation occurs via group spawning. It is assumed that each resident individual divides its gametes evenly across M groups, whereas mutant individuals can instead spread their gametes over a larger or smaller number of groups (note that the author assumes that M = m, but this assumption could be relaxed without undermining the core argument). Spreading gametes out across a larger number of spawning groups does not increase the concentration of opposite-sex gametes they encounter (Fig. 2). However, a mutant that spreads its gametes more widely reduces the density of its own gametes across those groups in which it spawns. This in turn results in there being more opposite-sex gametes for each gamete of the mutant’s sex in those groups. For example, in Fig. 2, mutant males spawn in twice as many groups as resident males and thereby halve the density of their own sperm in each group. The resulting egg-to-sperm ratio of (frac{4}{6}=frac{2}{3}) is more favourable than the ratio of (frac{4}{8}=frac{1}{2}) that the resident males experience. Mutant females can similarly increase local sperm-to-egg ratios by spreading their eggs over more groups. However, in contrast to males, this only leads to fitness benefit if fertilisation is inefficient, and even then the benefit to females is very modest (scarcely perceptible in Fig. 1D). Gamete spreading reduces wasteful competition among the mutants’ own gametes for fertilisation. Such ‘local’ gamete competition, like gamete competition more generally, is stronger among sperm than among eggs because sperm are more numerous under anisogamy13,14. Consequently, as in Model 1, Bateman gradients are always steeper in males (Fig. 1C, D). Recall that the results of the above models emerge in the absence of any assumptions beyond the sex difference in the number of gametes produced.The third and final model allows for a further pre-existing difference between the sexes in addition to anisogamy: internal fertilisation, which is common and widespread in animals (Fig. 2)15. Each female is assumed to mate with m males, while each male divides his gametes evenly among m females. As in the previous two models, males benefit more than females from additional matings under most conditions. However, in the particular case where fertilisation is highly inefficient and the ratio of sperm to eggs is not too large, the pattern can theoretically reverse, such that female Bateman gradients exceed their male counterparts (Fig. 1F). The reason is that the effects of gamete concentration are asymmetric under internal fertilisation: Multiple mating by a female increases the local concentration of sperm its eggs experience, whereas a male’s multiple mating does not increase the concentration of eggs around its sperm (Fig. 2). Under conditions of severe sperm limitation—due to both weak anisogamy and highly inefficient fertilisation—this can lead to females benefitting more from additional matings than males (Fig. 1F). Although intriguing, it is unclear whether this finding has any empirical relevance, as sperm limitation is probably rarely severe in internal fertilisers. Under more realistic conditions of moderate to high fertilisation rates, sex differences in the degree of local gamete competition once again become decisive, and male Bateman gradients exceed their female counterparts (Fig. 1E). More

