A gene for all seasons: The evolutionary consequences of HIF-1 in carcinogenesis, tumor growth and metastasis.

Oxygen played a pivotal role in the evolution of multicellularity during the Cambrian Explosion. Not surprisingly, responses to fluctuating oxygen concentrations are integral to the evolution of cancer-a disease characterized by the breakdown of multicellularity. Poorly organized tumor vasculature results in chaotic patterns of blood flow characterized by large spatial and temporal variations in intra-tumoral oxygen concentrations. Hypoxia-inducible growth factor (HIF-1) plays a pivotal role in enabling cells to adapt, metabolize, and proliferate in low oxygen conditions. HIF-1 is often constitutively activated in cancers, underscoring its importance in cancer progression. Here, we argue that the phenotypic changes mediated by HIF-1, in addition to adapting the cancer cells to their local environment, also "pre-adapt" them for proliferation at distant, metastatic sites. HIF-1-mediated adaptations include a metabolic shift towards anaerobic respiration or glycolysis, activation of cell survival mechanisms like phenotypic plasticity and epigenetic reprogramming, and formation of tumor vasculature through angiogenesis. Hypoxia induced epigenetic reprogramming can trigger epithelial to mesenchymal transition in cancer cells-the first step in the metastatic cascade. Highly glycolytic cells facilitate local invasion by acidifying the tumor microenvironment. New blood vessels, formed due to angiogenesis, provide cancer cells a conduit to the circulatory system. Moreover, survival mechanisms acquired by cancer cells in the primary site allow them to remodel tissue at the metastatic site generating tumor promoting microenvironment. Thus, hypoxia in the primary tumor promoted adaptations conducive to all stages of the metastatic cascade from the initial escape entry into a blood vessel, intravascular survival, extravasation into distant tissues, and establishment of secondary tumors.

Looking at the bid picture: A framework for identifying reverse auctions in ecological systems.

Biological market theory can be used to explain intraspecific cooperation, interspecific mutualism, and sexual selection through models of game theory. These models describe the interactions between organisms as two classes of traders (buyers/sellers) exchanging commodities in the form of goods (e.g. food, shelter, matings) and services (e.g. warning calls, protection). Here, we expand biological market theory to include auction theory where bidding serves to match buyers and sellers. In a reverse auction, the seller increases the value of the item or decreases the cost until a buyer steps forward. We provide several examples of ecological systems that may have reverse auctions as underlying mechanisms to form mutualistic relationships. We focus on the yellow baboon (Papio cynocephalus) mating system as a case study to propose how the mechanisms of a reverse auction, which have the unintended but emergent consequence of producing a mutually beneficial outcome that improves collective reproductive benefits of the troop in this multi-female multi-male polygynandrous social system. For the yellow baboon, we posit that the "seller" is the reproductively cycling female, and the "buyer" is a male looking to mate with a cycling female. To the male, the "item for the sale" is the opportunity to sire an offspring, the price is providing safety and foraging time (via consortship) to the female. The "increasing value of the item for sale" is the chance of conception, which increases with each cycle since a female has resumed cycling post-partum. The female's sexual swelling is an honest indicator of that cycle's probability of conception, and since resident males can track a female's cycle since resumption, there is transparency. The males presumably know the chance of conception when choosing to bid by offering consortship. Across nature, this reverse auction game likely exists in other inter- and intraspecific social relationships. Considering an ecological system as a reverse auction broadens our view of social evolution and adaptations through the lens of human economic structures.

Designing an assay to evaluate behavioral responses to opposite-sex conspecifics in the endangered black-footed ferret (Mustela nigripes).

The endangered black-footed ferret (ferret; Mustela nigripes) is a North American carnivore that is actively managed to reestablish self-sustaining wild populations. Behavioral abnormalities have been reported in the breeding program and may be a limiting factor for the species' success. Our goal was to design and test an assay that examines the ferret's exploratory response to odor cues in the form of soiled bedding from opposite-sex conspecifics. Across two breeding seasons, males and females were tested using a T-maze that connected their home nest box to two novel nest boxes containing two different conspecific's soiled bedding. For a control, we provided two clean bedding samples. We ran linear mixed models to determine the effect of sex, type of odor cue (soiled, clean), and order of trial (first, second) on time exploring and proportion of that time spent in each behavior. Ferrets spent the majority of time in the novel nest boxes sniffing (44%), standing alert (27%) and scratching (14%). Males explored for longer than females; however, both displayed similar behaviors. Type of cue influenced behavior, with ferrets sniffing more among soiled cues than clean cues. Habituation to the assay was also observed, with less exploration and more standing alert during the second trial of the day. This study is the first step in characterizing the ferret's exploratory response and provides information regarding vital investigatory and vigilance behaviors. The continual development of this assay to further evaluate reproductive and mate choice behaviors will facilitate more successful breeding of the species.

