Probability Of Population Extinction Research Articles

Stochastic differential equation models for tumor population growth

In this paper we develop stochastic differential equation models for tumor population growth with immunization. We investigate especially the effect of a multiplicative noise on the progression of tumor evolution. Then, we perform a computational analysis in order to assess the behavior of the solution process. With this, we analyze the population extinction probability and the probability of persistence. In the case of persistence we analyze the behavior of the steady probability density and the evolution of its mean and variance. We further calculate the mean first passage time in order to describe the probability transitions between the extinction state and the state of the stable tumor. It is found that an increasing noise intensity rate enhances the probability of the extinction of the tumor.

The impact of dams on the population viability of a migratory fish in the Yangtze River, China

Abstract The global diversity of freshwater fish has been greatly reduced as a result of human alteration. In the Yangtze River, China, the species composition has changed hugely owing to dam construction and overfishing. However, insufficient data have prevented the status of several fish species being evaluated, including that of largemouth bronze gudgeon (Coreius guichenoti), which is a commercially important endemic species. This study describes the effects of the Xiangjia Dam on populations of C. guichenoti. A multivariate autoregressive state‐space model was applied to catch per unit effort data derived from drifting gill nets deployed in the mid‐channel before (2005–2012) and after (2013–2018) the construction of the dam. The analysis indicated that the mean instantaneous population growth rate of the population was −0.252 over the entire period and that the growth rates of both total and local populations have declined. Before the impoundment, the probability of population extinction was close to 1, which was the result of overfishing. After impoundment, the probability of extinction became 1 at all sites, and the time until quasi‐extinction has decreased. Based on the Euler–Lotka equation, the reproductive parameter (á) has declined by more than 95%. The results show that the population of C. guichenoti in the upper Yangtze is almost certain to become extinct under the current conditions because of the Xiangjiaba Dam blocking migration routes. To protect this population, conservation measures, such as hatchery supplementation, the removal of small hydropower stations in the tributaries and the relocation of fish, are required.

A Trade-Off between Robustness to Environmental Fluctuations and Speed of Evolution.

AbstractUnderstanding how a species' life history affects its capacity to cope with environmental changes is important in the context of rapid climate changes. Reinterpreting previous results from a well-developed theoretical framework, we show that a trade-off exists between a species' ability to genetically adapt to long-term gradual environmental changes and its ability to demographically resist short-term environmental perturbations, causing variation in its vital rates. Surprisingly, this important insight has not been made formally explicit before. Choosing archetypal life histories along the fast-slow pace-of-life continuum and modeling their eco-evolutionary dynamics, we further show that long-lived species have larger demographic robustness to interannual fluctuations but limited trait evolutionary responses in gradually changing environments. In contrast, short-lived species had larger evolvability but reduced demographic robustness. This trade-off bears heavily on extinction probabilities of populations tracking fast trait changes in stochastic environments. Faster trait evolution in short-lived species came at the expense of their higher sensitivity to short-term fluctuations, causing higher extinction rates than for long-lived species. Long-lived species persisted better on short timescales but built maladaptation and an extinction debt over time. This work shows how modeling species' eco-evolutionary dynamics can help to assess species vulnerability to environmental changes.

A Simulation Model of Sustained-Yield Harvest for Northern Bobwhite in South Texas