Contents of Cd and Ca in Panax notogensing rootsThe Ca content of P. notoginseng roots increased significantly with the increase of lime application rates under the same concentration of oxalic acid sprayed on leaves (Table 2). Compared with no lime application, the Ca content was the highest increased by 212% under 3750 kg hm−2 lime without spraying oxalic acid. The content of Ca slightly increased with the increase of oxalic acid spraying concentrations under the same rate of lime application.Table 2 Effects of foliar spraying of oxalic acid on contents of Cd and Ca in roots of Panax notoginseng under Cd stress.Full size tableThe contents of Cd in roots ranged from 0.22 to 0.70 mg kg−1. The content of 2250 kg hm−2 Cd decreased greatly with the increase of lime application rates under the same spraying concentration of oxalic acid. Compared with the control, the root Cd contents decreased by 68.57% under the application of 2250 kg hm−2 lime and 0.1 mol L−1 oxalic acid spraying. The Cd contents of P. notoginseng roots decreased significantly with the increase of oxalic acid spraying concentrations under application of non-lime and 750 kg hm−2 lime. The root Cd contents decreased at first and then increased with the increase of oxalic acid concentrations under the application of 2250 kg hm−2 lime and 3750 kg hm−2 lime. In addition, the Bivariate analysis showed that the Ca content of P. notoginseng roots was significantly affected by lime (F = 82.84**), and the Cd content of P. notoginseng roots was significantly affected by lime (F = 74.99**) and oxalic acid (F = 7.72*).MDA contents and relative antioxidase activitiesThe content of MDA decreased greatly with the increase of the rates of lime application and oxalic acid spraying concentrations. There was no significant difference in the content of MDA in the roots of P. notoginseng with non-lime and 3750 kg hm−2 lime application. Under 750 kg hm−2, 2250 kg hm−2 lime application, the MDA content with 0.2 mol L−1 oxalic acid spraying concentration treatment decreased by 58.38% and 40.21% comparing with non-oxalic acid spraying application, respectively. The content of MDA (7.57 nmol g−1) was the lowest under 750 kg hm−2 lime application and 0.2 mol L−1 oxalic acid spraying treatment (Fig. 1).Figure 1Effects of foliar spraying of oxalic acid on contents of malondialdehyde in roots of Panax notoginseng under Cd stress. Notes The figure legend showed the spray concentration of oxalic acid (mol L−1), different lowercase letters indicate significant differences between treatments at the same lime application rate (P  Rb1  > R1. The contents of the three saponins had no significant difference with increase of the concentrations of oxalic acid spraying and no application of lime (Table 4).Table 4 Effects of foliar oxalate application on the percentages of three saponins in roots of Panax notoginseng under Cd stress.Full size tableThe contents of R1 with 0.2 mol L−1 oxalic acid spraying was significantly lower than that without oxalic acid spraying and rates of 750 or 3750 kg hm−2 lime application. Under the concentration of 0 or 0.1 mol L−1 oxalic acid spraying, there was no significant difference in contents of R1 with increase of rates of lime application. Under the concentration of 0.2 mol L−1 oxalic acid spraying, the contents of R1 with 3750 kg hm−2 lime was significantly lower 43.84% than that without lime application (Table 4).The contents of Rg1 increased at first and then decreased with the increase of oxalic acid spraying concentrations and 750 kg hm−2 lime application. Under the application rates of 2250 or 3750 kg hm−2 lime, the contents of Rg1 decreased with the increase of oxalic acid spraying concentration. With the same concentration of oxalic acid spraying, the Rg1 content increased at first and then decreased with the increase of lime application rates. Compared with the control, except that the Rg1 content with three concentrations of oxalic acid spraying and 750 kg hm−2 lime was higher than that of the control, the contents of Rg1 in the roots of P. notoginseng under other treatments was lower than that of the control. The Rg1 content was the highest with 750 kg hm−2 lime and 0.1 mol L−1 oxalic acid spraying treatment, which was higher 11.54% than that of the control (Table 4).The contents of Rb1 increased first and then decreased with the increase of oxalic acid spraying concentration and 2250 kg hm−2 lime application. The content of Rb1 with 0.1 mol L−1 oxalic acid spraying reached the maximum value of 3.46%, which was higher 74.75% than that without oxalic acid spraying treatment. Under other lime application treatments, there was no significant difference among different oxalic acid spraying concentrations. With 0.1 and 0.2 mol L−1 oxalic acid spraying treatments, the contents of Rb1 decreased at first and then decreased with the increase of lime application rates (Table 4).Contents of flavonoidsWith the same concentration of oxalic acid spraying, the content of flavonoids increased at first and then decreased with the increase of the amounts of lime application. There was no significant difference in the content of flavonoids under different concentrations of oxalic acid spraying without the application of lime or 3750 kg hm−2 lime. Under 750 and 2250 kg hm−2 lime application, the content of flavonoids increased at first and then decreased with the increase of the concentration of oxalic acid spraying. Under the treatment of 750 kg hm−2 application and 0.1 mol L−1 oxalic acid spraying, the content of flavonoids was the highest, which was 4.38 mg g−1, which was higher 18.38% than that of the same rate of lime application and without spraying oxalic acid. The content of flavonoids with 0.1 mol L−1 oxalic acid spraying treatment increased by 21.74% compared with that without oxalic acid spraying treatment and 2250 kg hm−2 lime application (Fig. 5).Figure 5Effects of foliar spraying of oxalate on the contents of flavonoids in roots of Panax notoginseng under Cd stress.Full size imageBivariate analysis showed that the content of soluble sugar in P. notoginseng root was significantly relationship with the amount of lime application and the concentration of oxalic acid spraying. The content of soluble protein in root was significantly relationship with lime application rates, both of lime and oxalic acid. The contents of free amino acid and proline in roots were significantly relationship with lime application rates, oxalic acid spraying concentrations, both of lime and oxalic acid (Table 5).Table 5 Variance analysis of the effects of oxalic acid, calcium and cadmium on the contents of multiple medicinal ingredients in the roots of Panax notoginseng (F value).Full size tableThe content of R1 in the root of P. notoginseng was significantly relationship with oxalic acid spraying concentrations, lime application rates, both of lime and oxalic acid. The content of flavonoids was significantly relationship with oxalic acid spraying concentrations, lime application rates. More

Clemens, R. et al. Oats, more than just a whole grain: an introduction. Br. J. Nutr. 112, S1–S3 (2014).CAS 
PubMed 
Article 

Google Scholar 
Stewart, D. & Mcdougal, G. Oat agriculture, cultivation and breeding targets: implications for human nutrition and health. Br. J. Nutr. 2, 50–57 (2014).Article 
CAS 

Google Scholar 
Ren, C. Z. et al. “Twelfth Five-Year” Development Report of China’s Oat and Buckwheat Industry. Xi’an: Shaanxi Science and Technology Press, 2011–2015 (2016).Gleick, P. H. & Palaniappan, M. Peak water limits to freshwater withdrawal and use. Proc. Indian Natl. Sci. Acad. 107, 11155–11162 (2010).ADS 
CAS 

Google Scholar 
Yu, L., Zhao, X., Gao, X. & Siddique, K. H. M. Improving/maintaining water-use efficiency and yield of wheat by deficit irrigation: A global meta-analysis. Agric. Water Manag. 228, 105906 (2020).Article 

Google Scholar 
Bai, W., Zhang, H., Liu, B., Wu, Y. & Song, J. Effects of super-absorbent polymers on the physical and chemical properties of soil following different wetting and drying cycles. Soil Use Manag. 26, 253–260 (2010).Article 

Google Scholar 
Döll, P. Impact of climate change and variability on irrigation requirements: A global perspective. Clim. Change 54, 269–293 (2002).ADS 
Article 

Google Scholar 
Harris, F. et al. The water use of Indian diets and socio- demographic factors related to dietary blue water footprint. Sci. Total Environ. 587, 128–136 (2017).ADS 
PubMed 
Article 
CAS 

