{"paper_id":"3582dee9-3f68-43fd-aa4a-fd9f62be2ec1","body_text":"Fueling a predator death -trap: Trophic subsidies and the risk of 1 \nmanagement-induced collapse in a predator-prey system 2 \nRunning head: Trophic subsidies and management traps 3 \nABSTRACT 4 \n1. Anthropogenic subsidies create complex ecological dynamics, yet their interaction with invasive species 5 \nmanagement is poorly understood. Managing subsidies or predators in isolation risks perverse outcomes, 6 \nincluding population collapses, demanding a more holistic understanding. 7 \n2. We employed a Pattern-Oriented Inference framework to synthesize multiple lines of evidence for the 8 \nendemic Noronha skink (Trachylepis atlantica) across an archipelago. We analyzed three key patterns 9 \nusing complementary methods: (i) population density, estimated via capture-mark-recapture and 10 \nnegative binomial GLMs of count data; (ii) individual body size, using gamma GLMs; and (iii) injury 11 \nrates, via tail-autotomy analysis. 12 \n3. We documented a dramatic density gradient driven by predation pressure. Skink populations were over 13 \nthree times denser on predator-light secondary islands (0.411 ind/m², 95% CI: 0.297–0.568) than in 14 \npredator-rich PARNAMAR (0.125 ind/m², 95% CI: 0.090–0.174). Although anthropogenic subsidies 15 \nboosted density by 82% in the inhabited APA (0.227 ind/m², 95% CI: 0.174–0.297), this was 16 \ninsufficient to overcome the severe impact of invasive predators. 17 \n4. This created a paradox where density , a traditional population success metric, was inverse to size, an 18 \nindicator of individual fitness. On the main island, although the subsidized APA was denser than 19 \nPARNAMAR, individual condition was no better. Adult males in the APA were as small as those in the 20 \nlowest-density sites and significantly smaller than males on the secondary islands. Predation pressure 21 \nexplains this gradient, with tail-loss injury rates peaking in the APA (29.3%), remaining high in PARNA 22 \n(25.0%), and dropping about 50% on the secondary islands (15.0%). 23 \n.CC-BY 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted August 30, 2025. ; https://doi.org/10.1101/2025.08.26.672345doi: bioRxiv preprint \n\n5. Synthesis and applications: The convergence of these patterns supports a \"predator death -trap\" 24 \nhypothesis, where trophic subsidies in the inhabited APA fuel high skink recruitment, masking extreme 25 \nmortality from a subsidized predator community and other anthropogenic threats. This dynamic 26 \nproduces high population turnover and truncates size structure by selectively removing larger, older 27 \nadults and may explain patterns seen elsewhere . Our findings have critical management implications: 28 \nremoving food subsidies without concurrent, effective control of key invasive predators could trigger a 29 \npopulation collapse. We advocate integrated, multi -species management and provide robust evidence 30 \nfor the threatened status of this endemic reptile. 31 \nKeywords: ecological trap, invasive species, island conservation, management trap, Pattern-Oriented Inference, 32 \npopulation sink, reptile conservation, Trachylepis atlantica, trophic subsidy. 33 \n1. INTRODUCTION 34 \nDue to their geographic isolation, oceanic islands foster unique evolutionary dynamics, resulting in high rates of 35 \nendemism and unique community structures (Kier et al., 2009). However, this isolation also makes island biota 36 \nexceptionally vulnerable to anthropogenic disturbances and biological invasions, primary drivers of the ongoing 37 \nbiodiversity crisis and have caused numerous extinctions (Spatz et al., 2017) . Understanding the complex and 38 \noften interacting impacts of these cumulative pressures is a central challenge for applied ecology (Maeda et al., 39 \n2019; Oppel et al., 2014). 