Recommended sustainable harvest rates for northern bobwhite (Colinus virginianus) vary greatly and range from 25% to 70% of the prehunt population. Because northern bobwhite populations have declined across their geographic range, determining sustainable harvest levels is critical for effective management. Our objectives were to use simulation modeling to identify sustainable rates of bobwhite harvest, probability of population persistence, and minimum viable population estimates. We also conducted a sensitivity analysis to evaluate the impacts of harvest on northern bobwhite populations in Texas, USA. We constructed a simulation model using Program STELLA 9.0 for a hypothetical northern bobwhite population on 800 ha in the South Texas Plains USA and modeled population dynamics to 100 years over a range of harvest rates (0–40%). A 20% harvest rate produced the greatest average yields (mean ± standard error = 231 ± 10 bobwhites harvested/year). Given a quasi-extinction criterion of ≤40 bobwhites (≤0.05 bobwhite/ha), a 30% harvest rate resulted in a high probability of quasi-extinction (PE = 0.75) within 47.8 ± 2.3 years. A 40% harvest rate was not sustainable (PE = 1.0), with quasi-extinction occurring within 15.5 ± 2.6 years. Harvesting northern bobwhite populations in the South Texas Plains at rates of 20−25% of the prehunt population should maximize long-term harvest while minimizing the probability of population extinction. Spring densities of 0.60−0.80 bobwhite/ha may represent minimum viable spring densities for northern bobwhite populations in the South Texas Plains as these are the densities associated with sustainable 20-25% harvest rates. Harvest rates >30% are likely to be excessive with respect to long-term population persistence for northern bobwhite populations in the South Texas Plains.

Environmental range per unit space determines a unimodal pattern of species richness along a heterogeneity gradient

Although many studies have focused on the effects of the environment and area on local patterns of species richness, few studies have demonstrated how to reconcile the availability of more niches with smaller habitat areas in heterogeneous localities. Here, the environmental range that a species prefers was defined as a niche; a space was defined as an available space if the environmental range of the space matches a niche; and the metric ‘environmental range per unit space (ERUS)' was presented to describe the heterogeneity of localities. Because the spaces with stressful environmental ranges, outside the niche, increased with increasing heterogeneity, available spaces did not continue to indefinitely increase, but the proportion of available spaces in spaces was low at high heterogeneous localities. Consequently, the probability of species occurring in their respective available spaces was unimodal. Due to the presence of large spaces in homogenous localities and more spaces in heterogeneous localities, the interval distances between nonadjacent spaces were large in these localities. Together, the changes in the number and proportion of available spaces and distance between spaces determined the unimodal probability of species dispersing into their respective available spaces. Thus, the probability of species coexisting was unimodal because it is important for coexisting species to grow in their respective available spaces. The probability of population extinction increased with increasing heterogeneity because the available spaces became narrower. In this way, the ERUS strongly influence species richness: a unimodal richness along the heterogeneity gradient occurred in suitable, suboptimal and stressful environments and a unimodal algae richness occurred in a lake and river. These results challenge the viewpoint that richness increases with heterogeneity, providing information about the conservation of richness in very homogeneous and heterogeneous regions, and highlighting the importance of balancing the roles of environment and space in understanding and predicting richness.

A cumulative effects model for population trajectories of resident killer whales in the Northeast Pacific

Like numerous species at risk, the resident killer whale populations of the Northeast Pacific are vulnerable to the cumulative effects of anthropogenic threats. A Pathways of Effects conceptual model summarised the current understanding of each threat (prey availability, acoustic and physical disturbance, and contaminants), threat interactions, and potential impacts to fecundity and mortality. A Population Viability Analysis utilised the most recent available data to quantify impacts of threats on population parameters. The impacts of individual and cumulative threat scenarios on modelled Southern and Northern Resident Killer Whale populations were compared to the observed population demographics to define a model that best captured the real world dynamics. Of the individual and combined threat models tested, the cumulative model incorporating all threats predicted demographic rates closest to those observed for both populations. Recent low Chinook salmon abundance and its interactions with vessel disturbance and contamination strongly influenced modelled killer whale population dynamics. The cumulative effects population viability analysis model projected a mean increase in the modelled Northern Resident Killer Whale population to the carrying capacity within 25 years. In contrast, the mean modelled Southern Resident Killer Whale population trajectory was projected to decline under current conditions, with a 26% probability of population extinction, and in those projections, extinction was estimated to occur after 86 (± 11) years. Our results highlight the importance of considering the collective impact of multiple threats to imperilled species and the necessity of testing management and mitigation measures aimed at recovery using a holistic, validated model.

