Understanding the effects of seasonal variation in prey availability on prey switching by large carnivores

Optimal foraging theory predicts that carnivores select prey species based on intrinsic factors, such as body size, vulnerability, and abundance. Prey abundance can vary significantly, especially when move in out of an area en masse search food. However, little is known about how these resource pulses influence the profiles large carnivores. Using data lion (Panthera leo) cheetah (Acinonyx jubatus) kills Maasai Mara Kenya, we investigate whether changes abundance, a result mass annual migration herbivores, two carnivore species. Furthermore, for there are sex-specific differences response to from 387 220 (160 female 60 male), found had strong profiles, but cheetahs this varied by sex social grouping. More specifically, during migration, influx wildebeest (Connochaetes taurinus), lions male (particularly those coalitions) were more likely feed than migration. In addition, less abundant, switched buffalo (Syncerus caffer). Overall, breadth was narrower compared most significant coalitions cheetahs. These could have impact herbivore dynamics, human-wildlife conflict ecological interactions broadly. Through detailed characterisation contribute understanding predator–prey dynamics trophic complex, multi-species ecosystems illustrate importance taking into account inter- intraspecific variations predators modelling dynamics. Nadharia bora ya lishe inatabiri kwamba wanyama walao nyama huchagua spishi zinazowindwa kulingana na vipengele vya ndani, kama vile kimo mwili mazingira magumu, wingi. Wingi wa mawindo unaweza kutofautiana kwa kiasi kikubwa, hasa wakati zinazowinda huingia kutoka katika eneo wingi kutafuta chakula. Hata hivyo, kidogo inajulikana kuhusu jinsi kundi hizi za rasilimali huathiri wasifu wanaokula haswa wakubwa. Kwa kutumia kuua simba duma nchini tunachunguza ikiwa mabadiliko mawindo, kutokana uhamaji mkubwa kila mwaka mimea, hali mbili nyama.Zaidi hayo, kuna tofauti jinsia mahususi kukabiliana mawindo. mauaji (jike 160 dume 60), tuligundua kuwa yalikuwa ushawishi kwenye lakini hii ilitofautiana makundi kijamii. Hasa zaidi, uhamiaji, kunapokuwa nyumbu (hasa wale walio miungano) walikuwa uwezekano kuwala kuliko nje uhamaji. Isitoshe, walipopungua, walibadilika kula nyati ujumla, upana ulikuwa finyu ikilinganishwa ilikuwa muhimu zaidi miungano dume. Mabadiliko haya yanaweza athari mienendo majani, migogoro binadamu wanyamapori mwingiliano ikolojia zaidi. Kupitia uainishaji kina tunachangia uelewaji wanaowinda wengine kitropiki mifumo tata, nyingi kuonyesha umuhimu kuzingatia ndani kuiga wanaowinda. What animals consume integral part animal ecology food web it morphology (Van Valkenburgh & Wayne, 2010), condition (Moorhouse-Gann et al., 2020), growth rate (Hooker 2017), disease transmission (Gakuya 2012), space-use (Broekhuis 2021), intraguild predation (Palomares Caro, 1999), competition (Helldin Danielsson, 2007), community composition (Ripple Beschta, 2004). The optimal predator will prefer yields energy per unit handling time, which be influenced factors both (e.g. defence mechanisms health status) (less time needed find abundant prey; MacArthur Pianka, 1966, Pyke 1977). Therefore, preferred increases, profile should decrease profitable items no longer interest. Alternatively, if decreases, then switch nonpreferred prey, behaviour referred switching. Several studies explored drivers switching Kjellander Nordström, 2003; van Leeuwen 2013) observational systems where they choose between multiple different relatively scarce Davidson 2013; Elbroch Owen-Smith Mills, 2008). effect systems, still unclear. Dietary however key our mechanistic structure provides indication number connections within (Beckerman 2006). responses according or grouping potentially adding additional complexity Changes environmental conditions increased rainfall periods drought. For example, herbivores their births coincide with availability brought rains (Ogutu 2011), whereas drought increase mortality due (Abraham 2019). Indeed, has been shown carnivores, leo), (Davidson 2013). also come through movement individuals migrate. This movement, often triggered plant productivity, cause hyperabundance ephemeral followed depletion time. While research effects (Yang paucity knowledge terms migratory Africa. East Africa, approximately 1.4 million taurinus) other ungulates, including plains zebra (Equus quagga) Thomson's gazelle (Gazella thomsoni), migrate every year wet season range Serengeti, Tanzania, dry Mara, Kenya (Holdo 2009). temporal opportunity empirically test case jubatus). Serengeti ecosystem patterns (Scheel Packer, 1995). We build explicitly characterising comparing period incorporated study understand may differ. general, 92–632 kg (Clements 2014), caffer), occasionally kill smaller (Hayward Kerley, 2005), while 14–40 2014). 