40 \nThe archipelago of Fernando de Noronha, Brazil, exemplifies this challenge. Noronha is home to the endemic 41 \nNoronha skink (Trachylepis atlantica), a lizard that evolved in a historically predator-free environment (Rocha 42 \net al., 2009) , and an i mportant pollinator species for the native mulungu tree  (Erythrina velutina). The main 43 \nisland of the archipelago is now inhabited and hosts a rich suite of invasive species, including black rats (Rattus 44 \nrattus), stray and feral cats (Felis catus), tegu lizards (Salvator merianae), and the cattle egret (Bubulcus ibis), 45 \nall of which are documented predators of the Noronha skink (Gaiotto et al., 2020; Gasparini et al., 2007; 46 \nMicheletti et al., 2020) . In contrast, t he smaller, uninhabited secondary islands, while still harboring invasive 47 \n.CC-BY 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted August 30, 2025. ; https://doi.org/10.1101/2025.08.26.672345doi: bioRxiv preprint \n\nrats—except for one island, where eradication has been successful—are largely free from cats and tegu lizards 48 \n(Abrahão et al., 2019; Russell et al., 2018). 49 \nComplicating this dynamic is the direct and indirect influence of human settlement on the main island, which is 50 \nadministered as both a protected Environmental Protection Area (APA) and a more strictly protected National 51 \nPark (PARNAMAR). While both regions host the full suite of invasive predators, the APA, which contains the 52 \nurban areas, provides anthropogenic food subsidies (e.g., refuse) that can alter resource availability for both 53 \nskinks and predators (Gasparini et al., 2007) . These potential benefits, however, are coupled with a suite of 54 \nconcentrated negative pressures uniqu e to the APA, including direct persecution linked to tourism -related 55 \nconcerns (e.g., business owners fearing that lizards may disturb visitors), alongside predation from domestic and 56 \nstray animals, and profound habitat modification . This creates a classic management dilemma: decisions must 57 \nbe made in a complex system where such countervailing effects are difficult to separate , but obtaining enough 58 \ndata to inform all parameters is logistically infeasible. For example, although a general decline in skink density 59 \non the main island has been noted  (AEMA, 2017), the lack of a clear understanding of the relative importance 60 \nof these interacting drivers has impeded the development of robust conservation strategies and has hindered 61 \nefforts to formally classify the species as ‘Vulnerable’ or ‘Threatened’ under IUCN criteria (IUCN, 2014). 62 \nThis archipelago -wide gradient of invasive predator presence, coupled with differences in human influence 63 \nbetween management zones, creates a natural experiment for assessing their cumulative impacts, which we use 64 \nto address this challenge directly. We adopt a Pattern-Oriented Inference (POI) framework —a novel approach 65 \nfor synthesizing the types of disparate datasets common in applied ecology — inspired by the Pattern-Oriented 66 \nModelling approach (Grimm et al., 2005) , which uses the principle that an explanatory hypothesis gains 67 \nsubstantial credibility if it can simultaneously explain multiple, independent patterns observed at different scales 68 \nor levels of organization. By integrating multiple lines of evidence and focusing on a suite of robust patterns—69 \n(1) population density, (2) individual body size, and (3) rates of injury— we test the overarching hypothesis that 70 \nthe interplay between invasive predators and human activities transforms inhabited areas into a ‘predator death-71 \ntrap,’ which in turn generates a high-turnover population dynamic that functions as an ‘invisible sink’. Our goal 72 \nis to demonstrate that even with inherent data limitations, a structured synthesis can provide a clear understanding 73 \n.CC-BY 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted August 30, 2025. ; https://doi.org/10.1101/2025.08.26.672345doi: bioRxiv preprint \n\nof system dynamics and generate robust recommendations to guide urgent management decisions while avoiding 74 \nperverse outcomes, such as intensifying predation pressure and causing a collapse of the Noronha skink 75 \npopulation. Ultimately, such a framework can provide a strong e vidence foundation for the effective wildlife 76 \nmanagement. 77 \n2. METHODS 78 \nTo untangle the complex interactions between invasive species, human activities, and skink populations, we 79 \nadopted a Pattern-Oriented Inference (POI) framework. This approach, inspired by Pa ttern-Oriented Modeling 80 \n(Grimm et al., 1996, 2005; Grimm & Railsback, 2012), uses multiple, independent patterns observed in a system 81 \nto make robust inferences about underlying ecological processes, even in the face of uncertainty. We focused on 82 \nthree key patterns: population density, individual body size, and non -lethal injury rates, wh ich were analyzed 83 \nacross three distinct management zones within the archipelago, representing a gradient of invasive species 84 \npressure and human influence. 