A logistic-harvest model with allee effect under multiplicative noise

This work is devoted to the study of a stochastic logistic growth model with and without the Allee effect. Such a model describes the evolution of a population under environmental stochastic fluctuations and is in the form of a stochastic differential equation driven by multiplicative Gaussian noise. With the help of the associated Fokker–Planck equation, we analyze the population extinction probability and the probability of reaching a large population size before reaching a small one. We further study the impact of the harvest rate, noise intensity and the Allee effect on population evolution. The analysis and numerical experiments show that if the noise intensity and harvest rate are small, the population grows exponentially, and upon reaching the carrying capacity, the population size fluctuates around it. In the stochastic logistic-harvest model without the Allee effect, when noise intensity becomes small (or goes to zero), the stationary probability density becomes more acute and its maximum point approaches one. However, for large noise intensity and harvest rate, the population size fluctuates wildly and does not grow exponentially to the carrying capacity. So as far as biological meanings are concerned, we must catch at small values of noise intensity and harvest rate. Finally, we discuss the biological implications of our results.

Genetic variation in resistance and high fecundity impede viral biocontrol of invasive fish

Abstract Common carp Cyprinus carpio is one of the top global invasive vertebrates and can cause significant ecological damage. The Australian Government's National Carp Control Program (NCCP) proposes to release Koi herpesvirus (KHV) to eradicate feral carp in one of the largest ecological interventions ever attempted. Ecological and human health risks have been highlighted regarding the release of a highly pathogenic viral biocontrol for an aquatic species. The efficacy of KHV has also been questioned, and it has not been demonstrated to produce lasting population reductions. We developed an individual‐based model (IBM) to examine the ecological and evolutionary response of a carp population after KHV release. This simulated the interaction between fish life history, viral epidemiology, host genetic resistance and population demography to critically evaluate the impact of KHV release under optimal conditions and a ‘best‐case scenario’ for disease transmission. KHV will rarely result in prolonged reductions or population extinctions. Crucially, realistic scenarios result in a rapidly rebounding population of resistant individuals. Additional measures aimed to reduce carp population recovery rate (e.g. with genetic engineering) require rapid efficacy to significantly reduce carp numbers alongside KHV. Fish fecundity has an overwhelming influence on viral efficacy as a biocontrol agent when combined with genetic resistance within a population. A high probability of population extinction is only met when carp fecundity is reduced to 1% of biological observations. Synthesis and applications. We use an individual‐based model to evaluate the efficacy of Koi herpesvirus biocontrol in Common Carp, and find that high host fecundity combined with genetic resistance results in rapid population rebound after initial large fish kills. Biocontrol approaches relying on natural selection lose efficacy over successive generations as resistance genes increase in frequency. Given the intense logistical effort and risks to ecosystems and human health associated with large fish kills after viral release, we suggest that sustained manual removal, alongside ecological restoration to favour recovery of native species, provides a risk‐free approach to reducing populations.

Insights From the Ecology of Information to Cancer Control.

Uniquely in nature, living systems must acquire, store, and act upon information. The survival and replicative fate of each normal cell in a multicellular organism is determined solely by information obtained from its surrounding tissue. In contrast, cancer cells as single-cell eukaryotes live in a disrupted, heterogeneous environment with opportunities and hazards. Thus, cancer cells, unlike normal somatic cells, must constantly obtain information from their environment to ensure survival and proliferation. In this study, we build upon a simple mathematical modeling framework developed to predict (1) how information promotes population persistence in a highly heterogeneous environment and (2) how disruption of information resulting from habitat fragmentation increases the probability of population extinction. Because (1) tumors grow in a highly heterogeneous microenvironment and (2) many cancer therapies fragment tumors into isolated, small cancer cell populations, we identify parallels between these 2 systems and develop ideas for cancer cure based on lessons gleaned from Anthropocene extinctions. In many Anthropocene extinctions, such as that of the North American heath hen (Tympanuchus cupido cupido), a large and widespread population was initially reduced and fragmented owing to overexploitation by humans (a “first strike”). After this, the small surviving populations are vulnerable to extinction from environmental or demographic stochastic disturbances (a “second strike”). Following this analogy, after a tumor is fragmented into small populations of isolated cancer cells by an initial therapy, additional treatment can be applied with the intent of extinction (cure). Disrupting a cancer cell’s ability to acquire and use information in a heterogeneous environment may be an important tactic for causing extinction following an effective initial therapy. Thus, information, from the scale of cells within tumors to that of species within ecosystems, can be used to identify vulnerabilities to extinction and opportunities for novel treatment strategies.