A Markovian decision model of adaptive cancer treatment and quality of life.

This paper develops and analyzes a Markov chain model for the treatment of cancer. Cancer therapy is modeled as the patient's Markov Decision Problem, with the objective of maximizing the patient's discounted expected quality of life years. Patients make decisions on the duration of therapy based on the progression of the disease as well as their own preferences. We obtain a powerful analytic decision tool through which patients may select their preferred treatment strategy. We illustrate the tradeoffs patients in a numerical example and calculate the value lost to a cohort in suboptimal strategies. In a second model patients may make choices to include drug holidays. By delaying therapy, the patient temporarily forgoes the gains of therapy in order to delay its side effects. We obtain an analytic tool that allows numerical approximations of the optimal times of delay.

The context dependence of non-consumptive predator effects.

Non-consumptive predator effects (NCEs) are now widely recognised for their capacity to shape ecosystem structure and function. Yet, forecasting the propagation of these predator-induced trait changes through particular communities remains a challenge. Accordingly, focusing on plasticity in prey anti-predator behaviours, we conceptualise the multi-stage process by which predators trigger direct and indirect NCEs, review and distil potential drivers of contingencies into three key categories (properties of the prey, predator and setting), and then provide a general framework for predicting both the nature and strength of direct NCEs. Our review underscores the myriad factors that can generate NCE contingencies while guiding how research might better anticipate and account for them. Moreover, our synthesis highlights the value of mapping both habitat domains and prey-specific patterns of evasion success ('evasion landscapes') as the basis for predicting how direct NCEs are likely to manifest in any particular community. Looking ahead, we highlight two key knowledge gaps that continue to impede a comprehensive understanding of non-consumptive predator-prey interactions and their ecosystem consequences; namely, insufficient empirical exploration of (1) context-dependent indirect NCEs and (2) the ways in which direct and indirect NCEs are shaped interactively by multiple drivers of context dependence.

Artificial selection for host resistance to tumour growth and subsequent cancer cell adaptations: an evolutionary arms race.

BACKGROUND: Cancer progression is governed by evolutionary dynamics in both the tumour population and its host. Since cancers die with the host, each new population of cancer cells must reinvent strategies to overcome the host's heritable defences. In contrast, host species evolve defence strategies over generations if tumour development limits procreation. METHODS: We investigate this "evolutionary arms race" through intentional breeding of immunodeficient SCID and immunocompetent Black/6 mice to evolve increased tumour suppression. Over 10 generations, we injected Lewis lung mouse carcinoma cells [LL/2-Luc-M38] and selectively bred the two individuals with the slowest tumour growth at day 11. Their male progeny were hosts in the subsequent round. RESULTS: The evolved SCID mice suppressed tumour growth through biomechanical restriction from increased mesenchymal proliferation, and the evolved Black/6 mice suppressed tumour growth by increasing immune-mediated killing of cancer cells. However, transcriptomic changes of multicellular tissue organisation and function genes allowed LL/2-Luc-M38 cells to adapt through increased matrix remodelling in SCID mice, and reduced angiogenesis, increased energy utilisation and accelerated proliferation in Black/6 mice. CONCLUSION: Host species can rapidly evolve both immunologic and non-immunologic tumour defences. However, cancer cell plasticity allows effective phenotypic and population-based counter strategies.

Determining the effectiveness of using dermal swabs to evaluate the stress physiology of laboratory cephalopods: A preliminary investigation.

To better comprehend the physiology of cephalopods, we used a minimal invasive technique of skin mucus swabs to measure immunoreactive corticosteroids in three cephalopod species commonly kept in captivity and promoted as new model organisms: Euprymna berryi, Sepia bandensis, and Octopus chierchiae. We compared results between sexes and age classes and then evaluated their stress responses during acclimation to a new habitat. To better understand glucocorticoid production, we conducted an adrenocorticotropic hormone, using Cosyntropin (an adrenocorticotropin (ACTH) analogue) challenge with a saline control and swabbed their mantles at 15-minute intervals for 2 h. Results showed cortisol was higher for younger individuals. Additionally, cortisol and corticosterone concentrations decreased by 2-fold after 2 to 4 days of acclimation to a new habitat. We were able to successfully measure 2-fold increase in immunoreactive corticosteroids which reacted with cortisol and corticosterone assays for all the species following ACTH injection, although not all individuals responded similarly. With further investigation, this technique can increase our understanding and management of cephalopods in captivity.