85 \n2.1 Study Area and Design 86 \nThe study was conducted in the Fernando de Noronha archipelago (3°51'13.71\"S, 32°25′25.63\"W), a Brazilian 87 \nfederal territory located in the Atlantic Ocean (Figure 1). The archipelago encompasses a total terrestrial area of 88 \n18.22 km², dominated by the main island (16.89 km²) and a series of smaller secondary islands (1.33 km²). The 89 \nclimate of Fernando de Noronha is consistently warm, with sea surface temperatures avera ging 27 °C and 90 \natmospheric temperatures generally between 25 and 31 °C. Annual precipitation is approximately 1,400 mm, 91 \nfalling predominantly from January through July, while August to December constitutes the drier period 92 \n(WeatherSpark, 2024) . Original v egetation on the archipelago is classified as Seasonal Deciduous Forest, 93 \nshowing marked contrasts between the wet and dry seasons (Teixeira & Linsker, 2003). 94 \nThe main island—the only inhabited island—is divided into two contiguous federal protected areas that form 95 \nthe basis of  our study design. The first is PARNAMAR, the strictly protected Marine National Park (IUCN 96 \nCategory II), which covers approximately 70% of the island’s terrestrial area  (11,82 km 2). This site is 97 \nuninhabited, lacks direct anthropogenic subsidies, but contains the full suite of key invasive predators: cats (Felis 98 \n.CC-BY 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted August 30, 2025. ; https://doi.org/10.1101/2025.08.26.672345doi: bioRxiv preprint \n\ncatus), tegus, and rats, as well as egrets . The second is the APA, the inhabited Environmental Protection Area 99 \n(IUCN Category V), which covers the remaining 30% of the island  (5,07 km2). In 201 7, this site supported a 100 \nresident population of approximately 2,900 people and attracted significant tourism. Like PARNAMAR, it 101 \ncontains the full predator suite  with a higher free ranging cat density (Dias et al., 2017) , but it is additionally 102 \ncharacterized by substantial human presence, including urban development, habitat modification, and th e 103 \navailability of anthropogenic subsidies.  A third site was defined to represent a \"baseline\" environment. These 104 \nare the ‘secondary islands’—a group of small, uninhabited islands that are largely free of cattle egrets, invasive 105 \ncats and tegu lizards. While all except one (Ilha do Meio) also host invasive black rats, all secondary islands lack 106 \nthe direct human pressure and subsidies found in the APA. 107 \n2.2 Data Collection and Analysis 108 \nTo investigate our three core patterns, we employed distinct analytical approaches tailored to the available data 109 \nfor each pattern.  All statistical analyses were performed in R version 4.4.2  (R Core Team, 2024) . The full 110 \nworkflow including all data and code—models, parameterization, outputs, and diagnostics—are freely available 111 \non GitHub (see Data Availability Statement) and provided as an annex to this manuscript (Appendix A). 112 \nPattern 1: Population Density 113 \nWe estimated skink density on the three sites using two complementary methods. First, we used point count data 114 \ncollected at standardized survey locations with a 2 -meter radius (area ≈ 12.57 m²) to  model variation in skink 115 \ndensity on PARNAMAR, APA and secondary islands. We fitted a negative binomial generalized linear model 116 \n(GLM) using the MASS package in R  (Venables & Ripley, 2002), with skink counts as the response variable. 117 \nThe model included two fixed-effect predictors: ‘invasive species presence’ (InvasiveSpeciesPresence), a binary 118 \nfactor indicating the presence of the full invasive predator suite versus a reduced suite on the secondary islands, 119 \nand ‘food supplementation’ (FoodSupplementation), a binary factor representing the presence or absence of 120 \nanthropogenic subsidies. To account for the size of the survey area and express the results in terms of density, 121 \nwe included the natural logarithm of the survey area as an offset term.  