Uncertainty and sensitivity analyses of extinction probabilities suggest that adult female mortality is the weakest link for populations of tsetse (Glossina spp).

BackgroundA relatively simple life history allows us to derive an expression for the extinction probability of populations of tsetse, vectors of African sleeping sickness. We present the uncertainty and sensitivity analysis of the extinction probability, to offer key insights into factors affecting the control or eradication of tsetse populations.MethodsWe represent tsetse population growth as a branching process, and derive closed form estimates of population extinction from that model. Statistical and mathematical techniques are used to analyse the uncertainties in estimating extinction probability, and the sensitivity of the extinction probability to changes in input parameters representing the natural life history and vital dynamics of tsetse populations.ResultsFor fixed values of input parameters, the sensitivity of extinction probability depends on the baseline parameter values. Extinction probability is most sensitive to the probability that a female is inseminated by a fertile male when daily pupal mortality is low, whereas the extinction probability is most sensitive to daily mortality rate for adult females when daily pupal mortality, and extinction probabilities, are high. Global uncertainty and sensitivity analysis show that daily mortality rate for adult females has the highest impact on the extinction probability.ConclusionsThe high correlation between extinction probability and daily female adult mortality gives a strong argument that control techniques which increase daily female adult mortality may be the single most effective means of ensuring eradication of tsetse population.

Giraffe translocation population viability analysis

Most populations of giraffes have declined in recent decades, leading to the recent IUCN decision to upgrade the species to Vulnerable status, and some subspecies to Endangered. Translocations have been used as a conservation tool to re-introduce giraffes to previously occupied areas or establish new populations, but guidelines for founding populations are lacking. To provide general guidelines for translocation projects regarding feasibility, we simulated various scenarios of translocated giraffe populations to identify viable age and sex distributions of founding populations using population viability analysis (PVA) implemented in Vortex software. We explored the parameter space for demography and the genetic load, examining how variation in founding numbers and sex ratios affected 100 yr probability of population extinction and genetic diversity. We found that even very small numbers of founders (N ≤ 10 females) can appear to be successful in the first decades due to transient positive population growth, but with moderate population growth rate and moderate genetic load, long-term population viability (probability of extinction <0.01) was only achieved with ≥30 females and ≥3 males released. To maintain >95% genetic diversity of the source population in an isolated population, 50 females and 5 males are recommended to compose the founding population. Sensitivity analyses revealed first-year survival and reproductive rate were the simulation parameters with the greatest proportional influence on probability of extinction and genetic diversity. These simulations highlight important considerations for translocation success and data gaps including true genetic load in wild giraffe populations.

Spatial heterogeneity stabilizes predator-prey interactions at the microscale while patch connectivity controls their outcome.