Google Scholar 
Unesco. Water and jobs: Facts and figures. Perugia, Italy: UNESCO, World Water Assessment Program. Retrieved from http://unesdoc.unesco.org/images/0024/002440/244041e.pdf (2016).Landi, A. et al. Land suitability evaluation for surface, sprinkle and drip irrigation methods in Fakkeh Plain. Iran. J. Appl. Anim. Sci. 8, 3646–3653 (2008).ADS 

Google Scholar 
Kang, S. et al. Improving agricultural water productivity to ensure food security in China under changing environment: From research to practice. Agric. Water Manag. 179, 5–17 (2017).Article 

Google Scholar 
Yang, D. et al. Effect of drip irrigation on wheat evapotranspiration, soil evaporation and transpiration in Northwest China. Agric. Water Manag. 232, 106001 (2020).Article 

Google Scholar 
Xu, S. T., Zhang, L., Neil, B. & McLaughlin, Mi. Effect of synthetic and natural water absorbing soil amendment soil physical properties under potato production in a semi-arid region. Soil Till. Res. 148, 31–39 (2015).Article 

Google Scholar 
Roper, M. M., Ward, P. R., Keulen, A. F. & Hill, J. R. Under no-tillage and stubble retention, soil water content and crop growth are poorly related to soil water repellency. Soil Till. Res. 126, 143–150 (2013).Article 

Google Scholar 
Zhao, H. et al. Ridge-furrow with full plasticfilm mulching improves water use efficiency and tuber yields of potato in a se miarid rainfed ecosystem. Field Crop Research. 161, 137–148 (2014).Article 

Google Scholar 
Li, J. et al. Effects of micro-sprinkling with different irrigation amount on grain yield and water use efficiency of winter wheat in the North China Plain. Agric. Water Manag. 224, 105736 (2019).Article 

Google Scholar 
Chouhan, S. S., Awasthi, M. K. & Nema, R. K. Studies on water productivity and yields responses of wheat based on drip irrigation systems in clay loam soil. Indian J. Sci. Technol. 8, 650 (2015).Article 

Google Scholar 
Liao, L., Zhang, L. & Bengtsson, L. Soil moisture variation and water consumption of spring wheat and their effects on crop yield under drip irrigation. Irrigat. Drainag. Syst. 22, 253–270 (2008).Article 

Google Scholar 
Jha, S. K. et al. Response of growth, yield and water use efficiency of winter wheat to different irrigation methods and scheduling in North China Plain. Agric. Water Manag. 217, 292–302 (2019).Article 

Google Scholar 
Yan, Z., Fengxin, W., Qi, Z., Kaijing, Y. & Youliang, Z. Effect of drip tape distance and irrigation amount on spring wheat yield and water use efficiency. Chin. Agric. Sci. Bull. 32, 194–199 (2016).
Google Scholar 
Chen, R. et al. Lateral spacing in drip-irrigated wheat: the effects on soil moisture, yield, and water use efficiency. Field Crop Res. 179, 52–62 (2015).Article 

Google Scholar 
Shock, C. C., Feibert, E.B.G., & Saunders, L. D. Water management for drip-irrigated spring wheat. Annual Rep. Med. Chem.. 2007 (2005).Bhardwaj, A. K., Shainberg, I., Goldstein, D., Warrington, D. N. & Levy, G. J. Water retention and hydraulic conductivity of cross-linked polyacrylamides in sandy soils. Soil Sci. Soc. Am. J. 71, 406–412 (2007).ADS 
CAS 
Article 

Google Scholar 
Demitri, C., Scalera, F., Madaghiele, M., Sannino, A. & Maffezzoli, A. Potential of cellulose-based superabsorbent hydrogels as water reservoir in agriculture. Int. J. Polym. Sci. 2013, 1–6 (2013).Article 
CAS 

Google Scholar 
Islam, M. R. et al. Effectiveness of a water-saving super-absorbent polymer in soil water conservation for corn (Zea mays L.) based on eco- physiological parameters. J. Agric. Food Sci. 91, 1998–2005 (2011).CAS 
Article 

Google Scholar 
Nazarli, H., Zardashti, M. R., Darvishzadeh, R. & Najafi, S. The effect of water stress and polymer on water use efficiency, yield, and several morphological traits of sunflower under greenhouse condition. Notulae Scientia Biologicae. 2, 53–58 (2010).Article 

Google Scholar 
Huettermann, A., Orikiriza, L. J. & Agaba, H. Application of superabsorbent polymers for improving the ecological chemistry of degraded or polluted lands. Clean: Soil, Air, Water 37, 517–526 (2009).CAS 

Google Scholar 
Jain, N. K., Meena, H. N. & Bhaduri, D. Improvement in productivity, water use efficiency, and soil nutrient dynamics of summer peanut (Arachis hypogaea L) through use of polythene mulch, hydrogel, and nutrient management. Commun. Soil Sci. Plant Anal. 48, 549–564 (2017).CAS 
Article 

Google Scholar 
Shekari, F., Javanmard, A. & Abbasi, A. Effects of super absorbent polymer application on yield and yield components of rapeseed. Notulae Scientia Biologicae. 7, 361–366 (2015).Article 

