{"id":"c2e22ff5-713f-4cb6-a0dd-ec1dfa49fa1a","arxiv_id":"2506.16284","paper_version":1,"verdict":"CONDITIONAL","confidence":"MODERATE","novelty_score":6.0,"correctness_risk":"medium","formal_verification":"none","parameter_count":5,"one_line_summary":"In a spatial rock-paper-scissors model, adding rare targeted jumps to one species shifts dominance to its predator and changes coexistence chances.","lead":"This paper simulates a rock-paper-scissors ecosystem where one species can spend energy to jump toward clusters of the species it beats. The jumps flip which species dominates and, at intermediate mobility, can help all three species coexist.","discovery_kind":"extension","skeptic_critique":{"model":"deepseek-v4-flash","headline":"Central dominance shift depends on the never-specified jump-attempt limit Nt and an unused threshold β; if targeting rarely fires at low η, the effect may vanish.","rationale":"The reader's weakest-assumption analysis identified the unspecified Nt and the strict all-neighbour targeting rule as critical, and this stress-test independently converges on the same point after reading the model description. The mechanism is ecologically plausible: a rare, well-placed jump into a prey-rich region should strengthen species 1 and indirectly favour species 3. However, the entire qualitative result depends on the probability that a jump attempt succeeds, which is controlled by Nt and by the suitability criterion. Since Nt is never assigned a value and β is defined but never used, the simulation is under-specified and the reported dominance shift cannot be reproduced from the text. This is not an objection to the biological idea but to the load-bearing implementation detail: if the targeting rule rarely fires at low η, the system collapses to ordinary random-walk RPS, and the central claim disappears. The concrete test directly varies the unspecified parameters and checks whether the qualitative conclusions are stable. Because the reader already conditioned acceptance on fixing these issues, the verdict remains CONDITIONAL rather than changing to ACCEPT or REJECT.","tokens_in":10243,"tokens_out":3681,"duration_ms":47577,"concrete_test":"Run the Section 5 coexistence protocol (L = 100, 1000 simulations, m from 0.05 to 0.95, η = 0.05 and 0.25) for Nt = 1, 5, 10, and 100, and for a relaxed suitability rule such as at least 6/8 or 4/8 neighbours of species 2. Record the dominant species and coexistence probability for each combination. If the dominance of species 3 and the coexistence windows vanish for small Nt or relaxed β, the central claim depends on an unspecified implementation choice; if the curves are unchanged across Nt and β, the concern is resolved.","verdict_should_be":"UNCHANGED","load_bearing_attack":"The central claim that even low energy allocation to jumping shifts cyclic dominance rests on successful jumps actually occurring. In Section 2, step (iv)(b), a landing site is suitable only if all eight Moore neighbours are occupied by species 2; the parameter β ∈ [0,1], defined as a 'leap threshold', is never used in the algorithm. The number of jump attempts Nt (parameter 4) is introduced but no value is given anywhere, and the text is internally inconsistent about other parameters (Section 3 states R = 250 with β = 1, while the Fig. 2 caption states R = 5 with β = 0.1). For low η, mobility is already selected with probability m, and among those actions only fraction η are jump attempts; if Nt is small, most attempts fail and the organism performs a nearest-neighbour random walk, so the model reduces to classical RPS and the reported dominance shift should disappear. If Nt is instead large enough to guarantee finding an all-species-2 site, then 'low energy allocated to jumping' is not low in realized jump frequency, and the effect could be an artifact of a hidden large-Nt choice. Without a specified Nt and a used β, the dominance shift and coexistence curves are not reproducible, and the qualitative claim is not established as generic.","agreement_with_reader":"agree"},"referee_report":{"model":"deepseek-v4-flash","summary":"This paper extends spatial rock–paper–scissors simulations by giving species 1 a saltatory targeting strategy: with probability η, a selected individual scans a perception disk of radius R for an empty site whose eight Moore neighbours are all occupied by the species it beats (species 2), jumps there, and otherwise performs a nearest-neighbour random walk. The authors report density time series, snapshot sequences, autocorrelation-based length scales l_i, and coexistence probabilities as functions of mobility m and η. Their central claims