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Many infectious diseases exist as multiple variants, with interactions between variants potentially driving epidemiological dynamics. These diseases include dengue, which infects hundreds of millions of people every year and exhibits complex multi-serotype dynamics. Antibodies produced in response to primary infection by one of the four dengue serotypes can produce a period of temporary cross-immunity (TCI) to infection by other serotypes. After this period, the remaining antibodies can facilitate the entry of heterologous serotypes into target cells, thus enhancing severity of secondary infection by a heterologous serotype. This represents antibody-dependent enhancement (ADE). In this study, we analyze an epidemiological model to provide novel insights into the importance of TCI and ADE in producing cyclic outbreaks of dengue serotypes. Our analyses reveal that without TCI, such cyclic outbreaks are synchronous across serotypes and only occur when ADE produces high transmission rates. In contrast, the presence of TCI allows asynchronous cycles of serotypes by inducing a time lag between recovery from primary infection by one serotype and secondary infection by another, with such cycles able to occur without ADE. Our results suggest that TCI is a fundamental driver of asynchronous cycles of dengue serotypes and possibly other multi-variant diseases. [ABSTRACT FROM AUTHOR]

A central goal in ecology is to understand what maintains species diversity in local communities. Classic ecological theory1,2 posits that niches dictate the maximum number of species that can coexist in a community and that the richness of observed species will be below this maximum only where immigration is very low. A new alternative theory3,4 is that niches, instead, dictate the minimum number of coexisting species and that the richness of observed species will usually be well above this because of ongoing immigration. We conducted an experimental test to discriminate between these two unified theories using a manipulative field experiment with tropical intertidal communities. We found, consistent with the new theory, that the relationship of species richness to immigration rate stabilized at a low value at low immigration rates and did not saturate at high immigration rates. Our results suggest that tropical intertidal communities have low niche diversity and are typically in a dispersal-assembled regime where immigration is high enough to overfill the niches. Observational data from other studies3,5 suggest that these conclusions may generalize to other ecological systems. Our new experimental approach can be adapted for other systems and be used as a ‘niche detector’ and a tool for assessing when communities are niche versus dispersal assembled.This study shows through a field experiment that tropical intertidal communities switch from a niche- to a dispersal-assembled regime as immigration rates rise. [ABSTRACT FROM AUTHOR]

The question of whether biodiversity conservation and carbon conservation can be synergistic hinges on the form of the biodiversity–productivity relationship (BPR), a fundamental ecological pattern. The stakes are particularly high when it comes to forests, which at a global level comprises a large fraction of both biodiversity and carbon. And yet, in forests, the BPR is relatively poorly understood. In this review, we critically evaluate research on forest BPRs, focussing on the experimental and observational studies of the last 2 decades. We find general support for a positive forest BPR, suggesting that biodiversity and carbon conservation are synergistic to a degree. However, we identify several major caveats: (i) although, on average, productivity may increase with biodiversity, the highest-yielding forests are often monocultures of very productive species; (ii) productivity typically saturates at fewer than ten species; (iii) positive BPRs can be driven by some third variable, in particular stem density, instead of a causal arrow from biodiversity to productivity; (iv) the BPR's sign and magnitude varies across spatial grains and extents, and it may be weak at scales relevant to conservation; and (v) most productivity estimates in forests are associated with large errors. We conclude by explaining the importance of these caveats for both conservation programmes focussed on protection of existing forests and conservation programmes focussed on restoring or replanting forests. [ABSTRACT FROM AUTHOR]

Ecology lacks a holistic approach that can model phenomena across temporal and spatial scales, largely because of the challenges in modelling systems with a large number of interacting constituents. This hampers our understanding of complex ecosystems and the impact that human interventions (e.g., deforestation, wildlife harvesting and climate change) have on them. Here we use density functional theory, a computational method for many-body problems in physics, to develop a computational framework for ecosystem modelling. Our methods accurately fit experimental and synthetic data of interacting multi-species communities across spatial scales and can project to unseen data. As the key concept we establish and validate a cost function that encodes the trade-offs between the various ecosystem components. We show how this single general modelling framework delivers predictions on par with established, but specialised, approaches for systems from predatory microbes to territorial flies to tropical tree communities. Our density functional framework thus provides a promising avenue for advancing our understanding of ecological systems. Modelling diverse ecological phenomena across scales with a single mathematical framework is challenging. Here, the authors draw on density functional theory to develop a framework that bridges between mechanistic theories at fine scales and statistical models at large scales. [ABSTRACT FROM AUTHOR]