Google Scholar 
Wang, L. et al. Drip irrigation mode and water-retaining agent on growth regulation and water-saving effect of small coffee. Chin. J. Drainag. Irrigat. Mech. Eng. 33, 796–801 (2015).
Google Scholar 
Liu, P. et al. Effects of soil treatments on soil moisture and soybean yield under the condition of underground drip irrigation. Water Saving Irrigat. 25–28 (2019).Li, R. et al. Effects of water-retaining agent on soil water, fertilizer and corn yield under drip irrigation. J. Drainag. Irrigat. Mech. Eng. 36, 1337–1344 (2018).
Google Scholar 
Ma, B. L., Biswas, D. K., Zhou, Q. P. & Ren, C. Z. Comparisons among cultivars of wheat, hulled and hulless oats: Effects of N fertilization on growth and yield. Can. J. Plant Sci. 92, 1213–1222 (2012).Article 

Google Scholar 
He, W. Effects of different irrigation methods on photosynthesis and soil biological characteristics of oat. Inner Mongolia: Hohhot, Inner Mongolia Agricultural University Master’s Thesis (2013).Wu, N. et al. Effects of water-retaining agent dosage on the yield and quality of naked oats under two irrigation methods. J. Crops 35, 1552–1557 (2009).CAS 

Google Scholar 
Gee, G.W., Bauder, J.W.,. Particle-size analysis. In: Klute, A. (Ed.), Methods of Soil Analysis, Part 1. Soil Science Society of America, South Segoe Road, Madison, WI 53711 USA. 383–409 (1986).Lu, R. Soil Agricultural Chemical Analysis Method (China Agricultural Science and Technology Press, 2000).
Google Scholar 
Wang, D. Water use efficiency and optimal supplemental irrigation in a high yield wheat field. Field Crop Res. 213, 213–220 (2017).Article 

Google Scholar 
Chen, Y. et al. Straw strips mulch on furrows improves water use efficiency and yield of potato in a rainfed semiarid area. Agric. Water Manag. 211, 142–151 (2019).Article 

Google Scholar 
Finn, D. et al. Effect of added nitrogen on plant litter decomposition depends on initial soil carbon and nitrogen stoichiometry. Soil Biol. Biochem. 91, 160–168 (2015).CAS 
Article 

Google Scholar 
Mo, F., Wang, J. Y., Xiong, Y. C., Nguluu, S. N. & Li, F. M. Ridge-furrow mulching system in semiarid Kenya: A promising solution to improve soil water availability and maize productivity. Eur. J. Agron. 80, 124–136 (2016).Article 

Google Scholar 
Luo, C. L. et al. Dual plastic film and straw mulching boosts wheat productivity and soil quality under the El Nino in semiarid Kenya. Sci. Total Environ. 738, 139808 (2020).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Bengough, A. G. Water dynamics of the root zone: Rhizosphere biophysics and its control on soil hydrology. Vadose Zone Journal. 11, 1–6 (2012).Article 

Google Scholar 
Zobel, R. W. Plant Roots: Rowth, Activity and Interaction with Soils. Crop Sci. 46, 2699 (2006).Article 

Google Scholar 
Scholl, P. et al. Root induced changes of effective 1D hydraulic properties in a soil column. Plant Soil 381, 193–213 (2014).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Williams, S. M. & Weil, R. R. Crop cover root channels may alleviate soil compaction effects on soybean crop. Soil Sci. Soc. Am. J. 68, 1403–1409 (2010).Article 

Google Scholar 
Farrell, C., Ang, X. Q. & Rayner, J. P. Water-retention additives increase plant available water in green roof substrates. Ecol. Eng. 52, 112–118 (2013).Article 

Google Scholar 
Agaba, H. et al. Effects of hydrogel amendment to different soils on plant available water and survival of trees under drought conditions. Clean: Soil, Air, Water 38, 328–335 (2010).CAS 

Google Scholar 
Wu, L., Liu, M. Z. & Liang, R. Preparation and properties of a double-coated slow release NPK compound fertilizer with superabsorbent and water-retention. Biores. Technol. 99, 547–554 (2008).CAS 
Article 

Google Scholar 
Afshar, R. K. et al. Interactive effect of deficit irrigation and soil organic amendments on seed yield and flavonolignan production of milk thistle (Silybum marianum L. Gaertn.). Ind. Crops Prod. 58, 166–172 (2014).CAS 
Article 

Google Scholar 
Wang, L. Effects of different sowing dates and fertilizer rates on the growth and yield of oats in Yinshan hilly area. Hohhot, Inner Mongolia Agricultural University Master’s Thesis (2020).Liu, Y. G. et al. Influence of planting density on the yield of naked oats and its constituent factors. J. Wheat Crops 28, 140–143 (2008).
Google Scholar 
Jia, Z. F. Effects of sowing rate and row spacing on grain quality of naked oat. Seed. 32, 67–69 (2013).
Google Scholar 
Lascano, R. J. & Van Bavel, C. H. M. Stimulation and measurement of evaporation from bare soil. Soil Sci. Soc. Am. J. 50, 1127–1132 (1986).ADS 
Article 