are that even small η shifts cyclic dominance toward species 3 (the species that beats the jumper), that saltatory targeting reduces the characteristic length scale of species 1 and 2, and that the strategy enhances coexistence in a narrow intermediate mobility window (0.3≤m≤0.35) but jeopardises it for m>0.35.","tokens_in":10561,"tokens_out":5078,"duration_ms":59866,"significance":"If established, the model would provide a concrete, mechanism-based prediction that targeted long-range movement can reverse cyclic-dominance balance and alter biodiversity in spatially extended microbial and animal systems. Strengths are that no parameters are fitted to outcomes; length scales and coexistence probabilities are direct simulation measurements, and the model is simple enough to reproduce. The main limitations are reproducibility-related: Nt is never specified, β is unused, several parameter values conflict, and the spectral-density formula appears incorrect. These issues are fixable and do not by themselves invalidate the qualitative picture, but they must be resolved before the quantitative claims can be accepted.","major_comments":[{"comment":"The number of jump attempts Nt is introduced but never assigned a value in any simulation, and β is defined as a leap threshold but is never used in step (iv)(b), which instead requires all eight Moore neighbours of the candidate site to be occupied by species 2. The text is also internally inconsistent about other parameters: Section 3 states R=250 and β=1, while the Fig. 2 caption states R=5 and β=0.1. Without a specified Nt and a used β, the simulations are not reproducible, and the realized jump frequency is uncontrolled: for small Nt the targeting rule almost never fires and the strategy degenerates to ordinary random walks, which would erase the reported dominance shift at low η.","section":"Section 2, parameter 4 and algorithm step (iv)"},{"comment":"The spectral density S_i(κ) is defined as the sum of φ_i(κ), not the squared modulus |φ_i(κ)|^2. The Wiener–Khinchin relation requires the power spectrum; as written, Eq. (3) does not yield the autocorrelation function. The characteristic length scales l_i in Fig. 5 therefore rest on an unjustified transform, and the quantitative values (for example l1≈3, l2≈4, l3≈23 at η=0.05) may not be meaningful.","section":"Section 4, Eq. (2)"},{"comment":"The text says that organisms interact using the Moore neighbourhood with eight immediate neighbours, but the algorithm in Section 2 states that selection, reproduction, and ordinary movement choose one of the four nearest neighbours. This distinction changes the game's spatial correlations and must be clarified. In addition, the perception radius R is given conflicting values: Section 3 says R=250, while the Fig. 2 caption says R=5; R controls the maximum jump distance, so this inconsistency directly affects the reported spatial patterns.","section":"Sections 2 and 3, model definition and parameter values"},{"comment":"The coexistence probabilities are plotted without error bars or confidence intervals, even though each point is a binomial proportion over 1000 simulations. The qualitative distinction between biodiversity enhancement at 0.3≤m≤0.35 and biodiversity loss for m>0.35 needs at least standard errors; otherwise one cannot assess whether differences among η curves are within statistical noise. The exact values of m used should also be stated, since the text says the range starts at 0.05 while the figure axis starts at 0.1.","section":"Section 5 and Fig. 6"},{"comment":"The central claim that even a low energy allocation to jumping shifts the cyclic dominance balance is supported only by a single simulation at η=0.25 (Fig. 3) and by the length-scale data in the Fig. 5 inset, not by an ensemble-averaged measure of density dominance as a function of η. Please provide mean densities or a dominance index with error bars for low η (for example η=0.05 and η=0.10) to establish that the effect is generic rather than a property of one trajectory at moderate η.","section":"Section 3.1 and abstract"}],"minor_comments":[{"comment":"The caption lists times 't = 140, t = 280, t = 560, t = 880, t = 1140, t = 176, t = 260, t = 2360, and t = 4760', while the text says the panels show t = 0, 5, 10, 25, 45, 100, 120, 140, 190, 220; these lists cannot both be correct and should be reconciled.","section":"Fig. 4 caption"},{"comment":"The phrase 'empty space must be in a region where the local density of species i+1 is high' is only operationalized by the all-eight-neighbours rule in step (iv)(b); a formal definition of 'high density' would avoid ambiguity.","section":"Section 