Between 1970 and 1989, the Soviet Union's population experienced a rate of natural increase that was consistently higher (sometimes by a significant margin) than that of the United States. In 1970, these increases were fairly similar at 9.2 and 8.8 per 1,000 population respectively, however the margin was considerably larger by the middle of the decade.

Although the Soviet Union's birth and death rates were both higher than those of the U.S. in most of these years, the larger disparity in birth rates is the reason for the USSR's higher rate of natural increase. However, while the USSR had a higher rate of natural increase, this did not mean that the Soviet population grew faster than that of the United States; the U.S. had a much higher net migration rate, which brought population growth rates much closer in the 1970s and 1980s.

Russia Rosstat Forecast: Mean: Natural Increase data was reported at -541,194.000 NA in 2035. This records a decrease from the previous number of -540,267.000 NA for 2034. Russia Rosstat Forecast: Mean: Natural Increase data is updated yearly, averaging -409,061.000 NA from Dec 2017 (Median) to 2035, with 19 observations. The data reached an all-time high of -155,731.000 NA in 2017 and a record low of -541,194.000 NA in 2035. Russia Rosstat Forecast: Mean: Natural Increase data remains active status in CEIC and is reported by Federal State Statistics Service. The data is categorized under Global Database’s Russian Federation – Table RU.GD012: Vital Statistics: Forecast: Rosstat: Annual.

Russia Rosstat Forecast: Mean: per 1000 Population: Natural Increase data was reported at -3.800 NA in 2035. This records a decrease from the previous number of -3.700 NA for 2034. Russia Rosstat Forecast: Mean: per 1000 Population: Natural Increase data is updated yearly, averaging -2.800 NA from Dec 2017 (Median) to 2035, with 19 observations. The data reached an all-time high of -1.000 NA in 2017 and a record low of -3.800 NA in 2035. Russia Rosstat Forecast: Mean: per 1000 Population: Natural Increase data remains active status in CEIC and is reported by Federal State Statistics Service. The data is categorized under Global Database’s Russian Federation – Table RU.GD012: Vital Statistics: Forecast: Rosstat: Annual.

In Czechia, the highest natural population increase in the observed period was recorded in 2010 at 10.3 thousand. In 2023, the natural population change was less than -21.6 thousand, meaning that the number of live births was lower than the number of deaths. Natural population change is the difference between the number of live births and deaths during a given period.

The COVID-19 pandemic resulted in an increase in the global death rate, but had little to no significant impact on birth rates, causing population growth to dip slightly. On a global level, population growth is determined by the difference between the birth and death rate, and this is known as the rate of natural change - on a national or regional level, population change is also affected by migration. Ongoing trends Since the middle of the 20th century, the global birth rate has been well above the global death rate, however, the gap between these figures has grown closer in recent years. The death rate is projected to overtake the birth rate in the 2080s, which means that the world's population will then go into decline. In the future, death rates will increase due to ageing populations across the world and a plateau in life expectancy. Why does this change? There are many reasons for falling death and birth rates in recent decades. Falling death rates have been driven by a reduction in infant and child mortality, as well as increased life expectancy. Falling birth rates were also driven by the reduction in child mortality, whereby mothers would have fewer children as survival rates rose - other factors include the drop in child marriage, improved contraception access and efficacy, and women choosing to have children later in life.

World population growth rate for 2023 was 0.92%, a 0.13% increase from 2022.

<ul style='margin-top:20px;'>

<li>World population growth rate for 2022 was <strong>0.79%</strong>, a <strong>0.07% decline</strong> from 2021.</li>
<li>World population growth rate for 2021 was <strong>0.87%</strong>, a <strong>0.15% decline</strong> from 2020.</li>
<li>World population growth rate for 2020 was <strong>1.01%</strong>, a <strong>0.05% decline</strong> from 2019.</li>
</ul>Annual population growth rate for year t is the exponential rate of growth of midyear population from year t-1 to t, expressed as a percentage . Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.

