Woody plant encroachment drives population declines in 20% of common open ecosystem bird species.

Grassy ecosystems cover more than 40% of the world's terrestrial surface, supporting crucial ecosystem services and unique biodiversity. These ecosystems have experienced major losses from conversion to agriculture with the remaining fragments threatened by global change. Woody plant encroachment, the increase in woody cover threatening grassy ecosystems, is a major global change symptom, shifting the composition, structure, and function of plant communities with concomitant effects on all biodiversity. To identify generalisable impacts of encroachment on biodiversity, we urgently need broad-scale studies on how species respond to woody cover change. Here, we make use of bird atlas, woody cover change data (between 2007 and 2016) and species traits, to assess: (1) population trends and woody cover responses using dynamic occupancy models; (2) how outcomes relate to habitat, diet and nesting traits; and (3) predictions of future occupancy trends, for 191 abundant, southern African bird species. We found that: (1) 63% (121) of species showed a decline in occupancy, with 18% (34) of species' declines correlated with increasing woody cover (i.e. losers). Only 2% (4) of species showed increasing population trends linked with increased woody cover (i.e. winners); (2) Open habitat specialist, invertivorous, ground nesting birds were the most frequent losers, however, we found no definitive evidence that the selected traits could predict outcomes; and (3) We predict open habitat loser species will take on average 52 years to experience 50% population declines with current rates of encroachment. Our results bring attention to concerning region-wide declining bird population trends and highlight woody plant encroachment as an important driver of bird population dynamics. Importantly, these findings should encourage improved management and restoration of our remaining grassy ecosystems. Furthermore, our findings show the importance of lands beyond protected areas for biodiversity, and the urgent need to mitigate the impacts of woody plant encroachment on bird biodiversity.

The impact of accelerating population aging on service industry development: Evidence from China.

The demographic structure is an important factor influencing the development of the services industry. As the country with the world's most serious aging problem, China's service industry structure is likely to undergo profound changes in response to the rapid demographic transition. Therefore, this paper examines the effect of population aging on the development of the service industry in the context of China's accelerating population aging. The study found that: (1) Population aging has a significant "inverted U" effect on the development of the services industry. (2) The impact of population aging on the development of the service industry has obvious regional and industry heterogeneity. The study of regional heterogeneity found that population aging in economically developed regions has a more obvious effect on the development of the service industry than in economically less developed regions. Industry heterogeneity studies found that population aging has an obvious promotional effect on the development of medical and other rigid demand industries, while the effect on other non-rigid demand industries is not significant. (3) The threshold effect test found that when the degree of population aging exceeds the threshold, the stimulating effect of population aging on the development of the services industry is no longer significant. The research in this paper provides useful insights into the likely response to changes in the industrial structure of the services industry, and offers some implications for countries with similar demographic profiles to China.

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.

Taxis-driven complex patterns of a plankton model.

This paper reports an important conclusion that self-diffusion is not a necessary condition for inducing Turing patterns, while taxis could establish complex pattern phenomena. We investigate pattern formation in a zooplankton-phytoplankton model incorporating phytoplankton-taxis, where phytoplankton-taxis describes the zooplankton that tends to move toward the high-densities region of the phytoplankton population. By using the phytoplankton-taxis sensitivity coefficient as the Turing instability threshold, one shows that the model exhibits Turing instability only when repulsive phytoplankton-taxis is added into the system, while the attractive-type phytoplankton-taxis cannot induce Turing instability of the system. In addition, the system does not exhibit Turing instability when the phytoplankton-taxis disappears. Numerically, we display the complex patterns in 1D, 2D domains and on spherical and zebra surfaces, respectively. In summary, our results indicate that the phytoplankton-taxis plays a pivotal role in giving rise to the Turing pattern formation of the model. Additionally, these theoretical and numerical results contribute to our understanding of the complex interaction dynamics between zooplankton and phytoplankton populations.

52,000 years of woolly rhinoceros population dynamics reveal extinction mechanisms.