The Enemy Within: How Does a Bacterium Inhibit the Foraging Aptitude and Risk Management Behavior of Allenby's Gerbils?

AbstractMicrobes inhabiting multicellular organisms have complex, often subtle effects on their hosts. Gerbillus andersoni allenbyi are commonly infected with Mycoplasma haemomuris-like bacteria, which may cause mild nutrient (choline, arginine) deficiencies. However, are there more serious ecological consequences of infection, such as effects on foraging aptitudes and risk management? We tested two alternatives: the nutrient compensation hypothesis (does nutrient deficiency induce infected gerbils to make up for the shortfall by foraging more and taking greater risks?) and (2) the lethargy hypothesis (do sick gerbils forage less, and are they compromised in their ability to detect predators or risky microhabitats?). We compared the foraging and risk management behavior of infected and noninfected gerbils. We experimentally infected gerbils with the bacteria, which allowed us to compare between noninfected, acutely infected (peak infection loads), and chronically infected (low infection loads) individuals. Our findings supported the lethargy hypothesis over the nutrient compensation hypothesis. Infected individuals incurred dramatically elevated foraging costs, including less efficient foraging, diminished "quality" of time spent vigilant, and increased owl predation. Interestingly, gerbils that were chronically infected (lower bacteria load) experienced larger ecological costs than acutely infected individuals (i.e., peak infection loads). This suggests that the debilitating effects of infection occur gradually, with a progressive decline in the quality of time gerbils allocated to foraging and managing risk. These increased long-term costs of infection demonstrate how small direct physiological costs of infection can lead to large indirect ecological costs. The indirect ecological costs of this parasite appear to be much greater than the direct physiological costs.

Unstable population dynamics in obligate co-operators.

Cooperation significantly impacts a species' population dynamics as individuals choose others to associate with based upon fitness opportunities. Models of these dynamics typically assume that individuals can freely move between groups. Such an assumption works well for facultative co-operators (e.g. flocking birds, schooling fish, and swarming locusts) but less so for obligate co-operators (e.g. canids, cetaceans, and primates). With obligate co-operators, the fitness consequences from associations are stronger compared to facultative co-operators. Consequently, individuals within a group should be more discerning and selective over their associations, rejecting new members and even removing current members. Incorporating such aspects into population models may better reflect obligately cooperative species. In this paper, we create and analyze a model of the population dynamics of obligate co-operators. In our model, a behavioral game determines within-group population dynamics that then spill over into between-group dynamics. Our analysis shows that group number increases when population dynamics are stable, but additional groups lead to unstable population dynamics and an eventual collapse of group numbers. Using a more general analysis, we identify a fundamental mismatch between the stability of the behavioral dynamics and the stability of the population dynamics. When one is stable, the other is not. Our results suggest that group turnover may be inherent to the population dynamics of obligate co-operators. The instability arises from a non-chaotic deterministic process, and such dynamics should be predictable and testable.

Cancer Community Ecology.

Here we advocate Cancer Community Ecology as a valuable focus of study in Cancer Biology. We hypothesize that the heterogeneity and characteristics of cancer cells within tumors should vary systematically in space and time and that cancer cells form local ecological communities within tumors. These communities possess limited numbers of species determined by local conditions, with each species in a community possessing predictable traits that enable them to cope with their particular environment and coexist with each other. We start with a discussion of concepts and assumptions that ecologists use to study closely related species. We then discuss the competitive exclusion principle as a means for knowing when two species should not coexist, and as an opening towards understanding how they can. We present the five major categories of mechanisms of coexistence that operate in nature and suggest that the same mechanisms apply towards understanding the diversification and coexistence of cancer cell species. They are: Food-Safety Tradeoffs, Diet Choice, Habitat Selection, Variance Partitioning, and Competition-Colonization Tradeoffs. For each mechanism, we discuss how it works in nature, how it might work in cancers, and its implications for therapy.

What Is the Storage Effect, Why Should It Occur in Cancers, and How Can It Inform Cancer Therapy?

