Diverse drivers such as climate, soil fertility, neighborhood competition, and functional traits all contribute to variation in tree stem demographic rates. However, these demographic drivers operate at different scales, making it difficult to compare the relative importance of each driver on tree demography. Using c. 20,000 stem records from New Zealand's temperate rain forests, we analyzed the growth, recruitment, and mortality rates of 48 tree species and determined the relative importance of demographic drivers in a multi-level modelling approach. Tree species’ maximum height emerged as the one most strongly associated with all demographic rates, with a positive association with growth rate and negative associations with recruitment and mortality rates. Climate, soil properties, neighborhood competition, stem size, and other functional traits also played significant roles in shaping demographic rates. Forest structure and functional composition were linked to climate and soil, with warm, dry climates and fertile soil associated with higher growth and recruitment rates. Neighborhood competition affected demographic rates depending on stem size, with smaller stems experiencing stronger negative effects, suggesting asymmetric competition where larger trees exert greater competitive effects on smaller trees. Our study emphasizes the importance of considering multiple drivers of demographic rates to better understand forest tree dynamics.

The role of conspecific density dependence (CDD) in the maintenance of species richness is a central focus of tropical forest ecology. However, tests of CDD often ignore the integrated effects of CDD over multiple life-stages and their long-term impacts on population demography. We combined a 10-year time series of seed production, seedling recruitment and sapling and tree demography of three dominant Southeast Asian tree species that adopt a mast fruiting phenology. We used these data to construct individual-based models that examine the effects of CDD on population growth rates (λ) across life-history stages. Recruitment was driven by positive CDD for all species, supporting the predator satiation hypothesis, while negative CDD affected seedling and sapling growth of two species, significantly reducing λ. This negative CDD on juvenile growth overshadowed the positive CDD of recruitment, suggesting the cumulative effects of CDD during seedling and sapling development has greater importance than the positive CDD during infrequent masting events. Overall, CDD varied between positive and negative across life-history stages for all species, suggesting that assessments of CDD on transitions between just two stages (e.g. seeds-seedlings or juveniles-mature trees) likely misrepresents the importance of CDD on population growth and stability.

This data publication includes tree measurements taken from 2008-2013 across a gradient of forest types in the Pinaleno Mountains in southeastern Arizona, USA. Tree data include: species, pith date, and last recorded fire date. These data were collected as part of the USDA Forest Service, Rocky Mountain Research Station (RMRS) Growth and Demography of Pinaleno High Elevation Forests research project.

Due to decades of fire suppression, much of the Upper Midwest savanna habitat has converted to oak woodland. In efforts to restore oak savanna habitat, fire has been re-introduced in many of these woodlands. A primary purpose of these burns is to kill the fire-sensitive mesophytic tree species, which had established themselves during the decades of fire suppression, reduce the number of understory trees, and preserve the larger more widely spaced oaks. It is clear from ongoing efforts that restoring oak savannas will require frequent fires over decades. But frequent fires over the long term can also threaten the desirable oaks. Long-term demographic studies at savanna restoration sites experiencing frequent fires are necessary to determine the extent to the frequent burns are supporting and/or confounding restoration goals. Results presented here are from a twenty-five-year demographic study of an Upper Midwest bur oak (Quercus macrocarpa) savanna/woodland experiencing frequent fire, during which both the survival and growth of more than 9,000 trees were documented. Survival was assessed annually and growth every five years. In the face of frequent fires, stem survival was found to be strongly associated with tree species, stem size, and stem growth. In turn, stem growth was found to be related to tree species and stem size. Decades of frequent burning in this oak woodland have substantially reduced the abundance of unwanted trees, specifically mesophytic species and Q. ellipsoidalis, the latter which outcompetes Q. macrocarpa in the absence of fire. While Q. macrocarpa mid-sized (10-25 cm dbh) and large (> 25 cm dbh) trees are quite resistant to fire and now dominate the savanna landscape, they are not immune from fire-induced mortality. It is recommended that the number and density of these trees should be re-evaluated every few years to ensure that desirable numbers remain. If necessary, fires should be suspended for a period of time. This will give smaller Q. macrocarpa trees time to grow larger and become more fire-resistant, thereby ensuring successive generations of Q. macrocarpa.

