This statistic shows the 20 countries with the highest population growth rate in 2024. In SouthSudan, the population grew by about 4.65 percent compared to the previous year, making it the country with the highest population growth rate in 2024. The global population Today, the global population amounts to around 7 billion people, i.e. the total number of living humans on Earth. More than half of the global population is living in Asia, while one quarter of the global population resides in Africa. High fertility rates in Africa and Asia, a decline in the mortality rates and an increase in the median age of the world population all contribute to the global population growth. Statistics show that the global population is subject to increase by almost 4 billion people by 2100. The global population growth is a direct result of people living longer because of better living conditions and a healthier nutrition. Three out of five of the most populous countries in the world are located in Asia. Ultimately the highest population growth rate is also found there, the country with the highest population growth rate is Syria. This could be due to a low infant mortality rate in Syria or the ever -expanding tourism sector.

In the middle of 2023, about 60 percent of the global population was living in Asia.The total world population amounted to 8.1 billion people on the planet. In other words 4.7 billion people were living in Asia as of 2023. Global populationDue to medical advances, better living conditions and the increase of agricultural productivity, the world population increased rapidly over the past century, and is expected to continue to grow. After reaching eight billion in 2023, the global population is estimated to pass 10 billion by 2060. Africa expected to drive population increase Most of the future population increase is expected to happen in Africa. The countries with the highest population growth rate in 2024 were mostly African countries. While around 1.47 billion people live on the continent as of 2024, this is forecast to grow to 3.9 billion by 2100. This is underlined by the fact that most of the countries wit the highest population growth rate are found in Africa. The growing population, in combination with climate change, puts increasing pressure on the world's resources.

Context

2021 World Population dataset which gets updated daily.

Content

2021_population.csv: File contains data for only live 2021 population count which gets updated daily. Also contains more information about the country's growth rate, area, etc. timeseries_population_count.csv: File contains data for live population count which gets updated daily but it contains last updated data also. Data in this file is managed day-wise.

Inspiration

This type of data can be used for population-related use cases. Like, my own dataset COVID Vaccination in World (updated daily), which requires population data. I believe there are more use cases that I didn't explore yet but might other Kaggler needs this. Time-series related use-case can be implemented on this data but I know it will take time to compile that amount of data. So stay tuned.

Laos LA: Survey Mean Consumption or Income per Capita: Total Population: 2017 PPP per day data was reported at 6.520 Intl $/Day in 2018. This records an increase from the previous number of 5.410 Intl $/Day for 2012. Laos LA: Survey Mean Consumption or Income per Capita: Total Population: 2017 PPP per day data is updated yearly, averaging 5.965 Intl $/Day from Dec 2012 (Median) to 2018, with 2 observations. The data reached an all-time high of 6.520 Intl $/Day in 2018 and a record low of 5.410 Intl $/Day in 2012. Laos LA: Survey Mean Consumption or Income per Capita: Total Population: 2017 PPP per day data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Laos – Table LA.World Bank.WDI: Social: Poverty and Inequality. Mean consumption or income per capita (2017 PPP $ per day) used in calculating the growth rate in the welfare aggregate of total population.;World Bank, Global Database of Shared Prosperity (GDSP) (http://www.worldbank.org/en/topic/poverty/brief/global-database-of-shared-prosperity).;;The choice of consumption or income for a country is made according to which welfare aggregate is used to estimate extreme poverty in the Poverty and Inequality Platform (PIP). The practice adopted by the World Bank for estimating global and regional poverty is, in principle, to use per capita consumption expenditure as the welfare measure wherever available; and to use income as the welfare measure for countries for which consumption is unavailable. However, in some cases data on consumption may be available but are outdated or not shared with the World Bank for recent survey years. In these cases, if data on income are available, income is used. Whether data are for consumption or income per capita is noted in the footnotes. Because household surveys are infrequent in most countries and are not aligned across countries, comparisons across countries or over time should be made with a high degree of caution.

Chad Survey Mean Consumption or Income per Capita: Total Population: 2017 PPP per day data was reported at 3.880 Intl $/Day in 2022. This records an increase from the previous number of 3.810 Intl $/Day for 2018. Chad Survey Mean Consumption or Income per Capita: Total Population: 2017 PPP per day data is updated yearly, averaging 3.845 Intl $/Day from Dec 2018 (Median) to 2022, with 2 observations. The data reached an all-time high of 3.880 Intl $/Day in 2022 and a record low of 3.810 Intl $/Day in 2018. Chad Survey Mean Consumption or Income per Capita: Total Population: 2017 PPP per day data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Chad – Table TD.World Bank.WDI: Social: Poverty and Inequality. Mean consumption or income per capita (2017 PPP $ per day) used in calculating the growth rate in the welfare aggregate of total population.;World Bank, Global Database of Shared Prosperity (GDSP) (http://www.worldbank.org/en/topic/poverty/brief/global-database-of-shared-prosperity).;;The choice of consumption or income for a country is made according to which welfare aggregate is used to estimate extreme poverty in the Poverty and Inequality Platform (PIP). The practice adopted by the World Bank for estimating global and regional poverty is, in principle, to use per capita consumption expenditure as the welfare measure wherever available; and to use income as the welfare measure for countries for which consumption is unavailable. However, in some cases data on consumption may be available but are outdated or not shared with the World Bank for recent survey years. In these cases, if data on income are available, income is used. Whether data are for consumption or income per capita is noted in the footnotes. Because household surveys are infrequent in most countries and are not aligned across countries, comparisons across countries or over time should be made with a high degree of caution.

