Relatório da OPAS mostra que as DCNTs continuam sendo a principal causa de morte e incapacidade nas Américas e alerta os países para que preparem os sistemas de saúde para uma população que envelhece rapidamente

Um novo relatório da Organização Pan-Americana da Saúde (OPAS) revela que, embora a expectativa de vida tenha aumentado nas Américas, também aumentou o número de pessoas que vivem com Doenças Crônicas Não Transmissíveis (DCNT).

Impact of infectious diseases on wild bovidae populations in Thailand: insights from population modelling and disease dynamics.

The wildlife and livestock interface is vital for wildlife conservation and habitat management. Infectious diseases maintained by domestic species may impact threatened species such as Asian bovids, as they share natural resources and habitats. To predict the population impact of infectious diseases with different traits, we used stochastic mathematical models to simulate the population dynamics over 100 years for 100 times in a model gaur (Bos gaurus) population with and without disease. We simulated repeated introductions from a reservoir, such as domestic cattle. We selected six bovine infectious diseases; anthrax, bovine tuberculosis, haemorrhagic septicaemia, lumpy skin disease, foot and mouth disease and brucellosis, all of which have caused outbreaks in wildlife populations. From a starting population of 300, the disease-free population increased by an average of 228% over 100 years. Brucellosis with frequency-dependent transmission showed the highest average population declines (-97%), with population extinction occurring 16% of the time. Foot and mouth disease with frequency-dependent transmission showed the lowest impact, with an average population increase of 200%. Overall, acute infections with very high or low fatality had the lowest impact, whereas chronic infections produced the greatest population decline. These results may help disease management and surveillance strategies support wildlife conservation.

The persistence of bipartite ecological communities with Lotka-Volterra dynamics.

The assembly and persistence of ecological communities can be understood as the result of the interaction and migration of species. Here we study a single community subject to migration from a species pool in which inter-specific interactions are organised according to a bipartite network. Considering the dynamics of species abundances to be governed by generalised Lotka-Volterra equations, we extend work on unipartite networks to we derive exact results for the phase diagram of this model. Focusing on antagonistic interactions, we describe factors that influence the persistence of the two guilds, locate transitions to multiple-attractor and unbounded phases, as well as identifying a region of parameter space in which consumers are essentially absent in the local community.

Assessing climate niche similarity between persian fallow deer (Dama mesopotamica) areas in Iran.

The Persian fallow deer or Mesopotamian fallow Deer (Dama mesopotamica, Brook 1875), a species of significant ecological importance, had faced the threat of extinction in Iran. One conservation strategy involved the translocation of Persian deer to enclosed areas across Iran, where they were afforded protection from external threats and provided with essential care by human caretakers. While human caretakers diligently attend to their needs and mitigate external threats, climate variables may now become critical factors affecting population dynamics in enclosed areas. This study aims to assess the similarity in climate niches between the original area (Dez and Karkheh) of the Persian deer species and 11 newly enclosed areas. To achieve this, we employed climate data and ecological niche modeling (ENM) techniques to assess the variations in climate among 12 areas. We utilized the environmental equivalency test to determine whether the environmental spaces of area pairs exhibit significant differences and whether these spaces are interchangeable. Extrapolation analyses were also constructed in the next steps to explore climatic conditions in original fallow deer habitats that are non-analogous to those in other parts of Iran. Our results reveal significant disparities in climate conditions between the original and all translocated areas. Based on observations of population growth in specific enclosed areas where translocated deer populations have thrived, we hypothesize that the species may demonstrate a non-equilibrium distribution in Iran. Consequently, these new areas could potentially be regarded as part of the species' potential climate niche. Extrapolation analysis showed that for a significant portion of Iran, extrapolation predictions are highly uncertain and potentially unreliable for the translocation of Persian fallow deer. However, the primary objective of translocation efforts remains the establishment of self-sustaining populations of Persian deer capable of thriving in natural areas beyond enclosed areas, thus ensuring their long-term survival and contributing to preservation efforts. Evaluating the success of newly translocated species requires additional time, with varying levels of success observed. In cases where the growth rate of the species in certain enclosed areas falls below expectations, it is prudent to consider climate variables that may contribute to population declines. Furthermore, for future translocations, we recommend selecting areas with climate similarities to regions where the species has demonstrated growth rates.

A Diffusion-Based Approach for Simulating Forward-in-Time State-Dependent Speciation and Extinction Dynamics.