Methods Field observations were conducted at the Cedar Creek Ecosystem Science Reserve (CCESR) located in east-central Minnesota (Latitude: 45.401, Longitude -93.201). During 1988, I initiated the GLADES (Grid for Landscape Analysis and DEmographic Study) project with the establishment of a square 16 ha grid (consisting of 1600 10 x 10 m cells) in a portion of Cedar Creek’s oak woodland/savanna habitat. This grid was set up in a north-south configuration, using 1.5 m x 0.95 cm diam iron rebars to mark the grid nodes. A Cartesian coordinate system was used to map tree stems in the grid. Each cell was identified by the x-y coordinates in the southwest corner of the cell.

In 1995, numbered aluminum tags were nailed into stems > 10 cm. In 1996, the tags were nailed into stems 5-9.9 cm dbh and attached with wire to stems 2-4.9 cm dbh. The dbh of these stems was measured and recorded when initially tagged. In addition, the cell in which the stem was located was documented, as well as the stem’s x-y location within the cell (determined visually). A burn program was instituted in the grid area in 1987, and the study grid contains three different burn units. Burn unit 1 (6.17 ha) was burned four times between 1987 and 1995 (prior to this study) and eleven times during the twenty-five-year study (1995-2020). Burn unit 2 (5.98 ha) was burned once prior to the study (1992) and nine times between 1995-2020; burn unit 3 (3.25 ha) was burned for the first time in 2000 and eight times after that.

All stems were visited annually and their statuses (live, dead standing (snag), or dead fallen) recorded. The dbh of live stems was measured every five years. To facilitate some analyses involving stem size (dbh), Quercus stems were grouped into three size categories based on their dbh in 1995 or 1996 (2-9.9 cm dbh, 10-24.9 cm, and >25 cm). Survival and growth rates of the two Quercus species and eight mesophytic species were analyzed using JMP Pro 15.1 (SAS Institute, Inc.).

About this dataset

Context

The dataset tabulates the Marked Tree population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for Marked Tree. The dataset can be utilized to understand the population distribution of Marked Tree by age. For example, using this dataset, we can identify the largest age group in Marked Tree.

Key observations

The largest age group in Marked Tree, AR was for the group of age 55 to 59 years years with a population of 228 (10.20%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in Marked Tree, AR was the 40 to 44 years years with a population of 15 (0.67%). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group in consideration
• Population: The population for the specific age group in the Marked Tree is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Marked Tree total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Marked Tree Population by Age. You can refer the same here

Tree demography is foundational to ecology and conservation, from mass tree die-offs to forest recovery. Plot-level studies of tree demography, including field measurements of tagged individuals, have been fundamental for developing ecological theory and forest management strategies. However, the limited spatial extent of field plots impedes generalizing plot-level models for spatial predictions across heterogeneous landscapes. Novel high-spatial resolution remote sensing imagery has opened the possibility for measuring tree demographic rates with continuous spatial coverage at landscape to regional extents. Remote sensing derived measurements could address pressing research questions, including disentangling causes of high variation in natural regeneration across secondary forest landscapes. Despite the promise of high-spatial resolution imagery for ecology, applying these data to ecological questions will require novel modeling approaches that can account for large amounts of spatial data that often include hierarchical structure. In this thesis, I apply high-resolution remote sensing to upscale tree demography at landscape scales, and provide guidelines for ecologists seeking to parametrize spatially explicit models for neighbor interactions by combining field data, high-resolution remote sensing, and Bayesian quantitative methods. Chapter 1 demonstrates how high-spatial resolution remote sensing can help improve predictions of tree recruitment at the landscape scale. This chapter is the first step towards new support tools that inform restoration projects about where and which species will regenerate naturally in agricultural landscapes. Chapter 2 addresses how to optimize neighbor interaction models using the Hamiltonian Monte Carlo algorithm. I demonstrate how ragged matrices could solve data storage inefficiencies associated with the neighbor interaction models' pairwise structure. I also provide code for a model parametrization that solves a sampling pathology associated with high correlation in hierarchical structures and an overview of metrics to assess when this hierarchical structure pathology is present. Chapter 3 explores the influence of biophysical and anthropogenic drivers on tree mortality in agricultural landscapes using high-resolution remote sensing data. The results suggest that accessibility and land management are core factors that could be managed to prevent the mortality of agricultural trees. Educational initiatives and new policies that address anthropogenic factors could be the answer to reduce agricultural tree loss. Overall, this thesis brings together Bayesian statistical methods with novel high-resolution remote sensing to overcome the spatial limitation of field measurements and produce spatial predictions and inference on drivers of tree demography across heterogeneous landscapes.

