Abstract New advents in technology have improved our ability to study and track host-associated organisms. Often, these organisms experience vastly different spatial and temporal scales than their hosts. However, host-associated organisms are not independent of their hosts nor are hosts independent of their host-associated organisms. Rather, processes at the host and host-associated organism scales interact to alter outcomes for both the host and its symbionts. Often, host-associated organisms are described in terms of metapopulations, wherein individual hosts act as habitat patches for their symbionts. When hosts themselves also exist in patchy environments, the result is metapopulation structure at two distinct scales. In this paper, we develop a model to explore how the incorporation of multiscale metapopulation dynamics impacts metapopulation predictions at both the host and symbiont scales. While related to several disease models, our system differs in its inclusion of full colonization and extinction dynamics at both scales, and its emphasis on how the interaction between colonization and extinction at these two scales impacts the host and its host-associated organisms, including pathogens as well as symbionts that are beneficial to the host. Overall, our multiscale metapopulation model predicts rich dynamics that often deviate from the dynamics of metapopulation models built for either the host or its host-associated organisms independently.

Habitat fragmentation divides populations into smaller subpopulations. At the same time, the Allee effect reduces the growth and thereby the viability of small populations. Hence, habitat fragmentation and the Allee effect can synergistically amplify negative impacts on spatially distributed populations. To support endangered populations, management and conservation strategies aim to improve connectivity between subpopulations by creating corridors and stepping stones, for instance. This study investigates how enhanced connectivity (strength of connections between subpopulations in terms of dispersal rate) influences a fragmented population subject to the Allee effect. Using a generic two-patch discrete-time model with a positively density-dependent growth function, we study the impact of connectivity on the asymptotic total population size through simulations. Due to the Allee effect, low connectivity can lead to a decline in the asymptotic total population size, which we call the Allee pit. However, increased connectivity facilitates the rescue effect, wherein a persistent subpopulation in one patch can save an extinction-prone subpopulation in another patch. We find that for connectivity to benefit the asymptotic total population size, dispersal must be sufficiently large to push the smaller subpopulation above its Allee threshold. If dispersal is below this critical dispersal rate, there remains a detrimental effect on the asymptotic total population size. Therefore, this study implies that conservation strategies should not only aim to increase connectivity in fragmented populations subject to Allee effects but also ensure that the critical dispersal rate is surpassed.

BackgroundThe relationship between the environmental (ED) or habitat (HD) diversity of a landscape and its species richness (S) is of global interest. The standard linear relationship tested is that total S rises with an increase in variability of environmental properties.FindingsWe recognize three basic S − ED patterns: convex, unimodal, and concave. These are shown to be based on three underlying species − area (S − A) curves: power, logarithmic, and sigmoid. From these, we find that the standard linear relationship lacks theoretical support. There are two sets of circumstances that can lead to a humped relationship: a particular type of S-A curve (logarithmic), and the operation of negative secondary effects as habitats become smaller and more isolated. The preponderance of positive linear and dearth of unimodal S − ED and S − HD relationships reported so far can be attributed to six causes. These include: only testing for linear relationships; limited data sets that exclude small, unique, or isolated habitats; regressions against non-causal variables; and/or use of biased data that have not been ground-truthed.ConclusionsInformed by the underlying S − A curves and the level of negative biotic effects at high ED, one can predict the numerous shapes of the S − ED curve. Hump-backed S − ED curves should apply widely in regions with species-rich biotas and where the environmental range is large and numerous isolated habitats are present.

Climate change can affect reef fish both directly (e.g., mortality, growth, fecundity) and indirectly (e.g., habitat degradation). The extent to which the effects of rising water temperature could drive changes in fish populations and if and how these effects may interact with potential management interventions remain unclear. The objective of this study was to test various hypothesized mechanisms by which sea surface temperature (SST) could affect reef fish population dynamics and explore these effects in combination with fishing effort restrictions and spatial closures. To do this, we modeled hypothesized relationships between SST and two governing parameters of the fish populations: intrinsic growth rate (r) and carrying capacity (K). We coupled these temperature-dependent fish population models with a fisheries harvest model and explored interactions between thermal effects, fishing effort level, and spatial closures. Under small closure scenarios, we found that the thermal effects models predicted substantially lower fish population biomass and harvest compared to the baseline (constant r and K) model. Under large closure scenarios, the thermal effects models more closely resembled the baseline. Generally, incorporating spatial closures mitigated some of the detrimental thermal effects on fish biomass and allowed for increased harvest under certain fishing effort levels. Whether intrinsic growth or carrying capacity most affected fish population levels also depended on the fishing effort and the spatial closure area. Overall, we described how fishing effort and spatial closures can influence the relative importance of key processes and the extent to which rising water temperatures affect fish populations and harvest.