We explored two alternative model 122 \nformulations to test the robustness o f our results. These included (i) a model with an interaction term between 123 \n‘invasive species presence’  and ‘food supplementation’ , and (ii) a generalized linear mixed -effects model 124 \n.CC-BY 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted August 30, 2025. ; https://doi.org/10.1101/2025.08.26.672345doi: bioRxiv preprint \n\n(GLMM) with a random intercept for study site to account for potential spat ial grouping. Model comparison 125 \nusing Akaike Information Criterion (AIC) confirmed that the simpler GLM provided the best fit to the data, as 126 \nthe interaction term was not estimable due to data sparseness and the random intercept in the GLMM showed 127 \nnegligible variance. We therefore selected the main effects GLM for inference and assessed its adequacy using 128 \nsimulation-based residual diagnostics via the DHARMa package in R (Hartig, 2024), which included checks for 129 \noverdispersion, zero-inflation, and uniformity in residual distributions. 130 \nSecond, for a more detailed assessment of skink density on the main island, we conducted a capture-mark-131 \nrecapture analysis within the APA and PARNAMAR sites. We applied a Poisson-log normal mark-resight model 132 \nusing the RMark package in R (Laake, 2013), which allowed joint estimation of the resighting probability (alpha) 133 \nand the super -population size ( U) at each site. We constructed a candidate set of five biologically motivated 134 \nmodels to test the influence of site and sampling effort on detection and population size parameters. Models were 135 \nranked based on AIC corrected for small sample sizes (AICc), and the model with the lowest AICc was selected 136 \nfor inference. 137 \nPattern 2: Individual Body Size 138 \nTo investigate impacts on individuals body size, we analyzed head length as a stable morphometric trait. Unlike 139 \nvariables such as tail length or body mass, which may vary due to injury or recent feeding, head length reflects 140 \nskeletal structure and is not affected by tail loss or transient weight changes. It also provides a more reliable and 141 \nconsistent measure than snout–vent length, which can be more error-prone due to curvature or movement during 142 \nhandling. Given that head length is a continuous and strictly positive variable, we fitted a gamma generali zed 143 \nlinear model (GLM) with a log link function. An initial model tested for main effects of sex and site on head 144 \nlength. To assess whether environmental conditions affected males and females differently, a second model 145 \nincluded an interaction term ( sex × site). Model fit was evaluated using diagnostic plots, including residuals 146 \nversus fitted values and Q-Q plots, to verify assumptions of the gamma distribution. Estimated marginal means 147 \nand post-hoc pairwise comparisons among group levels were performed wit h Tukey-adjusted p-values were 148 \ncomputed using the emmeans package (Lenth, 2025). 149 \n.CC-BY 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted August 30, 2025. ; https://doi.org/10.1101/2025.08.26.672345doi: bioRxiv preprint \n\nPattern 3: Injury Rates (signs of tail autotomy) 150 \nTo assess variation in predation pressure across regions,  we quantified the frequency of tail autotomy (i.e., tail 151 \nloss or signs of regrowth) . While intraspecific aggression is a known cause of tail autotomy in this species 152 \n(Gasparotto, 2021), a difference in  prevalence of injury across sites can  serve as a robust proxy for sublethal 153 \npredation pressure. For each individual, the presence or absence of autotomy was recorded, and a contingency 154 \ntable was constructed to summarize the number of inju red versus uninjured individuals across the three sites. 