Natural landscapes are both fragmented and heterogeneous, affecting the distribution of organisms, and their interactions. While predation in homogeneous environments increases the probability of population extinction, fragmentation/heterogeneity promotes coexistence and enhances community stability as shown by experimentation with animals and microorganisms, and supported by theory. Patch connectivity can modulate such effects but how microbial predatory interactions are affected by water-driven connectivity is unknown. In soil, patch habitability by microorganisms, and their connectivity depend upon the water saturation degree (SD). Here, using the obligate bacterial predator Bdellovibrio bacteriovorus, and a Burkholderia prey, we show that soil spatial heterogeneity profoundly affects predatory dynamics, enhancing long-term co-existence of predator and prey in a SD-threshold dependent-manner. However, as patches and connectors cannot be distinguished in these soil matrices, metapopulations cannot be invoked to explain the dynamics of increased persistence. Using a set of experiments combined with statistical and physical models we demonstrate and quantify how under full connectivity, predation is independent of water content but depends on soil microstructure characteristics. In contrast, the SD below which predation is largely impaired corresponds to a threshold below which the water network collapses and water connectivity breaks down, preventing the bacteria to move within the soil matrix.

Enhanced reproductive success revealed key strategy for persistence of devastated populations in Himalayan food‐deceptive orchid, Dactylorhiza hatagirea

AbstractAnthropogenic disturbances adversely affect populations of rare and endemic plants, resulting in reduction of their population size and performance. Among different plant groups, deceptive terrestrial orchids are vulnerable and possess greater extinction risks because of rarity in occurrence. To understand the response of food‐deceptive terrestrial orchids to disturbances, we selected Dactylorhiza hatagirea as our representative species, which is endemic to Himalaya, and studied its natural populations. This species is rare for being habitat specific, pollination limited and threatened in its natural habitats. We tested the hypothesis that disturbances lead to reduction in population size and plant performance of food‐deceptive terrestrial orchids. For assessing the impact of disturbance, two contrasting groups, heavily devastated (HD) and lightly devastated (LD), were identified on the basis of frequency and intensity of disturbance (harvesting of plant for tubers) by interviewing local people, medicinal plant extractors and shepherds. HD sites, in comparison to LD sites, were found to have smaller population sizes, but showed an increase in plant growth traits (plant height, specific leaf area, leaf N and specific shoot length). Similarly, plants at HD sites were found to have invested less in inflorescence (inflorescence size, inflorescence length, inflorescence length fraction and flowers per length), but despite that showed higher reproductive success. This was a clear indication of enhanced performance of its populations driven by disturbances. Our findings suggested that food‐deceptive species in small populations tend to reduce the probability of population extinction and have the capability to recover rapidly if conserved in time.

Dynamics of starvation and recovery predict extinction risk and both Damuth\u2019s law and Cope\u2019s rule

The eco-evolutionary dynamics of species are fundamentally linked to the energetic constraints of their constituent individuals. Of particular importance is the interplay between reproduction and the dynamics of starvation and recovery. To elucidate this interplay, here we introduce a nutritional state-structured model that incorporates two classes of consumers: nutritionally replete, reproducing consumers, and undernourished, nonreproducing consumers. We obtain strong constraints on starvation and recovery rates by deriving allometric scaling relationships and find that population dynamics are typically driven to a steady state. Moreover, these rates fall within a “refuge” in parameter space, where the probability of population extinction is minimized. We also show that our model provides a natural framework to predict steady state population abundances known as Damuth's law, and maximum mammalian body size. By determining the relative stability of an otherwise homogeneous population to a competing population with altered percent body fat, this framework provides a principled mechanism for a selective driver of Cope’s rule.

A stochastic model for the probability of malaria extinction by mass drug administration

BackgroundMass drug administration (MDA) has been proposed as an intervention to achieve local extinction of malaria. Although its effect on the reproduction number is short lived, extinction may subsequently occur in a small population due to stochastic fluctuations. This paper examines how the probability of stochastic extinction depends on population size, MDA coverage and the reproduction number under control, Rc. A simple compartmental model is developed which is used to compute the probability of extinction using probability generating functions. The expected time to extinction in small populations after MDA for various scenarios in this model is calculated analytically.ResultsThe results indicate that mass drug administration (Firstly, Rc must be sustained at Rc < 1.2 to avoid the rapid re-establishment of infections in the population. Secondly, the MDA must produce effective cure rates of >95% to have a non-negligible probability of successful elimination. Stochastic fluctuations only significantly affect the probability of extinction in populations of about 1000 individuals or less. The expected time to extinction via stochastic fluctuation is less than 10 years only in populations less than about 150 individuals. Clustering of secondary infections and of MDA distribution both contribute positively to the potential probability of success, indicating that MDA would most effectively be administered at the household level.ConclusionsThere are very limited circumstances in which MDA will lead to local malaria elimination with a substantial probability.

