a+: an increase in the variable favours nest survival.bThe persistence of the nesting-platform is predicted to be different for each builder species.

Evaluating the status of threatened and endangered salmonid populations requires information on the current status of the threats (e.g., habitat, hatcheries, hydropower, and invasives) and the risk of extinction (e.g., status and trend in the Viable Salmonid Population criteria). For salmonids in the Pacific Northwest, threats generally result in changes to physical and biological characteristi...

Long-term sustainability of breeds depends on having sufficient genetic diversity for adaptability to change, whether driven by climatic conditions or by priorities in breeding programs. Genetic diversity in Suffolk sheep in the U.S. was evaluated in four ways: 1) using genetic relationships from pedigree data [(n=64,310 animals recorded in the U.S. National Sheep Improvement Program (NSIP)]; 2) using molecular data (n=304 Suffolk genotyped with the OvineHD BeadChip); 3) comparing Australian (n=109) and Irish (n=55) Suffolk sheep to those in the U.S. using molecular data; and 4) assessing genetic relationships (connectedness) among active Suffolk flocks (n=18) in NSIP. By characterizing genetic diversity, a goal was to define the structure of a reference population for use for genomic selection strategies in this breed. Pedigree-based mean inbreeding level for the most recent year of available data was 5.5%. Ten animals defined 22.8% of the current gene pool. The effective population size (Ne) ranged from 27.5 to 244.2 based on pedigree and was 79.5 based on molecular data. Expected (HE) and observed (HO) heterozygosity were 0.317 and 0.306, respectively. Model-based population structure included 7 subpopulations. From Principal Component Analysis, countries separated into distinct populations. Within the U.S. population, flocks formed genetically disconnected clusters. A decline in genetic diversity over time was observed from both pedigree and genomic-based derived measures with evidence of population substructure as measured by FST. Using these measures of genetic diversity, a framework for establishing a genomic reference population in U.S. Suffolk sheep engaged in NSIP was proposed.

The "Forest Proximate People" (FPP) dataset is one of the data layers contributing to the development of indicator #13, “number of forest-dependent people in extreme poverty,” of the Collaborative Partnership on Forests (CPF) Global Core Set of forest-related indicators (GCS). The FPP dataset provides an estimate of the number of people living in or within 5 kilometers of forests (forest-proximate people) for the year 2019 with a spatial resolution of 100 meters at a global level.

For more detail, such as the theory behind this indicator and the definition of parameters, and to cite this data, see: Newton, P., Castle, S.E., Kinzer, A.T., Miller, D.C., Oldekop, J.A., Linhares-Juvenal, T., Pina, L. Madrid, M., & de Lamo, J. 2022. The number of forest- and tree-proximate people: A new methodology and global estimates. Background Paper to The State of the World’s Forests 2022 report. Rome, FAO.

Contact points:

Maintainer: Leticia Pina

Maintainer: Sarah E., Castle

Data lineage:

The FPP data are generated using Google Earth Engine. Forests are defined by the Copernicus Global Land Cover (CGLC) (Buchhorn et al. 2020) classification system’s definition of forests: tree cover ranging from 15-100%, with or without understory of shrubs and grassland, and including both open and closed forests. Any area classified as forest sized ≥ 1 ha in 2019 was included in this definition. Population density was defined by the WorldPop global population data for 2019 (WorldPop 2018). High density urban populations were excluded from the analysis. High density urban areas were defined as any contiguous area with a total population (using 2019 WorldPop data for population) of at least 50,000 people and comprised of pixels all of which met at least one of two criteria: either the pixel a) had at least 1,500 people per square km, or b) was classified as “built-up” land use by the CGLC dataset (where “built-up” was defined as land covered by buildings and other manmade structures) (Dijkstra et al. 2020). Using these datasets, any rural people living in or within 5 kilometers of forests in 2019 were classified as forest proximate people. Euclidean distance was used as the measure to create a 5-kilometer buffer zone around each forest cover pixel. The scripts for generating the forest-proximate people and the rural-urban datasets using different parameters or for different years are published and available to users. For more detail, such as the theory behind this indicator and the definition of parameters, and to cite this data, see: Newton, P., Castle, S.E., Kinzer, A.T., Miller, D.C., Oldekop, J.A., Linhares-Juvenal, T., Pina, L., Madrid, M., & de Lamo, J. 2022. The number of forest- and tree-proximate people: a new methodology and global estimates. Background Paper to The State of the World’s Forests 2022. Rome, FAO.

References:

Buchhorn, M., Smets, B., Bertels, L., De Roo, B., Lesiv, M., Tsendbazar, N.E., Herold, M., Fritz, S., 2020. Copernicus Global Land Service: Land Cover 100m: collection 3 epoch 2019. Globe.