Intratumor heterogeneity is a feature of cancer that is associated with progression, treatment resistance, and recurrence. However, the mechanisms that allow diverse cancer cell lineages to coexist remain poorly understood. The storage effect is a coexistence mechanism that has been proposed to explain the diversity of a variety of ecological communities, including coral reef fish, plankton, and desert annual plants. Three ingredients are required for there to be a storage effect: (1) temporal variability in the environment, (2) buffered population growth, and (3) species-specific environmental responses. In this article, we argue that these conditions are observed in cancers and that it is likely that the storage effect contributes to intratumor diversity. Data that show the temporal variation within the tumor microenvironment are needed to quantify how cancer cells respond to fluctuations in the tumor microenvironment and what impact this has on interactions among cancer cell types. The presence of a storage effect within a patient's tumors could have a substantial impact on how we understand and treat cancer.

Intercontinental test of constraint-breaking adaptations: Testing behavioural plasticity in the face of a predator with novel hunting strategies.

Constraint-breaking adaptations are evolutionary tools that provide a mechanism for incumbent-replacement between species filling similar ecological roles. In common-garden experiments, we exposed populations of two desert rodents to two different viper species, testing their ability to adjust to novel predators that use different hunting strategies. We aimed to understand whether both predators and prey with constraint-breaking adaptations actually manifest comparative advantage over their counterparts. We used convergent species from desert dunes in the Mojave Desert in North America, Merriam's kangaroo rat Dipodomys merriami and the sidewinder rattlesnake Crotalus cerastes, and from the Negev Desert in the Middle East, the greater Egyptian gerbil Gerbillus pyramidum and the Saharan horned viper Cerastes cerastes. Both Mojave species hold constraint-breaking adaptations in relation to their counterparts from the Negev. The rattlesnakes have heat sensing organs (pits) and the kangaroo rats have fur-lined cheek pouches that allow for greater foraging efficiency and food preservation. Using patch-use theory, we evaluated the rodents' risk-assessment from each snake-separately, together and in combination with barn owls. Initially each rodent species foraged less in the presence of its familiar snake, but within a month both foraged less in the presence of the pit-viper (sidewinder). Our findings indicate a level of learning, and behavioural plasticity, in both rodents and ability to assess the risk from novel predators. The kangaroo rats were capable of harvesting far greater amounts of resources under the same conditions of elevated risk. However, the reason for their advantage may lie in bi-pedal agility and not only their ability collect food more efficiently.

High School Internship Program in Integrated Mathematical Oncology (HIP IMO): Five-Year Experience at Moffitt Cancer Center.

Modern cancer research, and the wealth of data across multiple spatial and temporal scales, has created the need for researchers that are well versed in the life sciences (cancer biology, developmental biology, immunology), medical sciences (oncology) and natural sciences (mathematics, physics, engineering, computer sciences). College undergraduate education traditionally occurs in disciplinary silos, which creates a steep learning curve at the graduate and postdoctoral levels that increasingly bridge multiple disciplines. Numerous colleges have begun to embrace interdisciplinary curricula, but students who double major in mathematics (or other quantitative sciences) and biology (or medicine) remain scarce. We identified the need to educate junior and senior high school students about integrating mathematical and biological skills, through the lens of mathematical oncology, to better prepare students for future careers at the interdisciplinary interface. The High school Internship Program in Integrated Mathematical Oncology (HIP IMO) at Moffitt Cancer Center has so far trained 59 students between 2015 and 2019. We report here on the program structure, training deliverables, curriculum and outcomes. We hope to promote interdisciplinary educational activities early in a student's career.

Patch use in the arctic ground squirrel: effects of micro-topography and shrub encroachment in the Arctic Circle.

We investigated the roles of vegetation structure, micro-topographic relief, and predator activity patterns (time of day) on the perception of predatory risk of arctic ground squirrels (Urocitellus parryii), an abundant pan-Arctic omnivore, in Arctic Circle tundra on the North Slope of Alaska, where tundra vegetation structure has been predicted to change in response to climate. We quantified foraging intensity by measuring the giving-up densities (GUDs) of the arctic ground squirrels in experimental foraging patches along a heath-graminoid-shrub moist tundra gradient. We hypothesized that foraging intensity of arctic ground squirrels would be greatest and GUDs lowest, where low-stature vegetation or raised micro-topography improves sightlines for predator detection. Furthermore, GUDs should vary with time of day and reflect 24-h cycles of varying predation risk. Foraging intensity varied temporally, being highest in the afternoon and lowest overnight. During the morning, foraging intensity was inversely correlated with the normalized difference vegetation index (NDVI), a proxy for vegetation productivity and cover. Foraging was additionally measured within landscapes of fear, confirming that vegetative and topographic obstructions of sightlines reduces foraging intensity and increases GUDs. We conclude that arctic ground squirrels may affect Arctic Circle vegetation of tundra ecosystems, but these effects will vary spatially and temporally.