Google Scholar 
Lv, P. et al. Effects of descending distance under wide sowing conditions on wheat yield and dry matter accumulation and transport. J. Wheat Crops 40, 1–6 (2020).
Google Scholar 
Sun, H. Y. et al. Effects of different row spacing on evapotranspiration and yield of winter wheat in wheat fields. Chin. J. Agric. Eng. 1, 22–26 (2006).
Google Scholar 
Li, G. X. et al. Effects of sowing row spacing on yield and water use efficiency of dryland wheat in different years. Agric. Technol. Equipm. 1, 22–26 (2012).ADS 

Google Scholar 
Chen, S. Y. et al. Effects of planting row spacing on soil evaporation and water use in winter wheat fields. Chin. J. Ecol. Agric. 14, 86–89 (2006).
Google Scholar 
Yang, Y. H. et al. Effects of water-retaining agent on soil moisture and utilization of winter wheat at different growth stages. Chin. J. Agric. Eng. 26, 19–26 (2010).
Google Scholar 
Yang, Y. H. et al. Effects of different moisture conservation tillage measures on water consumption characteristics and annual water use of wheat and maize. North China Agric. J. 32, 103–110 (2017).
Google Scholar 
Du, S. N. et al. Effects of Water and PAM Application Modes on Soil Moisture and Maize Growth. Chin. J. Agric. Eng. 24, 30–35 (2008).
Google Scholar 
Tian, L. et al. Effects of combined application of water-retaining agent and microbial fertilizer on dry matter accumulation, distribution, transport and yield of dry oat. J. Ecol. 39, 2996–3003 (2020).
Google Scholar  More

The following section assesses our main results in terms of the growth in fenced areas over time relative to 1) types of protection, 2) administrative boundaries, and 3) other fences.Fencing relative to land governanceAcross the Greater Mara, a general growth in fenced areas can be observed throughout the 00 s but in particular over the last decade (Fig. 1). Based on satellite images, 35,067 ha were fenced in 1985, corresponding to c. 5%. In the following 25 years there was only an insignificant increase in fenced plots. However, from 2010, the number of fences suddenly grew rapidly, and in the following period (2015–2020) the fenced area increased even more radically, in an exponential manner (Fig. 2). For example, in 2015 there was 63,112 ha of fenced land; in 2016 this number rose to c. 75,176 ha, corresponding to a c. 20% annual increase. From 2010 to 2020, the ha fenced area increased by 170%. This corresponds to a roughly four times increase in the area enclosed by fences during the study period (1985–2020).Figure 2Conservative estimate of the fenced area of the entire Greater Mara, Kenya (1985–2020) expressed in hectares.Full size imageIn almost all regions, the number of fences continued to increase in 2019–20 (Fig. 2). The result is a total of 130,277 ha of fenced land in 2020, corresponding to 19% of the Greater Mara.Hence, there appears to be a building momentum in the expansion of fences in the Greater Mara: those regions that had many fences in 2016 ( > 1,000 ha) continue to experience an increase in the area enclosed by fences, with fences spreading almost everywhere in 2020 in particular. Those regions with the fewest fences in 2016 ( More

USDA, N. Census of Horticultural Specialties (USDA, 2014).
Google Scholar 
USDA, N. Census of Horticultural Specialties (USDA, 2019).
Google Scholar 
Soliman, A. S. & Shanan, N. T. The role of natural exogenous foliar applications in alleviating salinity stress in Lagerstroemia indica L. seedlings. J. Appl. Hortic. 19, 35–45 (2017).Article 

Google Scholar 
Chappell, M. R., Braman, S. K., Williams-Woodward, J. & Knox, G. J. J. o. E. H. Optimizing plant health and pest management of Lagerstroemia spp. in commercial production and landscape situations in the southeastern United States: A review. 30, 161–172 (2012).Gu, M., Merchant, M., Robbins, J. & Hopkins, J. Crape Myrtle Bark Scale: A New Exotic Pest. Texas A&M AgriLife Ext. Service. EHT 49 (2014).Kondo, T., Gullan, P. J. & Williams, D. J. Coccidology. The study of scale insects (Hemiptera: Sternorrhyncha: Coccoidea). Ciencia y Tecnología Agropecuaria 9, 55–61 (2008).Article 

Google Scholar 
Jiang, N. & Xu, H. Observertion on Eriococcus lagerostroemiae Kuwana. J. Anhui Agric. Coll. 25, 142–144 (1998).
Google Scholar 
He, D., Cheng, J., Zhao, H. & Chen, S. Biological characteristic and control efficacy of Eriococcus lagerstroemiae. Chin. Bull. Entomol. 45, 812–814 (2008).
Google Scholar 
Harcourt, D. The development and use of life tables in the study of natural insect populations. Annu. Rev. Entomol. 14, 175–196 (1969).Article 

Google Scholar 
Leslie, P. H. On the use of matrices in certain population mathematics. Biometrika 33, 183–212 (1945).MathSciNet 
CAS 
PubMed 
MATH 
Article 

Google Scholar 
Birch, L. The intrinsic rate of natural increase of an insect population. J. Anim. Ecol., 15–26 (1948).Chi, H. Life-table analysis incorporating both sexes and variable development rates among individuals. Environ. Entomol. 17, 26–34 (1988).Article 