Switzerland Survey Mean Consumption or Income per Capita: Total Population: 2017 PPP per day data was reported at 80.140 Intl $/Day in 2020. This records an increase from the previous number of 77.360 Intl $/Day for 2015. Switzerland Survey Mean Consumption or Income per Capita: Total Population: 2017 PPP per day data is updated yearly, averaging 78.750 Intl $/Day from Dec 2015 (Median) to 2020, with 2 observations. The data reached an all-time high of 80.140 Intl $/Day in 2020 and a record low of 77.360 Intl $/Day in 2015. Switzerland Survey Mean Consumption or Income per Capita: Total Population: 2017 PPP per day data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Switzerland – Table CH.World Bank.WDI: Social: Poverty and Inequality. Mean consumption or income per capita (2017 PPP $ per day) used in calculating the growth rate in the welfare aggregate of total population.;World Bank, Global Database of Shared Prosperity (GDSP) (http://www.worldbank.org/en/topic/poverty/brief/global-database-of-shared-prosperity).;;The choice of consumption or income for a country is made according to which welfare aggregate is used to estimate extreme poverty in the Poverty and Inequality Platform (PIP). The practice adopted by the World Bank for estimating global and regional poverty is, in principle, to use per capita consumption expenditure as the welfare measure wherever available; and to use income as the welfare measure for countries for which consumption is unavailable. However, in some cases data on consumption may be available but are outdated or not shared with the World Bank for recent survey years. In these cases, if data on income are available, income is used. Whether data are for consumption or income per capita is noted in the footnotes. Because household surveys are infrequent in most countries and are not aligned across countries, comparisons across countries or over time should be made with a high degree of caution.

Sweden SE: Survey Mean Consumption or Income per Capita: Total Population: 2011 PPP per day data was reported at 53.850 Intl $/Day in 2015. This records an increase from the previous number of 48.980 Intl $/Day for 2010. Sweden SE: Survey Mean Consumption or Income per Capita: Total Population: 2011 PPP per day data is updated yearly, averaging 51.415 Intl $/Day from Dec 2010 (Median) to 2015, with 2 observations. The data reached an all-time high of 53.850 Intl $/Day in 2015 and a record low of 48.980 Intl $/Day in 2010. Sweden SE: Survey Mean Consumption or Income per Capita: Total Population: 2011 PPP per day data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Sweden – Table SE.World Bank: Poverty. Mean consumption or income per capita (2011 PPP $ per day) used in calculating the growth rate in the welfare aggregate of total population.; ; World Bank, Global Database of Shared Prosperity (GDSP) circa 2010-2015 (http://www.worldbank.org/en/topic/poverty/brief/global-database-of-shared-prosperity).; ; The choice of consumption or income for a country is made according to which welfare aggregate is used to estimate extreme poverty in PovcalNet. The practice adopted by the World Bank for estimating global and regional poverty is, in principle, to use per capita consumption expenditure as the welfare measure wherever available; and to use income as the welfare measure for countries for which consumption is unavailable. However, in some cases data on consumption may be available but are outdated or not shared with the World Bank for recent survey years. In these cases, if data on income are available, income is used. Whether data are for consumption or income per capita is noted in the footnotes. Because household surveys are infrequent in most countries and are not aligned across countries, comparisons across countries or over time should be made with a high degree of caution.

China Survey Mean Consumption or Income per Capita: Bottom 40% of Population: 2017 PPP per day data was reported at 6.220 Intl $/Day in 2020. This records an increase from the previous number of 4.780 Intl $/Day for 2015. China Survey Mean Consumption or Income per Capita: Bottom 40% of Population: 2017 PPP per day data is updated yearly, averaging 5.500 Intl $/Day from Dec 2015 (Median) to 2020, with 2 observations. The data reached an all-time high of 6.220 Intl $/Day in 2020 and a record low of 4.780 Intl $/Day in 2015. China Survey Mean Consumption or Income per Capita: Bottom 40% of Population: 2017 PPP per day data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s China – Table CN.World Bank.WDI: Social: Poverty and Inequality. Mean consumption or income per capita (2017 PPP $ per day) of the bottom 40%, used in calculating the growth rate in the welfare aggregate of the bottom 40% of the population in the income distribution in a country.;World Bank, Global Database of Shared Prosperity (GDSP) (http://www.worldbank.org/en/topic/poverty/brief/global-database-of-shared-prosperity).;;The choice of consumption or income for a country is made according to which welfare aggregate is used to estimate extreme poverty in the Poverty and Inequality Platform (PIP). The practice adopted by the World Bank for estimating global and regional poverty is, in principle, to use per capita consumption expenditure as the welfare measure wherever available; and to use income as the welfare measure for countries for which consumption is unavailable. However, in some cases data on consumption may be available but are outdated or not shared with the World Bank for recent survey years. In these cases, if data on income are available, income is used. Whether data are for consumption or income per capita is noted in the footnotes. Because household surveys are infrequent in most countries and are not aligned across countries, comparisons across countries or over time should be made with a high degree of caution.