A two-phenotype model of immune evasion by cancer cells.

We propose a model with two types of cancer cells differentiated by their defense mechanisms against the immune system. "Selfish" cancer cells develop defense mechanisms that benefit the individual cell, whereas "cooperative" cells deploy countermeasures that increase the chance of survival of every cell. Our phenotypes capture the two main features of the tumor's efforts to avoid immune destruction, crypticity against immune cells for the selfish cells, and tumor-induced immunosuppression for the cooperative cells. We identify steady states of the system and show that only homogeneous tumors can be stable in both size and composition. We show that under generic parameter values, a tumor of selfish cells is more benign than a tumor of cooperative cells, and that a treatment against cancer crypticity may promote immunosuppression and increase cancer growth.

Optimal control to develop therapeutic strategies for metastatic castrate resistant prostate cancer.

In metastatic castrate resistant prostate cancer (mCRPC), abiraterone is conventionally administered continuously at maximal tolerated dose until treatment failure. The majority of patients initially respond well to abiraterone but the cancer cells evolve resistance and the cancer progresses within a median time of 16 months. Incorporating techniques that attempt to delay or prevent the growth of the resistant cancer cell phenotype responsible for disease progression have only recently entered the clinical setting. Here we use evolutionary game theory to model the evolutionary dynamics of patients with mCRPC subject to abiraterone therapy. In evaluating therapy options, we adopt an optimal control theory approach and seek the best treatment schedule using nonlinear constrained optimization. We compare patient outcomes from standard clinical treatments to those with other treatment objectives, such as maintaining a constant total tumor volume or minimizing the fraction of resistant cancer cells within the tumor. Our model predicts that continuous high doses of abiraterone as well as other therapies aimed at curing the patient result in accelerated competitive release of the resistant phenotype and rapid subsequent tumor progression. We find that long term control is achievable using optimized therapy through the restrained and judicious application of abiraterone, maintaining its effectiveness while providing acceptable patient quality of life. Implementing this strategy will require overcoming psychological and emotional barriers in patients and physicians as well as acquisition of a new class of clinical data designed to accurately estimate intratumoral eco-evolutionary dynamics during therapy.

Unlimited niche packing in a Lotka-Volterra competition game.

A central question in the study of ecology and evolution is: "Why are there so many species?" It has been shown that certain forms of the Lotka-Volterra (L-V) competition equations lead to an unlimited number of species. Furthermore, these authors note how any change in the nature of competition (the competition kernel) leads to a finite or small number of coexisting species. Here we build upon these works by further investigating the L-V model of unlimited niche packing as a reference model and evolutionary game for understanding the environmental factors restricting biodiversity. We also examine the combined eco-evolutionary dynamics leading up to the species diversity and traits of the ESS community in both unlimited and finite niche-packing versions of the model. As an L-V game with symmetric competition, we let the strategies of individuals determine the strength of the competitive interaction (like competes most with like) and also the carrying capacity of the population. We use a mixture of analytic proofs (for one and two species systems) and numerical simulations. For the model of unlimited niche packing, we show that a finite number of species will evolve to specific convergent stable minima of the adaptive landscape (also known as species archetypes). Starting with a single species, faunal buildup can proceed either through species doubling as each diversity-specific set of minima are reached, or through the addition of species one-by-one by randomly assigning a speciation event to one of the species. Either way it is possible for an unlimited number or species to evolve and coexist. We examine two simple and biologically likely ways for breaking the unlimited niche-packing: (1) some minimum level of competition among species, and (2) constrain the fundamental niche of the trait space to a finite interval. When examined under both ecological and evolutionary dynamics, both modifications result in convergent stable ESSs with a finite number of species. When the number of species is held below the number of species in an ESS coalition, we see a diverse array of convergent stable niche archetypes that consist of some species at maxima and some at minima of the adaptive landscape. Our results support those of others and suggest that instead of focusing on why there are so many species we might just as usefully ask, why are there so few species?