We establish a general framework using a diffusion approximation to simulate forward-in-time state counts or frequencies for cladogenetic state-dependent speciation-extinction (ClaSSE) models. We apply the framework to various two- and three-region geographic-state speciation-extinction (GeoSSE) models. We show that the species range state dynamics simulated under tree-based and diffusion-based processes are comparable. We derive a method to infer rate parameters that are compatible with given observed stationary state frequencies and obtain an analytical result to compute stationary state frequencies for a given set of rate parameters. We also describe a procedure to find the time to reach the stationary frequencies of a ClaSSE model using our diffusion-based approach, which we demonstrate using a worked example for a two-region GeoSSE model. Finally, we discuss how the diffusion framework can be applied to formalize relationships between evolutionary patterns and processes under state-dependent diversification scenarios.

Source-Sink Dynamics in a Two-Patch SI Epidemic Model with Life Stages and No Recovery from Infection.

This study presents a comprehensive analysis of a two-patch, two-life stage SI model without recovery from infection, focusing on the dynamics of disease spread and host population viability in natural populations. The model, inspired by real-world ecological crises like the decline of amphibian populations due to chytridiomycosis and sea star populations due to Sea Star Wasting Disease, aims to understand the conditions under which a sink host population can present ecological rescue from a healthier, source population. Mathematical and numerical analyses reveal the critical roles of the basic reproductive numbers of the source and sink populations, the maturation rate, and the dispersal rate of juveniles in determining population outcomes. The study identifies basic reproduction numbers R 0 for each of the patches, and conditions for the basic reproduction numbers to produce a receiving patch under which its population. These findings provide insights into managing natural populations affected by disease, with implications for conservation strategies, such as the importance of maintaining reproductively viable refuge populations and considering the effects of dispersal and maturation rates on population recovery. The research underscores the complexity of host-pathogen dynamics in spatially structured environments and highlights the need for multi-faceted approaches to biodiversity conservation in the face of emerging diseases.

Future trends of marine fish biomass distributions from the North Sea to the Barents Sea.

Climate warming is one of the facets of anthropogenic global change predicted to increase in the future, its magnitude depending on present-day decisions. The north Atlantic and Arctic Oceans are already undergoing community changes, with warmer-water species expanding northwards, and colder-water species retracting. However, the future extent and implications of these shifts remain unclear. Here, we fitted a joint species distribution model to occurrence data of 107, and biomass data of 61 marine fish species from 16,345 fishery independent trawls sampled between 2004 and 2022 in the northeast Atlantic Ocean, including the Barents Sea. We project overall increases in richness and declines in relative dominance in the community, and generalised increases in species' ranges and biomass across three different future scenarios in 2050 and 2100. The projected decline of capelin and the practical extirpation of polar cod from the system, the two most abundant species in the Barents Sea, drove an overall reduction in fish biomass at Arctic latitudes that is not replaced by expanding species. Furthermore, our projections suggest that Arctic demersal fish will be at high risk of extinction by the end of the century if no climate refugia is available at eastern latitudes.

Prey group defense and hunting cooperation among generalist-predators induce complex dynamics: a mathematical study.

Group defense in prey and hunting cooperation in predators are two important ecological phenomena and can occur concurrently. In this article, we consider cooperative hunting in generalist predators and group defense in prey under a mathematical framework to comprehend the enormous diversity the model could capture. To do so, we consider a modified Holling-Tanner model where we implement Holling type IV functional response to characterize grazing pattern of predators where prey species exhibit group defense. Additionally, we allow a modification in the attack rate of predators to quantify the hunting cooperation among them. The model admits three boundary equilibria and up to three coexistence equilibrium points. The geometry of the nontrivial prey and predator nullclines and thus the number of coexistence equilibria primarily depends on a specific threshold of the availability of alternative food for predators. We use linear stability analysis to determine the types of hyperbolic equilibrium points and characterize the non-hyperbolic equilibrium points through normal form and center manifold theory. Change in the model parameters leading to the occurrences of a series of local bifurcations from non-hyperbolic equilibrium points, namely, transcritical, saddle-node, Hopf, cusp and Bogdanov-Takens bifurcation; there are also occurrences of global bifurcations such as homoclinic bifurcation and saddle-node bifurcation of limit cycles. We observe two interesting closed 'bubble' form induced by global bifurcations due to change in the strength of hunting cooperation and the availability of alternative food for predators. A three dimensional bifurcation diagram, concerning the original system parameters, captures how the alternation in model formulation induces gradual changes in the bifurcation scenarios. Our model highlights the stabilizing effects of group or gregarious behaviour in both prey and predator, hence supporting the predator-herbivore regulation hypothesis. Additionally, our model highlights the occurrence of "saltatory equilibria" in ecological systems and capture the dynamics observed for lion-herbivore interactions.