Dijkstra, L., Florczyk, A.J., Freire, S., Kemper, T., Melchiorri, M., Pesaresi, M. and Schiavina, M., 2020. Applying the degree of urbanisation to the globe: A new harmonised definition reveals a different picture of global urbanisation. Journal of Urban Economics, p.103312.

WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton; Department of Geography and Geosciences, University of Louisville; Departement de Geographie, Universite de Namur) and Center for International Earth Science Information Network (CIESIN), Columbia University, 2018. Global High Resolution Population Denominators Project - Funded by The Bill and Melinda Gates Foundation (OPP1134076). https://dx.doi.org/10.5258/SOTON/WP00645

Online resources:

GEE asset for "Forest proximate people - 5km cutoff distance"

This dataset contains results from the Aurora Australis Voyage 7 (KROCK) 1992-93, related to mesoscale distribution of krill and zooplankton communities in Prydz Bay in relation to physical and biological oceanographic parameters. There were five objectives of this project: to define the distribution patterns and abundance of krill in the krill dominated continental shelf area of the Prydz Bay region; to define the krill population structure within this area and the distribution pattern of developmental stages, especially spawning females; to define the distribution patterns and composition of the other two principal communities, neritic and oceanic, which border the krill dominated community; to specifically determine the zooplankton composition within the main feeding area of Adelie Penguins from Bechervaise Island monitoring site, Mawson; to record and analyse various physical and biological processes, eg. salinity, temperature, ice and phytoplankton, to determine how these parameters affect the observed distribution patterns. Surveys of krill and other zooplankton were taken in Prydz Bay, Antarctica between January and February 1993. At each station, rectangular midwater trawls and CTDs/bottle casts were made. During the program, echosounders and echointegrators were operating to provide krill abundance and distribution data, in addition to that from the RMT trawls. Initial analysis has shown that Euphausia crystallorophias dominates the neritic community on the shelf, while Euphausia superba was found not to occur in high abundance in the central Prydz Bay area between 70 and 78 degrees East. This dataset is a subset of the full cruise.

The objective of this subtask of the Trans-Atlantic Study of Calanus (TASC) programme is to define the biochemical components of the diet needed for Calanus growth and reproduction and to determine, using laboratory cultures, how growth, egg production, and egg viability vary with the diversity of diet.

This subtask will establish cultures of C. finmarchicus, using material collected in the field programme, and will build on experience with C. helgolandicus, cultures of which are currently maintained over multiple generations at PML. This approach will provide relevant information for understanding life cycle phenomena and contribute to the calibration and validation of the population dynamics model (subtask 14). The culture facility will provide a central resource for TASC, both for studying behavioural mechanisms determining life history strategy, and enable new biochemical and molecular techniques to be evaluated under controlled conditions, before deployment in the field programme. In addition the laboratory culture experiments will address aspects of overwintering physiology based on suggestions from the field programme. The effect of environmental variables will be considered and the aim will be to mimic multi-generation Calanus population dynamics in the laboratory. It is an ultimate goal to have both sibling species in simultaneous culture, enabling critical comparative physiological studies to be made under defined conditions.

An increased effort in nutritional biochemistry, particularly lipid biochemistry, exploring the dietary links between Calanus and its food environment will significantly advance understanding of the relationships between diet and production. Dietary diversity is expected to enhance production. Recognising the importance of omnivory (Kleppel, 1993), new approaches are needed to establish relations between food quantity and quality, and development rate and egg production. It is well established that lipids play a vital role in the life history strategies of polar organisms (Sargent et al., 1993). However, it is poorly understood: a) how environmental variables determine the production of lipids in the marine environment and hence the availability to C. finmarchicus, b) the rate at which dietary lipid is ingested/assimilated by C. finmarchicus and/or biosynthesised in the field, c) if, in some circumstances, the availability of essential dietary lipids in the marine environment affects the growth and reproduction of Calanus. Optimal growth and egg production by Calanus requires an adequate food composition; some essential fatty acids, for example, cannot be synthesised by copepods. It is not clear whether the natural food environment is generally adequate in dietary terms, or whether Calanus spp. are sometimes limited by food composition in nature as opposed to food concentration. This needs to be determined; it is important to establish whether fecundity is driven by food characteristics, and to incorporate this critical linkage in models. This component of TASC will interact strongly with the proposed field programme, by providing key analytical and shipboard (weathership "M") experimental input to TASC cruises, and also by testing, under defined laboratory conditions, critical hypotheses generated by the field programme.

Controlled culture experiments under defined regimes will be combined with detailed lipid and molecular analysis, and population dynamics and modelling.

Context

[INSEE][1] is the official french institute gathering data of many types around France. It can be demographic (Births, Deaths, Population Density...), Economic (Salary, Firms by activity / size...) and more.
It can be a great help to observe and measure inequality in the french population.