Organisms have evolved diverse adaptive strategies to cope with environmental fluctuations. Slow-growing long-lived species tend to exhibit low temporal variability in population growth (strongly buffered demographically), whereas fast-growing short-lived species optimize growth in favorable years (weakly buffered). These patterns set up the expectation that differentiation in demographic buffering may reduce disparities in long-term fitness among species, enhancing the potential for coexistence in variable environments. Yet, this expectation has never been empirically tested for trees. Here, we quantified differences in long-term population growth among 204 co-occurring tropical trees spanning a life-history spectrum from strongly to weakly buffered. We found predictable variation in long-term population fitness for species at low densities, pointing to demographic differentiation as a key for coexistence in fluctuating environments. Simulated increases in temperature, precipitation, and drought variability led to divergent impacts on species' fitness and increased fitness differences. Together, these findings provide a novel perspective on the mechanisms that underpin the astounding tree diversity in tropical forests.

These data were compiled to help understand how climate change may impact dryland pinyon-juniper ecosystems in coming decades, and how resource management might be able to minimize those impacts. Objective(s) of our study were to model the demographic rates of PJ woodlands to estimate the areas that may decline in the future vs. those that will be stable. We quantified populations growth rates across broad geographic areas, and identified the relative roles of recruitment and mortality in driving potential future changes in population viability in 5 tree species that are major components of these dry forests. We used this demographic model to project pinyon-juniper population stability under future climate conditions, assess how robust these projected changes are, and to identify where on the landscape management strategies that decrease tree competition would effectively resist population decline. These data represent estimated recruitment, mortality and population growth across the distribution of five common pinyon-juniper species across the US Southwest. These data were collected by the US Forest service in their monitoring program, which is a systematic survey of forested regions across the entire US. Our data is from western US states, including AZ, CA, CO, ID, MT, NM, ND, NV, OR, SD, TX, UT, and was collected between 2000-2007, depending on state census collection times. These data were collected by the Forest Inventory and Analysis program of the USDA US Forest Service. Within each established plot, all adult trees greater than 12.7 cm (5 in.) diameter at breast height (DBH) are assigned unique tags and tracked within four, 7.32 m (24 ft.) radius subplots. All saplings <12.7 cm & > 2.54 cm (1 in.) DBH are assigned unique tags and tracked within four, 2.07 m (6.8 ft.) radius microplots within the larger adult plots. Finally, seedlings <2.54 cm DBH are counted within the same microplots as the saplings. Two censuses were conducted 10 years apart in each plot. These data can be used to inform how tree species have unique responses to changing climate conditions and how management actions, like tree density reduction, may effectively resist transformation away from pinyon-juniper woodland to other ecosystem types.

Resource specialists persist on a narrow range of resources. Consequently, the abundance of key resources should drive vital rates, individual fitness and population viability. While Neotropical forests feature both high levels of biodiversity and numbers of specialist species, no studies have directly evaluated how the variation of key resources affects the fitness of a tropical specialist. Here, we quantified the effect of key tree species density and forest cover on the fitness of three-toed sloths (Bradypus variegatus), an arboreal folivore strongly associated with Cecropia trees, in Costa Rica using a multi-year demographic, genetic and space use dataset. We found that the density of Cecropia trees was strongly and positively related to both adult survival and reproductive output. A matrix model parameterized with Cecropia-demography relationships suggested positive growth of sloth populations, even at low densities of Cecropia (0.7 trees/ha). Our study shows the first direct link between the density of a key resource to demographic consequences of a tropical specialist, underscoring the sensitivity of tropical specialists to the loss of a single key resource, but also point to targeted conservation measures to increase that resource. Finally, our study reveals that previously disturbed and regenerating environments can support viable populations of tropical specialists.