Analyzing post-COVID-19 demographic and mobility changes in Andalusia using mobile phone data.

This work studies changes in the demographics of the different spatial units that make up the Andalusia region in Spain throughout the year 2021, with the aim of seeing the progressive recovery of the population after the COVID-19 pandemic. Mobile phone data from Origin-Destination matrices has been used, due to the ease of obtaining updated information quickly and constantly. A methodology has been developed to transform the number of travelers into an estimated population without biases, and an interpolation function has been used to take into account all the data available in the year 2021. Results show a direct link between the demographic changes in Andalusia and the removal of the mobility restrictions caused by the COVID-19 pandemic, with an increase of non-related work mobility and a decrease of static population. Travel distances between home and work places are also affected, with an increase of long trips after the end of the mobility restrictions. In addition, different patterns have been visualized, such as the concentration of commuting in the metropolitan areas of the region during working days, the population growth in rural areas during weekends, or the population displacement to coastal areas in summer.

White-tailed deer population dynamics in a multipredator landscape shaped by humans.

Large terrestrial mammals increasingly rely on human-modified landscapes as anthropogenic footprints expand. Land management activities such as timber harvest, agriculture, and roads can influence prey population dynamics by altering forage resources and predation risk via changes in habitat, but these effects are not well understood in regions with diverse and changing predator guilds. In northeastern Washington state, USA, white-tailed deer (Odocoileus virginianus) are vulnerable to multiple carnivores, including recently returned gray wolves (Canis lupus), within a highly human-modified landscape. To understand the factors governing predator-prey dynamics in a human context, we radio-collared 280 white-tailed deer, 33 bobcats (Lynx rufus), 50 cougars (Puma concolor), 28 coyotes (C. latrans), and 14 wolves between 2016 and 2021. We first estimated deer vital rates and used a stage-structured matrix model to estimate their population growth rate. During the study, we observed a stable to declining deer population (lambda = 0.97, 95% confidence interval: 0.88, 1.05), with 74% of Monte Carlo simulations indicating population decrease and 26% of simulations indicating population increase. We then fit Cox proportional hazard models to evaluate how predator exposure, use of human-modified landscapes, and winter severity influenced deer survival and used these relationships to evaluate impacts on overall population growth. We found that the population growth rate was dually influenced by a negative direct effect of apex predators and a positive effect of timber harvest and agricultural areas. Cougars had a stronger effect on deer population dynamics than wolves, and mesopredators had little influence on the deer population growth rate. Areas of recent timber harvest had 55% more forage biomass than older forests, but horizontal visibility did not differ, suggesting that timber harvest did not influence predation risk. Although proximity to roads did not affect the overall population growth rate, vehicle collisions caused a substantial proportion of deer mortalities, and reducing these collisions could be a win-win for deer and humans. The influence of apex predators and forage indicates a dual limitation by top-down and bottom-up factors in this highly human-modified system, suggesting that a reduction in apex predators would intensify density-dependent regulation of the deer population owing to limited forage availability.

Spatio-Temporal distribution of a vector of cutaneous leishmaniasis: Pintomyia longiflocosa, in a population from the Colombian Andean Mountains.

BACKGROUND: Leishmaniasis, a neglected disease and public health concern, is associated with various factors such as biological, social, economical conditions and climate, increasing the risk of human infection. Understanding the population dynamics of the vectors, like Pintomyia longiflocosa, and its relationship with ecological variables is crucial for developing effective strategies to control sand fly populations and combat cutaneous leishmaniasis in a tropical country like Colombia. METHODOLOGY: Adult sand flies were collected in three different sample locations: outdoor, indoor, and peri-domestic areas in three houses located in the rural settlement of Campoalegre (Huila) between February 2020 and February 2021, using the CDC light traps. The sand fly density was quantified and associated with the sample locations and the sampling months using Analysis of Variance and Pearson correlations. PRINCIPAL FINDINGS: In the period of the sample, 98.86% of sand fly collected was identified as Pi. longiflocosa. The density of this species was significantly different between males and females, the latter contributing more to density in all sample locations (P<0.0001). The outdoor was the sample location with the highest and most significative density in this study (70%, P = 0.04). The density of these sand flies is related to the seasonality of Campoalegre, revealing a density peak from February and June to October (P < 0.05). Finally, precipitation is the environmental variable prominently linked to the density pattern, showing a negative correlation with it. Months with the highest precipitations show the lowest values of Pi. longiflocosa abundance. CONCLUSIONS/SIGNICANCE: Our investigation reveals a inverse correlation between precipitation levels and the abundance of Pi. longiflocosa in Campoalegre (Huila), particularly in outdoor areas. This suggests that vector control strategies to periods of reduced precipitation in outdoor settings could offer an effective approach to minimizing cases of cutaneous leishmaniasis in the region.