Content

Four files are in the dataset :

• base_etablissement_par_tranche_effectif : give information on the number of firms in every french town, categorized by size , come from [INSEE][2].
  • CODGEO : geographique code for the town (can be joined with code_insee column from "name_geographic_information.csv')
  • LIBGEO : name of the town (in french)
  • REG : region number
  • DEP : depatment number
  • E14TST : total number of firms in the town
  • E14TS0ND : number of unknown or null size firms in the town
  • E14TS1 : number of firms with 1 to 5 employees in the town
  • E14TS6 : number of firms with 6 to 9 employees in the town
  • E14TS10 : number of firms with 10 to 19 employees in the town
  • E14TS20 : number of firms with 20 to 49 employees in the town
  • E14TS50 : number of firms with 50 to 99 employees in the town
  • E14TS100 : number of firms with 100 to 199 employees in the town
  • E14TS200 : number of firms with 200 to 499 employees in the town
  • E14TS500 : number of firms with more than 500 employees in the town

• name_geographic_information : give geographic data on french town (mainly latitude and longitude, but also region / department codes and names )

  • EU_circo : name of the European Union Circonscription
  • code_région : code of the region attached to the town
  • nom_région : name of the region attached to the town
  • chef.lieu_région : name the administrative center around the town
  • numéro_département : code of the department attached to the town
  • nom_département : name of the department attached to the town
  • préfecture : name of the local administrative division around the town
  • numéro_circonscription : number of the circumpscription
  • nom_commune : name of the town
  • codes_postaux : post-codes relative to the town
  • code_insee : unique code for the town
  • latitude : GPS latitude
  • longitude : GPS longitude
  • éloignement : i couldn't manage to figure out what was the meaning of this number

• net_salary_per_town_per_category : salaries around french town per job categories, age and sex

  • CODGEO : unique code of the town
  • LIBGEO : name of the town
  • SNHM14 : mean net salary
  • SNHMC14 : mean net salary per hour for executive
  • SNHMP14 : mean net salary per hour for middle manager
  • SNHME14 : mean net salary per hour for employee
  • SNHMO14 : mean net salary per hour for worker
  • SNHMF14 : mean net salary for women
  • SNHMFC14 : mean net salary per hour for feminin executive
  • SNHMFP14 : mean net salary per hour for feminin middle manager
  • SNHMFE14 : mean net salary per hour for feminin employee
  • SNHMFO14 : mean net salary per hour for feminin worker
  • SNHMH14 : mean net salary for man
  • SNHMHC14 : mean net salary per hour for masculin executive
  • SNHMHP14 : mean net salary per hour for masculin middle manager
  • SNHMHE14 : mean net salary per hour for masculin employee
  • SNHMHO14 : mean net salary per hour for masculin worker
  • SNHM1814 : mean net salary per hour for 18-25 years old
  • SNHM2614 : mean net salary per hour for 26-50 years old
  • SNHM5014 : mean net salary per hour for >50 years old
  • SNHMF1814 : mean net salary per hour for women between 18-25 years old
  • SNHMF2614 : mean net salary per hour for women between 26-50 years old
  • SNHMF5014 : mean net salary per hour for women >50 years old
  • SNHMH1814 : mean net salary per hour for men between 18-25 years old
  • SNHMH2614 : mean net salary per hour for men between 26-50 years old
  • SNHMH5014 : mean net salary per hour for men >50 years old

• population : [demographic][3] information in France per town, age, sex and living mode

  • NIVGEO : geographic level (arrondissement, communes...)
  • CODGEO : unique code for the town
  • LIBGEO : name of the town (might contain some utf-8 errors, this information has better quality name_geographic_information)
  • MOCO : cohabitation mode : [list and meaning available in Data description]
  • AGE80_17 : age category (slice of 5 years) | ex : 0 -> people between 0 and 4 years old
  • SEXE : sex, 1 for men | 2 for women
  • NB : Number of people in the category

• departments.geojson : contains the borders of french departments. From [Gregoire David (github)][4]

These datasets can be merged by : CODGEO = code_insee

Acknowledgements

The entire dataset has been created (and actualized) by INSEE, I just uploaded it on Kaggle after doing some jobs and checks ...