The extinction of the woolly rhinoceros (Coelodonta antiquitatis) at the onset of the Holocene remains an enigma, with conflicting evidence regarding its cause and spatiotemporal dynamics. This partly reflects challenges in determining demographic responses of late Quaternary megafauna to climatic and anthropogenic causal drivers with available genetic and paleontological techniques. Here, we show that elucidating mechanisms of ancient extinctions can benefit from a detailed understanding of fine-scale metapopulation dynamics, operating over many millennia. Using an abundant fossil record, ancient DNA, and high-resolution simulation models, we untangle the ecological mechanisms and causal drivers that are likely to have been integral in the decline and later extinction of the woolly rhinoceros. Our 52,000-y reconstruction of distribution-wide metapopulation dynamics supports a pathway to extinction that began long before the Holocene, when the combination of cooling temperatures and low but sustained hunting by humans trapped woolly rhinoceroses in suboptimal habitats along the southern edge of their range. Modeling indicates that this ecological trap intensified after the end of the last ice age, preventing colonization of newly formed suitable habitats, weakening stabilizing metapopulation processes, triggering the extinction of the woolly rhinoceros in the early Holocene. Our findings suggest that fragmentation and resultant metapopulation dynamics should be explicitly considered in explanations of late Quaternary megafauna extinctions, sending a clarion call to the fragility of the remaining large-bodied grazers restricted to disjunct fragments of poor-quality habitat due to anthropogenic environmental change.

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.

How do host population dynamics impact Lyme disease risk dynamics in theoretical models?

Lyme disease is the most common wildlife-to-human transmitted disease reported in North America. The study of this disease requires an understanding of the ecology of the complex communities of ticks and host species involved in harboring and transmitting this disease. Much of the ecology of this system is well understood, such as the life cycle of ticks, and how hosts are able to support tick populations and serve as disease reservoirs, but there is much to be explored about how the population dynamics of different host species and communities impact disease risk to humans. In this study, we construct a stage-structured, empirically-informed model with host dynamics to investigate how host population dynamics can affect disease risk to humans. The model describes a tick population and a simplified community of three host species, where primary nymph host populations are made to fluctuate on an annual basis, as commonly observed in host populations. We tested the model under different environmental conditions to examine the effect of environment on the interactions of host dynamics and disease risk. Results show that allowing for host dynamics in the model reduces mean nymphal infection prevalence and increases the maximum annual prevalence of nymphal infection and the density of infected nymphs. Effects of host dynamics on disease measures of nymphal infection prevalence were nonlinear and patterns in the effect of dynamics on amplitude in nymphal infection prevalence varied across environmental conditions. These results highlight the importance of further study of the effect of community dynamics on disease risk. This will involve the construction of further theoretical models and collection of robust field data to inform these models. With a more complete understanding of disease dynamics we can begin to better determine how to predict and manage disease risk using these models.

Dams trigger exponential population declines of migratory fish.

The impact of dams on global migratory fish stocks is a major challenge and remains seriously underestimated. China has initiated a dozen fish rescue programs for the dams on the Yangtze River, focusing on five flagship species-Chinese sturgeon, Chinese paddlefish, Yangtze sturgeon, Chinese sucker, and Coreius guichenoti. Despite 40 years of effort, these five fishes are on the verge of extinction. Here, we propose an analytical tool that includes a framework of fish migration taxonomy and six life cycle models, the concepts of invalid stock and the dam impact coefficient, and a simplified population model. We then clarify the migration patterns and life cycles of these fishes and show that the Yangtze dams have severely disrupted the life cycle integrity of these species, causing seven types of invalid stocks and their exponential population declines. Last, we discuss six scientific misjudgments underpinning the fish rescue programs and recommend reforms to China's fish rescue strategy.

Mobility census for monitoring rapid urban development.

Monitoring urban structure and development requires high-quality data at high spatio-temporal resolution. While traditional censuses have provided foundational insights into demographic and socio-economic aspects of urban life, their pace may not always align with the pace of urban development. To complement these traditional methods, we explore the potential of analysing alternative big-data sources, such as human mobility data. However, these often noisy and unstructured big data pose new challenges. Here, we propose a method to extract meaningful explanatory variables and classifications from such data. Using movement data from Beijing, which are produced as a by-product of mobile communication, we show that meaningful features can be extracted, revealing, for example, the emergence and absorption of subcentres. This method allows the analysis of urban dynamics at a high-spatial resolution (here 500 m) and near real-time frequency, and high computational efficiency, which is especially suitable for tracing event-driven mobility changes and their impact on urban structures.