155 \nWe then used Pearson’s Chi -squared test, implemented in base R  (R Core Team, 2024) , to test whether the 156 \nproportion of individuals with autotomy differed significantly among sites. Given the potential for low statistical 157 \npower due to limited sample sizes, we conducted a detailed post -hoc power analysis to formally evaluate the 158 \nsensitivity of our Chi -squared test. This analysis, using the pwr package in R  (Champely, 2020), included: (i) 159 \ncalculating the achieved power of the 3x2 omnibus test based on the observed effect size (Cohen’s w); (ii) 160 \nestimating the total sample size required to achieve 80% power; (iii) calculating pairwise power for two -161 \nproportion tests with unequal sample sizes; and (iv) determining the minimum detectable differ ence (MDD) at 162 \n80% power for key contrasts involving the smallest sample sizes. To validate these analytic results, we also 163 \nperformed a simulation-based power analysis with 5,000 replicates. 164 \n3. RESULTS 165 \nOur analyses revealed three distinct patterns in the Noronha skink populations converging to one theory:  the 166 \ncomplex interplay between invasive predators and anthropogenic subsidies. 167 \nPattern 1: A Density Gradient Driven by Invasive Predators and Food Subsidies  168 \nThe skink population density varied significantly across the three sites. For the negative binomial generalized 169 \nlinear model of point counts, residual diagnostics confirmed a good model fit, with simulated residuals closely 170 \nfollowing expected distributions and no evidence of systematic deviation, overdispersion, or outliers. The model 171 \nexplained a modest but reasonable proportion of the variance (Nagelkerke’s R² = 0.17), as is typical for 172 \necological count data. The model estimated the highest density on the secondary islands (0.411 individuals/m², 173 \n95% CI: 0.295 –0.573) and significantly lower densities on the predator -rich main island, with the subsidized 174 \n.CC-BY 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted August 30, 2025. ; https://doi.org/10.1101/2025.08.26.672345doi: bioRxiv preprint \n\nAPA (0.204 ind/m², 95% CI: 0.153–0.273) having a higher density than the unsubsidized PARNAMAR (0.156 175 \nind/m², 95% CI: 0.115–0.213), although not statistically significant (Figure 2). This pattern was, however, further 176 \nclarified by the more detailed capture-mark-recapture analysis.  177 \nThe top-ranked capture-mark-recapture model, which included an effect of site on super -population size ( U), 178 \nhad the lowest AICc (855.39; ΔAICc = 1.80 compared to the next best model; Appendix A, p. 40). Estimated 179 \npopulation sizes were significantly lower in PARNAMAR colonies compared to those in the APA (β = -2.00, p 180 \n< 0.001), despite a significantly higher observation probability for PARNAMAR (β = 0.41, p < 0.05). Together, 181 \nthese results establish a clear pattern, where secondary islands present a significantly larger population density 182 \nas APA, which in turn, presents a larger population than PARNAMAR. 183 \nPattern 2: Size Structure Reveals Demographic Truncation on the Main Island 184 \nThe population's size structure did not directly correspond to the density pattern, revealing a critical discrepancy 185 \non the main island. While the APA supported a higher density than PARNAMAR, its adult males were no larger, 186 \npointing to differential mortality pressures (Figure 3). A gamma generalized linear model  that included an 187 \ninteraction between sex and site provided a better fit to the head length data (AIC = 24.116) than a model with 188 \nonly main effects (AIC = 25.051). The sex × site interaction term was significant (sexM:sitePARNA, p = 0.0285), 189 \nindicating that differences in size between sites were primarily driven by changes in the male population. Model 190 \ndiagnostics confirmed data quality with no outliers detected, and residuals displayed no major deviations from 191 \nmodel assumptions (see Appendix A).  192 \nPost-hoc pairwise comparisons (Tukey-adjusted) revealed the specific nature of this interaction (Figure 3). While 193 \nthere were no significant size differences among females across the three sites (e.g., females on secondary islands 194 \nvs. females in the APA, p = 1.00; females in the APA vs. females in the PARNAMAR, p = 0.99), the effect on 195 \nmales was pronounced. Males on the secondary islands were significantly larger than males from both the APA 196 \n(p = 0.0214) and PARNAMAR (p = 0.0195). There was no statistical size difference between males inhabiting 197 \nthe APA and PARNAMAR (p = 0.9998). This establishes a clear pattern of demographic truncation, where the 198 \nlargest size classes of males are notably absent from the main island populations, regardless of subsidy presence. 