Human cooperation (paying a cost to benefit others) is puzzling from a Darwinian perspective, particularly in groups with strangers who cannot repay nor are family members. The beneficial effects of cooperation typically increase nonlinearly with the number of cooperators, e.g., increasing returns when cooperation is low and diminishing returns when cooperation is high. Such nonlinearity can allow cooperation between strangers to persist evolutionarily if a large enough proportion of the population are already cooperators. However, if a lone cooperator faces a conflict between the group's and its own interests (a social dilemma), that raises the question of how cooperation arose in the first place. We use a mathematically tractable evolutionary model to formalise a chronological narrative that has previously only been investigated verbally: given that ancient humans interacted mostly with family members (genetic homophily), cooperation evolved first by kin selection, and then persisted in situations with nonlinear benefits as homophily declined or even if interactions with strangers became the norm. The model also predicts the coexistence of cooperators and defectors observed in the human population (polymorphism), and may explain why cooperators in behavioural experiments prefer to condition their contribution on the contributions of others (conditional cooperation in public goods games). [ABSTRACT FROM AUTHOR]

Theoretical and empirical studies suggest that as immigration increases, ecological communities transition from a niche-structured regime to an immigration-structured regime. The niche-structured regime is the domain of classic niche models; the immigration-structured regime is the domain of island biogeography and related theories. A recent unified model predicted a biphasic species–area relationship (SAR) arising from the transition between the two regimes, but the generality and scope of this relationship remain unclear. Here we study the transition further to address three key questions: (1) Can MacArthur and Wilson's classic graphical paradigm of intersecting immigration and extinction curves be adapted to capture the niche-structured regime that occurs at low-immigration rates? (2) Do different ecological models predict a similar biphasic SAR? (3) Can the biphasic island SAR be reconciled with the classic triphasic SAR observed in mainland biogeography? On the first point, we find that the transition can be incorporated into MacArthur and Wilson's graphical paradigm by forcing the extinction curves sharply downwards at low species richness, reflecting the stabilizing effect of niche processes. On the second point, we confirm that a variety of simple ecological models produce qualitatively similar biphasic SARs. On the third point, we find that a unified model predicts an overall four-phase SAR with the second phase being a shallow niche-structured phase that is rarely observed in mainland SARs, which we hypothesize is because local communities on mainlands are usually in the immigration-structured regime. [ABSTRACT FROM AUTHOR]

The relationship between species richness and productivity changes with spatial scale, but the way in which it changes and the underlying mechanisms remain unclear. We address this critical knowledge gap using a new mechanistic model of the spatial scaling of species richness–productivity (SP) relationships for a local community. Our model is neutral and hence assumes that species dynamics are driven by dispersal limitation and demographic stochasticity. We showed analytically that SP relationships predicted by our model are typically unimodal. Consistent with previous simulation-based studies, the positive phase of our unimodal SP relationship was driven by a sampling effect ("more-individuals effect") whereas the negative phase was driven by relatively more propagules being of local as opposed to external origin ("dilution effect"). Our main novel finding related to the spatial scaling of the unimodal SP relationship: the peak shifted to the left with increasing spatial scale, such that the decreasing phase covered a greater range of productivity. This was driven by an increase in the strength of the dilution effect relative to the more-individuals effect, reflecting higher area/perimeter ratios at larger spatial scales. Our theoretical predictions are qualitatively consistent with the spatial scaling of SP relationships documented for trees in localized forest communities across the world. [ABSTRACT FROM AUTHOR]

Natural communities at all spatiotemporal scales are subjected to a wide variety of environmental pressures, resulting in random changes in the demographic rates of species populations. Previous analyses have examined the effects of such environmental variance on the long-term growth rate and time to extinction of single populations, but studies of its effects on the diversity of communities remain scarce. In this study, we construct a new master-equation model incorporating demographic and environmental variance and use it to examine how statistical patterns of diversity, as encapsulated by species-abundance distributions (SADs), are altered by environmental variance. Unlike previous diffusion models with environmental variance uncorrelated in time (white noise), our model allows environmental variance to be correlated at different timescales (colored noise), thus facilitating representation of phenomena such as yearly and decadal changes in climate. We derive an exact analytical expression for SADs predicted by our model together with a close approximation, and use them to show that the main effect of adding environmental variance is to increase the proportion of abundant species, thus flattening the SAD relative to the log-series form found in the neutral case. This flattening effect becomes more prominent when environmental variance is more correlated in time and has greater effects on species' demographic rates, holding all other factors constant. Furthermore, we show how our model SADs are consistent with those from diffusion models near the white noise limit. The mathematical techniques we develop are catalysts for further theoretical work exploring the consequences of environmental variance for biodiversity. [ABSTRACT FROM AUTHOR]

Nutrient enrichment of native grasslands can promote invasion by exotic plant species, leading to reduced biodiversity and altered ecosystem function. Empirical evidence suggests that positive feedbacks may make such transitions difficult to reverse. We developed a mathematical model of grassland dynamics in which one group of species (native) is a better competitor for nitrogen (N) and another group (exotic) is a better competitor for light. We parameterized the model for a grassland community and reproduced observed transitions from a native- to an exotic-dominated state under N loading. Within known bounds of parameter values, both smooth and hysteretic transitions are plausible. The model also predicts that N loading alone is insufficient to achieve a transition to an exotic-dominated state on a timescale relevant to grassland management (a few decades), and that therefore some other disturbance (e.g., fire suppression or heaving grazing) must be present to accelerate it. The model predicts that to restore a grassland to a native-dominated state after N inputs have been reduced, fire and carbon supplements would be most effective. Further field research in N-enriched invaded grasslands is required to establish the strengths of positive feedbacks and, in turn, the consequences of anthropogenic modification of grasslands worldwide. [ABSTRACT FROM AUTHOR]

