Spatio-temporal Population Research Articles

Sampling data of macro-invertebrates collected in grasslands under restoration succession in a lowland stream-valley system.

Publication of data from past field studies on invertebrate populations is of high importance, as there is much added value for them to be used as baselines to study spatiotemporal population and community dynamics in these groups. Therefore, a dataset consisting of occurrence data on epigaeic invertebrates collected in 1996 was standardised into the Darwin core format and cross-checked in order to make it publicly available following FAIR data principles. With publication, it can contribute to the biodiversity assessment of terrestrial invertebrates, thereby improving the availability and accessibility of much-needed historical datasets on macro-invertebrates.Here, we present sampling event data on invertebrates from four grasslands taken out of agricultural production over the span of several decades, effectively displaying a chronosequence on the effects of agricultural extensification. The data were collected by means of a standardised sampling design using pyramid traps, pitfall traps and soil samples. The raw data presented in this data paper have not been published before. They consist of 20,000+ records of nearly 70,000 specimens from 121 taxonomic groups. The data were collected using a standardised field study set-up and specimens were identified by taxonomic specialists. Most groups were identified up to family level, with eight groups identified up to species level. The occurrence data are complemented by information on plant composition, meteorological data and soil physical characteristics. The dataset has been registered in the Global Biodiversity Information Facility (GBIF): http://doi.org/10.15468/7n499e.

Sensing the Environmental Inequality of PM2.5 Exposure Using Fine-Scale Measurements of Social Strata and Citizenship Identity

Exposure to PM2.5 pollution poses substantial health risks, with the precise quantification of exposure being fundamental to understanding the environmental inequalities therein. However, the absence of high-resolution spatiotemporal ambient population data, coupled with an insufficiency of attribute data, impedes a comprehension of the environmental inequality of exposure risks at a fine scale. Within the purview of a conceptual framework that interlinks social strata and citizenship identity with environmental inequality, this study examines the environmental inequality of PM2.5 exposure with a focus on the city of Xi’an. Quantitative metrics of the social strata and citizenship identities of the ambient population are derived from housing price data and mobile phone big data. The fine-scale estimation of PM2.5 concentrations is predicated on the kriging interpolation method and refined by leveraging an advanced dataset. Employing geographically weighted regression models, we examine the environmental inequality pattern at a fine spatial scale. The key findings are threefold: (1) the manifestation of environmental inequality in PM2.5 exposure is pronounced among individuals of varying social strata and citizenship identities within our study area, Xi’an; (2) nonlocal residents situated in the northwestern precincts of Xi’an are subject to the most pronounced PM2.5 exposure; and (3) an elevated socioeconomic status is identified as an attenuating factor, capable of averting the deleterious impacts of PM2.5 exposure among nonlocal residents. These findings proffer substantial practical implications for the orchestration of air pollution mitigation strategies and urban planning initiatives. They suggest that addressing the wellbeing of the marginalized underprivileged cohorts, who are environmentally and politically segregated under the extant urban planning policies in China, is of critical importance.

Multi-scale population analysis unit construction method considering scene feature variability and long/short-term patterns in spatiotemporal population activities

ABSTRACT Differences in the spatial scale and component elements of urban scenes affect the analysis of spatiotemporal changes in population distribution (PD) patterns. Fixed scales and geometric forms constrained previous analyses of PD and spatiotemporal changes, which neglected the realistic characteristics of urban scenarios. These limitations hinder the ability to capture the diversity and spatiotemporal representation of PD patterns across multiple spatial scales. This study developed a multi-spatial scale population analysis unit (PAU) construction method considering the scenario heterogeneity and long/short-term patterns of spatiotemporal population changes (PC). Initially, we decompose the multi-scale changes in population time series patterns and their relationships with scene features along the temporal dimension to analyze the primary and secondary factors. Starting from the temporal characteristics of the PD and PC, we established a validation and correction method for the factors. Finally, combined with a multi-feature clustering method, a multi-scale PAU construction method driven by scene feature factors is proposed. Experiments were conducted at different spatial scales in both routine and emergent scenarios. The results indicated that this method can help to obtain more homogeneous analysis regions and enhance the stability and phase pattern representations of changes in PDs, thereby improving the interpretability of analytical results.

