scholarly journals Origins of house mice in ecological niches created by settled hunter-gatherers in the Levant 15,000 y ago

2017 ◽  
Vol 114 (16) ◽  
pp. 4099-4104 ◽  
Author(s):  
Lior Weissbrod ◽  
Fiona B. Marshall ◽  
François R. Valla ◽  
Hamoudi Khalaily ◽  
Guy Bar-Oz ◽  
...  
Keyword(s):  
Environmental Influence ◽  
Human Mobility ◽  
Ecological Niches ◽  
House Mice ◽  
Hunter Gatherers ◽  
Wild Mice ◽  
Selection Dynamics ◽  
Pastoral Households ◽  
Animal Communities

Reductions in hunter-gatherer mobility during the Late Pleistocene influenced settlement ecologies, altered human relations with animal communities, and played a pivotal role in domestication. The influence of variability in human mobility on selection dynamics and ecological interactions in human settlements has not been extensively explored, however. This study of mice in modern African villages and changing mice molar shapes in a 200,000-y-long sequence from the Levant demonstrates competitive advantages for commensal mice in long-term settlements. Mice from African pastoral households provide a referential model for habitat partitioning among mice taxa in settlements of varying durations. The data reveal the earliest known commensal niche for house mice in long-term forager settlements 15,000 y ago. Competitive dynamics and the presence and abundance of mice continued to fluctuate with human mobility through the terminal Pleistocene. At the Natufian site of Ain Mallaha, house mice displaced less commensal wild mice during periods of heavy occupational pressure but were outcompeted when mobility increased. Changing food webs and ecological dynamics in long-term settlements allowed house mice to establish durable commensal populations that expanded with human societies. This study demonstrates the changing magnitude of cultural niche construction with varying human mobility and the extent of environmental influence before the advent of farming.

scholarly journals Special Issue on Climate Migration

2021 ◽  
pp. 1-3
Author(s):  
Anda David ◽  
Frédéric Docquier
Keyword(s):  
Climate Change ◽  
Human Mobility ◽  
Economic Research ◽  
Special Issue ◽  
Low Latitude ◽  
Weather Shocks ◽  
Temperature Trends ◽  
Agricultural Areas ◽  
Slow Onset

How do weather shocks influence human mobility and poverty, and how will long-term climate change affect future migration over the course of the 21st century? These questions have gained unprecedented attention in public debates as global warming is already having severe impacts around the world, and prospects for the coming decades get worse. Low-latitude countries in general, and their agricultural areas in particular, have contributed the least to climate change but are the most adversely affected. The effect on people's voluntary and forced displacements is of major concern for both developed and developing countries. On 18 October 2019, Agence Française de Développement (AFD) and Luxembourg Institute of Socio-Economic Research (LISER) organized a workshop on Climate Migration with the aim of uncovering the mechanisms through which fast-onset variables (such as weather anomalies, storms, hurricanes, torrential rains, floods, landslides, etc.) and slow-onset variables (such as temperature trends, desertification, rising sea level, coastal erosion, etc.) influence both people's incentives to move and mobility constraints. This special issue gathers five papers prepared for this workshop, which shed light on (or predict) the effect of extreme weather shocks and long-term climate change on human mobility, and stress the implications for the development community.

scholarly journals Climate Mobility and Development Cooperation

2021 ◽  
Author(s):  
Robert Stojanov ◽  
Sarah Rosengaertner ◽  
Alex de Sherbinin ◽  
Raphael Nawrotzki
Keyword(s):  
Climate Adaptation ◽  
Human Mobility ◽  
Climate Impacts ◽  
Development Cooperation ◽  
Climate Variability And Change ◽  
Policy Frameworks ◽  
And Migration ◽  
And Function ◽  
Role And Function

AbstractDevelopment cooperation actors have been addressing climate change as a cross-cutting issue and investing in climate adaptation projects since the early 2000s. More recently, as concern has risen about the potential impacts of climate variability and change on human mobility, development cooperation actors have begun to design projects that intentionally address the drivers of migration, including climate impacts on livelihoods. However, to date, we know little about the development cooperation’s role and function in responding to climate related mobility and migration. As such, the main aim of this paper is to outline the policy frameworks and approaches shaping development cooperation actors’ engagement and to identify areas for further exploration and investment. First, we frame the concept of climate mobility and migration and discuss some applicable policy frameworks that govern the issue from various perspectives; secondly, we review the toolbox of approaches that development cooperation actors bring to climate mobility; and third, we discuss the implications of the current Covid-19 pandemic and identify avenues for the way forward. We conclude that ensuring safe and orderly mobility and the decent reception and long-term inclusion of migrants and displaced persons under conditions of more severe climate hazards, and in the context of rising nationalism and xenophobia, poses significant challenges. Integrated approaches across multiple policy sectors and levels of governance are needed. In addition to resources, development cooperation actors can bring data to help empower the most affected communities and regions and leverage their convening power to foster more coordinated approaches within and across countries.