Albania Survey Mean Consumption or Income per Capita: Total Population: 2017 PPP per day data was reported at 13.950 Intl $/Day in 2020. This records an increase from the previous number of 13.320 Intl $/Day for 2018. Albania Survey Mean Consumption or Income per Capita: Total Population: 2017 PPP per day data is updated yearly, averaging 13.635 Intl $/Day from Dec 2018 (Median) to 2020, with 2 observations. The data reached an all-time high of 13.950 Intl $/Day in 2020 and a record low of 13.320 Intl $/Day in 2018. Albania Survey Mean Consumption or Income per Capita: Total Population: 2017 PPP per day data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Albania – Table AL.World Bank.WDI: Social: Poverty and Inequality. Mean consumption or income per capita (2017 PPP $ per day) used in calculating the growth rate in the welfare aggregate of total population.;World Bank, Global Database of Shared Prosperity (GDSP) (http://www.worldbank.org/en/topic/poverty/brief/global-database-of-shared-prosperity).;;The choice of consumption or income for a country is made according to which welfare aggregate is used to estimate extreme poverty in the Poverty and Inequality Platform (PIP). The practice adopted by the World Bank for estimating global and regional poverty is, in principle, to use per capita consumption expenditure as the welfare measure wherever available; and to use income as the welfare measure for countries for which consumption is unavailable. However, in some cases data on consumption may be available but are outdated or not shared with the World Bank for recent survey years. In these cases, if data on income are available, income is used. Whether data are for consumption or income per capita is noted in the footnotes. Because household surveys are infrequent in most countries and are not aligned across countries, comparisons across countries or over time should be made with a high degree of caution.

The statistic shows the total population of India from 2020 to 2030. In 2024, the estimated total population in India amounted to approximately 1.44 billion people. Total population in India India currently has the second-largest population in the world and is projected to overtake top-ranking China within forty years. Its residents comprise more than one-seventh of the entire world’s population, and despite a slowly decreasing fertility rate (which still exceeds the replacement rate and keeps the median age of the population relatively low), an increasing life expectancy adds to an expanding population. In comparison with other countries whose populations are decreasing, such as Japan, India has a relatively small share of aged population, which indicates the probability of lower death rates and higher retention of the existing population. With a land mass of less than half that of the United States and a population almost four times greater, India has recognized potential problems of its growing population. Government attempts to implement family planning programs have achieved varying degrees of success. Initiatives such as sterilization programs in the 1970s have been blamed for creating general antipathy to family planning, but the combined efforts of various family planning and contraception programs have helped halve fertility rates since the 1960s. The population growth rate has correspondingly shrunk as well, but has not yet reached less than one percent growth per year. As home to thousands of ethnic groups, hundreds of languages, and numerous religions, a cohesive and broadly-supported effort to reduce population growth is difficult to create. Despite that, India is one country to watch in coming years. It is also a growing economic power; among other measures, its GDP per capita was expected to triple between 2003 and 2013 and was listed as the third-ranked country for its share of the global gross domestic product.

New World player activity dataset from MMO Populations, combining monthly enhanced players and 30-day daily estimates generated from public signals.

Denmark DK: Survey Mean Consumption or Income per Capita: Total Population: 2017 PPP per day data was reported at 66.150 Intl $/Day in 2021. This records an increase from the previous number of 60.670 Intl $/Day for 2016. Denmark DK: Survey Mean Consumption or Income per Capita: Total Population: 2017 PPP per day data is updated yearly, averaging 63.410 Intl $/Day from Dec 2016 (Median) to 2021, with 2 observations. The data reached an all-time high of 66.150 Intl $/Day in 2021 and a record low of 60.670 Intl $/Day in 2016. Denmark DK: Survey Mean Consumption or Income per Capita: Total Population: 2017 PPP per day data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Denmark – Table DK.World Bank.WDI: Social: Poverty and Inequality. Mean consumption or income per capita (2017 PPP $ per day) used in calculating the growth rate in the welfare aggregate of total population.;World Bank, Global Database of Shared Prosperity (GDSP) (http://www.worldbank.org/en/topic/poverty/brief/global-database-of-shared-prosperity).;;The choice of consumption or income for a country is made according to which welfare aggregate is used to estimate extreme poverty in the Poverty and Inequality Platform (PIP). The practice adopted by the World Bank for estimating global and regional poverty is, in principle, to use per capita consumption expenditure as the welfare measure wherever available; and to use income as the welfare measure for countries for which consumption is unavailable. However, in some cases data on consumption may be available but are outdated or not shared with the World Bank for recent survey years. In these cases, if data on income are available, income is used. Whether data are for consumption or income per capita is noted in the footnotes. Because household surveys are infrequent in most countries and are not aligned across countries, comparisons across countries or over time should be made with a high degree of caution.