The niche is a fundamental ecological concept that underpins many explanations of patterns of biodiversity. The complexity of niche processes in ecological systems, however, means that it is difficult to capture them accurately in theoretical models of community assembly. In this study, we build upon simple neutral biodiversity models by adding the important ingredient of overlapping niche structure. Our model is spatially implicit and contains a fixed number of equal-sized habitats. Each species in the metacommunity arises through a speciation event; at which time, it is randomly assigned a fundamental niche or set of environments/habitats in which it can persist. Within each habitat, species compete with other species that have different but overlapping fundamental niches. Species abundances then change through ecological drift; each, however, is constrained by its maximum niche breadth and by the presence of other species in its habitats. Using our model, we derive analytical expressions for steady-state species abundance distributions, steady-state distributions of niche breadth across individuals and across species, and dynamic distributions of niche breadth across species. With this framework, we identify the conditions that produce the log-series species abundance distribution familiar from neutral models. We then identify how overlapping niche structure can lead to other species abundance distributions and, in particular, ask whether these new distributions differ significantly from species abundance distributions predicted by non-overlapping niche models. Finally, we extend our analysis to consider additional distributions associated with realized niche breadths. Overall, our results show that models with overlapping niches can exhibit behavior similar to neutral models, with the caveat that species with narrow fundamental niche breadths will be very rare. If narrow-niche species are common, it must be because they are in a non-overlapping niche or have countervailing advantages over broad-niche species. This result highlights the role that niches can play in establishing demographic neutrality. [ABSTRACT FROM AUTHOR]

Many problems in ecology require the estimation of rates of dispersal of individuals or propagules across physical boundaries. Such problems arise in invasion ecology, forest dynamics, and the neutral theory of biodiversity. In a forest plot, for example, one might ask what proportion of the seed rain originates from outside the plot. A recent study presented analytical approximations that relate the rate of immigration across a boundary to plot geometry and to the parameters of a dispersal kernel in one- and two-dimensional environments. In this study, we provide a more rigorous derivation of these expressions and we derive a more general expression that applies in environments of arbitrary dimension. We discuss potential applications of the one-, two-, and three-dimensional results to ecological problems. [ABSTRACT FROM AUTHOR]

central challenge in community ecology is to predict patterns of biodiversity with mechanistic models. The neutral model of biodiversity is a simple model that appears to provide parsimonious and accurate predictions of biodiversity patterns in some ecosystems, even though it ignores processes such as species interactions and niche structure. In a recent paper, we used analytical techniques to reveal why the mean predictions of the neutral model are robust to niche structure in high diversity but not low-diversity ecosystems. In the present paper, we explore this phenomenon further by generating stochastic simulated data from a spatially implicit hybrid niche-neutral model across different speciation rates. We compare the resulting patterns of species richness and abundance with the patterns expected from a pure neutral and a pure niche model. As the speciation rate in the hybrid model increases, we observe a surprisingly rapid transition from an ecosystem in which diversity is almost entirely governed by niche structure to one in which diversity is statistically indistinguishable from that of the neutral model. Because the transition is rapid, one prediction of our abstract model is that high-diversity ecosystems such as tropical forests can be approximated by one simple model-the neutral model-whereas low-diversity ecosystems such as temperate forests can be approximated by another simple model-the niche model. Ecosystems that require the hybrid model are predicted to be rare, occurring only over a narrow range of speciation rates. [ABSTRACT FROM AUTHOR]

Understanding the factors that govern the commonness and rarity of individual species is a central challenge in community ecology. Empirical studies have often found that abundance is related to traits associated with competitive ability and suitability to the local environment and, more recently, also to negative conspecific density dependence. Here, we construct a theoretical framework to show how a species' abundance is, in general, expected to be dependent on its per-capita growth rate when rare and the rate at which its growth rate declines with increasing abundance (strength of stabilization). We argue that per-capita growth rate when rare can be interpreted as competitive ability and that strength of stabilization largely reflects negative conspecific inhibition. We then analyze a simple spatially implicit model in which each species is defined by three parameters that affect its juvenile survival: its generalized competitive effect on others, its generalized response to competition, and an additional negative effect on conspecifics. This model facilitates the stable coexistence of an arbitrarily large number of species and qualitatively reproduces empirical relationships between abundance, competitive ability, and negative conspecific density dependence. Our results provide theoretical support for the combined roles of competitive ability and negative density dependence in the determination of species abundances in real ecosystems, and suggest new avenues of research for understanding abundance in models and in real communities. [ABSTRACT FROM AUTHOR]