scholarly journals Tracking the global reduction of marine traffic during the COVID-19 pandemic

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
David March ◽  
Kristian Metcalfe ◽  
Joaquin Tintoré ◽  
Brendan J. Godley
Keyword(s):  
Large Scale ◽  
Human Mobility ◽  
Western Mediterranean ◽  
Western Mediterranean Sea ◽  
Marine Traffic ◽  
Human Movements ◽  
Exclusive Economic Zones ◽  
Global Impacts ◽  
Economic Zones

AbstractThe COVID-19 pandemic has resulted in unparalleled global impacts on human mobility. In the ocean, ship-based activities are thought to have been impacted due to severe restrictions on human movements and changes in consumption. Here, we quantify and map global change in marine traffic during the first half of 2020. There were decreases in 70.2% of Exclusive Economic Zones but changes varied spatially and temporally in alignment with confinement measures. Global declines peaked in April, with a reduction in traffic occupancy of 1.4% and decreases found across 54.8% of the sampling units. Passenger vessels presented more marked and longer lasting decreases. A regional assessment in the Western Mediterranean Sea gave further insights regarding the pace of recovery and long-term changes. Our approach provides guidance for large-scale monitoring of the progress and potential effects of COVID-19 on vessel traffic that may subsequently influence the blue economy and ocean health.

scholarly journals Insights into mammalian biology from the wild house mouse Mus musculus

eLife ◽  
2015 ◽  
Vol 4 ◽  
Author(s):  
Megan Phifer-Rixey ◽  
Michael W Nachman
Keyword(s):  
House Mouse ◽  
Mus Musculus ◽  
Genetic Model ◽  
Inbred Strains ◽  
Mendelian Inheritance ◽  
Model Organisms ◽  
House Mice ◽  
Small Subset ◽  
Wild Mice ◽  
Wide Range

The house mouse, Mus musculus, was established in the early 1900s as one of the first genetic model organisms owing to its short generation time, comparatively large litters, ease of husbandry, and visible phenotypic variants. For these reasons and because they are mammals, house mice are well suited to serve as models for human phenotypes and disease. House mice in the wild consist of at least three distinct subspecies and harbor extensive genetic and phenotypic variation both within and between these subspecies. Wild mice have been used to study a wide range of biological processes, including immunity, cancer, male sterility, adaptive evolution, and non-Mendelian inheritance. Despite the extensive variation that exists among wild mice, classical laboratory strains are derived from a limited set of founders and thus contain only a small subset of this variation. Continued efforts to study wild house mice and to create new inbred strains from wild populations have the potential to strengthen house mice as a model system.

Predicting Human Mobility with Reinforcement-Learning-Based Long-Term Periodicity Modeling

2021 ◽  
Vol 12 (6) ◽  
pp. 1-23
Author(s):  
Shuo Tao ◽  
Jingang Jiang ◽  
Defu Lian ◽  
Kai Zheng ◽  
Enhong Chen
Keyword(s):  
Reinforcement Learning ◽  
Human Mobility ◽  
Recurrent Network ◽  
Mobility Prediction ◽  
Learning Framework ◽  
Temporal Features ◽  
Wide Range ◽  
Spatio Temporal ◽  
Historical Trajectory

Mobility prediction plays an important role in a wide range of location-based applications and services. However, there are three problems in the existing literature: (1) explicit high-order interactions of spatio-temporal features are not systemically modeled; (2) most existing algorithms place attention mechanisms on top of recurrent network, so they can not allow for full parallelism and are inferior to self-attention for capturing long-range dependence; (3) most literature does not make good use of long-term historical information and do not effectively model the long-term periodicity of users. To this end, we propose MoveNet and RLMoveNet. MoveNet is a self-attention-based sequential model, predicting each user’s next destination based on her most recent visits and historical trajectory. MoveNet first introduces a cross-based learning framework for modeling feature interactions. With self-attention on both the most recent visits and historical trajectory, MoveNet can use an attention mechanism to capture the user’s long-term regularity in a more efficient way. Based on MoveNet, to model long-term periodicity more effectively, we add the reinforcement learning layer and named RLMoveNet. RLMoveNet regards the human mobility prediction as a reinforcement learning problem, using the reinforcement learning layer as the regularization part to drive the model to pay attention to the behavior with periodic actions, which can help us make the algorithm more effective. We evaluate both of them with three real-world mobility datasets. MoveNet outperforms the state-of-the-art mobility predictor by around 10% in terms of accuracy, and simultaneously achieves faster convergence and over 4x training speedup. Moreover, RLMoveNet achieves higher prediction accuracy than MoveNet, which proves that modeling periodicity explicitly from the perspective of reinforcement learning is more effective.

scholarly journals Between Foragers and Farmers: Climate Change and Human Strategies in Northwestern Patagonia