Spatio-temporal patterns and population exposure risks of urban heat island in megacity Shanghai, China

Accompanied by global warming and rapid urbanization, the urban heat island (UHI) effect has been intensifying, which leads to an increased risk of population heat exposure, especially in mega-cities. However, there are fewer studies on the identification of UHI ranges and the associated population heat exposure risks, particularly on the fine scale. Therefore, this study took Shanghai as a case study and explored the spatio-temporal evolution characteristics of the UHI ranges and population heat exposure risks, based on five-period MODIS land surface temperature (LST) product, population density distribution data, and land use and cover change data from 2000 to 2020, combined with the temperature attenuation mutation (TAM) method, breakpoint regression model, population heat exposure relative risk assessment method, and spatial autocorrelation analysis. The results showed that: (1) From 2000 to 2020, the UHI range in Shanghai was continuously expanding, and the intensity of the surface UHI was gradually increasing. The overall pattern was characterized by a stable large heat island in the central urban area and new small heat islands that continued to emerge in the peripheral suburbs. (2) The population heat exposure risks in Shanghai intensified from 2000 to 2020, with an increasing number of people exposed to high-intensity UHI ranges, doubling the population coverage in these areas. By the end of 2020, the population exposed to UHI ranges accounted for approximately 81 % of the total population of Shanghai. (3) The spatial pattern of population heat exposure risks from 2000 to 2020 was generally similar. Population heat exposure regions of high risk level were primarily concentrated in the central urban areas, showing typical spatial clustering characteristics, while population heat exposure regions of low risk level were mainly dispersed in the peripheral suburbs, and showed a gradual transformation trend into population heat exposure regions of high risk level. Our findings can provide scientific basis and decision support for precise and refined urban heat risk control and planning management.

Spatiotemporal dynamics of prey-predator model incorporating Holling-type II functional response with fear and its carryover effects.

The recent focus in the fields of biology and ecology has centered on the significant attention given to the mathematical modeling and analyzing the spatiotemporal population distribution among species engaged in interactions. This paper explores the dynamics of the temporal and spatiotemporal delayed Bazykin-type prey-predator model, incorporating fear and its carryover effect. In our model, we incorporated a functional response of the Holling-type II. In the temporal model, a detailed dynamic analysis was carried out, investigating the positivity and boundedness of solutions, establishing the uniqueness and existence of positive interior equilibria, and examining both local and global stability. Additionally, we explored the presence of saddle-node, transcritical, and Hopf bifurcations varying attack rate parameter. The delayed system shows highly periodic behavior. Additionally, for the spatiotemporal model, we provide a complete analysis of local and global stability, and we derive the conditions for the existence of Turing instability for both self-diffusion and cross-diffusion, respectively. The two-dimensional diffusive model is further discussed, highlighting various Turing patterns, including holes, stripes, and hot and cold spots, along with their biological significance. Numerical simulations are executed to validate the analytical findings in both temporal and spatiotemporal models.

Spatial analysis of outdoor indecent assault risk: a study using ambient population data

Spatiotemporal data on ambient populations have recently become widely available. Although previous studies have indicated a link between the spatial patterns of crime occurrence and ambient population distribution, more detailed information, such as the population most likely to be victims by gender and age group, could better predict the risk of crime occurrence. Therefore, this study aimed to analyze the risk of indecent assault, a typical crime with a high number of young female victims, in southern Kyoto Prefecture. We utilized population distribution by gender and age group at different times of the day. After extracting daily patterns (factors) of the population using non-negative matrix factorization, we statistically modeled the risk of indecent assault using a spatial conditional autoregressive model. The results showed that the model, which considered a spatiotemporal ambient population, demonstrated superior performance during nighttime hours. Furthermore, by interpreting the factors significantly associated with the risk of crime occurrence, the findings provided valuable insights into local crime prevention measures that consider daily temporal changes in the gender and age-group composition of individuals present in a specific area.

Genetic analysis of Octopus cyanea reveals high gene flow in the South-West Indian Ocean.