Following a spike to 2.5 children per woman in the mid-1960s (during the second wave of the post-WWII baby boom), Germany's fertility rate then fell sharply to around 1.5 children per woman in the 1970s, and it has fluctuated between 1.2 and 1.6 children per woman ever since. Germany's fertility rate has been below the natural replacement level of roughly 2.1 children per woman since 1970, meaning that long-term natural population growth is unsustainable. In fact, Germany has experienced a natural population decline in every year since 1972, and its population has only grown or been sustained at its current level through high net immigration rates.Find more statistics on other topics about Germany with key insights such as crude birth rate, life expectancy of women at birth, and total life expectancy at birth.

This dataset contains percentage cover of plants, mean numbers of aphids, mean counts of predators and mean counts of herbivores on three crops (field bean, wheat and oilseed rape) within different grassland types (improved, restored and species rich). Data were collected in 2013 on five farms in the Salisbury Plain area of the UK as part of the Wessex Biodiversity and Ecosystem Services Sustainability (BESS) project within the UK Natural Environment Research Council (NERC) BESS programme. This data set was used to provide an assessment of the potential for different grassland types to provide natural pest control ecosystem services. The study uses sentinel plants of the three crops established in the grasslands to monitor herbivorous pest insects, predatory insect occurrence and the population growth rates of artificially established aphids. Full details about this dataset can be found at https://doi.org/10.5285/4c02ae08-5703-46f4-947e-80e5d0a34a28

From 1950 to 2023, the cyclone Bhola that hit Bangladesh in 1970 was the deadliest natural disaster in the world. The exact death toll is impossible to calculate, but it is estimated that over 300,000 lives were lost as a result of the cyclone. The Tangshan earthquake in China in 1976 is estimated to have caused the second highest number of fatalities. The Haiti earthquake The fifth deadliest natural disaster during this period was the earthquake in Haiti in 2010. However, death tolls vary between 100,000 and 316,000, meaning that some estimates makes it the deadliest natural disaster in the world since 1950, and the deadliest earthquake since 1900. Sixty percent of the country’s hospitals and eighty percent of the country’s schools were destroyed. It was the worst earthquake to hit the Caribbean in 200 years, with a magnitude of 7.0 at its epicenter only 25 kilometers away from Haiti’s capital, Port-au-Prince. Poor construction practices were to blame for many of the deaths; Haiti’s buildings were not earthquake resistant and were not built according to building code due to a lack of licensed building professionals. High population density was also to blame for the high number of fatalities. One fourth of the country’s inhabitants lived in the Port-au-Prince area, meaning half of the country’s population was directly affected by the earthquake. Increasing extreme weather As global warming continues to accelerate climate change, it is estimated that natural catastrophes such as cyclones, rainfalls, landslides, and heat waves will intensify in the coming years and decades. For instance, the economic losses caused by natural disasters worldwide increased since 2015. Moreover, it is expected that countries in the Global South will be affected the most by climate change in the coming years, and many of these are already feeling the impact of climate change.

rm: intrinsic rate of natural increase, GRR: gross reproduction rate, R0: net reproduction rate, Tc: mean generation time (in days), Dt: doubling time (in days), and λ: finite rate of increase.

Rosstat预测：平均值：每1000人：自然增长在12-01-2035达-3.800NA，相较于12-01-2034的-3.700NA有所下降。Rosstat预测：平均值：每1000人：自然增长数据按年更新，12-01-2017至12-01-2035期间平均值为-2.800NA，共19份观测结果。该数据的历史最高值出现于12-01-2017，达-1.000NA，而历史最低值则出现于12-01-2035，为-3.800NA。CEIC提供的Rosstat预测：平均值：每1000人：自然增长数据处于定期更新的状态，数据来源于Федеральная служба государственной статистики，数据归类于全球数据库的俄罗斯联邦 – Table RU.GD012: Vital Statistics: Forecast: Rosstat: Annual。

Sample sizes (number of trees) are indicated between parentheses.