199 \n.CC-BY 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted August 30, 2025. ; https://doi.org/10.1101/2025.08.26.672345doi: bioRxiv preprint \n\nPattern 3: Injury Rates Align with a High-Pressure Environment on the Main Island  200 \nProviding a mechanistic link to the observed size truncation, rates of non-lethal injury (tail autotomy) followed 201 \na trend of elevated pressure on the main island. The proportion of injured individuals was highest in the APA 202 \n(29.3%), followed by PARNAMAR (25.0%), and was lowest on the Secondary Islands (15.0%).  Despite this 203 \nclear directional pattern, the overall difference was not statistically significant (Pearson’s Chi-squared test: χ² = 204 \n1.61, df = 2, p = 0.45). Our post-hoc power analysis revealed that this was a consequence of low statistical power. 205 \nWith our realized sample sizes, the achieved power to detect an effect of the observed magnitude was only ~19%, 206 \nand an estimated ~729 individuals would be required to reach the standard 80% power threshold. 207 \nThe minimum detectable difference for comparisons involving the small secondary island sample was 32.6–34.1 208 \npercentage points, indicating only very large effects could be reliably detected. Together, these analyses confirm 209 \nour interpretation that the non-significant test result is due to statistical limitations rather than the absence of a 210 \nbiological effect. The observed trend of higher injury rates on the main island the refore provides a final, 211 \ncorroborating line of evidence that aligns with the body size data and supports the hypothesis that skinks, 212 \nparticularly in the APA, experience a higher rate of sublethal predator encounters. 213 \n4. DISCUSSION 214 \nMaking robust management dec isions for species of conservation concern often requires synthesizing 215 \ninformation from multiple, imperfect sources of data. In this study, we employed a 'Pattern-Oriented Inference' 216 \nframework to integrate results from population density models, individual morphometrics, and rates of injury to 217 \nbuild a cohesive understanding of the complex pressures facing Trachylepis atlantica , the island endemic 218 \nNoronha skink lizard. The convergence of these distinct patterns provides a powerful line of evidence that 219 \ntranscends the limitations of any single analysis. It resolves an apparent ecological paradox by revealing that the 220 \ninhabited area of the main island functions as a pred ator death -trap, a dynamic with profound and urgent 221 \nimplications for the conservation of this endemic species. 222 \nOur results establish a clear density gradient across the sites (secondary islands > APA > PARNAMAR), which 223 \ncan be explained by the interplay of top-down and bottom-up forces. The high density on the secondary islands 224 \n.CC-BY 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted August 30, 2025. ; https://doi.org/10.1101/2025.08.26.672345doi: bioRxiv preprint \n\nserves as a crucial baseline, demonstrating the species' potential in an environment with reduced predator 225 \npressure, even without anthropogenic subsidies. Conversely, the significantly suppressed density in the predator-226 \nrich PARNAMAR reflects the strong top-down control exerted by the full suite of invasive predators, particularly 227 \ncats, tegus, cattle egrets,  and rats (Gaiotto et al., 2020; Micheletti et al., 202 0). The most insightful finding, 228 \nhowever, is the intermediate density in the APA. Here, anthropogenic food subsidies appear to provide a bottom-229 \nup stimulus, likely boosting skink recruitment and survival enough to elevate the population density above that 230 \nof the unsubsidized PARNAMAR. However, while subsidy -driven increases have been observed elsewhere  231 \n(Plaza & Lambertucci, 2017) , our work demonstrates a critical caveat: this apparent recovery can conceal the 232 \ntransition of a habitat into a high-mortality sink. 233 \nThe key to deciphering the system lies in how size-selective predation resolves the apparent paradox on the main 234 \nisland. Predation is rarely random, and traits that increase conspicuousness, such as large body size and territorial 235 \nbehaviour, often elevate mortality risk. For instance, Bateman and