Google Scholar 
Chi, H. & Liu, H. Two new methods for the study of insect population ecology. Bull. Inst. Zool. Acad. Sin 24, 225–240 (1985).
Google Scholar 
Fathipour, Y. & Maleknia, B. in Ecofriendly Pest Management for Food Security (ed Omkar) 329–366 (Academic Press, 2016).Auad, A. et al. The impact of temperature on biological aspects and life table of Rhopalosiphum padi (Hemiptera: Aphididae) fed with signal grass. Fla. Entomol. 569–577 (2009).Qu, Y. et al. Sublethal and hormesis effects of beta-cypermethrin on the biology, life table parameters and reproductive potential of soybean aphid Aphis glycines. Ecotoxicology 26, 1002–1009 (2017).CAS 
PubMed 
Article 

Google Scholar 
Araujo, E. S., Benatto, A., Mogor, A. F., Penteado, S. C. & Zawadneak, M. A. Biological parameters and fertility life table of Aphis forbesi Weed, 1889 (Hemiptera: Aphididae) on strawberry. Braz. J. Biol. 76, 937–941. https://doi.org/10.1590/1519-6984.04715 (2016).CAS 
Article 
PubMed 

Google Scholar 
Krishnamoorthy, S. V. & Mahadevan, N. R. Life table studies of sugarcane scale, Melanaspis glomerata G. J. Entomol. Res. 27, 203–212 (2003).
Google Scholar 
Uematsu, H. Studies on life table for an armored scale insect, Aonidiella taxus Leonardi (Homoptera: Diaspididae). J. Fac. Agric. Kyushu Univ. (1979).Hill, M. G., Mauchline, N. A., Hall, A. J. & Stannard, K. A. Life table parameters of two armoured scale insect (Hemiptera: Diaspididae) species on resistant and susceptible kiwifruit (Actinidia spp.) germplasm. N. Z. J. Crop Hortic. Sci. 37, 335–343 (2009).Article 

Google Scholar 
Yong, C. X. W. Z. C. & Shaoyun, Z. J. Y. S. W. Age-specific life table of chinese white wax scale (Ericerus pela) natural population and analysis of death key factors. Scientia Silvae Sinica 9 (2008).Rosado, J. F. et al. Natural biological control of green scale (Hemiptera: Coccidae): a field life-table study. Biocontrol. Sci. Technol. 24, 190–202 (2014).Article 

Google Scholar 
Fand, B. B., Gautam, R. D., Chander, S. & Suroshe, S. S. Life table analysis of the mealybug, Phenacoccus solenopsis Tinsley (Hemiptera: Pseudococcidae) under laboratory conditions. J. Entomol. Res. 34, 175–179 (2010).
Google Scholar 
Vargas-Madríz, H. et al. Life and fertility table of Bactericera cockerelli (Hemiptera: Triozidae), under different fertilization treatments in the 7705 tomato hybrid. Rev. Chil. entomol. 39 (2014).Huang, Y. B. & Chi, H. Age-stage, two-sex life tables of Bactrocera cucurbitae (Coquillett)(Diptera: Tephritidae) with a discussion on the problem of applying female age-specific life tables to insect populations. Insect Sci. 19, 263–273 (2012).Article 

Google Scholar 
Saska, P. et al. Leaf structural traits rather than drought resistance determine aphid performance on spring wheat. J. Pest. Sci. 94, 423–434 (2021).Article 

Google Scholar 
Ma, K., Tang, Q., Xia, J., Lv, N. & Gao, X. Fitness costs of sulfoxaflor resistance in the cotton aphid, Aphis gossypii Glover. Pestic. Biochem. Physiol. 158, 40–46 (2019).CAS 
PubMed 
Article 

Google Scholar 
Ullah, F. et al. Fitness costs in clothianidin-resistant population of the melon aphid, Aphis gossypii. PLoS ONE 15, e0238707 (2020).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Güncan, A. & Gümüş, E. Influence of different hazelnut cultivars on some demographic characteristics of the filbert aphid (Hemiptera: Aphididae). J. Econ. Entomol. 110, 1856–1862 (2017).PubMed 
Article 

Google Scholar 
Bailey, R., Chang, N.-T., Lai, P.-Y. & Hsu, T.-C. Life table of cycad scale, Aulacaspis yasumatsui (Hemiptera: Diaspididae), reared on Cycas in Taiwan. J. Asia Pac. Entomol. 13, 183–187 (2010).Article 

Google Scholar 
Wang, Z., Chen, Y. & Diaz, R. Temperature-dependent development and host range of crapemyrtle bark scale, Acanthococcus lagerstroemiae (Kuwana)(Hemiptera: Eriococcidae). Fla. Entomol. 102, 181–186 (2019).Article 

Google Scholar 
Zhang, Z.-J. et al. A determining factor for insect feeding preference in the silkworm, Bombyx mori. PLoS Biol. 17, e3000162 (2019).PubMed 
PubMed Central 
Article 

Google Scholar 
Wang, Z., Chen, Y., Diaz, R. & Laine, R. A. Physiology of crapemyrtle bark scale, Acanthococcus lagerstroemiae (Kuwana), associated with seasonally altered cold tolerance. J. Insect Physiol. 112, 1–8 (2019).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Suh, S.-J. Notes on some parasitoids (Hymenoptera: Chalcidoidea) associated with Acanthococcus lagerstroemiae (Kuwana)(Hemiptera: Eriococcidae) in the Republic of Korea. Insecta mundi 0690, 1–5 (2019).
Google Scholar 
Meindl, G. A., Bain, D. J. & Ashman, T.-L. Edaphic factors and plant–insect interactions: Direct and indirect effects of serpentine soil on florivores and pollinators. Oecologia 173, 1355–1366 (2013).ADS 
PubMed 
Article 