Measuring complexity for hierarchical models using effective degrees of freedom.

Hierarchical models can express ecological dynamics using a combination of fixed and random effects, and measurement of their complexity (effective degrees of freedom, EDF) requires estimating how much random effects are shrunk toward a shared mean. Estimating EDF is helpful to (1) penalize complexity during model selection and (2) to improve understanding of model behavior. I applied the conditional Akaike Information Criterion (cAIC) to estimate EDF from the finite-difference approximation to the gradient of model predictions with respect to each datum. I confirmed that this has similar behavior to widely used Bayesian criteria, and I illustrated ecological applications using three case studies. The first compared model parsimony with or without time-varying parameters when predicting density-dependent survival, where cAIC favors time-varying demographic parameters more than conventional Akaike Information Criterion. The second estimates EDF in a phylogenetic structural equation model, and identifies a larger EDF when predicting longevity than mortality rates in fishes. The third compares EDF for a species distribution model fitted for 20 bird species and identifies those species requiring more model complexity. These highlight the ecological and statistical insight from comparing EDF among experimental units, models, and data partitions, using an approach that can be broadly adopted for nonlinear ecological models.

Evolutionary Game Dynamics with Environmental Feedback in a Network with Two Communities.

Recent developments of eco-evolutionary models have shown that evolving feedbacks between behavioral strategies and the environment of game interactions, leading to changes in the underlying payoff matrix, can impact the underlying population dynamics in various manners. We propose and analyze an eco-evolutionary game dynamics model on a network with two communities such that players interact with other players in the same community and those in the opposite community at different rates. In our model, we consider two-person matrix games with pairwise interactions occurring on individual edges and assume that the environmental state depends on edges rather than on nodes or being globally shared in the population. We analytically determine the equilibria and their stability under a symmetric population structure assumption, and we also numerically study the replicator dynamics of the general model. The model shows rich dynamical behavior, such as multiple transcritical bifurcations, multistability, and anti-synchronous oscillations. Our work offers insights into understanding how the presence of community structure impacts the eco-evolutionary dynamics within and between niches.

Species interactions and eco-evolutionary dynamics of dispersal: the diversity dependence of dispersal.

Dispersal plays a pivotal role in the eco-evolutionary dynamics of spatially structured populations, communities and ecosystems. As an individual-based trait, dispersal is subject to both plasticity and evolution. Its dependence on conditions and context is well understood within single-species metapopulations. However, species do not exist in isolation; they interact locally through various horizontal and vertical interactions. While the significance of species interactions is recognized for species coexistence and food web functioning, our understanding of their influence on regional dynamics, such as their impact on spatial dynamics in metacommunities and meta-food webs, remains limited. Building upon insights from behavioural and community ecology, we aim to elucidate biodiversity as both a driver and an outcome of connectivity. By synthesizing conceptual, theoretical and empirical contributions from global experts in the field, we seek to explore how a more mechanistic understanding of diversity-dispersal relationships influences the distribution of species in spatially and temporally changing environments. Our findings highlight the importance of explicitly considering interspecific interactions as drivers of dispersal, thus reshaping our understanding of fundamental dynamics including species coexistence and the emergent dynamics of metacommunities and meta-ecosystems. We envision that this initiative will pave the way for advanced forecasting approaches to understanding biodiversity dynamics under the pressures of global change. This article is part of the theme issue 'Diversity-dependence of dispersal: interspecific interactions determine spatial dynamics'.

The role of Allee effects for Gaussian and Lévy dispersals in an environmental niche.

In the study of biological populations, the Allee effect detects a critical density below which the population is severely endangered and at risk of extinction. This effect supersedes the classical logistic model, in which low densities are favorable due to lack of competition, and includes situations related to deficit of genetic pools, inbreeding depression, mate limitations, unavailability of collaborative strategies due to lack of conspecifics, etc. The goal of this paper is to provide a detailed mathematical analysis of the Allee effect. After recalling the ordinary differential equation related to the Allee effect, we will consider the situation of a diffusive population. The dispersal of this population is quite general and can include the classical Brownian motion, as well as a Lévy flight pattern, and also a "mixed" situation in which some individuals perform classical random walks and others adopt Lévy flights (which is also a case observed in nature). We study the existence and nonexistence of stationary solutions, which are an indication of the survival chance of a population at the equilibrium. We also analyze the associated evolution problem, in view of monotonicity in time of the total population, energy consideration, and long-time asymptotics. Furthermore, we also consider the case of an "inverse" Allee effect, in which low density populations may access additional benefits.