Octopus cyanea (Gray, 1849), abundant in the South-West Indian Ocean (SWIO), constitutes a vital resource for both subsistence and commercial fisheries. However, despite this socioeconomic importance, and recent indications of overfishing, little is known about the population structure of O. cyanea in the region. To inform sustainable management strategies, this study assessed the spatio-temporal population structure and genetic variability of O. cyanea at 20 sites in the SWIO (Kenya, Tanzania, Mozambique, Madagascar, Mauritius, Rodrigues, and the Seychelle Islands) by complementary analysis of mitochondrial DNA (mtDNA) noncoding region (NCR) sequences and microsatellite markers. MtDNA analysis revealed a shallow phylogeny across the region, with demographic tests suggesting historic population fluctuations that could be linked to glacial cycles. Contrary to expectations, NCR variation was comparable to other mtDNA regions, indicating that the NCR is not a hypervariable region. Both nuclear and mtDNA marker types revealed a lack of genetic structure compatible with high gene flow throughout the region. As adults are sedentary, this gene flow likely reflects connectivity by paralarval dispersal. All samples reported heterozygote deficits, which, given the overall absence of structure, likely reflect ephemeral larval recruitment variability. Levels of mtDNA and nuclear variability were similar at all locations and congruent with those previously reported for harvested Octopodidae, implying resilience to genetic erosion by drift, providing current stock sizes are maintained. However, as O. cyanea stocks in the SWIO represent a single, highly connected population, fisheries may benefit from additional management measures, such as rotational closures aligned with paralarval ecology and spanning geopolitical boundaries.

The Poultry Red Mite, Dermanyssus gallinae, travels far but not frequently, and takes up permanent residence on farms

Management of Dermanyssus gallinae, a cosmopolitan hematophagous mite responsible for damage in layer poultry farming, is hampered by a lack of knowledge of its spatio-temporal population dynamics. Previous studies have shown that the circulation of this pest between farms is of strictly anthropogenic origin, that a mitochondrial haplogroup has been expanding on European farms since the beginning of the 21st century and that its local population growth may be particularly rapid. To refine our understanding of how D. gallinae spreads within and among farms, we characterized the genetic structure of mite populations at different spatial scales and sought to identify the main factors interrupting gene flow between poultry houses and between mitochondrial haplogroups. To this end, we selected and validated the first set of nuclear microsatellite markers for D. gallinae and sequenced a region of the CO1-encoding mitochondrial gene in a subsample of microsatellite-genotyped mites. We also tested certain conditions required for effective contamination of a poultry house through field experimentation, and conducted a survey of practices during poultry transfers. Our results confirm the role of poultry transport in the dissemination of mite populations, but the frequency of effective contamination after the introduction of contaminated material into poultry houses seems lower than expected. The high persistence of mites on farms, even during periods when poultry houses are empty and cleaned, and the very large number of nodes in the logistic network (large number of companies supplying pullets or transporting animals) undoubtedly explain the very high prevalence on farms. Substantial genetic diversity was measured in farm populations, probably as a result of the mite's known haplodiploid mode of sexual reproduction, coupled with the dense logistic network. The possibility of the occasional occurrence of asexual reproduction in this sexually reproducing mite was also revealed in our analyses, which could explain the extreme aggressiveness of its demographic dynamics under certain conditions.

Spatiotemporal distribution and population trends of Sindh ibex (Capra aegagrus blythii) in Balochistan during 2019–2022

The increased pressures generated by human activities in form of climate change and habitat fragmentation have caused serious threats for Sindh ibex (Capra aegagrus blythii). Balochistan, recognized as one of the most vulnerable regions to climate change in Pakistan, has limited data on the distribution and population status of this species. To address this gap, our study aims to assess the spatial and temporal distribution and population trend of Sindh ibex in the Khuzdar and Lasbela districts of Balochistan. The study covered an area of approximately 45,123.97 km2. It involved a double-observer survey at ten sites from 2019 to 2022, using the BBRecapture package in the R programming language to estimate ibex population trend and dispersion. We provided a comprehensive update of the species geographic range, along with estimates of its current abundance and population trends. Over the course of four years, the ibex population fluctuated. The ibexes detected dropped from 720 (male to female ratio 1:1.21) and 710 (male to female ratio 1:1.08) in 2019 and 2020, respectively, to 550 (male to female ratio 1:1.35) and 548 (male to female ratio 1:1.09). Overall, this study provides valuable insights into the population trends, gender ratios, habitat preferences, and density of Sindh ibex in Balochistan over the four-year period. These findings contribute significantly to the baseline data on the species ecology and will further help in the conservation of these species at local scale.