Google Scholar 
Wielgolaski, F. E. Phenological modifications in plants by various edaphic factors. Int. J. Biometeorol. 45, 196–202 (2001).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Uchida, R. in Plant nutrient management in Hawaii’s soils (ed Raymond S. Uchida James A. Silva) 31–55 (University of Hawaii at Manoa, College of Agriculture & Tropical Resources, 2000).Flanders, S. E. Observations on host plant induced behavior of scale insects and their endoparasites. Can. Entomol. 102, 913–926 (1970).Article 

Google Scholar 
Yang, T.-C. & Chi, H. Life tables and development of Bemisia argentifolii (Homoptera: Aleyrodidae) at different temperatures. J. Econ. Entomol. 99, 691–698 (2006).PubMed 
Article 

Google Scholar 
Tuan, S. J., Lee, C. C. & Chi, H. Population and damage projection of Spodoptera litura (F.) on peanuts (Arachis hypogaea L.) under different conditions using the age-stage, two-sex life table. Pest Manag. Sci. 70, 805–813 (2014).CAS 
PubMed 
Article 

Google Scholar 
Vafaie, E. et al. Seasonal population patterns of a new scale pest, Acanthococcus lagerstroemiae Kuwana (Hemiptera: Sternorrhynca: Eriococcidae), of Crapemyrtles in Texas, Louisiana, and Arkansas. J. Environ. Hortic. 38, 8–14 (2020).Article 

Google Scholar 
Vafaie, E. K. Bark and systemic insecticidal control of Acanthococcus (= Eriococcus) lagerstroemiae (Hemiptera: Eriococcidae) on Potted Crapemyrtles, 2017. Arthropod manag. tests 44, tsy109 (2019).Vafaie, E. K. & Knight, C. M. J. A. M. T. Bark and systemic insecticidal control of Acanthococcus (= Eriococcus) lagerstroemiae (Crapemyrtle Bark Scale) on Landscape Crapemyrtles, 2016. 42, tsx130 (2017).Vafaie, E. & Gu, M. Insecticidal control of crapemyrtle bark scale on potted crapemyrtles, Fall 2018. Arthropod. Manag. Tests 44, tsz061 (2019).Article 

Google Scholar 
Aktar, M. W., Sengupta, D. & Chowdhury, A. J. I. t. Impact of pesticides use in agriculture: their benefits and hazards. 2, 1 (2009).Grafton-Cardwell, E. & Vehrs, S. Monitoring for organophosphate-and carbamate-resistant armored scale (Homoptera: Diaspididae) in San Joaquin valley citrus. J. Econ. Entomol. 88, 495–504 (1995).CAS 
Article 

Google Scholar 
Almarinez, B. J. M. et al. Biological control: A major component of the pest management program for the invasive coconut scale insect, Aspidiotus rigidus Reyne, in the Philippines. Insects 11, 745 (2020).PubMed Central 
Article 

Google Scholar 
Grout, T. & Richards, G. Value of pheromone traps for predicting infestations of red scale, Aonidiella aurantii (Maskell)(Hom., Diaspididae), limited by natural enemy activity and insecticides used to control citrus thrips, Scirtothrips aurantii Faure (Thys., Thripidae). J. Appl. Entomol. 111, 20–27 (1991).Article 

Google Scholar 
Grafton-Cardwell, E., Millar, J., O’Connell, N. & Hanks, L. Sex pheromone of yellow scale, Aonidiella citrina (Homoptera: Diaspididae): Evaluation as an IPM tactic. J. Agric. Urban. Entomol. 17, 75–88 (2000).CAS 

Google Scholar 
Jactel, H., Menassieu, P., Lettere, M., Mori, K. & Einhorn, J. Field response of maritime pine scale, Matsucoccus feytaudi Duc. (Homoptera: Margarodidae), to synthetic sex pheromone stereoisomers. J. Chem. Ecol. 20, 2159–2170 (1994).CAS 
PubMed 
Article 

Google Scholar 
Mendel, Z. et al. Outdoor attractancy of males of Matsucoccus josephi (Homoptera: Matsucoccidae) and Elatophilus hebraicus (Hemiptera: Anthocoridae) to synthetic female sex pheromone of Matsucoccus josephi. J. Chem. Ecol. 21, 331–341 (1995).CAS 
PubMed 
Article 

Google Scholar 
Zada, A. et al. Sex pheromone of the citrus mealybug Planococcus citri: Synthesis and optimization of trap parameters. J. Econ. Entomol. 97, 361–368 (2004).CAS 
PubMed 
Article 

Google Scholar 
Zhang, Z. & Shi, Y. Studies on the Morphology and Biology of Eriococcus Lagerstroemiae Kuwana. J. Shandong Agri. Univ. 2 (1986).Savopoulou-Soultani, M., Papadopoulos, N. T., Milonas, P. & Moyal, P. Abiotic factors and insect abundance. PSYCHE 2012 (2012).Vandegehuchte, M. L., de la Pena, E. & Bonte, D. Relative importance of biotic and abiotic soil components to plant growth and insect herbivore population dynamics. PLoS ONE 5, e12937 (2010).ADS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Clavijo McCormick, A. Can plant–natural enemy communication withstand disruption by biotic and abiotic factors?. Ecol. Evol. 6, 8569–8582 (2016).PubMed 
PubMed Central 
Article 