COVID-19 Trends MethodologyOur goal is to analyze and present daily updates in the form of recent trends within countries, states, or counties during the COVID-19 global pandemic. The data we are analyzing is taken directly from the Johns Hopkins University Coronavirus COVID-19 Global Cases Dashboard, though we expect to be one day behind the dashboard’s live feeds to allow for quality assurance of the data.Revisions added on 4/23/2020 are highlighted.Revisions added on 4/30/2020 are highlighted.Discussion of our assertion of an abundance of caution in assigning trends in rural counties added 5/7/2020. Correction on 6/1/2020Methodology update on 6/2/2020: This sets the length of the tail of new cases to 6 to a maximum of 14 days, rather than 21 days as determined by the last 1/3 of cases. This was done to align trends and criteria for them with U.S. CDC guidance. The impact is areas transition into Controlled trend sooner for not bearing the burden of new case 15-21 days earlier.Reasons for undertaking this work:The popular online maps and dashboards show counts of confirmed cases, deaths, and recoveries by country or administrative sub-region. Comparing the counts of one country to another can only provide a basis for comparison during the initial stages of the outbreak when counts were low and the number of local outbreaks in each country was low. By late March 2020, countries with small populations were being left out of the mainstream news because it was not easy to recognize they had high per capita rates of cases (Switzerland, Luxembourg, Iceland, etc.). Additionally, comparing countries that have had confirmed COVID-19 cases for high numbers of days to countries where the outbreak occurred recently is also a poor basis for comparison.The graphs of confirmed cases and daily increases in cases were fit into a standard size rectangle, though the Y-axis for one country had a maximum value of 50, and for another country 100,000, which potentially misled people interpreting the slope of the curve. Such misleading circumstances affected comparing large population countries to small population counties or countries with low numbers of cases to China which had a large count of cases in the early part of the outbreak. These challenges for interpreting and comparing these graphs represent work each reader must do based on their experience and ability. Thus, we felt it would be a service to attempt to automate the thought process experts would use when visually analyzing these graphs, particularly the most recent tail of the graph, and provide readers with an a resulting synthesis to characterize the state of the pandemic in that country, state, or county.The lack of reliable data for confirmed recoveries and therefore active cases. Merely subtracting deaths from total cases to arrive at this figure progressively loses accuracy after two weeks. The reason is 81% of cases recover after experiencing mild symptoms in 10 to 14 days. Severe cases are 14% and last 15-30 days (based on average days with symptoms of 11 when admitted to hospital plus 12 days median stay, and plus of one week to include a full range of severely affected people who recover). Critical cases are 5% and last 31-56 days. Sources:U.S. CDC. April 3, 2020 Interim Clinical Guidance for Management of Patients with Confirmed Coronavirus Disease (COVID-19). Accessed online. Initial older guidance was also obtained online. Additionally, many people who recover may not be tested, and many who are, may not be tracked due to privacy laws. Thus, the formula used to compute an estimate of active cases is: Active Cases = 100% of new cases in past 14 days + 19% from past 15-30 days + 5% from past 31-56 days - total deaths.We’ve never been inside a pandemic with the ability to learn of new cases as they are confirmed anywhere in the world. After reviewing epidemiological and pandemic scientific literature, three needs arose. We need to specify which portions of the pandemic lifecycle this map cover. The World Health Organization (WHO) specifies six phases. The source data for this map begins just after the beginning of Phase 5: human to human spread and encompasses Phase 6: pandemic phase. Phase six is only characterized in terms of pre- and post-peak. However, these two phases are after-the-fact analyses and cannot ascertained during the event. Instead, we describe (below) a series of five trends for Phase 6 of the COVID-19 pandemic.Choosing terms to describe the five trends was informed by the scientific literature, particularly the use of epidemic, which signifies uncontrolled spread. The five trends are: Emergent, Spreading, Epidemic, Controlled, and End Stage. Not every locale will experience all five, but all will experience at least three: emergent, controlled, and end stage.This layer presents the current trends for the COVID-19 pandemic by country (or appropriate level). There are five trends:Emergent: Early stages of outbreak. Spreading: Early stages and depending on an administrative area’s capacity, this may represent a manageable rate of spread. Epidemic: Uncontrolled spread. Controlled: Very low levels of new casesEnd Stage: No New cases These trends can be applied at several levels of administration: Local: Ex., City, District or County – a.k.a. Admin level 2State: Ex., State or Province – a.k.a. Admin level 1National: Country – a.k.a. Admin level 0Recommend that at least 100,000 persons be represented by a unit; granted this may not be possible, and then the case rate per 100,000 will become more important.Key Concepts and Basis for Methodology: 10 Total Cases minimum threshold: Empirically, there must be enough cases to constitute an outbreak. Ideally, this would be 5.0 per 100,000, but not every area has a population of 100,000 or more. Ten, or fewer, cases are also relatively less difficult to track and trace to sources. 21 Days of Cases minimum threshold: Empirically based on COVID-19 and would need to be adjusted for any other event. 21 days is also the minimum threshold for analyzing the “tail” of the new cases curve, providing seven cases as the basis for a likely trend (note that 21 days in the tail is preferred). This is the minimum needed to encompass the onset and duration of a normal case (5-7 days plus 10-14 days). Specifically, a median of 5.1 days incubation time, and 11.2 days for 97.5% of cases to incubate. This is also driven by pressure to understand trends and could easily be adjusted to 28 days. Source used as basis:Stephen A. Lauer, MS, PhD *; Kyra H. Grantz, BA *; Qifang Bi, MHS; Forrest K. Jones, MPH; Qulu Zheng, MHS; Hannah R. Meredith, PhD; Andrew S. Azman, PhD; Nicholas G. Reich, PhD; Justin Lessler, PhD. 2020. The Incubation Period of Coronavirus Disease 2019 (COVID-19) From Publicly Reported Confirmed Cases: Estimation and Application. Annals of Internal Medicine DOI: 10.7326/M20-0504.New Cases per Day (NCD) = Measures the daily spread of COVID-19. This is the basis for all rates. Back-casting revisions: In the Johns Hopkins’ data, the structure is to provide the cumulative number of cases per day, which presumes an ever-increasing sequence of numbers, e.g., 0,0,1,1,2,5,7,7,7, etc. However, revisions do occur and would look like, 0,0,1,1,2,5,7,7,6. To accommodate this, we revised the lists to eliminate decreases, which make this list look like, 0,0,1,1,2,5,6,6,6.Reporting Interval: In the early weeks, Johns Hopkins' data provided reporting every day regardless of change. In late April, this changed allowing for days to be skipped if no new data was available. The day was still included, but the value of total cases was set to Null. The processing therefore was updated to include tracking of the spacing between intervals with valid values.100 News Cases in a day as a spike threshold: Empirically, this is based on COVID-19’s rate of spread, or r0 of ~2.5, which indicates each case will infect between two and three other people. There is a point at which each administrative area’s capacity will not have the resources to trace and account for all contacts of each patient. Thus, this is an indicator of uncontrolled or epidemic trend. Spiking activity in combination with the rate of new cases is the basis for determining whether an area has a spreading or epidemic trend (see below). Source used as basis:World Health Organization (WHO). 16-24 Feb 2020. Report of the WHO-China Joint Mission on Coronavirus Disease 2019 (COVID-19). Obtained online.Mean of Recent Tail of NCD = Empirical, and a COVID-19-specific basis for establishing a recent trend. The recent mean of NCD is taken from the most recent fourteen days. A minimum of 21 days of cases is required for analysis but cannot be considered reliable. Thus, a preference of 42 days of cases ensures much higher reliability. This analysis is not explanatory and thus, merely represents a likely trend. The tail is analyzed for the following:Most recent 2 days: In terms of likelihood, this does not mean much, but can indicate a reason for hope and a basis to share positive change that is not yet a trend. There are two worthwhile indicators:Last 2 days count of new cases is less than any in either the past five or 14 days. Past 2 days has only one or fewer new cases – this is an extremely positive outcome if the rate of testing has continued at the same rate as the previous 5 days or 14 days. Most recent 5 days: In terms of likelihood, this is more meaningful, as it does represent at short-term trend. There are five worthwhile indicators:Past five days is greater than past 2 days and past 14 days indicates the potential of the past 2 days being an aberration. Past five days is greater than past 14 days and less than past 2 days indicates slight positive trend, but likely still within peak trend time frame.Past five days is less than the past 14 days. This means a downward trend. This would be an