Health Impacts of Future Prescribed Fire Smoke: Considerations From an Exposure Scenario in California

AbstractIn response to increasing wildfire risks, California plans to expand the use of prescribed fire. We characterized the anticipated change in health impacts from exposure to smoke under a future fire‐management scenario relative to a historical period (2008–2016). Using dispersion models, we estimated daily fine particulate matter (PM2.5) emissions from hypothetical future prescribed fires on 500,000‐acres classified as high priority. To evaluate health impacts, we calculated excess daily cardiorespiratory emergency department visit rates attributed to all‐source PM2.5, distinguishing the portion of the burden attributed to prescribed fire. The total burden was differentiated by fire type and by smoke strata‐specific days to calculate strata‐specific burden rates, which were then applied to estimate the burden in the future scenario. This analysis suggests that the exposure to prescribed fire smoke, measured as the number of persons exposed per year, would be 15 times greater in the future. However, these exposures were associated with lower concentrations compared to the historical period. The increased number of exposure days led to an overall increase in the future health burden. Specifically, the northern, central, and southern regions experienced the largest burden increase. This study introduces an approach that integrates spatiotemporal exposure differences, baseline morbidity, and population size to assess the impacts of prescribed fire under a future scenario. The findings highlight the need to consider both the level and frequency of exposure to guide strategies to safeguard public health as well as aid forest management agencies in making informed decisions to protect communities while mitigating wildfire risks.

Drivers of spatio-temporal population dynamics of game species in a mountain landscape

Since the end of the nineteenth century, socio-economic changes have greatly altered the Central European landscape and the structural and functional quality of habitats. Urban sprawl areas have appeared, a reduction of multiple forest uses has resulted in the densification of forests and agricultural land use has changed fundamentally through specialisation and intensification. Many of these changes affect biodiversity. To determine the important drivers of spatio-temporal dynamics of the population of 28 game species, we first considered a total of 130 potential explanatory variables. Second, we aggregated the main drivers of single-species models for habitat guilds. Third, we evaluated the results to aid in the development and implementation of mitigation measures for different ecoregions. We used harvest data as a surrogate for population density from 1875 to 2014 in South Tyrol, Italy. In generalised linear models, we used environmental characteristics such as climate, landscape diversity and structures, land cover, hunting, wildlife diseases, competition and predation, land-use type, and intensity (including pesticide use) as explanatory variables to predict the spatio-temporal dynamics of game species. The important drivers are land use and management changes (intensification in the agriculturally favourable areas, extensification or abandonment in the unfavourable areas) as well as associated changes in the landscape features, diversity and structure, and hunting management. Climatic variables, interspecific competition and diseases only play a subordinate role. The dynamics of the habitat guilds and their drivers provide concrete indications for measures to maintain or improve the habitat quality for the investigated species. Particularly important are transfer payments to ensure extensive agricultural use, increasingly through the takeover of personnel costs, but also for the installation of an independent body that monitors and evaluates the effectiveness of the measures.

Evaluating genotyping-in-thousands by sequencing as a geneticmonitoring tool for a climate sentinel mammal using non-invasive and archival samples.

Genetic tools for wildlife monitoring can provide valuable information on spatiotemporal population trends and connectivity, particularly in systems experiencing rapid environmental change. Multiplexed targeted amplicon sequencing techniques, such as genotyping-in-thousands by sequencing (GT-seq), can provide cost-effective approaches for collecting genetic data from low-quality and quantity DNA samples, making them potentially useful for long-term wildlife monitoring using non-invasive and archival samples. Here, we developed a GT-seq panel as a potential monitoring tool for the American pika (Ochotona princeps) and evaluated its performance when applied to traditional, non-invasive, and archival samples, respectively. Specifically, we optimized a GT-seq panel (307 single nucleotide polymorphisms (SNPs)) that included neutral, sex-associated, and putatively adaptive SNPs using contemporary tissue samples (n = 77) from the Northern Rocky Mountains lineage of American pikas. The panel demonstrated high genotyping success (94.7%), low genotyping error (0.001%), and excellent performance identifying individuals, sex, relatedness, and population structure. We subsequently applied the GT-seq panel to archival tissue (n = 17) and contemporary fecal pellet samples (n = 129) collected within the Canadian Rocky Mountains to evaluate its effectiveness. Although the panel demonstrated high efficacy with archival tissue samples (90.5% genotyping success, 0.0% genotyping error), this was not the case for the fecal pellet samples (79.7% genotyping success, 28.4% genotyping error) likely due to the exceptionally low quality/quantity of recovered DNA using the approaches implemented. Overall, our study reinforced GT-seq as an effective tool using contemporary and archival tissue samples, providing future opportunities for temporal applications using historical specimens. Our results further highlight the need for additional optimization of sample and genetic data collection techniques prior to broader-scale implementation of a non-invasive genetic monitoring tool for American pikas.