2, parameter 3"},{"comment":"The normalisation in Eq. (4) should specify how ties and the radial binning of |r'|=x+y are handled, and whether the denominator is evaluated before or after summing over degenerate displacements.","section":"Eq. (4)"},{"comment":"There is a typo 'adress' in the second paragraph, and reference [22] has an inconsistent page range; these should be corrected during revision.","section":"Introduction"},{"comment":"The phrase 'saltatory energy fraction flightη = 0.25' appears to have a stray word 'flight'; the notation should be cleaned throughout.","section":"Section 3"}],"recommendation":"major_revision","confidential_remarks":"The manuscript would benefit from a reproducibility table listing every parameter value used in each figure, including Nt, R, β, lattice size, and number of runs. I did not treat the heavy self-citation as a scientific defect, but the discussion should distinguish the present targeting rule more sharply from the authors' earlier ambush and safeguard strategies so that the novelty is unambiguous."},"author_rebuttal":null,"desk_editor":{"model":"deepseek-v4-flash","letter":"The core idea here is actually new: energy-limited directed jumps toward prey-dense sites, distinct from the Levy-flight and ambush strategies already in the literature. The reported consequence—that even rare jumps shift dominance to the species that beats the jumper—is clean and visible in the density and autocorrelation data. The length-scale collapse and the coexistence crossover with mobility are the kind of quantitative outputs that make this worth a serious look. The authors also argue the mechanism clearly: a jumper gains prey but exposes itself to species 3, so the cyclic balance tilts. That part holds together conceptually.\n\nThe soft spots are mostly about missing numbers and internal inconsistencies, but one of them is load-bearing. The biggest problem is that Nt, the number of jump attempts, is defined but never assigned a value. This matters because the low-eta effect depends on jump attempts actually finding a suitable site. If Nt is small, the strategy degenerates to a nearest-neighbor random walk and the dominance shift should vanish. If Nt is large, then 'low energy allocated to jumping' may not correspond to rare jumps in realized behavior. Either way, the central quantitative claim is not reproducibly specified. The stress-test note is right on this.\n\nThe beta parameter is introduced in the model section but never used in the algorithm—step (iv)(b) simply requires all eight Moore neighbors to be species 2, with no role for beta. The text and figure captions also disagree: Section 3 says R=250 and beta=1, while the Fig. 2 caption gives R=5 and beta=0.1. Equation (2) appears to omit the squared modulus in the spectral density definition. The coexistence curves in Fig. 6 have no error bars, which is a minor fix given they average over 1000 runs.\n\nThese are all fixable, and none of them by itself proves the qualitative effect is wrong. But together they mean the paper, as currently written, cannot be independently reproduced. No code or data is provided, so the reader has to take the simulation outputs on faith until the parameters are pinned down.\n\nWho gets value from this? Researchers working on spatial rock-paper-scissors models and movement ecology, especially those interested in how behavioral rules alter coexistence. A serious referee could help the authors clean this up and make the result trustworthy. I would not sink the paper; I would send it to review with a demand for the missing parameter values and consistency fixes. My own verdict is skeptical-but-intrigued, and I would not cite it in its present form.","headline":"A genuinely new simulation rule for spatial RPS that flips cyclic dominance, but the manuscript is not reproducible as written because a load-bearing parameter (Nt) is never given and other parameters conflict.","tokens_in":11021,"tokens_out":2063,"would_cite":false,"duration_ms":26807,"reading_group":"maybe","serious_thinker":"yes","would_accept_peer_review":true},"rs_alignment":null,"lean_confirmation":null,"pith_extraction":{"msc":[],"pacs":[],"model":"deepseek-v4-flash","headline":"This paper claims that even a small energy allocation to targeted jumping in a three-species cyclic game flips the dominance balance so that the species that hunts the jumper becomes the winner.","keywords":["rock-paper-scissors game","saltatory targeting","spatial pattern formation","coexistence probability","May-Leonard model","Moore neighbourhood","behavioural movement strategy","cyclic dominance"],"falsifier":"Run the model at η=0.05 