Occupation of native ecosystems by invasive plant species alters their structure and/or function. In Hawaii, a subset of introduced plants is regarded as extremely harmful due to competitive ability, ecosystem modification, and biogeochemical habitat degradation. By controlling this subset of highly invasive ecosystem modifiers, conservation managers could significantly reduce native ecosystem degradation. To assess the invasibility of vulnerable native ecosystems, we selected a proxy subset of these invasive plants and developed robust ensemble species distribution models to define their respective potential distributions. The combinations of all species models using both binary and continuous habitat suitability projections resulted in estimates of species richness and diversity that were subsequently used to define an invasibility metric. The invasibility metric was defined from species distribution models with 0.8; True Skill Statistic >0.75) as evaluated per species. Invasibility was further projected onto a 2100 Hawaii regional climate change scenario to assess the change in potential habitat degradation. The distribution defined by the invasibility metric delineates areas of known and potential invasibility under current climate conditions and, when projected into the future, estimates potential reductions in native ecosystem extent due to climate-driven invasive incursion. We have provided the code used to develop these metrics to facilitate their wider use (Code S1). This work will help determine the vulnerability of native-dominated ecosystems to the combined threats of climate change and invasive species, and thus help prioritize ecosystem and species management actions.

The movement of organisms between habitats is a fundamental process that occurs within all ecological disciplines. Once the organism has entered a recipient habitat, its behavior generates a movement pattern as it may remain, move on, return, or constantly move between, producing different population dynamics and environmental changes. Originally, “spillover” was one of these distinct patterns - the uni-directional movement from a donor habitat to a different, adjacent recipient habitat. However, ecological definitions of spillover have become overly generalized to include any cross-habitat movement. As spillover research has nearly doubled since 2018, it is imperative to have universal nomenclature and methods that can quantify the term. This will allow us to advance our understanding of organism behavior in dynamic landscapes. To assess how spillover has been addressed within empirical literature, we reviewed 337 studies and organized them into the ecological disciplines of agriculture, disease, fisheries, and habitat fragmentation. Each study’s definition of spillover and the methods used to quantify the term was analyzed using four definition criteria that differentiates different cross-habitat movement patterns. We then determined the specificity of the definition and if the methods used matched the definition provided. Authors often define spillover as a movement (45%) but assess the location of organisms instead (96%). Additionally, 98% of studies assume direct movement out of the donor habitat, which can lead to an over-estimation of movement distance and spillover effect within the recipient habit. Overall, few studies (12%) included methods that matched their own definition, revealing a distinct mismatch. This was particularly noticeable within the fisheries discipline, likely the result of studies incorporating 1.5-fold more criteria within their definitions. There is much theory of the potential impact of organism movement, yet different movement patterns are often not differentiated empirically. Thus, the actual impact within natural systems is unclear. This ambiguity additionally limits communication and collaboration that need universal definitions and methodology. Techniques that quantify movement directly, such as tracking and capture-mark-recapture, are more suited to understanding effective long-term management implications and the impacts of disturbance on populations and communities. Methods We compiled a database of spillover studies that were found in the Web of Science (http:www.webofknowledge.com) records up to March 31, 2021. We used the search terms “spillover” and “spill over”. We then excluded categories outside of the biology discipline (e.g., economic or chemical spillover) as well as human epidemiology literature, which uses language very distinct from ecological work. As the remaining publications included several hundred papers disparate from organismal spillover, we further refined our search using the terms “organism”, “biodiversity”, or “population”. Articles included in our database 1) specifically mentioned “spillover” or “spill over” within the text, 2) used living organisms as the propagule of movement, and 3) empirically assessed spillover or the consequences of spillover. In this way, we collected a broad spectrum of papers that included ecological, behavioral, evolutionary, applied, and basic science articles.

The increasing availability of hundreds of whole bacterial genomes provides opportunities for enhanced understanding of the genes and alleles responsible for clinically important phenotypes and how they evolved. However, it is a significant challenge to develop easy-to-use and scalable methods for characterizing these large and complex data and relating it to disease epidemiology. Existing approaches typically focus on either homologous sequence variation in genes that are shared by all isolates, or non-homologous sequence variation - focusing on genes that are differentially present in the population. Here we present a comparative genomics approach that simultaneously approximates core and accessory genome variation in pathogen populations and apply it to pathogenic species in the genus Campylobacter. A total of 7 published Campylobacter jejuni and Campylobacter coli genomes were selected to represent diversity across these species, and a list of all loci that were present at least once was compiled. After filtering duplicates a 7-isolate reference pan-genome, of 3,933 loci, was defined. A core genome of 1,035 genes was ubiquitous in the sample accounting for 59% of the genes in each isolate (average genome size of 1.68 Mb). The accessory genome contained 2,792 genes. A Campylobacter population sample of 192 genomes was screened for the presence of reference pan-genome loci with gene presence defined as a BLAST match of ≥70% identity over ≥50% of the locus length - aligned using MUSCLE on a gene-by-gene basis. A total of 21 genes were present only in C. coli and 27 only in C. jejuni, providing information about functional differences associated with species and novel epidemiological markers for population genomic analyses. Homologs of these genes were found in several of the genomes used to define the pan-genome and, therefore, would not have been identified using a single reference strain approach.