Google Scholar 
Nebapure, S. M. & Sagar, D. Insect-plant interaction: A road map from knowledge to novel technology. Karnataka J. Agric. Sci. 28, 1–7 (2015).
Google Scholar 
Murashige, T. & Skoog, F. A revised medium for rapid growth and bio assays with tobacco tissue cultures. Physiol. Plant. 15, 473–497 (1962).CAS 
Article 

Google Scholar 
Hogendorp, B. K., Cloyd, R. A. & Swiader, J. M. Effect of nitrogen fertility on reproduction and development of citrus mealybug, Planococcus citri Risso (Homoptera: Pseudococcidae), feeding on two colors of coleus Solenostemon scutellarioides L. Codd. Environ. Entomol. 35, 201–211 (2006).Article 

Google Scholar 
Lema, K. & Mahungu, N. in Tropical root crops: Production and uses in Africa: proceedings of the Second Triennial Symposium of the International Society for Tropical Root Crops-Africa Branch held in Douala, Cameroon, 14-19 Aug. 1983. (IDRC, Ottawa, ON, CA).McClure, M. S. Dispersal of the scale Fiorinia externa (Homoptera: Diaspididae) and effects of edaphic factors on its establishment on hemlock. Environ. Entomol. 6, 539–544 (1977).Article 

Google Scholar 
Salama, H., Amin, A. & Hawash, M. Effect of nutrients supplied to citrus seedlings on their susceptibility to infestation with the scale insects Aonidiella aurantii (Maskell) and Lepidosaphes beckii (Newman)(Coccoidea). Zeitschrift für Angewandte Entomologie 71, 395–405 (1972).Article 

Google Scholar 
Rasmann, S. & Pellissier, L. in Climate Change and Insect Pests Vol. 8 (ed P. Niemelä C. Björkman) 38–53 (Wallingford, UK: CAB Int., 2015).Wang, Z. & Li, S. Effects of nitrogen and phosphorus fertilization on plant growth and nitrate accumulation in vegetables. J. Plant Nutr. 27, 539–556 (2004).CAS 
Article 

Google Scholar 
Da Costa, P. B. et al. The effects of different fertilization conditions on bacterial plant growth promoting traits: Guidelines for directed bacterial prospection and testing. Plant Soil. 368, 267–280 (2013).Article 

Google Scholar 
Dong, H., Kong, X., Li, W., Tang, W. & Zhang, D. Effects of plant density and nitrogen and potassium fertilization on cotton yield and uptake of major nutrients in two fields with varying fertility. Field Crops Res. 119, 106–113 (2010).Article 

Google Scholar 
Aulakh, M., Dev, G. & Arora, B. Effect of sulphur fertilization on the nitrogen–sulphur relationships in alfalfa (Medicago sativa L. Pers.). Plant Soil. 45, 75–80 (1976).CAS 
Article 

Google Scholar 
Powell, G., Tosh, C. R. & Hardie, J. Host plant selection by aphids: Behavioral, evolutionary, and applied perspectives. Annu. Rev. Entomol. 51, 309–330 (2006).CAS 
PubMed 
Article 

Google Scholar 
Sauge, M. H., Grechi, I. & Poëssel, J. L. Nitrogen fertilization effects on Myzus persicae aphid dynamics on peach: Vegetative growth allocation or chemical defence?. Entomol. Exp. Appl. 136, 123–133 (2010).CAS 
Article 

Google Scholar 
Chen, Y., Serteyn, L., Wang, Z., He, K. & Francis, F. Reduction of plant suitability for corn leaf aphid (Hemiptera: Aphididae) under elevated carbon dioxide condition. Environ. Entomol. (2019).Miller, D. R. & Kosztarab, M. Recent advances in the study of scale insects. Annu. Rev. Entomol. 24, 1–27 (1979).CAS 
Article 

Google Scholar 
Hardy, N. B., Peterson, D. A. & Normark, B. B. Scale insect host ranges are broader in the tropics. Biol. Lett. 11, 20150924 (2015).PubMed 
PubMed Central 
Article 

Google Scholar 
Chen, Q. et al. Age-stage, two-sex life table of Parapoynx crisonalis (Lepidoptera: Pyralidae) at different temperatures. PLoS ONE 12, e0173380 (2017).PubMed 
PubMed Central 
Article 

Google Scholar 
Li, X. et al. Density-dependent demography and mass-rearing of Carposina sasakii (Lepidoptera: Carposinidae) incorporating life table variability. J. Econ. Entomol. 112, 255–265 (2019).PubMed 
Article 

Google Scholar 
Ning, S., Zhang, W., Sun, Y. & Feng, J. Development of insect life tables: comparison of two demographic methods of Delia antiqua (Diptera: Anthomyiidae) on different hosts. Sci. Rep. 7, 1–10 (2017).ADS 
Article 

Google Scholar 
TWOSEX-MSChart: A computer program for the age-stage, two-sex life table analysis (2020).Goodman, D. Optimal life histories, optimal notation, and the value of reproductive value. Am. Nat. 119, 803–823 (1982).MathSciNet 
Article 

Google Scholar 
Efron, B. & Tibshirani, R. J. An Introduction to the Bootstrap (CRC Press, 1994).MATH 
Book 

Google Scholar  More