Prolonged exposure to extreme heat can result in illness and death. In urban areas of dense concentrations of pavement, buildings, and other surfaces that absorb and retain heat, extreme heat conditions can arise regularly and create harmful environmental exposures for residents daily during certain parts of the year. Tree canopies provide shade and help to cool the environment, making mature trees with large canopies a simple and effective way to reduce urban heat. We develop a demographically representative 1 (agent): 1 (person) agent-based model to understand the extent to which different demographics of residents in Norfolk, VA are equitably shaded from extreme heat conditions during a walk on a clear summer day. We use the model to assess the extent to which the city's Tree Planting Plan will be effective in remediating any existing inequities. Our results show that inequitable conditions exist for residents (1) at different education levels, (2) at different income levels and, (3) living in different census tracts. Norfolk's Tree Planting Program effectively reduces the distance residents of all demographics walk in extreme heat. However, residents of the city at lower income levels still experience statically significantly more extreme heat exposure due to a lack of tree canopies in summer months than those at higher income levels.

These data correspond to wood functional traits and demographic rates (i.e., growth and mortality rates) measured at different ontogenetic stages in 19 forest tree species from eastern Amazonia.

Although functional traits are defined based on their impact on demographic parameters, trait-demography relationships are often reported as weak. These weak relationships might be due to disregarding trait interactions and environmental contexts, which should modulate species trait-demography relationships. We applied different models, including boosted regression tree (BRT) models, to investigate changes in the relationship between traits and demographic rates of tropical tree species in plots along an elevational gradient and among time intervals between censuses, analyzing the effect of a strong drought event. Based on a large dataset of 18,000 tree individuals from 133 common species, distributed among twelve 1-ha plots (habitats) in the Atlantic Forest (Brazil), we evaluated how trait interactions and the environmental context influence the demographic rates (growth, mortality, and recruitment). Functional traits, trait-trait, and trait-habitat interactions predicted demography with a good fit through either BRTs or linear mixed-models. Changes in growth rates were best related to size (diameter), and mortality rates to habitats, while changes in recruitment rates were best related to the specific leaf area. Moreover, the influence of traits differed among time intervals, and for demographic parameters, habitat affected growth and mortality by interacting with diameter. Here, we provide evidence that trait-demography relationships can be improved when considering the environmental context (space and time) and trait interactions to cope with the complexity of changes in the demography of tropical tree communities. Thus, to expand predictions of demography based on functional traits, we show that it is useful to fully incorporate the concept of multiple trait-fitness optima, resulting from trait interactions in different habitats and growth conditions. Methods Data from forest inventories conducted in twelve 1-ha plots distributed in undisturbed areas of “Restinga” (one plot), Lowland forest (four plots), Submontane forest (four plots), and Montane forest (three plots) of the Serra do Mar. All woody stems (trees, palms, and tree ferns) with a diameter at breast height (DBH) equal to or larger than 4.8 cm were tagged, taxonomically identified, and measured for diameter and re-censused four times over 12 years (2005 – 2016). The forest inventories database represents 22,770 stems from 21,509 tree individuals belonging to 685 species from 70 botanical families. For each species, we collected data on six functional traits representing the leaf, seed, and wood economics spectra. We measured leaf area (LA, cm2), leaf dry matter content (LDMC, mg g- 1), and specific leaf area (SLA, cm2 g- 1) from ten leaves of ten individuals per species. As a measure of the species’ potential size, hereafter referred to as ‘DBH’, we calculated the 0.95 percentile of the distribution of stem DBH for each species using the forest inventories dataset. Seed mass (SM, mg) and wood density (WD, cm3 g- 1) were obtained from three global repositories, Global wood density database (Zanne et al., 2009), BIEN (Maitner et al., 2018) and TRY (Kattge et al., 2011), and from the literature (Bello et al., 2017; Bufalo et al., 2016; Chave et al., 2009; Wanderley et al., 2016). When the same species was present in two or more datasets, we computed the average for its trait values.

About this dataset

Context

The dataset tabulates the data for the Green Tree, PA population pyramid, which represents the Green Tree population distribution across age and gender, using estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. It lists the male and female population for each age group, along with the total population for those age groups. Higher numbers at the bottom of the table suggest population growth, whereas higher numbers at the top indicate declining birth rates. Furthermore, the dataset can be utilized to understand the youth dependency ratio, old-age dependency ratio, total dependency ratio, and potential support ratio.