Fleming (2011) demonstrated that large, 236 \nterritorial adult m ale anoles suffered significantly higher rates of sublethal predation attempts from cats, 237 \nproviding a direct, evidence -based mechanism for the size -selective pressure we propose is acting on the 238 \nNoronha skink. In the APA, this pressure is amplified because anthropogenic subsidies support high densities of 239 \nboth skinks and their invasive predators (Dias et al., 2017), potentially increasing lethal encounters. Moreover, 240 \nhuman activity in the APA reduces the availability of alternative native prey (particularly birds), likely 241 \nconcentrating predation pressure on skinks as one of the few abundant resources remaining.  The outcome is a 242 \nstark pattern of demographic tr uncation, where the selective removal of the largest and oldest males leaves a 243 \nhigh-turnover population dominated by smaller, younger individuals. This directly explains why the subsidized 244 \nAPA, despite supporting more skinks, has males no larger than those  in the resource -poor, predator -rich 245 \nPARNAMAR. The trend of higher injury rates in the APA provides a final, corroborating line of evidence, 246 \nconfirming that this truncated size structure is a consequence of relentless mortality, not stunted growth. 247 \nThe con vergence of these patterns —subsidized density, a truncated male size structure, and elevated injury 248 \nrates—strongly supports our central hypothesis: the inhabited APA functions as a predator death-trap. Ecological 249 \ntraps occur when an environmental cue, whic h normally indicates high-quality habitat, leads an organism to a 250 \n.CC-BY 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted August 30, 2025. ; https://doi.org/10.1101/2025.08.26.672345doi: bioRxiv preprint \n\nlow-quality patch where its fitness is compromised (Patten & Kelly, 2010). In Noronha, the abundance of food 251 \nin the APA likely serves as an attractive cue for skinks, concentrating their population. However, these same 252 \nsubsidies also support a high -density, subsidized predator community  (Dias et al., 2017) . The result is a fatal 253 \ncombination of high prey density and high predator density in the same location, creating an intensified predator-254 \nprey dynamic that transforms the APA from a subsidized refuge into a population sink. 255 \nOur findings reveal a critical and non -obvious management trap that could have catastrophic consequences : 256 \nremoving food subsidies in the APA without first reducing invasive predators. Because subsidies currently fuel 257 \nhigh recruitment, eliminating them in isolation would suppress prey production while leaving a dense predator 258 \ncommunity intact —thereby increasing per -capita predation risk and plausibly precipit ating a population 259 \ncollapse, as suggested for the species in theoretical studies (Gasparini et al., 2007) . Effective conservation 260 \ntherefore requires an integrated sequence: (i) implement coordinated, sustained control of key invasive predators 261 \n(e.g., cats, tegus, cattle egrets, rats); (ii) only then phase down anthropogenic subsidies via improved waste 262 \nmanagement and feeding restrictions; and (iii) track explicit triggers (density, size‐structure, and injury rates) 263 \nunder a real-time adaptive monitoring fram ework (Micheletti et al., 2025) . This strategy addresses both top -264 \ndown and bottom-up drivers simultaneously, avoiding management-induced feedbacks and aligning actions with 265 \nthe multi-line evidence that the APA currently functions as a predator death-trap. 266 \nOur integrated results provide strong, cohesive evidence that the Noronha skink is facing cryptic but severe 267 \nthreats that warrant s re-assessing the species as at least “Vulnerable” under IUCN criteria (A2: observed 268 \npopulation decline; C1: small and declining population size; IUCN, 2014), a conclusion previously obscured by 269 \nits apparent abundance in the APA. This concern is further heightened by its insular life -history strategy: the 270 \nspecies exhibits a reduced, seasonal reproductive pattern compared with continental congeners (Migliore et al., 271 \n2017), reflecting an evolutionary history in a predator-free environment. Such traits likely lower its resilience to 272 \nthe novel and intense predation pressures it currently faces.  