Urbanization is one of the major forms of habitat alteration occurring at the present time. Although this is typically deleterious to biodiversity, some species flourish within these human-modified landscapes, potentially leading to negative and/or positive interactions between people and wildlife. Hence, up-to-date assessment of urban wildlife populations is important for developing appropriate management strategies. Surveying urban wildlife is limited by land partition and private ownership, rendering many common survey techniques difficult. Garnering public involvement is one solution, but this method is constrained by the inherent biases of non-standardised survey effort associated with voluntary participation. We used a television-led media approach to solicit national participation in an online sightings survey to investigate changes in the distribution of urban foxes in Great Britain and to explore relationships between urban features and fox occurrence and sightings density. Our results show that media-based approaches can generate a large national database on the current distribution of a recognisable species. Fox distribution in England and Wales has changed markedly within the last 25 years, with sightings submitted from 91% of urban areas previously predicted to support few or no foxes. Data were highly skewed with 90% of urban areas having

Balancing human communities’ and ecosystems’ need for freshwater is one of the major challenges of the 21st century as population growth and improved living conditions put increasing pressure on freshwater resources. While frameworks to assess the environmental impacts of freshwater consumption have been proposed at the regional scale, an operational method to evaluate the consequences of consumption on different compartments of the water system and account for their interdependence is missing at the global scale. Here, we develop depletion factors that simultaneously quantify the effects of water consumption on streamflow, groundwater storage, soil moisture, and evapotranspiration globally. We estimate freshwater availability and water consumption using the output of a global-scale surface water–groundwater model for the period 1960–2000. The resulting depletion factors are provided for 8,664 river basins, representing 93% of the landmass with significant water consumption, i.e., excluding Greenland, Antarctica, deserts, and permanently frozen areas. Our findings show that water consumption leads to the largest water loss in rivers, followed by aquifers and soil, while simultaneously increasing evapotranspiration. Depletion factors vary regionally with ranges of up to four orders of magnitude depending on the annual consumption level, the type of water used, aridity, and water transfers between compartments. Our depletion factors provide valuable insights into the intertwined effects of surface and groundwater consumption on several hydrological variables over a specified period. The developed depletion factors can be integrated into sustainability assessment tools to quantify the ecological impacts of water consumption and help guide sustainable water management strategies, while accounting for the performance limitations of the underlying model.

The population growth rate (PGR) for Iiwi and Amakihi for feral pig control and predator removal in RCP8.5.

In 2023, over 68.82 percent of South Africa's total population lived in urban areas and cities. Urbanization defines the share of urban population from the total population of a country. Just like urbanization, the population density within the nation has risen, reaching 46 inhabitants per square kilometer, meaning more people are sharing less space. Many opportunities for work and leisure can be found in the urban locations of South Africa, and as such the five largest municipalities each now have over three million residents. Facing its economic strengths and drawbacks South Africa is a leading services destination, as it is one of the most industrialized countries in the continent of Africa. The majority of the country’s gross domestic product comes from the services sector, where more than 70 percent of the employed population works. Unemployment is seen as a critical indicator of the state of an economy, and for South Africa, a high rate of over 25 percent could indicate a need for a shift in economic policy. As of 2017, South Africa was one of the twenty countries with the highest rate of unemployment in the world.