Strawberry guava (waiawī, Psidium cattleyanum O. Deg., Myrtaceae) is a small tree invasive on oceanic islands where it may alter forest ecosystem processes and community structure. To better understand the dynamics of its invasion in Hawaiian rainforests in anticipation of the release of a biocontrol agent, we measured growth and abundance of vertical stems >= 0.5 cm DBH for 16 years (2005-2020) in an intact Metrosideros-Cibotium rainforest on windward Hawai'i Island. Specifically, we compared the growth and abundance of both shoots (originating from seed or from the root mat) and sprouts (originating above ground from established stems) in four replicate study sites. Mean stem density increased from 9562 stems/ha in 2005 to 26,595 stems/ha in 2020, the majority of which were stems < 2 cm DBH. Mean annual rates of population growth (lambda) varied between 1.03 and 1.17. Early in the invasion, both density and per capita recruitment of shoots was greater than that of sprouts, but as overall stem density increased over time, sprout abundance and recruitment came to surpass that of shoots. Relative growth rates among small stems < 2 cm DBH declined over time for both shoots and sprouts, but relative growth rates of sprouts were consistently greater than that of shoots after the first 3 years. The capacity of strawberry guava to recruit from both rooted shoots and vegetative sprouts contributes to the facility with which it can invade intact rainforest, persist in the forest understory, and respond to canopy opening. Strawberry guava thus poses a considerable risk of stand replacement for Hawaiian rainforests. Stand management will require perpetual efforts of guava control at high priority sites as extreme weather events associated with climate change bring canopy-opening events due to storms, drought and pathogens. Methods Sites: We measured guava stem diameters annually between 2005 and 2020 at each of four replicate study plots selected to represent early stages of strawberry guava invasions in intact Metrosideros-Cibotium rainforest on windward Hawai'i Island (Juvik and Juvik 1998). Wet forests in Hawai'i are high priority conservation areas because of the biological diversity they harbor and their importance in the water economy of the islands (Jacobi and Warshauer 1992, Tunison 1992). Our study plots were established in the following conservation areas: Kahauale'a Natural Area Reserve (KAH, 19o10'N, 155o10'W), Pu'u Maka'ala Natural Area Reserve (MAK, 19o34'N, 155o11'W), Ola'a Forest Reserve (OLA, 19o27'N, 155o11'W), and Upper Waiakea Forest Reserve (WAI, 19o35'N, 155o12'W). All sites are at approximately 900 m elevation and distances between sites are 2 to 17 km. Estimated annual rainfall is 3000-4000 mm at OLA and KAH and 4000-5000 mm at WAI and MAK (Giambelluca et al. 1996). Projected mean annual temperature based on adiabatic lapse rates is 17-17.5° C for the elevation range of the four study sites (Giambelluca and Schroeder 1998). All sites are on relatively young tholeiitic basalt lava flows that formed 200-1500 years BP (Wolfe and Morris 1996). The forests resemble native lowland (100-1200m elevation) wet forests with an 'ōhi'a lehua (Metrosideros polymorpha Gaud) overstory and an understory dominated by tree fern hāpu'u (Cibotium spp.) as described by Gagne and Cuddihy (1999) and Juvik and Juvik (1998). All areas are under conservation protection by the State of Hawai'i. Species: Strawberry guava (waiawī, Psidium cattleyanum O. Deg.) is a small tree, 2-8 m tall. The yellow-fruited form (P. cattleyanum f. lucidum), dominant in the forests studied here, is one of three forms common across Hawai'i (Wagner et al. 1999) occurring in similar habitats. Strawberry guava produces 2-3 cm diameter berries with multiple 5 mm long seeds (Wagner et al. 1999) via both sexual reproduction and apomixis. In the wet forests of Hawai'i, seeds germinate within a year and do not accumulate in a soil seed bank (Uowolo and Denslow 2008). In Hawai'i seeds are dispersed by birds, rodents, and pigs as well as humans.
Strawberry guava also reproduces vegetatively from both above-ground stems and from the root mat. For the purposes of this study, sprouts are defined as arising above-ground from established leaning or vertical stems. Such sprouts may overtake a leaning mother stem, obscuring the origin of older stems. Alternatively rooted shoots may arise via seed germination or directly from the root mat. In this study we measured and tracked vertical stems standing more than 45 degrees from horizontal and greater than 0.5 cm at breast height (1.37 m, DBH). The population thus contained both shoots, apparently originating from seed or roots, and sprouts, originating as branches from older shoots or sprouts. We were unable to distinguish root sprouts from seedlings non-destructively and thus identified stems with an obvious above-ground connection to a mother stem as sprouts; shoots arising from the soil with no obvious above-ground connection to an existing stem were assumed to have originated from seeds or roots. Huenneke and Vitousek (1990), working in forests in the same area found that the proportion of rooted stems arising from seeds versus from roots varied widely. Thus, our study population is narrowly defined as vertical stems arising directly from the soil (shoots) or vegetatively from previously established stems (sprouts); leaning stems were excluded. Surveys: At the start of the study (2005) all four sites had established populations of strawberry guava with a range of stem diameters represented. With one exception (OLA), we established one 0.25 ha plot at each site. The study plot at OLA, with an initially higher-density guava population, was 0.15 ha. All vertical stems at least 2 cm DBH were tagged in each plot and their diameters measured. In addition, we tagged and measured all vertical stems >= 0.5 cm DBH and < 2 cm DBH in a stratified random set of 5 x 5 m subplots at each site (KAH: 6 subplots; MAK: 5 subplots; OLA: 5 subplots; WAI: 11 subplots). Diameter was re-measured annually, and new recruits tagged. Stems dying and leaning to less than 45 deg from horizontal were noted and not included in the study population going forward. The population of strawberry guava at each site reported here thus comprised only vertical stems. Analyses: We calculated basal area and yearly relative growth rates (RGR=log (BA t+1/BA t) based on basal area for individual stems. Density (stems/ha) was calculated from sample plots to allow comparisons among sites with different sample areas; estimates of total population density was based on the sum of the density of stems >=2 cm DBH from the entire plot plus the estimate of density of small stems (>=0.5 cm DBH and < 2cm DBH) from the subplots. Thus, total estimated density comprised all vertical stems >=0.5 cm DBH for each site. Total basal area per hectare was calculated similarly. Lambda (N(t+1)/ N(t)) was calculated from total population densities. To better understand the pattern differences in shoots and sprouts, we focused on sources of variation among small stems < 2 cm DBH, which comprised the majority of the population. Per capita annual recruitment and per capita stem death plus initial leaning of stems were calculated for both shoots and sprouts as a function of the total number of stems of all sizes present in the previous year at each site. To determine whether lambda varied over time, we used linear mixed effects models using the lme() function in the nlme package (Pinheiro et al. 2023) in R (R Core Team, 2022). Year coded as a factor) was the fixed effect and site was the random effect. We accounted for temporal autocorrelation using AR1() auto correlation structure. We used a likelihood ratio test to assess whether the random effect of site was significant. To determine how shoots and sprouts differed over time in their densities, relative abundances, total basal area per ha, relative growth rates of stems < 2cm DBH, per capita recruitment, and per capita dying/leaning, we used linear mixed effects models using the lme() function in the nlme package.. For all models, we included stem type (shoot, sprout), year, and the stem type x year interaction as fixed effects (with year coded as a factor) and site as a random effect. Additionally, for the relative growth rate model we included a random effect of a stem ID nested within site. All models accounted for temporal autocorrelation using AR1() autocorrelation structure. When needed, we also accounted for heteroscedasticity by fitting different variances for each stem type in each year using varIdent(). Type III ANOVAs were run on the models to test significance of fixed effects. Post hoc tests were used to test for the difference between stem types in each year using the multcomp package (Hothorn et al. 2008). Marginal means and standard errors for plotting relative growth rates were calculated using the emmeans package (Lenth 2023). ANOVA results are provided in the figure captions. In addition, we estimated the ages of shoots in the population based on annual basal area increments. For this estimate we pooled data from the shoots at all four study sites under the assumption that the sites were samples of a forest-wide population of strawberry guava. Only shoot growth was used in this estimate because sprout growth is in part dependent on the mother stem. Shoot growth rates vary as a function of their DBH as well as a function of light availability and other microsite characteristics; thus, we used four estimates of annual growth increment to provide a range of age estimates. Excluding stems with zero or negative relative growth rates, we estimated smallest, largest, mean and median basal area increments of shoots in 1 cm DBH size-classes using data for the year 2019-2020. For the few stems larger than 12 cm DBH we pooled data for all remaining large stems to estimate the increment. For each 1 cm growth