Demographic effects of aggregation in the presence of a component Allee effect.

The component Allee effect (AE) is the positive correlation between an organism's fitness component and population density. Depending on the population spatial structure, which determines the interactions between organisms, a component AE might lead to positive density dependence in the population per-capita growth rate and establish a demographic AE. However, existing spatial models impose a fixed population spatial structure, which limits the understanding of how a component AE and spatial dynamics jointly determine the existence of demographic AEs. We introduce a spatially explicit theoretical framework where spatial structure and population dynamics are emergent properties of the individual-level demographic and movement rates. This framework predicts various spatial patterns depending on its specific parametrization, including evenly spaced aggregates of organisms, which determine the demographic-level by-products of the component AE. We find that aggregation increases population abundance and allows population survival in harsher environments and at lower global population densities when compared with uniformly distributed organisms. Moreover, aggregation can prevent the component AE from manifesting at the population level or restrict it to the level of each independent aggregate. These results provide a mechanistic understanding of how component AEs might operate for different spatial structures and manifest at larger scales.

Infestation of Lithodes santolla by Eremitione tuberculata: spatial and temporal variations in parasite prevalence and effect on host growth.

The southern king crab (SKC) Lithodes santolla is a crustacean parasitised by the bopyrid Eremitione tuberculata. This study aimed to analyse spatial and temporal variations in E. tuberculata prevalence in the juvenile SKC population of San Jorge Gulf (SJG) and adjacent waters (Argentine Patagonia), and evaluate the effects of the parasite on SKC juveniles to improve our understanding of its impact as a disease on SKC health condition. Moult increment and body weight were compared between parasitised and unparasitised individuals. The prevalence of E. tuberculata in SKC juveniles varied both spatially and temporally. In the south of SJG, the prevalence was 54.5% (n = 11). Temporal prevalence analysis revealed values lower than 17.4% in mid SJG during May and September 2015. No significant differences were observed in E. tuberculata prevalence between sexes or among seasons. Eremitione tuberculata had a negative effect on SKC growth (lower body dry mass, moult increment and relative increment rate) in parasitised individuals. We hypothesised that the higher prevalence of E. tuberculata in the south SJG could be attributed to the retention of parasite larvae and the presence of the frontal system in this part of the gulf. The temporal variations could reflect host mortality. Our results suggest that bopyrid infestation may have a more important role than previously believed in the dynamics of the SKC population in mid-Patagonia.

Climate change fluctuations can increase population abundance and range size.

Climate change threatens many species by a poleward/upward movement of their thermal niche. While we know that faster movement has stronger impacts, little is known on how fluctuations of niche movement affect population outcomes. Environmental fluctuations often affect populations negatively, but theory and experiments have revealed some positive effects. We study how fluctuations around the average speed of the niche impact a species' persistence, abundance and realized niche width under climate change. We find that the outcome depends on how fluctuations manifest and what the relative time scale of population growth and climate fluctuations are. When populations are close to extinction with the average speed, fluctuations around this average accelerate population decline. However, populations not yet close to extinction can increase in abundance and/or realized niche width from such fluctuations. Long-lived species increase more when their niche size remains constant, short-lived species increase more when their niche size varies.

When can higher-order interactions produce stable coexistence?

Most ecological models are based on the assumption that species interact in pairs. Diverse communities, however, can have higher-order interactions, in which two or more species jointly impact the growth of a third species. A pitfall of the common pairwise approach is that it misses the higher-order interactions potentially responsible for maintaining natural diversity. Here, we explore the stability properties of systems where higher-order interactions guarantee that a specified set of abundances is a feasible equilibrium of the dynamics. Even these higher-order interactions which lead to equilibria do not necessarily produce stable coexistence. Instead, these systems are more likely to be stable when the pairwise interactions are weak or facilitative. Correlations between the pairwise and higher-order interactions, however, do permit robust coexistence even in diverse systems. Our work not only reveals the challenges in generating stable coexistence through higher-order interactions but also uncovers interaction patterns that can enable diversity.