Pesticide reduces bumblebee colony initiation and increases probability of population extinction.

Pollinators are in global decline, and agricultural pesticides are a potential driver of this. Recent studies have suggested that pesticides may significantly impact bumblebee colonies, an important and declining group of pollinators. Here we show that colony founding queens, a critical yet vulnerable stage of the bumblebee lifecycle, are less likely to initiate a colony after exposure to thiamethoxam, a neonicotinoid insecticide. Bombus terrestris queens were exposed to field-relevant levels of thiamethoxam, and two natural stressors, the parasite Crithidia bombi, and varying hibernation durations. Exposure to thiamethoxam produced a 26% reduction in the proportion of queens that laid eggs, and advanced the timing of colony initiation, although we did not detect impacts of any experimental treatment on the ability of queens to produce adult offspring during the 14-week experimental period. As expected from previous studies, hibernation duration also had an impact on egg laying, but there was no significant interaction with insecticide treatment. Modelling the impacts of a 26% reduction in colony founding on population dynamics dramatically increased the likelihood of population extinction. This shows that neonicotinoids can affect this critical stage in the bumblebee lifecycle, and may have significant impacts on population dynamics.

A clear and present danger: impacts of poisoning on a vulture population and the effect of poison response activities

AbstractVultures in Africa are being poisoned deliberately by poachers to prevent the birds alerting authorities to the poachers’ illegal activities, or for harvesting and sale of body parts for use in witchcraft. Hundreds of vultures can be killed at a single poisoned elephant Loxodonta africana carcass, and although field staff trained in poison response activities can limit the damage, mortalities remain numerous. We used the population viability analysis programme VORTEX to simulate seven 100-year-long scenarios investigating various rates of poisoning mortalities and the remedial effects of poison response activities on a population of Critically Endangered white-backed vultures Gyps africanus breeding in Kruger National Park, South Africa. In six scenarios the population declined (λ &lt; 1); in three scenarios the population remained extant over the 100-year simulations but declined by 60–90% from a starting size of 2,400 individuals. In two scenarios one poisoned elephant carcass left untreated and causing the greatest number of vulture deaths was modelled as a catastrophic event with a 50% probability of annual occurrence, which resulted in a 100% probability of population extinction, with a mean time to extinction of 55–62 years. Effective poison response activities were modelled as a 70% reduction of mortality at each poisoned elephant carcass and resulted in population persistence after 100 years but with a c. 90% reduction in size (final n = 205). We highlight that although poison response activities will not prevent poisoning from occurring, they form an essential part of wider conservation actions designed to prevent local extinctions of vultures or other vulnerable species.

Assessment of demographic bottleneck in Indian horse and endangered pony breeds.