From 1950 to 2023, the cyclone Bhola that hit Bangladesh in 1970 was the deadliest natural disaster in the world. The exact death toll is impossible to calculate, but it is estimated that over 300,000 lives were lost as a result of the cyclone. The Tangshan earthquake in China in 1976 is estimated to have caused the second highest number of fatalities. The Haiti earthquake The fifth deadliest natural disaster during this period was the earthquake in Haiti in 2010. However, death tolls vary between 100,000 and 316,000, meaning that some estimates makes it the deadliest natural disaster in the world since 1950, and the deadliest earthquake since 1900. Sixty percent of the country’s hospitals and eighty percent of the country’s schools were destroyed. It was the worst earthquake to hit the Caribbean in 200 years, with a magnitude of 7.0 at its epicenter only 25 kilometers away from Haiti’s capital, Port-au-Prince. Poor construction practices were to blame for many of the deaths; Haiti’s buildings were not earthquake resistant and were not built according to building code due to a lack of licensed building professionals. High population density was also to blame for the high number of fatalities. One fourth of the country’s inhabitants lived in the Port-au-Prince area, meaning half of the country’s population was directly affected by the earthquake. Increasing extreme weather As global warming continues to accelerate climate change, it is estimated that natural catastrophes such as cyclones, rainfalls, landslides, and heat waves will intensify in the coming years and decades. For instance, the economic losses caused by natural disasters worldwide increased since 2015. Moreover, it is expected that countries in the Global South will be affected the most by climate change in the coming years, and many of these are already feeling the impact of climate change.