Time-dependent interaction modification generated from plant-soil feedback.

Pairwise interactions between species can be modified by other community members, leading to emergent dynamics contingent on community composition. Despite the prevalence of such higher-order interactions, little is known about how they are linked to the timing and order of species' arrival. We generate population dynamics from a mechanistic plant-soil feedback model, then apply a general theoretical framework to show that the modification of a pairwise interaction by a third plant depends on its germination phenology. These time-dependent interaction modifications emerge from concurrent changes in plant and microbe populations and are strengthened by higher overlap between plants' associated microbiomes. The interaction between this overlap and the specificity of microbiomes further determines plant coexistence. Our framework is widely applicable to mechanisms in other systems from which similar time-dependent interaction modifications can emerge, highlighting the need to integrate temporal shifts of species interactions to predict the emergent dynamics of natural communities.

Seasonal fluctuation and alternative host plants of vegetable crop-infesting tephritids in non-vegetable growing areas in South Sudanese zone of Burkina Faso.

This study was carried out in 3 types of biotopes where vegetable crops are not grown to highlight their contribution to the dynamics of vegetable-infesting flies. To this end, a trapping system based on a sexual attractant, the Cuelure associated with an insecticide was set up in 18 biotopes (6 natural areas, 6 mango orchards, and 6 agroforestry parks) in the regions of Hauts Bassins and Cascades in the South-West of Burkina Faso. During the trapping monitoring, which was done every 2 wk to collect insects captured, fruits present in 3 types of biotopes were sampled and incubated for insect emergence. Ten Dacus (Fabricius) [Diptera: Tephritidae] species and Zeugodacus cucurbitae (Coquillett) [Diptera: Tephritidae] were trapped in the study area. The predominant species captured was Z. cucurbitae (52.93%) followed by Dacus punctatifrons (Karsch) [Diptera: Tephritidae] (29.89%) and Dacus humeralis (Bezzi) (12.71%). Six tephritid species were emerged from 6 wild fruit species belonging to Cucurbitaceae, Apocynaceae, and Passifloraceae families. Fruit flies were more abundant from Jul to Nov with peaks observed in Aug or Oct depending on the species. Citrullus colocynthis L. (Cucurbitaceae), Lagenaria sp. (Cucurbitaceae), Passiflora foetida L. (Passifloraceae), and Passiflora sp. acted as reservoir host plants of Dacus ciliatus (Loew), Dacus bivittatus (Bigot), Dacus vertebratus (Bezzi) [Diptera: Tephritidae], D. punctatifrons, and Z. cucurbitae, the major vegetable insect pests in West Africa. The 3 types of biotopes acted as suitable refuge areas of vegetable crop-infesting fruit flies either for the favorable microclimate or for the alternative host plants.

The low survival rate of European hare leverets in arable farmland: evidence from the predation experiment.

The low survival rate of leverets may significantly contribute to steep population declines and slow recovery of European hares (Lepus europaeus). However, the leveret survival rate in farmlands with different landscape structures is poorly understood, and the existing evidence comes mainly from Western Europe. In this study, we explored the survival of leveret hare dummies along linear semi-natural habitats in homogeneous Central European arable farmland during the main part of the European hare reproduction period (March-April) in 2019 and 2020. The survival rate of hare leverets during the 14-day period was only 22.2%, and all predation events were recorded during the first six days of the experiment. Mammalian predators were responsible for 53.1% of predation events, avian predators for 40.8%, and agricultural operations for 6.1%. The red fox (Vulpes vulpes) was the dominant predator in our study area and was the primary cause of leveret dummy mortality (32.7%), but it also had the highest use-intensity and visit frequency of all of the study plots. Predation by avian predators was associated with patches of lower vegetation height and cover (such as plowed fields) and during daylight hours, whereas the opposite was true for mammalian predators. We propose that improving the habitat quality of arable landscapes by increasing the proportion and quality of extensively used non-farmed habitats (e.g., set-asides, wildflower areas, extensive meadows, fallow land, and semi-natural habitats on arable land) providing cover and shelter for leverets could be an effective management measure for reducing predation risk on leverets.

Emigration and fiscal gap in population-exporting region.