Quaternary ◽  
2020 ◽  
Vol 3 (2) ◽  
pp. 17
Author(s):  
Adolfo F. Gil ◽  
Ricardo Villalba ◽  
Fernando R. Franchetti ◽  
Clara Otaola ◽  
Cinthia C. Abbona ◽  
...  
Keyword(s):  
Human Population ◽  
Probability Distributions ◽  
Southern Annular Mode ◽  
Population Based ◽  
Hunter Gatherers ◽  
Temperature And Precipitation ◽  
N Isotopes ◽  
Wild Resources ◽  
C And N

In this paper we explore how changes in human strategies are differentially modulated by climate in a border area between hunter-gatherers and farmers. We analyze multiple proxies: radiocarbon summed probability distributions (SPDs), stable C and N isotopes, and zooarchaeological data from northwestern Patagonia. Based on these proxies, we discuss aspects of human population, subsistence, and dietary dynamics in relation to long-term climatic trends marked by variation in the Southern Annular Mode (SAM). Our results indicate that the farming frontier in northwestern Patagonia was dynamic in both time and space. We show how changes in temperature and precipitation over the last 1000 years cal BP have influenced the use of domestic plants and the hunting of highest-ranked wild animals, whereas no significant changes in human population size occurred. During the SAM positive phase between 900 and 550 years cal BP, warmer and drier summers are associated with an increase in C4 resource consumption (maize). After 550 years cal BP, when the SAM changes to the negative phase, wetter and cooler summer conditions are related to a change in diet focused on wild resources, especially meat. Over the past 1000 years, there was a non-significant change in the population based on the SPD.

scholarly journals Geocoding and spatio-temporal modeling of long-term PM2.5 and NO2 exposure: the Mexican Teachers´ Cohort

2021 ◽  
Author(s):  
KARLA CERVANTES-MARTINEZ ◽  
HORACIO RIOJAS-RODRÍGUEZ ◽  
CARLOS DÍAZ-AVALOS ◽  
HORTENSIA MORENO-MACÍAS ◽  
RUY LÓPEZ-RIDAURA ◽  
...  
Keyword(s):  
Predictive Accuracy ◽  
Human Mobility ◽  
Epidemiological Studies ◽  
Additive Models ◽  
Secondary Source ◽  
Source Information ◽  
Promising Alternative ◽  
Temporal Models ◽  
Spatio Temporal

Epidemiological studies on air pollution in Mexico often use the environmental concentrations of pollutants as measured by monitors closest to the home of participants as exposure proxies, yet this approach does not account for the space gradients of pollutants and ignores intra-city human mobility. This study aimed to develop high-resolution spatial and temporal models for predicting long-term exposure to PM2.5 and NO2 in ~16,500 participants from the Mexican Teachers’ Cohort study. We geocoded the home and work addresses of participants, and used secondary source information on geographical and meteorological variables as well as other pollutants to fit two generalized additive models capable of predicting monthly PM2.5 and NO2 concentrations during the 2004-2019 period. Both models were evaluated through 10-fold cross-validation, and showed high predictive accuracy with out-of-sample data and no overfitting (CV-RMSE=0.102 for PM2.5 and CV-RMSE=4.497 for NO2). Participants were exposed to a monthly average of 24.38 (6.78) mg/m3 of PM2.5 and 28.21 (8.00) ppb of NO2 during the study period. These models offer a promising alternative for estimating PM2.5 and NO2 exposure with high spatio-temporal resolution for epidemiological studies in the Mexico City Metropolitan Area.

scholarly journals Fine-tuning citrate synthase flux potentiates and refines metabolic innovation in the Lenski evolution experiment

eLife ◽  
2015 ◽  
Vol 4 ◽  
Author(s):  
Erik M Quandt ◽  
Jimmy Gollihar ◽  
Zachary D Blount ◽  
Andrew D Ellington ◽  
George Georgiou ◽  
...  
Keyword(s):  
Citrate Synthase ◽  
Fine Tuning ◽  
Ecological Niches ◽  
Glta Gene ◽  
Evolutionary Changes ◽  
Before And After ◽  
Evolution Experiment ◽  
History Of ◽  
Second Wave

Evolutionary innovations that enable organisms to colonize new ecological niches are rare compared to gradual evolutionary changes in existing traits. We discovered that key mutations in the gltA gene, which encodes citrate synthase (CS), occurred both before and after Escherichia coli gained the ability to grow aerobically on citrate (Cit+ phenotype) during the Lenski long-term evolution experiment. The first gltA mutation, which increases CS activity by disrupting NADH-inhibition of this enzyme, is beneficial for growth on the acetate and contributed to preserving the rudimentary Cit+ trait from extinction when it first evolved. However, after Cit+ was refined by further mutations, this potentiating gltA mutation became deleterious to fitness. A second wave of beneficial gltA mutations then evolved that reduced CS activity to below the ancestral level. Thus, dynamic reorganization of central metabolism made colonizing this new nutrient niche contingent on both co-opting and overcoming a history of prior adaptation.

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