This case study therefore ser ves as a critical 273 \ncautionary tale for conservation, demonstrating the danger of relying on single metrics like population density 274 \nin complex, subsidized ecosystems where a high density can mask an underlying population sink and create a 275 \ndangerous illusion of security. These findings also inform Brazil’s invasive species strategy, highlighting the 276 \n.CC-BY 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted August 30, 2025. ; https://doi.org/10.1101/2025.08.26.672345doi: bioRxiv preprint \n\nneed for integrated subsidy and predator control rather than piecemeal actions. Integrated eradication campaigns 277 \non islands elsewhere , such as New Zealand (Griffiths et al., 2012) , demonstrate the feasibility of coordinated 278 \ninvasive species and subsidies’ control (even if for public-safety or operational control), which could provide a 279 \nmodel for Noronha. 280 \nOur findings likely extend beyond Noronha. Similar subsidy–predator interactions have been reported for large 281 \nlizards (Jessop et al., 2012) and free-ranging cats (Fleming et al., 2022; Kazato et al., 2020; Maeda et al., 2019) 282 \non continental areas. F ood waste has even been directly linked to elevating carrying capacity and sustaining  283 \npredator guilds (Almaraz et al., 2022). We suggest that the predator death -trap dynamic may be a general risk 284 \nwherever subsidies elevate recruitment in prey populations but simultaneously fuel predator communities.  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It is made \nThe copyright holder for this preprintthis version posted August 30, 2025. ; https://doi.org/10.1101/2025.08.26.672345doi: bioRxiv preprint \n\n 401 \n  402 \nFigure 1. Map of the Fernando de Noronha archipelago, Brazil, depicting the spatial distribution of study sites and sampling efforts in \nrelation to key environmental drivers. The main island is divided into the protected PARNAMAR and the inhabited APA, representing \nzones with varying anthropogenic subsidies. Secondary islands (dark grey) represent areas with reduced invasive predator presence. \nYellow circles mark point count survey locations, and green circles denote capture-mark-recapture survey locations. \n.CC-BY 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted August 30, 2025. ; https://doi.org/10.1101/2025.08.26.672345doi: bioRxiv preprint \n\n  403 \nFigure 2. Skink density is strongly suppressed by the full invasive predator suite, a conclusion refined by a capture-mark-recapture \nanalysis. The main bars show estimated marginal mean densities of the Noronha skink (individuals / m²) from a Negative Binomial \nGLM of broad -scale point counts. Error bars represent 95% confidence intervals. Different letters (a, b) indicate stati stically \nsignificant differences based on this GLM, which shows that sites with a reduced predator suite support significantly higher densities \nthan main island sites. The bracket and annotation highlight a key finding from a separate, more detailed capture-mark-recapture \nanalysis conducted only on the main island: skink population size was confirmed to be significantly higher in the subsidized APA \ncompared to the unsubsidized PARNAMAR (p < 0.001). \n.CC-BY 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted August 30, 2025. ; https://doi.org/10.1101/2025.08.26.672345doi: bioRxiv preprint \n\n 404 \nFigure 3. Demographic truncation in male skinks is correlated with higher rates of non -lethal injury. While female skinks \n(left panels) show no significant differences in head length across sites  (mean ± 95% CI ), males (right panels) are \nsignificantly larger on the secondary islands compared to the main island sites (APA and PARNA) where we observe lower \ninvasive species and anthropogenic pressure . This smaller male body size on the main island coincides with a h igher \nproportion of individuals exhibiting tail autotomy (a proxy for predation pressure), particularly in the APA. Letters indicate \nsignificant differences (p < 0.05) in head length only. \n.CC-BY 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted August 30, 2025. ; https://doi.org/10.1101/2025.08.26.672345doi: bioRxiv preprint","source_license":"CC-BY-4.0","license_restricted":false}