Road traffic noise exposure assessment based on spatiotemporal data fusion

The current static assessment methods for road traffic noise exposure have limitations in representing spatiotemporal variations and only account for the noise exposure of registered residents. To address these issues, this study proposes an assessment method by fusing spatiotemporal noise and population distributions. This approach estimates spatiotemporal noise distributions through real-time noise monitoring data and an update model of noise source intensity calibrated by historical noise monitoring data and road segment speed data. Meanwhile, spatiotemporal population distributions are generated by aggregating standardized spatiotemporal trajectories of users extracted from mobile phone data. The proposed method is applied to evaluate the population exposure to traffic noise in a Chinese city in different hourly periods. The results demonstrate that this method is a quantitative tool for assessing road traffic noise exposure dynamically, providing policymakers with valuable information to locate hotspots of traffic noise over short periods of time.

Spatio-temporal Distribution and Population Dynamics of the Red Mullet Mullus barbatus Linnaeus, 1758 from the South-east Black Sea

A total of 2930 Mullus barbatus individuals collected from the Southeastern Black Sea coast between March 2017 and April 2018 were investigated regarding growth, mortality rates and the distribution determined by depth and season. M. barbatus is abundant along of 30-45 m depth in winter. Total length-weight relationship was determined as W=0.005L3.2344. Von Bertalanffy growth parameters for all individuals were calculated as L∞=28.19 cm, K=0.16 years-1, t0=-0.144 years. The maximum age was 5 years. The total length at 50% maturity was estimated as 11.63 cm in males and 11.68 cm in females. Exponential coefficients of natural mortality, total mortality, and fishing mortality rate of red mullet are estimated as 0.33 year-1, 1.001 year-1 and 0.67 year-1, respectively. The exploitation rate of population was calculated as 0.66 year-1. The fact that exploitation rate is above 0.5 may reflect a high fishing pressure on stock.

Slendr: a framework for spatio-temporal population genomic simulations on geographic landscapes.

One of the goals of population genetics is to understand how evolutionary forces shape patterns of genetic variation over time. However, because populations evolve across both time and space, most evolutionary processes also have an important spatial component, acting through phenomena such as isolation by distance, local mate choice, or uneven distribution of resources. This spatial dimension is often neglected, partly due to the lack of tools specifically designed for building and evaluating complex spatio-temporal population genetic models. To address this methodological gap, we present a new framework for simulating spatially-explicit genomic data, implemented in a new R package called slendr (www.slendr.net), which leverages a SLiM simulation back-end script bundled with the package. With this framework, the users can programmatically and visually encode spatial population ranges and their temporal dynamics (i.e., population displacements, expansions, and contractions) either on real Earth landscapes or on abstract custom maps, and schedule splits and gene-flow events between populations using a straightforward declarative language. Additionally, slendr can simulate data from traditional, non-spatial models, either with SLiM or using an alternative built-in coalescent msprime back end. Together with its R-idiomatic interface to the tskit library for tree-sequence processing and analysis, slendr opens up the possibility of performing efficient, reproducible simulations of spatio-temporal genomic data entirely within the R environment, leveraging its wealth of libraries for geospatial data analysis, statistics, and visualization. Here, we present the design of the slendr R package and demonstrate its features on several practical example workflows.

The potential for spatiotemporal population data sets for aviation noise studies

Aviation noise analysis has traditionally focused on modeling the noise from an average day of operations. We investigate the potential of moving from this static approach to a dynamic method of assessing aircraft noise experienced by people where they are as they move about the day and night. In this research conducted on behalf of the National Academy of Sciences Airport Cooperative Research Program, we evaluated population data sets that account for the movement of people between their daytime versus nighttime location and assessed their applicability for aviation noise studies. We provided guidance on using these spatiotemporal data sets for aviation noise studies using the Aviation Environmental Design Tool, including sample maps and analyses. We also discussed the limitations of spatiotemporal population data, namely they only account for a person's location by time of day and not whether they are engaged in noise-sensitive activities. A fuller picture of noise impact by location and time of day may be achieved by developing an activity-based model, which combines data on location and level of noise sensitivity. We outline the basic elements of such a model.