This paper analyzes how emigration impacts fiscal gap of population-exporting region in the long term. We construct a general equilibrium model of emigration and fiscal gap and make empirical verification using two-step system GMM model. Among the major lessons from this work, five general and striking results are worth highlighting: (1) the economic losses of emigration are the immediate cause of widening the fiscal gap. (2) in the short and long term, emigration can expand the fiscal revenue gap through the superimposed effect of tax rate and tax base. (3) the gap in fiscal expenditure is widened by the outflow of people in the short term. However, local governments would change the strategy to keep the spending gap from widening in the long run. (4) a positive impact of emigration on the fiscal gap. the more severe population emigration, the larger the fiscal gap. (5) when the trend of emigration becomes irreversible, the subsequent efforts of local governments to expand fiscal expenditure for attraction population would not only fail to revive the regional economy, but aggravate the expansion of fiscal gap. The contribution of research is twofold. On the one hand, it fills the theoretical gap between emigration and fiscal gap because previous studies have paid little attention to the fiscal problems of local government of population outflow. On the other hand, the selection of Northeast China that has been subject to long-term out-of-population migration is good evidence to verify this theory, which is tested very well using the 2S-GMM model. The comprehensive discussion on the relationship between emigration and fiscal gap is helpful to guide those continuous population-exporting regions that are facing a huge fiscal gap how to solve the fiscal gap and unsustainability from the perspective of fiscal revenue and expenditure.

A risk-induced dispersal strategy of the infected population for a disease-free state in the SIS epidemic model.

This article proposes a dispersal strategy for infected individuals in a spatial susceptible-infected-susceptible (SIS) epidemic model. The presence of spatial heterogeneity and the movement of individuals play crucial roles in determining the persistence and eradication of infectious diseases. To capture these dynamics, we introduce a moving strategy called risk-induced dispersal (RID) for infected individuals in a continuous-time patch model of the SIS epidemic. First, we establish a continuous-time n-patch model and verify that the RID strategy is an effective approach for attaining a disease-free state. This is substantiated through simulations conducted on 7-patch models and analytical results derived from 2-patch models. Second, we extend our analysis by adapting the patch model into a diffusive epidemic model. This extension allows us to explore further the impact of the RID movement strategy on disease transmission and control. We validate our results through simulations, which provide the effects of the RID dispersal strategy.

Contagion dynamics in time-varying metapopulation networks with node's activity and attractiveness.

The metapopulation network model is a mathematical framework used to study the spatial spread of epidemics with individuals' mobility. In this paper, we develop a time-varying network model in which the activity of a population is correlated with its attractiveness in mobility. By studying the spreading dynamics of the SIR (susceptible-infectious-recovered)-type disease in different correlated networks based on the proposed model, we theoretically derive the mobility threshold and numerically observe that increasing the correction between activity and attractiveness results in a reduced mobility threshold but suppresses the fraction of infected subpopulations. It also introduces greater heterogeneity in the spatial distribution of infected individuals. Additionally, we investigate the impact of nonpharmaceutical interventions on the spread of epidemics in different correlation networks. Our results show that the simultaneous implementation of self-isolation and self-protection is more effective in negatively correlated networks than that in positively correlated or non-correlated networks. Both self-isolation and self-protection strategies enhance the mobility threshold and, thus, slow down the spread of the epidemic. However, the effectiveness of each strategy in reducing the fraction of infected subpopulations varies in different correlated networks. Self-protection is more effective in positively correlated networks, whereas self-isolation is more effective in negatively correlated networks. Our study will provide insights into epidemic prevention and control in large-scale time-varying metapopulation networks.

Short-term extinction predicted by population viability analysis for a Neotropical salt marsh endemic bird.