Portugal PT: Survey Mean Consumption or Income per Capita: Total Population: 2017 PPP per day data was reported at 36.550 Intl $/Day in 2021. This records an increase from the previous number of 31.040 Intl $/Day for 2016. Portugal PT: Survey Mean Consumption or Income per Capita: Total Population: 2017 PPP per day data is updated yearly, averaging 33.795 Intl $/Day from Dec 2016 (Median) to 2021, with 2 observations. The data reached an all-time high of 36.550 Intl $/Day in 2021 and a record low of 31.040 Intl $/Day in 2016. Portugal PT: Survey Mean Consumption or Income per Capita: Total Population: 2017 PPP per day data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Portugal – Table PT.World Bank.WDI: Social: Poverty and Inequality. Mean consumption or income per capita (2017 PPP $ per day) used in calculating the growth rate in the welfare aggregate of total population.;World Bank, Global Database of Shared Prosperity (GDSP) (http://www.worldbank.org/en/topic/poverty/brief/global-database-of-shared-prosperity).;;The choice of consumption or income for a country is made according to which welfare aggregate is used to estimate extreme poverty in the Poverty and Inequality Platform (PIP). The practice adopted by the World Bank for estimating global and regional poverty is, in principle, to use per capita consumption expenditure as the welfare measure wherever available; and to use income as the welfare measure for countries for which consumption is unavailable. However, in some cases data on consumption may be available but are outdated or not shared with the World Bank for recent survey years. In these cases, if data on income are available, income is used. Whether data are for consumption or income per capita is noted in the footnotes. Because household surveys are infrequent in most countries and are not aligned across countries, comparisons across countries or over time should be made with a high degree of caution.