Emergence of task-related spatiotemporal population dynamics in transplanted neurons

Loss of nervous system tissue after severe brain injury is a main determinant of poor functional recovery. Cell transplantation is a promising method to restore lost tissue and function, yet it remains unclear if transplanted neurons can demonstrate the population level dynamics important for movement control. Here we present a comprehensive approach for long-term single neuron monitoring and manipulation of transplanted embryonic cortical neurons after cortical injury in adult male mice performing a prehension task. The observed patterns of population activity in the transplanted network strongly resembled that of healthy networks. Specifically, the task-related spatiotemporal activity patterns of transplanted neurons could be represented by latent factors that evolve within a low dimensional manifold. We also demonstrate reliable modulation of the transplanted networks using minimally invasive epidural stimulation. Our approach may allow greater insight into how restoration of cell-type specific network dynamics in vivo can restore motor function.

A step towards the integration of spatial dynamics in population dynamics models: Eastern Bering Sea snow crab as a case study

Considering spatial processes in population dynamics models can be difficult because of data limitations and computational costs. We adapted a high-resolution spatiotemporal assessment framework to better address fine-scale spatial heterogeneities based on theories of fish population dynamics and spatiotemporal statistics. Specifically, we developed a size-based state-space model for the snow crab (Chionoecetes opilio) population in the Eastern Bering Sea (EBS) to refine the representation of spatial processes in integrated population models, facilitate understanding of the drivers of spatiotemporal population dynamics, and provide new insights for management advice. The model fits to spatial survey and fishery-dependent catch data. It implicitly accounts for seasonal movement between the time of the survey and that of fishery to estimate fine-scale spatial population dynamic and fishing impacts, including potential environmental drivers. We quantify, for the first time, spatiotemporal variation in exploitable abundance, fishing mortality, recruitment, and mature and immature abundance. The model estimated declines in exploitable abundance and in fishing mortality with variable spatial distributions, and sporadic recruitment, spatially concentrated in the northeast EBS. Few spatial assessments have been used as the basis for management advice and we consider this study as a step towards the integration of spatial dynamics in stock assessment.

How environmental drivers of spatial synchrony interact

Spatial synchrony, the tendency for populations across space to show correlated fluctuations, is a fundamental feature of population dynamics, linked to central topics of ecology such as population cycling, extinction risk, and ecosystem stability. A common mechanism of spatial synchrony is the Moran effect, whereby spatially synchronized environmental signals drive population dynamics and hence induce population synchrony. After reviewing recent progress in understanding Moran effects, we here elaborate a general theory of how Moran effects of different environmental drivers acting on the same populations can interact, either synergistically or destructively, to produce either substantially more or markedly less population synchrony than would otherwise occur. We provide intuition for how this newly recognized mechanism works through theoretical case studies and application of our theory to California populations of giant kelp. We argue that Moran interactions should be common. Our theory and analysis explain an important new aspect of a fundamental feature of spatiotemporal population dynamics.

Blood analytes of hawksbill sea turtles (Eretmochelys imbricata) from Florida waters: reference intervals and size-relevant correlations

Assessments of health variables in wild animal populations have evolved into important tools for characterizing spatiotemporal population trends and fitness, effects of stressors, diseases, and ecosystem health. Blood as a sample matrix can be obtained fairly non-invasively in the field, with preservation and sample processing techniques that allow for readily available routine and advanced diagnostic testing of blood. For wild-caught hawksbill sea turtles (Eretmochelys imbricata) foraging in southeastern Florida, USA, the objectives of this study were to (1) establish reference intervals for hematological and 24 plasma biochemical analytes, (2) determine length-and body condition-specific relationships with blood analytes, and (3) determine how water temperature influenced plasma biochemical analytes. Reference intervals were established for clinically normal juvenile (n = 26) and subadult (n = 39) hawksbills, with descriptive data reported for adult turtles (n = 3). Although subadults (mainly captured at Palm Beach County) were heavier and larger with greater body depth, juveniles (mainly captured at Monroe County) had a higher body condition index. Positive length-specific correlations were identified for packed cell volume, eosinophils, aspartate aminotransferase, phosphorus, cholesterol, glutamate dehydrogenase, total protein, albumin, and globulins, with negative correlations including alkaline phosphatase, creatine kinase, calcium, calcium to phosphorus ratio, and glucose. Subadults had less frequent morphological features of red blood cell regeneration compared to juveniles. These findings provide insight into life-stage class differences regarding hematopoiesis, antigenic stimulation, somatic growth, dietary shifts, nutritional status, osmoregulation, metabolism, physical activity or stress levels, and possible habitat differences. Life-stage class is the likely driver for the observed blood analyte differences, in addition to influences from water temperature. The data herein offer baseline information for a snapshot in time for critically endangered hawksbills inhabiting the Florida reef system and for answering individual-and population-relevant questions of relevance to conservation and population management.