2018; Clements 2016; Radloff Du Toit, 2004; Rostro-García 2015), sexual dimorphism structure. Female tend males (Boast 1994) solitary, unless accompanied dependent cubs. Male cheetahs, hand, either solitary form groups, coalitions, consisting 2–5 2019; 1994). hypothesis sudden results profiles. Based (MacArthur 1966; 1977), predict proportionally If case, diverse) might become relative As result, that, each species/social group, similarities differ, indicated low degree overlap. because refrain killing 2018), pronounced females. conducted Greater Ecosystem south-west (1°S, 35°E; elevation c. 1700 m) where, south, borders National Park Tanzania. experiences bimodal pattern, spanning November–June July–October. characterised distinct periods: short (November–December) long (March–June; Ogutu attract migrating wildebeest, Serengeti. Generally, peaks July after numbers slowly decline until returned Tanzania November (Stelfox 1986). Independent substantial populations resident year-round, along buffalo, topi (Damaliscus lunatus jimela), Grant's (G. granti), impala (Aepyceros melampus), warthog (Phacochoerus africanus) hares (Lepus spp.). Between June 2013 October 2020, vehicle-based collection teams covered ~2400 km2 uniformly possible (see Broekhuis Gopalaswamy, 2016 details). When sighted, feeding event observed, present, date recorded addition scavenging. Scavenging directly observed inferred circumstantial evidence carcass presence predators. All scavenging livestock events removed prior analysis. livestock, rarely occurs wildlife areas, fieldwork occurred Thuo 2020). split following categories: females, single coalitions. No differentiation made females without cubs comparable 2018). classified one (January–May) (July–November) 1-month gap seasons (June December). To availability, calculated determine any periods, quantified overlap greater indicating similarity. metrics group. frequencies at killed group varying availability: tested frequency commonly differed using chi-squared goodness-of-fit Fisher's exact expected >5. difference found, post hoc tests Bonferroni correction Commonly total ≥10. below threshold grouped together category called ‘Other’. total, 607 17 Cheetah larger variety opposite (Table 1). across evenly distributed resulting breadths 1, Fig. (t = −3.11, d.f. 3, P-value 0.05) disproportionally groups. A (262 125 migration) 12 During 11 10 (ntotal ≥ 10) 245, 63.31%), 41, 10.49%), 37, 9.56%), 22, 5.68%) 18, 4.65%, Table proportions (χ2 52.50, 5, <0.001, 2). proportion significantly higher (P-value <0.001) being <0.001). resulted (Bpp 0.28) 0.07, similarity 64.5%. 1); (95 65 migration), 32 (22 28 (13 15 migration). (n 80; 50%) 44; 27.5%), 12; 7.5%). three 3.87, 0.27, 3). slight overall seven slightly broader 0.17) 0.14, small, (Opp 87.4%). Of cheetah, consumed barely five six did much 0.09) 0.24, 4) meant lower 76.40%) Most notably, but, (63.64%) (40.00%), not (Fisher's test; 4). periods. 7) proportions. comprised only 26.67% 76.92% 5.17, 0.02, considerably 0.33, Consequently, 33.30% Our show between, even within, line theory, (especially positively associated suggest does occur who, buffalo. occurrence various species, Artic foxes (Vulpes lagopus) who preying goose eggs lemming (Lemmus trimucronatus Dycrostonyx groenlandicus) densities (McKinnon Similarly, primary alternative depending vulnerability (Bissett 2012; previous fluctuations deaths, indicate similar driven space use. up coalition, sample size too small its significance. So, increases fully captured study. arid areas 52 make robust inferences (Beukes 2017). same cheetahs; however, collecting challenging generally reside thereby reducing sampling units 2016). Despite corroborate al. (2016) Additionally, differs within. exhibit switching, possibly related risk kleptoparasitism always access mechanism (Tallian like wider breadth. Numerous showing additionally respond differently highlight complexities It widely dynamically important feature webs direct indirect (Abrams 1998). gives chance recover what apparent mutualism. Tarangire, giraffe (Giraffa camelopardalis) calves decreased hence survival (Lee But population competition. Predators just functionally numerically, demographically reproductive change (Chevallier 2020; Giroux 2012) spatially movement-induced aggregation 2021). caused consequently 1998; Holt, pulses, large-scale migrations, impacts, changing system bottom-up driven, top-down (Jaksic 1997). high (lion density 17.08 >1 old/100 km2, 0.66–1.39 independent cheetahs/100 km2), highest unfenced 2021; Elliot thus lions, significant. interannual variation conditions, (Bartzke observe assumed effort, supported fact findings research. Estimating seasonal would provide insights potential undertaking wildlife, future technological computational advancements (Marchowski, findings, conservation implications (Bagchi, prevalence conflict. wolves (Canis lupus) wild (Sidorovich 2003). look (Mukeka study, excluded outside protected detection difficult. such, scats, combination molecular techniques (Thuo used quantify broadly thought stabilizing Understanding functioning. crucial transformed anthropogenic pressures. globe negatively impacted climate human-induced habitat loss fragmentation (Kauffman Permissions granted Commission Science, Technology Innovation (permit no.: NACOSTI/P/16/69633/10821), Wildlife Service KWS/BRM/5001), Narok County Government management conservancies. funded African Foundation, BAND Vidda WWF-UK, WWF-Kenya numerous private donors. thank team assisting Dennis Sonkoi helping translate abstract Swahili. FB conceived ideas; NM, BK collected data; MV, NM analysed MV led writing manuscript. authors contributed critically drafts gave final approval publication.