This application presents JobSeeker Payment (previously Newstart Allowance) and Youth Allowance (other) recipients by SA2, comparing June 2019 to June 2024, combined with detailed demographics to support a greater understanding of unemployment payment distribution across Australia and changes in payment receipt over time. The number of unemployment payment recipients as of June 2024 is represented by the size of the circle for each SA2 (the larger the circle, the higher number of people receiving an unemployment payment), while the colour of the circle represents the change in unemployment payment receipt (see the legend for further details). Layers can be applied to display further supporting data and once an SA2 has been selected, detailed statistics are available on the ‘SA2 statistics’ page.This application is the result of collaboration between the Department of Social Services (DSS), the Australian Bureau of Statistics (ABS) and Geoscience Australia (GA).The application presents SA2 geographies. Unemployment payments data is published by DSS on data.gov.au. All supporting data is from the Australian Bureau of Statistics 'Data by Region' releases. The datasets included in the app are listed below:DSS Payments by Statistical Area 2*Selected DSS government pensions and allowances from 2019 to 2024 by 2021 SA2Selected DSS government pensions and allowances from 2019 to 2024 by 2021 SA2 TEABS Socio-Economic Indexes for Areas (SEIFA) by 2021 SA2ABS Population and people by 2021 SA2 Nov 2023Regional Population Change 2022-23 by 2021 SA2ABS Economy and industry by 2021 SA2 Nov 2023ABS Persons born overseas by 2021 SA2 Nov 2023ABS Family and community by 2021 SA2 Nov 2023ABS Estimated resident population 2001–2021 by 2021 SA2ABS Education and employment by 2021 SA2 Nov 2023ABS Economy and industry by 2021 SA2*Note, periods prior to June 2023 have had a correspondence applied, to align the data to the Australian Statistical Geography Standard 2021 SA2 boundaries.The application was built using Experience Builder software and designed to display unemployment payment recipient distribution across the country alongside other relevant information. It is intended to familiarise non-GIS professionals with available data and tools, as well as the spatial format. It is not intended to replace GIS analysis for decision making. This application is designed primarily for desktop view. Mobile view may be made available in the future with reduced functionality.More information on data and statisticsDisclaimerTo protect the privacy of Australians, certain data has been modified by authorised entities, in compliance with privacy regulations. Due to this, statistics here should be taken as a guide to inform understanding, please assume a small margin of error when using the app.Data limitations • Areas with small populations (under 500), the data may have a higher margin of error. This is because minor inaccuracies can have a bigger impact in these areas. • In some cases, data may appear to be missing. This is where there is a 'Null' value meaning this information is unavailable for this area. • Total Unemployment Payment recipients are calculated by summing already rounded data, this may result in minor inaccuracies.• The application uses the most recent Australian Bureau of Statistics population data available at the time of publication. The differing data dates may cause discrepancies in the calculation of proportional statistics (e.g., a high proportion of Income Support receipt where there has been extensive population growth between 2021 (when the census was collected) and the reported income support data date).Statistical Area Level 2 boundaries Statistical Areas Level 2 (SA2s) are areas designed to represent a community that interacts together socially and economically. SA2s are updated every census to reflect current communities and follow suburb or local government areas where appropriate. SA2s are a common standard for understanding and representing population data. Learn more about SA2s.Unemployment payment data An unemployment payment refers to JobSeeker Payment (previously Newstart Allowance) and Youth Allowance (other), which are income support payments made to a recipient that helps with living costs, while they look for work. The income support payment data in this application is published by DSS and represents the number of unique recipients of each payment as at the last Friday of the reported month. To protect individuals’ privacy, all values have been rounded to the nearest 5, values from 1 to 7 are rounded to 5. Zero cells are actual zeros. For older periods, figures between 1-4 were randomly assigned a 0 or a 5. Note: reporting rules and policy settings have changed over time, the data in this application has been updated to align over the reported period. Data for periods prior to 2023 may not align with data previously published. See the DSS data on data.gov.au: DSS Benefit and Payment Recipient Demographics - quarterly data | data.gov.au.Resources• A guide to Australian Government payments: Information on the different income support payments • Social Security Guide: Information on the legislation and how it's applied • DSS Benefit and Payment Recipient Demographics: Quarterly Income Support data release. See ‘Glossary’ and ‘Data Descriptions’ tabs for further data details. • DSS JobSeeker Payment and Youth Allowance recipients: Monthly JobSeeker Payment and Youth Allowance (other) data release. Supporting statistics All supporting data and statistics are from the ABS through their data by regions products on the Digital Atlas. Much of this data was collected as part of the most recent census (conducted in 2021). Data not from the census has been labelled accordingly. To learn more please see the data by regions methodology.SEIFA score The Socio-Economic Indexes for Areas (SEIFA) summarises areas according to their relative socio-economic advantage and disadvantage then ranks them. The "IRSAD (percentile)" index used here shows where an area stands nationally in terms of disadvantage or advantage. Lower numbers indicate more disadvantage and higher numbers indicate more advantage. It's presented as a percentile to make it easier to understand the ranking. For example, an area with an IRSAD (percentile) of 5 is in the top 5% of disadvantaged areas in the country. Whereas an area with an IRSAD (percentile) of 96 is in the top 5% of advantaged areas in the country. Learn more about using and interpreting SEIFA data.

The population growth rate (PGR) for Iiwi and Amakihi for malaria tolerance and refractory mosquitoes for RCP8.5.

The population growth rate (PGR) for Iiwi and Amakihi mid-elevation forests for malaria tolerance and sterile or incompatible male mosquitoes for RCP8.5.

The population growth rate (PGR) for Iiwi and Amakihi for feral pig control and release of sterile/incompatible male mosquitoes in RCP8.5.

Descriptive statistics of study variables (N = 849).

Direct and indirect effects of neighborhood structure factors on parenting stress among Asian American parents.