Many tropical species show declining populations. The pantropical order Trogoniformes has 76% of its species ranked as declining, reflecting a world-wide problem. Here we report on the reproductive ecology and life history traits of the declining and near-threatened old world Whitehead’s Trogon (Harpactes whiteheadi), the declining new world Collared Trogon (Trogon collaris) and the stable Masked Trogon (T. personatus). We also reviewed the literature on reproductive ecology and life history traits of trogons to assess possible commonalities that might help explain population declines. We found that the declining Whitehead’s and Masked Trogons had reasonable nest success (32% and 25%, respectively), while the stable Masked Trogon had poor reproductive success (9%), all contrary to population trends. However, the limited literature data suggested that poor reproductive success may be common among trogons, which may contribute to population declines. Parents fed young at a low rate and had long on-bouts for incubation and nestling warming that reduced activity at the nest, as favored by high nest predation risk over evolutionary time. We found that young fledged from the nest with poorly developed wings, as also favored by high nest predation risk. Evolved nestling periods among trogon species suggests that poor wing development is likely common. Wing development has been shown to affect juvenile survival after leaving the nest. The poor wing development may be an important contributor to population declines that deserves more attention. Evolved life history traits are important to recognize as creating population vulnerabilities in a changing world. Methods Whitehead’s Trogon was studied in Kinabalu Park, Sabah, Malaysian Borneo (6° 05'N, 116° 33'E), a 754 km2 protected area of primary forest. Research was conducted during the 2009–2020 breeding seasons from early February to mid-June. Seven study plots were established at elevations of 1,450–1,950 m. These plots were contiguously located and included ca. 560 ha, with each plot ca. 60–70 ha in size (Martin & Mouton, 2020). Collared and Masked Trogons were studied in the northern Andes in Yacambú National Park, a 269 km2 area in Lara State, western Venezuela (9°38′N 69°40′W). The fieldwork was restricted to primary cloud forest habitat between 1400 and 2000 m, encompassing a similar elevation range to our study in Borneo. Data was collected during seven breeding seasons from 2002 to 2008 and from late February to early July. Research was conducted on seven study plots similar in size (ca. 60-70 ha) to those on the Borneo site (Martin and Mouton 2020). These trogons were not focal study species, such that we did not collect as comprehensive data as for the Whitehead’s Trogon. In general, the same standardized data collection methods were used in both Borneo and Venezuela studies, described as following. We located nests by observational cues of breeding pairs and systematic search (Martin & Geupel, 1993; Şahin Arslan & Martin, 2019; Şahin Arslan, Muñoz, & Martin, 2023), and measured the nest and nest-substrate heights using clinometers. We obtained the elevation of the nest location with a GPS device (Garmin, Olathe, Kansas, USA) for Whitehead’s Trogon. A nest initiation date was specified as the day the first egg was laid in a nest, and the egg-laying season was characterized by the distribution of nest initiation dates. Nests were checked daily during egg-laying and the first two days of incubation to obtain the exact day the last egg was laid to ascertain the start day of incubation. If a nest was found during incubation and was of unknown age, we checked the nest daily until hatch. Nests were also checked daily or twice daily near hatching and fledging to obtain exact timing of transitions for measuring incubation and nestling period lengths (Martin, Oteyza, Boyce, Lloyd, & Ton, 2015; Martin, Oteyza, Mitchell, Potticary, & Lloyd, 2015; Şahin Arslan et al., 2023). Otherwise, nests were generally checked every other day in Borneo, but from 1-4 days in Venezuela, to determine status and predation (Martin & Geupel, 1993). Clutch size was only used from nests located during building or egg-laying. We did not include nests observed later to ensure no partial loss was included (Martin et al., 2006). The incubation period was defined as the number of days between the last egg laid and last egg hatched (Martin, Auer, Bassar, Niklison, & Lloyd, 2007; Nice, 1954). The nestling period was defined as the days between the last egg hatched and the last nestling fledged and only used for nests where the last egg laid and hatch days were observed within 24 h of precision (Martin, Lloyd, et al., 2011). Daily nest predation rates and daily survival rates were estimated using maximum likelihood estimation via the Mayfield method (Hensler & Nichols, 1981; Mayfield, 1961, 1975). This method is highly correlated with the logistic exposure method (Şahin Arslan & Martin, 2023; Shaffer, 2004) but allows more ready comparisons with the wider availability of Mayfield estimates in the literature. We considered a nest successful if parents were observed feeding young outside the nest or the young left within two days of normal fledging age. If nest contents disappeared earlier, we considered it to be due to predation. We used an electronic scale with 0.001 g accuracy (ACCULAB, Elk Grove, Illinois, USA) to weigh fresh eggs on the day the last egg was laid or within the first 2 d of incubation. Nestlings were weighed for the first 3 days and then every other day throughout the rest of the nestling period, while also measuring wing chord and tarsus length using calipers (Mitutoyo) with an accuracy of 0.01 mm. As a part of a banding program, some adults were captured using mist-nets, and their mass, wing chord and tarsus lengths were measured. Parental behavior at nests was recorded using video cameras for Whitehead’s Trogon during both incubation and nestling stages starting near sunrise. We put 30x zoom video-cameras 4–10 m from the nests and camouflaged the cameras to prevent possible disturbance. We generally sought 6 h video recordings of parental behavior at a nest, but they varied from 4–9 h each day of video recording (mean duration during incubation = 5.96 + 0.24 h, N = 27; during nestling period = 6.33 + 0.13 h, N = 97). Parental activity of the two trogon species in Venezuela were not video-recorded. Video recordings were used to quantify incubation nest attentiveness, as well as brooding attentiveness and feeding rates during the nestling period (Martin, Oteyza, Boyce, et al., 2015; Martin, Oteyza, Mitchell, et al., 2015; Şahin Arslan & Martin, 2019). Incubation nest attentiveness was measured as the percent of total video time that a parent sat on the eggs for each day of video recording (Martin, Oteyza, Boyce, et al., 2015). Brooding attentiveness for nestlings was calculated as the percent of video time that a parent sat on the nestlings for each day of video-recording, and feeding rates as the number of feeding trips of both parents to the nest-h for that recording. Statistics We conducted all analyses in R.4.2.2 (R Core Team 2022) and we present mean values with standard errors, ranges, and sample sizes. We estimated growth rate constants (K) for mass, tarsus length, and wing chord using the logistic growth model (Remeš & Martin, 2002). The model is based on the equation: W(t) = A/1 + e (−K∗(t−ti)), where W(t) is body mass, tarsus length, or wing chord length, A is the asymptotic size, t is age and ti is the age at the inflection point where growth rate changes from accelerating to decelerating, and K is the maximum rate of growth which is obtained at the inflection point (Martin, 2015). We tested for differences in the growth curves between Whitehead’s and Collared Trogons using the nls function in R, and using nest identity as a random effect, while specifying the above equation and running a model for each species and then testing for model differences between species using anova. We used generalized linear mixed-effects models through the glmer function in the lme4 package (Bates, Mächler, Bolker, & Walker, 2015) to investigate the fixed effect of nestling age and brood size on feeding rate, with nest identity as a random effect. Brooding behavior changed in a backwards logistic curve (Şahin Arslan et al., 2023) and is described by the same three parameters as for growth rate above, where in this case A = asymptote at hatching day, K = instantaneous rate of change at the inflection time point, t = the inflection time point where the curve changes from accelerating to decelerating. We used the SSlogis function in the nlme package (Pinheiro & Bates, 2023) to describe the relationship and test for differences between brood sizes in slope (K), intercept (A), and inflection time point (t) of brooding behavior by Whitehead’s Trogon while using nest identity as a random effect. P ≤ 0.05 was considered as statistically significant throughout.