Bottleneck study of any continuously decreasing population is important and crucial issue in its conservation strategies including the analysis of simulated and real populations (Williamson-Natesan 2005; Busch et al. 2007). A bottleneck in a population can increase the rate of inbreeding, loss of genetic variation, fixation of deleterious alleles, thereby reducing evolutionary potential of animals to adapt to new selective pressures, such as climatic change or shift in available resources and increasing the probability of population extinction (Frankham 1995). The genetic changes caused by a bottleneck in a population’s effective size can lower the possibility of population’s persistence (Vrijenhoek 1994; Newman and Pilson 1997). Various endangered or threatened populations have been reported to have low levels of genetic variations (Vrijenhoek 1994; Gibbs et al. 1998). However, all the populations that have been reduced in size did not show quantifiable lower levels of genetic diversity (Waldman et al. 1998) which also necessitates the assessment of bottlenecks with molecular marker for their conservation and evolutionary genetics. India is bestowed with a rich biodiversity of equids in the form of two horses (Marwari and Kathiawari) and four endangered pony breeds (Bhutia, Spiti, Manipuri and Zanskari) besides indigenous donkeys and wild asses (Gupta et al. 2012a,b; 2014). Overall population of these breeds, specially endangered pony breeds has declined in most of the pockets in their home tracts (less than 1000) which is due to their decreased utility and increased modernization of transport system even in hilly and difficult terrains (Gupta et al. 2012a, b). It is expected that bottleneck might have taken

Modelling the negative effects of landscape fragmentation on habitat selection

Landscape fragmentation constrains movement of animals between habitat patches. Fragmentation may, therefore, limit the possibilities to explore and select the best habitat patches, and some animals may have to cope with low-quality patches due to these movement constraints. If so, these individuals experience lower fitness than individuals in high-quality habitat. I explored this negative effect of fragmentation on habitat selection in a modelling study. Model landscapes were generated containing different amounts of habitat with differences in the degree of connectivity. In these landscapes, the behaviour of two model species was simulated with different dispersal ranges. I found that habitat selection of the species with limited dispersal range increasingly deviates from optimal selection when fragmentation increases. This effect of fragmentation on habitat selection largely limits the spatial distribution of species with limited dispersal range because constrained habitat selection is expected to result in lower mean reproductive output when more individuals occur in low-quality habitat. In addition to the often suggested causes for extinction in small, isolated patches, i.e. increased sensitivity to environmental and demographic stochasticity, constrained habitat selection may lead to an increase in extinction probability of populations when a large fraction of the individuals occur in low-quality habitat.

InSTREAM-Gen: Modelling eco-evolutionary dynamics of trout populations under anthropogenic environmental change

Current rates of environmental change are exceeding the capacity of many populations to adapt to new conditions and thus avoid demographic collapse and ultimate extinction. In particular, cold-water freshwater fish species are predicted to experience strong selective pressure from climate change and a wide range of interacting anthropogenic stressors in the near future. To implement effective management and conservation measures, it is crucial to quantify the maximum rate of change that cold-water freshwater fish populations can withstand. Here, we present a spatially explicit eco-genetic individual-based model, inSTREAM-Gen, to predict the eco-evolutionary dynamics of stream-dwelling trout under anthropogenic environmental change. The model builds on a well-tested demographic model, which includes submodels of river dynamics, bioenergetics, and adaptive habitat selection, with a new genetic module that allows exploration of genetic and life-history adaptations to new environments. The genetic module models the transmission of two key traits, size at emergence and maturity size threshold. We parameterized the model for a brown trout (Salmo trutta L.) population at the warmest edge of its range to validate it and analyze its sensitivity to parameters under contrasting thermal profiles. To illustrate potential applications of the model, we analyzed the population's demographic and evolutionary dynamics under scenarios of (1) climate change-induced warming, and (2) warming plus flow reduction resulting from climate and land use change, compared to (3) a baseline of no environmental change. The model predicted severe declines in density and biomass under climate warming. These declines were lower than expected at range margins because of evolution towards smaller size at both emergence and maturation compared to the natural evolution under the baseline conditions. Despite stronger evolutionary responses, declining rates were substantially larger under the combined warming and flow reduction scenario, leading to a high probability of population extinction over contemporary time frames. Therefore, adaptive responses could not prevent extinction under high rates of environmental change. Our model demonstrates critical elements of next generation ecological modelling aiming at predictions in a changing world as it accounts for spatial and temporal resource heterogeneity, while merging individual behaviour and bioenergetics with microevolutionary adaptations.