The total population of Germany was estimated at over 84.4 million inhabitants in 2025, although it is projected to drop in the coming years and fall below 80 million in 2043. Germany is the most populous country located entirely in Europe, and is third largest when Russia and Turkey are included. Germany's prosperous economy makes it a popular destination for immigrants of all backgrounds, which has kept its population above 80 million for several decades. Population growth and stability has depended on immigration In every year since 1972, Germany has had a higher death rate than its birth rate, meaning its population is in natural decline. However, Germany's population has rarely dropped below its 1972 figure of 78.6 million, and, in fact, peaked at 84.7 million in 2024, all due to its high net immigration rate. Over the past 75 years, the periods that saw the highest population growth rates were; the 1960s, due to the second wave of the post-WWII baby boom; the 1990s, due to post-reunification immigration; and since the 2010s, due to high arrivals of refugees from conflict zones in Afghanistan, Syria, and Ukraine. Does falling population = economic decline? Current projections predict that Germany's population will fall to almost 70 million by the next century. Germany's fertility rate currently sits around 1.5 births per woman, which is well below the repacement rate of 2.1 births per woman. Population aging and decline present a major challenge economies, as more resources must be invested in elderly care, while the workforce shrinks and there are fewer taxpayers contributing to social security. Countries such as Germany have introduced more generous child benefits and family friendly policies, although these are yet to prove effective in creating a cultural shift. Instead, labor shortages are being combatted via automation and immigration, however, both these solutions are met with resistance among large sections of the population and have become defining political issues of our time.

India population growth rate for 2023 was 0.81%, a 0.12% increase from 2022.

<ul style='margin-top:20px;'>

<li>India population growth rate for 2022 was <strong>0.68%</strong>, a <strong>0.12% decline</strong> from 2021.</li>
<li>India population growth rate for 2021 was <strong>0.80%</strong>, a <strong>0.16% decline</strong> from 2020.</li>
<li>India population growth rate for 2020 was <strong>0.96%</strong>, a <strong>0.07% decline</strong> from 2019.</li>
</ul>Annual population growth rate for year t is the exponential rate of growth of midyear population from year t-1 to t, expressed as a percentage . Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.

Pakistan population growth rate for 2023 was 1.96%, a 0.06% increase from 2022.

<ul style='margin-top:20px;'>

<li>Pakistan population growth rate for 2022 was <strong>1.89%</strong>, a <strong>0.06% increase</strong> from 2021.</li>
<li>Pakistan population growth rate for 2021 was <strong>1.83%</strong>, a <strong>0.1% increase</strong> from 2020.</li>
<li>Pakistan population growth rate for 2020 was <strong>1.73%</strong>, a <strong>0.13% increase</strong> from 2019.</li>
</ul>Annual population growth rate for year t is the exponential rate of growth of midyear population from year t-1 to t, expressed as a percentage . Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.