Georgia GE: Survey Mean Consumption or Income per Capita: Total Population: 2011 PPP per day data was reported at 7.380 Intl $/Day in 2016. This records an increase from the previous number of 5.970 Intl $/Day for 2011. Georgia GE: Survey Mean Consumption or Income per Capita: Total Population: 2011 PPP per day data is updated yearly, averaging 6.675 Intl $/Day from Dec 2011 (Median) to 2016, with 2 observations. The data reached an all-time high of 7.380 Intl $/Day in 2016 and a record low of 5.970 Intl $/Day in 2011. Georgia GE: Survey Mean Consumption or Income per Capita: Total Population: 2011 PPP per day data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Georgia – Table GE.World Bank: Poverty. Mean consumption or income per capita (2011 PPP $ per day) used in calculating the growth rate in the welfare aggregate of total population.; ; World Bank, Global Database of Shared Prosperity (GDSP) circa 2010-2015 (http://www.worldbank.org/en/topic/poverty/brief/global-database-of-shared-prosperity).; ; The choice of consumption or income for a country is made according to which welfare aggregate is used to estimate extreme poverty in PovcalNet. The practice adopted by the World Bank for estimating global and regional poverty is, in principle, to use per capita consumption expenditure as the welfare measure wherever available; and to use income as the welfare measure for countries for which consumption is unavailable. However, in some cases data on consumption may be available but are outdated or not shared with the World Bank for recent survey years. In these cases, if data on income are available, income is used. Whether data are for consumption or income per capita is noted in the footnotes. Because household surveys are infrequent in most countries and are not aligned across countries, comparisons across countries or over time should be made with a high degree of caution.

Nicaragua NI: Survey Mean Consumption or Income per Capita: Total Population: 2011 PPP per day data was reported at 10.830 Intl $/Day in 2014. This records an increase from the previous number of 7.900 Intl $/Day for 2009. Nicaragua NI: Survey Mean Consumption or Income per Capita: Total Population: 2011 PPP per day data is updated yearly, averaging 9.365 Intl $/Day from Dec 2009 (Median) to 2014, with 2 observations. The data reached an all-time high of 10.830 Intl $/Day in 2014 and a record low of 7.900 Intl $/Day in 2009. Nicaragua NI: Survey Mean Consumption or Income per Capita: Total Population: 2011 PPP per day data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Nicaragua – Table NI.World Bank: Poverty. Mean consumption or income per capita (2011 PPP $ per day) used in calculating the growth rate in the welfare aggregate of total population.; ; World Bank, Global Database of Shared Prosperity (GDSP) circa 2010-2015 (http://www.worldbank.org/en/topic/poverty/brief/global-database-of-shared-prosperity).; ; The choice of consumption or income for a country is made according to which welfare aggregate is used to estimate extreme poverty in PovcalNet. The practice adopted by the World Bank for estimating global and regional poverty is, in principle, to use per capita consumption expenditure as the welfare measure wherever available; and to use income as the welfare measure for countries for which consumption is unavailable. However, in some cases data on consumption may be available but are outdated or not shared with the World Bank for recent survey years. In these cases, if data on income are available, income is used. Whether data are for consumption or income per capita is noted in the footnotes. Because household surveys are infrequent in most countries and are not aligned across countries, comparisons across countries or over time should be made with a high degree of caution.