Salt marshes pose challenges for the birds that inhabit them, including high rates of nest flooding, tipping, and predation. The impacts of rising sea levels and invasive species further exacerbate these challenges. To assess the urgency of conservation and adequacy of new actions, researchers and wildlife managers may use population viability analyses (PVAs) to identify population trends and major threats. We conducted PVA for Formicivora acutirostris, which is a threatened neotropical bird species endemic to salt marshes. We studied the species' demography in different sectors of an estuary in southern Brazil from 2006 to 2023 and estimated the sex ratio, longevity, productivity, first-year survival, and mortality rates. For a 133-year period, starting in 1990, we modeled four scenarios: (1) pessimistic and (2) optimistic scenarios, including the worst and best values for the parameters; (3) a baseline scenario, with intermediate values; and (4) scenarios under conservation management, with increased recruitment and/or habitat preservation. Projections indicated population decline for all assessment scenarios, with a 100% probability of extinction by 2054 in the pessimistic scenario and no extinction in the optimistic scenario. The conservation scenarios indicated population stability with 16% improvement in productivity, 10% improvement in first-year survival, and stable carrying capacity. The disjunct distribution of the species, with remnants concentrated in a broad interface with arboreal habitats, may seal the population decline by increasing nest predation. The species should be considered conservation dependent, and we recommend assisted colonization, predator control, habitat recovery, and ex situ conservation.

Population dynamics of dominant dinoflagellate species in the North Sea: in situ growth rates, photosynthetic potential, and losses due to parasitism.

In the North Sea, Tripos and Dinophysis are commonly occurring mixotrophic planktonic dinoflagellate genera. In order to understand their bloom dynamics, an occurring bloom dominated by T. furca and D. norvegica was followed for several days. High cell abundances of these species were located to estimate: in situ growth rates from cell cycle analyses, depth distributions, growth rates sustained by photosynthesis, and parasite infection prevalence in all T. furca, T. fusus, D. norvegica and D. acuminata. Cell abundances were over 10000 cells L-1 for T. furca and up to 18000 cells L-1 for D. norvegica. Cells accumulated between 15-25 m depth and presented low specific in situ growth rates of 0.04-0.15 d-1 for T. furca and 0.02-0.16 d-1 for D. norvegica. Photosynthesis could sustain growth rates of 0.01-0.18 d-1 for T. furca and 0.02 to 0.14 d-1 for D. norvegica, suggesting that these species were relying mainly on photosynthesis. Parasite infections where generally low, with occasional high prevalence in D. norvegica (by Parvilucifera sp.) and T. fusus (by Amoebophrya sp.), while both parasites showed comparable prevalence in D. acuminata, which could offset in situ growth rates by parasite-induced host mortality. The restructuring effect of parasites on dinoflagellate blooms is often overlooked and this study elucidates their effect to cell abundances and their growth at the final stages of a bloom.

Using neural ordinary differential equations to predict complex ecological dynamics from population density data.

Simple models have been used to describe ecological processes for over a century. However, the complexity of ecological systems makes simple models subject to modelling bias due to simplifying assumptions or unaccounted factors, limiting their predictive power. Neural ordinary differential equations (NODEs) have surged as a machine-learning algorithm that preserves the dynamic nature of the data (Chen et al. 2018 Adv. Neural Inf. Process. Syst.). Although preserving the dynamics in the data is an advantage, the question of how NODEs perform as a forecasting tool of ecological communities is unanswered. Here, we explore this question using simulated time series of competing species in a time-varying environment. We find that NODEs provide more precise forecasts than autoregressive integrated moving average (ARIMA) models. We also find that untuned NODEs have a similar forecasting accuracy to untuned long-short term memory neural networks and both are outperformed in accuracy and precision by empirical dynamical modelling . However, we also find NODEs generally outperform all other methods when evaluating with the interval score, which evaluates precision and accuracy in terms of prediction intervals rather than pointwise accuracy. We also discuss ways to improve the forecasting performance of NODEs. The power of a forecasting tool such as NODEs is that it can provide insights into population dynamics and should thus broaden the approaches to studying time series of ecological communities.

The impact of population aging on SME digital transformation: Evidence from China.

Many societies around the world are rapidly aging and this has implications for social and economic development. We collect data on NEEQ-listed enterprises from 2010 to 2021 in China and empirically test the effect of population aging on the digital transformation of small and medium-sized enterprises (SMEs). The findings show that population aging has a significant positive impact on SME digital transformation, and private enterprises and enterprises in eastern regions of China tend to benefit more than other regions. The mechanism studies find that population aging positively impacts SME digital transformation by increasing labor costs, facilitating human capital accumulation, and raising savings rates. Furthermore, the threshold effect analyses find that the marginal promotion effect of population aging will weaken with greater aging and will strengthen with a higher level of marketization. Finally, we provide policy recommendations for promoting digital transformation in SMEs against the background of population aging.