Spatial vs. non-spatial eco-evolutionary dynamics in a tumor growth model.

Metastatic prostate cancer is initially treated with androgen deprivation therapy (ADT). However, resistance typically develops in about 1 year - a clinical condition termed metastatic castrate-resistant prostate cancer (mCRPC). We develop and investigate a spatial game (agent based continuous space) of mCRPC that considers three distinct cancer cell types: (1) those dependent on exogenous testosterone (T+), (2) those with increased CYP17A expression that produce testosterone and provide it to the environment as a public good (TP), and (3) those independent of testosterone (T-). The interactions within and between cancer cell types can be represented by a 3 × 3 matrix. Based on the known biology of this cancer there are 22 potential matrices that give roughly three major outcomes depending upon the absence (good prognosis), near absence or high frequency (poor prognosis) of T- cells at the evolutionarily stable strategy (ESS). When just two cell types coexist the spatial game faithfully reproduces the ESS of the corresponding matrix game. With three cell types divergences occur, in some cases just two strategies coexist in the spatial game even as a non-spatial matrix game supports all three. Discrepancies between the spatial game and non-spatial ESS happen because different cell types become more or less clumped in the spatial game - leading to non-random assortative interactions between cell types. Three key spatial scales influence the distribution and abundance of cell types in the spatial game: i. Increasing the radius at which cells interact with each other can lead to higher clumping of each type, ii. Increasing the radius at which cells experience limits to population growth can cause densely packed tumor clusters in space, iii. Increasing the dispersal radius of daughter cells promotes increased mixing of cell types. To our knowledge the effects of these spatial scales on eco-evolutionary dynamics have not been explored in cancer models. The fact that cancer interactions are spatially explicit and that our spatial game of mCRPC provides in general different outcomes than the non-spatial game might suggest that non-spatial models are insufficient for capturing key elements of tumorigenesis.

Why Darwin would have loved evolutionary game theory.

Humans have marvelled at the fit of form and function, the way organisms' traits seem remarkably suited to their lifestyles and ecologies. While natural selection provides the scientific basis for the fit of form and function, Darwin found certain adaptations vexing or particularly intriguing: sex ratios, sexual selection and altruism. The logic behind these adaptations resides in frequency-dependent selection where the value of a given heritable phenotype (i.e. strategy) to an individual depends upon the strategies of others. Game theory is a branch of mathematics that is uniquely suited to solving such puzzles. While game theoretic thinking enters into Darwin's arguments and those of evolutionists through much of the twentieth century, the tools of evolutionary game theory were not available to Darwin or most evolutionists until the 1970s, and its full scope has only unfolded in the last three decades. As a consequence, game theory is applied and appreciated rather spottily. Game theory not only applies to matrix games and social games, it also applies to speciation, macroevolution and perhaps even to cancer. I assert that life and natural selection are a game, and that game theory is the appropriate logic for framing and understanding adaptations. Its scope can include behaviours within species, state-dependent strategies (such as male, female and so much more), speciation and coevolution, and expands beyond microevolution to macroevolution. Game theory clarifies aspects of ecological and evolutionary stability in ways useful to understanding eco-evolutionary dynamics, niche construction and ecosystem engineering. In short, I would like to think that Darwin would have found game theory uniquely useful for his theory of natural selection. Let us see why this is so.

The world's biomes and primary production as a triple tragedy of the commons foraging game played among plants.

Plants appear to produce an excess of leaves, stems and roots beyond what would provide the most efficient harvest of available resources. One way to understand this overproduction of tissues is that excess tissue production provides a competitive advantage. Game theoretic models predict overproduction of all tissues compared with non-game theoretic models because they explicitly account for this indirect competitive benefit. Here, we present a simple game theoretic model of plants simultaneously competing to harvest carbon and nitrogen. In the model, a plant's fitness is influenced by its own leaf, stem and root production, and the tissue production of others, which produces a triple tragedy of the commons. Our model predicts (i) absolute net primary production when compared with two independent global datasets; (ii) the allocation relationships to leaf, stem and root tissues in one dataset; (iii) the global distribution of biome types and the plant functional types found within each biome; and (iv) ecosystem responses to nitrogen or carbon fertilization. Our game theoretic approach removes the need to define allocation or vegetation type a priori but instead lets these emerge from the model as evolutionarily stable strategies. We believe this to be the simplest possible model that can describe plant production.