with Nt=1 and with the landing rule relaxed to allow, say, five of eight neighbours occupied by the prey species; if species 3 no longer becomes the dominant species at low mobility, the paper's claimed shift in cyclic dominance is not generic. A second check would measure the coexistence probability at m=0.33 with and without the jump rule to confirm the narrow enhancement window.","tokens_in":10039,"feed_emoji":"🎯","tokens_out":5803,"duration_ms":61529,"temperature":0.7,"pith_summary":"This paper asks what happens when one species in the classic three-way rock-paper-scissors competition stops moving randomly and sometimes spends energy to jump toward a neighbourhood full of the species it beats. Using stochastic lattice simulations of the May-Leonard model, the authors find that even a small jump probability shifts the balance of cyclic dominance: the jumping species becomes better at killing its prey, which lets the species that hunts the jumper take over as the most abundant. The strategy also shrinks the typical spatial domains of the jumper and its prey, enlarges the domain of the new dominant species, and destroys the spiral-wave patterns of the standard model. For low mobility the jumps can raise the probability that all three species coexist, but for higher mobility they reduce coexistence and eventually drive biodiversity to zero. The point of the work is that a realistic foraging tactic, with an explicit energy cost, can be added to spatial game models and changes both pattern and coexistence predictions in ways ecologists could look for.","feed_headline":"Rare strategic jumps flip rock-paper-scissors dominance","feed_subtitle":"Even a tiny jump budget tips the cyclic game to the jumper's predator and changes coexistence odds.","key_machinery":"The saltatory targeting algorithm is the central object: a leaping individual surveys a perception disc of radius R, then makes up to Nt attempts to find an empty landing site whose eight Moore neighbours are all occupied by the species it dominates (threshold β=1 in the main simulations), jumping there with probability η when selected for movement and otherwise performing a nearest-neighbour random walk. This is embedded in the May-Leonard stochastic lattice model, where at each step a random individual is chosen to select, reproduce, or move with fixed probabilities s, r, and m. The jump rule creates a nonlinear feedback between territory conquest and mobility: successful jumps put the jumper next to prey, increasing its future reproductive success, while failed jumps and the energy cost degrade it to ordinary diffusion. The paper uses spatial autocorrelation functions and their crossing of a fixed threshold to measure characteristic domain lengths, and repeated simulations with random initial conditions to measure coexistence probability.","core_discovery":"In the authors' model, species 1 occasionally allocates an energy fraction η to leap into an empty site whose eight Moore neighbours are all occupied by species 2, its prey; if no such site is found within Nt attempts it performs a random walk instead. The central discovery is that even η as low as 0.05 shifts the cyclic dominance balance: species 1 kills more of species 2, species 2 weakens, and species 3—the species that beats species 1—becomes the most abundant and most spatially correlated. The characteristic length scale of species 3's domains stays near the standard value (~24 lattice units) while those of species 1 and 2 drop to ~3 and ~4 at η=0.05, and the system's familiar spiral waves are replaced by unstable territory alternation. For the coexistence probability, the paper finds that saltatory jumping leaves biodiversity unchanged for mobility m<0.3, increases coexistence in the narrow band 0.3≤m≤0.35, and jeopardises it for m>0.35, with total collapse for m>0.6.","pith_inferences":["A defensive version of the same rule, jumping away from predator-rich zones, would be a natural next test and would presumably promote spatial cohesion and coexistence rather than undermine it.","Because the dominance flip appears at the smallest simulated jump fraction, the cyclic feedback amplifies a very weak behavioural bias; mapping the minimum η and minimum Nt needed to flip the winner would reveal how generic the effect is on finite lattices.","The unnamed value of Nt acts as an extra free parameter, so the reported effects should be re-examined across a range of Nt before being applied to real ecosystems."],"forward_implications":["Even a small energy allocation to targeted jumps (η=0.05) is enough to reverse the identity of the dominant species in a cyclic three-species community.","Saltatory