In tropical forests, deciduous and evergreen leaf habits represent contrasting tree adaptations to precipitation seasonality. Both rainfall seasonality and interannual variation in rainfall are determinants of forest deciduousness, but their relative in uence is not well understood. In this study, we evaluate the extent of deciduous-evergreen coexistence in tropical forests and develop a simple model of competition for water between leaf habits. Using this model, we formalize two mechanisms representing rainfall variability across time scales that may explain their stable coexistence: the temporal storage effect via interannual variability in rainfall vs. rainfall partitioning via evergreen access to dry-season rainfall. In our model, both mechanisms resulted in coexistence, but coexistence was more robust via resource partitioning. Empirically, remotely sensed deciduousness increased with precipitation seasonality, but effects of interannual rainfall variability on deciduousness were minor. We hypothesize that dry-season rainfall may prove a stronger in uence on coexistence between leaf habits, and that changes in rainfall seasonality will have a greater impact on forest deciduousness than changes in the interannual variability of rainfall.

Predators mediate the strength of trophic cascades indirectly by decreasing the number of prey consuming a basal resource and by altering prey responses that dictate prey foraging. The strength of these indirect effects further depends on abiotic factors. For example, attributes of the environment, such as turbulent flows in aquatic habitats that disrupt spatial information available from chemical cues, can impose “sensory stresses” that impair the ability of predators or prey to detect each other. The multi-faceted impacts of sensory stress on both the predators and prey create challenges in predicting the overall effect on the trophic cascade. Here, we explore how sensory stress affects the strength of trophic cascades using a tri-trophic dynamical model that incorporates the sensory environment and anti-predatory responses. We explore two crucial parameters that govern outcomes of the model. First, we allow predation rates to either strengthen or weaken depending on whether prey or predators are more sensitive to sensory stress, respectively. Second, we explore scenarios where anti-predatory responses can either drive a strong or weak reduction in prey foraging. We find that sensory stress usually weakens trophic cascades except in scenarios where predators are relatively unaffected by sensory stress and the loss of anti-predatory responses does not affect prey foraging. The model finally suggests that “hydra effects” can manifest, whereby an increase in prey population occurs despite an increase in per capita predation. This last feature emerges due to the interaction between logistic growth of the basal resource and anti-predatory responses reducing the over-consumption of the basal resource.

Since the work of von Bertalanffy (Q Rev Boil 32:217–231, 1957), several models have been proposed that relate the ontogenetic scaling of energy assimilation and metabolism to growth, which are able to describe ontogenetic growth trajectories for living organisms and collapse them onto a single universal curve (West et al. in Nature 413:628–631, 2001; Barnavar et al. in Nature 420:626, 2002). Nevertheless, all these ontogenetic growth models critically depend on fitting parameters and on the allometric scaling of the metabolic rate. Using a new metabolic rate relation (Escala in Theor Ecol 12(4):415–425, 2019) applied to a Bertalanffy-type ontogenetic growth equation, we find that ontogenetic growth can also be described by a universal growth curve for all studied species, but without the aid of any fitting parameters (i.e., no fitting procedure is performed on individual growth curves). We find that the inverse of the heart frequency mathrm f_H, rescaled by the ratio of the specific energies for biomass creation and metabolism, defines the characteristic timescale for ontogenetic growth. Moreover, our model also predicts a generation time and lifespan that explain the origin of several “Life History Invariants’ (Charnov in Oxford University Press, Oxford, 1993) and predict that the Malthusian parameter should be inversely proportional to both the generation time and lifespan, in agreement with the data in the literature (Duncan et al. in Ecology 88:324–333 2007; Dillingham et al. in Paper 535, 2016; Hatton et al. in PNAS 116(43):21616–21622 2019). In our formalism, several critical timescales and rates (lifespan, generation time, and intrinsic population growth rate) are all proportional to the heart frequency mathrm f_H, and thus, their allometric scaling relations come directly from the allometry of the heart frequency, which is typically mathrm f_H propto M^{-0.25} under basal conditions.