Hungary HU: Survey Mean Consumption or Income per Capita: Total Population: 2017 PPP per day data was reported at 31.010 Intl $/Day in 2021. This records an increase from the previous number of 23.010 Intl $/Day for 2016. Hungary HU: Survey Mean Consumption or Income per Capita: Total Population: 2017 PPP per day data is updated yearly, averaging 27.010 Intl $/Day from Dec 2016 (Median) to 2021, with 2 observations. The data reached an all-time high of 31.010 Intl $/Day in 2021 and a record low of 23.010 Intl $/Day in 2016. Hungary HU: Survey Mean Consumption or Income per Capita: Total Population: 2017 PPP per day data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Hungary – Table HU.World Bank.WDI: Social: Poverty and Inequality. Mean consumption or income per capita (2017 PPP $ per day) used in calculating the growth rate in the welfare aggregate of total population.;World Bank, Global Database of Shared Prosperity (GDSP) (http://www.worldbank.org/en/topic/poverty/brief/global-database-of-shared-prosperity).;;The choice of consumption or income for a country is made according to which welfare aggregate is used to estimate extreme poverty in the Poverty and Inequality Platform (PIP). The practice adopted by the World Bank for estimating global and regional poverty is, in principle, to use per capita consumption expenditure as the welfare measure wherever available; and to use income as the welfare measure for countries for which consumption is unavailable. However, in some cases data on consumption may be available but are outdated or not shared with the World Bank for recent survey years. In these cases, if data on income are available, income is used. Whether data are for consumption or income per capita is noted in the footnotes. Because household surveys are infrequent in most countries and are not aligned across countries, comparisons across countries or over time should be made with a high degree of caution.

Chile CL: Survey Mean Consumption or Income per Capita: Total Population: 2011 PPP per day data was reported at 25.970 Intl $/Day in 2020. This records an increase from the previous number of 22.960 Intl $/Day for 2015. Chile CL: Survey Mean Consumption or Income per Capita: Total Population: 2011 PPP per day data is updated yearly, averaging 24.465 Intl $/Day from Dec 2015 (Median) to 2020, with 2 observations. The data reached an all-time high of 25.970 Intl $/Day in 2020 and a record low of 22.960 Intl $/Day in 2015. Chile CL: Survey Mean Consumption or Income per Capita: Total Population: 2011 PPP per day data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Chile – Table CL.World Bank.WDI: Social: Poverty and Inequality. Mean consumption or income per capita (2011 PPP $ per day) used in calculating the growth rate in the welfare aggregate of total population.; ; World Bank, Global Database of Shared Prosperity (GDSP) (http://www.worldbank.org/en/topic/poverty/brief/global-database-of-shared-prosperity).; ; The choice of consumption or income for a country is made according to which welfare aggregate is used to estimate extreme poverty in the Poverty and Inequality Platform (PIP). The practice adopted by the World Bank for estimating global and regional poverty is, in principle, to use per capita consumption expenditure as the welfare measure wherever available; and to use income as the welfare measure for countries for which consumption is unavailable. However, in some cases data on consumption may be available but are outdated or not shared with the World Bank for recent survey years. In these cases, if data on income are available, income is used. Whether data are for consumption or income per capita is noted in the footnotes. Because household surveys are infrequent in most countries and are not aligned across countries, comparisons across countries or over time should be made with a high degree of caution.

Jordan JO: Survey Mean Consumption or Income per Capita: Bottom 40% of Population: 2011 PPP per day data was reported at 5.530 Intl $/Day in 2010. This records an increase from the previous number of 5.050 Intl $/Day for 2008. Jordan JO: Survey Mean Consumption or Income per Capita: Bottom 40% of Population: 2011 PPP per day data is updated yearly, averaging 5.290 Intl $/Day from Dec 2008 (Median) to 2010, with 2 observations. The data reached an all-time high of 5.530 Intl $/Day in 2010 and a record low of 5.050 Intl $/Day in 2008. Jordan JO: Survey Mean Consumption or Income per Capita: Bottom 40% of Population: 2011 PPP per day data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Jordan – Table JO.World Bank: Poverty. Mean consumption or income per capita (2011 PPP $ per day) used in calculating the growth rate in the welfare aggregate of the bottom 40% of the population in the income distribution in a country.; ; World Bank, Global Database of Shared Prosperity (GDSP) circa 2010-2015 (http://www.worldbank.org/en/topic/poverty/brief/global-database-of-shared-prosperity).; ; The choice of consumption or income for a country is made according to which welfare aggregate is used to estimate extreme poverty in PovcalNet. The practice adopted by the World Bank for estimating global and regional poverty is, in principle, to use per capita consumption expenditure as the welfare measure wherever available; and to use income as the welfare measure for countries for which consumption is unavailable. However, in some cases data on consumption may be available but are outdated or not shared with the World Bank for recent survey years. In these cases, if data on income are available, income is used. Whether data are for consumption or income per capita is noted in the footnotes. Because household surveys are infrequent in most countries and are not aligned across countries, comparisons across countries or over time should be made with a high degree of caution.