jumping breaks the coherent spiral waves of the standard model, replacing them with unstable, alternating territorial patches.","The characteristic size of the jumping species' and its prey's spatial domains shrinks dramatically, while the predator of the jumper keeps nearly standard-sized domains.","For low mobility (m<0.3) coexistence is unaffected, for 0.3≤m≤0.35 jumps improve coexistence, and for m>0.35 jumps reduce it, with complete biodiversity loss for m>0.6.","The model gives ecologists concrete parameters (η, R, β, Nt) for adding energy-limited directed dispersal to spatial competition models."],"supporting_citations":[{"why":"Sets the baseline: random mobility in the standard May-Leonard model can promote or jeopardize biodiversity, and defines the spiral-wave regime the saltatory model is compared against.","marker":"[2]"},{"why":"Supplies the non-conserved May-Leonard population dynamics on which the simulations are built.","marker":"[37]"},{"why":"Provides the closest prior behavioural strategy (ambush) and motivates the targeted-jump implementation.","marker":"[25]"},{"why":"Offers the random Levy-flight contrast that distinguishes targeted leaps from stochastic long-range relocations.","marker":"[38]"},{"why":"Contributes the broader behavioural movement-strategy framework, including safeguard behaviour, that the discussion extends to defensive jumps.","marker":"[26]"},{"why":"Gives the directional-mobility result against which the asymmetry introduced by saltatory jumps is interpreted.","marker":"[36]"}],"fun_headline_variants":["Tiny jump budget tips rock-paper-scissors game","Strategic leaps give edge to jumper's predator","Low-cost jumps reshape cyclic dominance balance","Jumping tactic boosts predator, shifts coexistence"],"cache_read_input_tokens":3200,"weakest_assumption_plain":"The core result depends on the assumption that a jumping individual can often find an empty site completely surrounded by its prey within a fixed number of attempts, a number Nt that the paper never assigns; if attempts are few or the 'all eight neighbours' rule is relaxed, the strategy degenerates to random walking and the low-energy dominance shift may not occur.","fun_headline_variants_meta":{"raw":{"variants":["Tiny jump budget tips rock-paper-scissors game","Strategic leaps give edge to jumper's predator","Low-cost jumps reshape cyclic dominance balance","Jumping tactic boosts predator, shifts coexistence"]},"model":"deepseek-v4-flash","effort":"low","cost_usd":0.000169,"raw_usage":{"total_tokens":1282,"prompt_tokens":979,"completion_tokens":303,"prompt_tokens_details":{"cached_tokens":384},"prompt_cache_hit_tokens":384,"prompt_cache_miss_tokens":595,"completion_tokens_details":{"reasoning_tokens":246}},"tokens_in":595,"tokens_out":303,"duration_ms":3572,"temperature":1.0,"reasoning_tokens":246,"cache_read_input_tokens":384,"cache_creation_input_tokens":0},"cache_creation_input_tokens":0},"created_at":"2026-08-06T23:44:08.165358+00:00","model_set":{"reader":"deepseek-v4-flash"},"falsifier":"Run the model at η=0.05 with Nt=1 and with the landing rule relaxed to allow, say, five of eight neighbours occupied by the prey species; if species 3 no longer becomes the dominant species at low mobility, the paper's claimed shift in cyclic dominance is not generic. A second check would measure the coexistence probability at m=0.33 with and without the jump rule to confirm the narrow enhancement window.","supporting_citations":[{"cited_title":"Reichenbach, M","cited_arxiv_id":null,"evidence_quote":"Sets the baseline: random mobility in the standard May-Leonard model can promote or jeopardize biodiversity, and defines the spiral-wave regime the saltatory model is compared against."},{"cited_title":null,"cited_arxiv_id":null,"evidence_quote":"Supplies the non-conserved May-Leonard population dynamics on which the simulations are built."},{"cited_title":"Barbalho, S","cited_arxiv_id":null,"evidence_quote":"Provides the closest prior behavioural strategy (ambush) and motivates the targeted-jump implementation."},{"cited_title":"Wang Dong, Z","cited_arxiv_id":null,"evidence_quote":"Offers the random Levy-flight contrast that distinguishes targeted leaps from stochastic long-range relocations."},{"cited_title":"Moura, J","cited_arxiv_id":null,"evidence_quote":"Contributes the broader behavioural movement-strategy framework, including safeguard behaviour, that the discussion extends to defensive jumps."},{"cited_title":null,"cited_arxiv_id":null,"evidence_quote":"Gives the directional-mobility result against which the asymmetry introduced by saltatory jumps is interpreted."}],"review_version":1}