Key observations

• Youth dependency ratio, which is the number of children aged 0-14 per 100 persons aged 15-64, for Green Tree, PA, is 21.6.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for Green Tree, PA, is 39.9.
• Total dependency ratio for Green Tree, PA is 61.5.
• Potential support ratio, which is the number of youth (working age population) per elderly, for Green Tree, PA is 2.5.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group for the Green Tree population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Green Tree for the selected age group is shown in the following column.
• Population (Female): The female population in the Green Tree for the selected age group is shown in the following column.
• Total Population: The total population of the Green Tree for the selected age group is shown in the following column.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Green Tree Population by Age. You can refer the same here

The purpose of this data package is to offer demographic data for U.S. cities. The data sources are multiple, the most important one being the U.S. Census Bureau, American Community Survey. In this case, the data was organized by the Big Cities Health Coalition (BCHC). Others are the New York City Department of City Planning and Department of Parks and Recreation, data being available through the NYC Open Data.

Cavities and the demographic performance of tropical rainforest trees

https://doi.org/10.5061/dryad.dz08kps7h

Description of the data and file structure

The data original field data from the Xishuangbanna forest plot contains diameter (DBH), presence of cavities, growth, survival, traits, and quadrat number. Additional files from model output to produce a figure and for joining model parameter outputs with trait data are provided. R code used to generate the models and figures is provided.

Files and variables

File: forFig2.csv

Description: Model output used for making figure 2.

Variables

• param: the model parameter. The parameter names match the models shown in the manuscript.
• mean: the mean of the posterior probability distribution for the parameter.
• sd: the standard deviation of the posterior probability distribution for the parameter.
• 2.50%: the 2.5% quantile of the posterior probability distribution f...

Demographic compensation – the opposing responses of vital rates along environmental gradients – potentially delays anticipated species’ range contraction under climate change, but no consensus exists on its actual contribution. We calculated population growth rate (λ) and demographic compensation across the distributional ranges of 81 North American tree species, and examined their responses to simulated warming and tree competition. We found that 43% of species showed stable population size at both northern and southern edges. Demographic compensation was detected in 25 species, yet fifteen of them still showed a potential retraction from southern edges, indicating that compensation alone cannot maintain range stability. Simulated climatic warming caused larger decreases in λ for most species, and weakened the effectiveness of demographic compensation in stabilizing ranges. These findings suggest that climate stress may surpass the limited capacity of demographic compensation and pose a threat to the viability of North American tree populations.

A short report examining the conceptual understanding of aspects that define viable populations of dominant Murray-Darling Basin floodplain eucalypts (River Red Gum, Black Box, Coolabah trees).

Demographic data was collected in two census years 2009 and 2016. During both censuses, girth at breast height or collar girth was measured for each individual. Girth was converted to diameter for analysis. This file contains information of plant sizes (diameter), survival, transition of tree to sprout and presence of harvesting for individuals of Acacia chundra, Chloroxylon swietenia and Gardenia gummifera.

The five Terrestrial Gradient sites were established in the early 1990s as part of the 1990 Coweeta LTER Renewal. The original terrestrial gradient sites were 20 x 40-m. In the late 1990s the plots were expanded to 80 x 80-m and later (around 1998) they were slope-corrected by Clark's lab using survey equipment. Much of the Coweeta LTER “core” datasets have been collected from the gradient plots. This study is one of the long-term studies that are ongoing with defined sampling intervals. The tree demography and census study consists of trees census every two years and seeds collected ~5 x each year.

This project was designed to investigate the response of plant growth and reproduction to short- and long-term variation in biotic and abiotic environmental variables. Several perennial taxa, including tree (Juniperus monsperma and Pinus edulis), shrub (Larrea tridentata) and bunch grasses (Oryzopsis hymenoides (now Achnaterum hymenoides) and Sporobolus contractus) species, were monitored at 1-3 sites differing in elevation and topography as well as edaphic variables and annual precipitation. The sites represented optimal or marginal/transitional zones for particular species. Demographic measurements were made biannually, after the 'wet' (fall) and 'dry' (spring) seasons. For tree and shrub species, estimates of growth and reproduction were based on branch demography, with ten branch tips from 10-20 individuals per species per site repeatedly measured from 1989-1993. For J. monsperma, P. edulis and L. tridentata, vegetative growth (i.e., branch growth) as well as reproduction were monitored. Additional measurements included needle length for P. edulis and leaf production, leaf size and branchlet production for L. tridentata. For grasses, basal diameter, leaf length and reproduction were monitored for 100 individuals per species per site. This project, SEV006, contains only data on pinon branch demography. Data on other variables and species is contained in SEV024, SEV025, SEV026, SEV027, and SEV028.