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319 results for “Population estimation”
Data from: Do island plant populations really have lower genetic variation than mainland populations? Effects of selection and distribution range on genetic diversity estimates
Ecological and evolutionary studies largely assume that island populations display low levels of neutral genetic variation. However, this notion has only been formally tested in a few cases involving plant taxa, and the confounding effect of selection on genetic diversity (GD) estimates based on putatively neutral markers has typically been overlooked. Here, we generated nuclear microsatellite and plastid DNA sequence data in Periploca laevigata, a plant taxon with an island-mainland distribution area, to (i) investigate whether selection affects GD estimates of populations across contrasting habitats and (ii) test the long-standing idea that island populations have lower GD than their mainland counterparts. Plastid data showed that colonization of the Canary Islands promoted strong lineage divergence within P. laevigata, which was accompanied by selective sweeps at several nuclear microsatellite loci. Inclusion of loci affected by strong divergent selection produced a significant downward bias in the GD estimates of the mainland lineage, but such underestimates were substantial (>14%) only when more than one loci under selection were included in the computations. When loci affected by selection were removed, we did not find evidence that insular Periploca populations have less GD than their mainland counterparts. The analysis of data obtained from a comprehensive literature survey reinforced this result, as overall comparisons of GD estimates between island and mainland populations were not significant across plant taxa (N=66), with the only exception of island endemics with narrow distributions. This study suggests that identification and removal of markers potentially affected by selection should be routinely implemented in estimates of GD, particularly if different lineages are compared. Furthermore, it provides compelling evidence that the expectation of low GD cannot be generalized to island plant populations.
Data from: Hierarchical distance sampling to estimate population sizes of common lizards across a desert ecoregion
1) Multi-species wildlife monitoring across large geographical regions is important for effective conservation planning in response to expected impacts from climate change and land use. Unlike many species of birds, mammals, and amphibians which can be efficiently sampled using automated sensors including cameras and sound recorders, reptiles are often much more challenging to detect, in part because of their typically cryptic behavior and generally small body sizes. Although many lizard species are more active during the day which makes them easier to detect using visual encounter surveys, they may be unavailable for sampling during certain periods of the day or year due to their sensitivity to temperature. 2) In recognition of these sampling challenges, we demonstrate application of a recent innovation in distance sampling that adjusts for temporary emigration between repeat survey visits. We used transect surveys to survey lizards at 229 sites throughout the Mojave Desert in California, USA, 2016. 3) We estimated a total population size of 80 million (90% CI: 64–97 million) for the three most common species of lizards across this 66,830 km2 ecoregion. We mapped how density at the 1-km2 scale was predicted to vary with vegetation cover and human development. We validated these results against independent surveys from the southern portion of our study area. 4) Our methods and results demonstrate how multi-species monitoring programs spanning arid ecoregions can better incorporate information about reptiles.
Data from: Phenotype-associated inbreeding biases estimates of inbreeding depression in a wild bird population
Inbreeding depression is usually quantified by regressing individual phenotypic values on inbreeding coefficients, implicitly assuming there is no correlation between an individual's phenotype and the kinship coefficient to its mate. If such an association between parental phenotype and parental kinship exists, and if the trait of interest is heritable, estimates of inbreeding depression can be biased. Here we first derive the expected bias as a function of the covariance between mean parental breeding value and parental kinship. Subsequently, we use simulated data to confirm the existence of this bias, and show that it can be accounted for in a quantitative genetic animal model. Finally, we use long-term individual-based data for white-throated dippers (Cinclus cinclus), a bird species in which inbreeding is relatively common, to obtain empirical estimate of this bias. We show that during part of the study period, parents of inbred birds had shorter wings than those of outbred birds, and as wing length is heritable, inbred individuals were smaller, independent of any inbreeding effects. This resulted in the overestimation of inbreeding effects. Similarly, during a period when parents of inbred birds had longer wings, we found that inbreeding effects were underestimated. We discuss how such associations may have arisen in this system, and why they are likely to occur in others, too. Overall, we demonstrate how less biased estimates of inbreeding depression can be obtained within a quantitative genetic framework, and suggest that inbreeding and additive genetic effects should be accounted for simultaneously whenever possible.
Data from: Estimation of a killer whale (Orcinus orca) population's diet using sequencing analysis of DNA from feces
Estimating diet composition is important for understanding interactions between predators and prey and thus illuminating ecosystem function. The diet of many species, however, is difficult to observe directly. Genetic analysis of fecal material collected in the field is therefore a useful tool for gaining insight into wild animal diets. In this study, we used high-throughput DNA sequencing to quantitatively estimate the diet composition of an endangered population of wild killer whales (Orcinus orca) in their summer range in the Salish Sea. We combined 175 fecal samples collected between May and September from five years between 2006 and 2011 into 13 sample groups. Two known DNA composition control groups were also created. Each group was sequenced at a ~330bp segment of the 16s gene in the mitochondrial genome using an Illumina MiSeq sequencing system. After several quality controls steps, 4,987,107 individual sequences were aligned to a custom sequence database containing 19 potential fish prey species and the most likely species of each fecal-derived sequence was determined. Based on these alignments, salmonids made up >98.6% of the total sequences and thus of the inferred diet. Of the six salmonid species, Chinook salmon made up 79.5% of the sequences, followed by coho salmon (15%). Over all years, a clear pattern emerged with Chinook salmon dominating the estimated diet early in the summer, and coho salmon contributing an average of >40% of the diet in late summer. Sockeye salmon appeared to be occasionally important, at >18% in some sample groups. Non-salmonids were rarely observed. Our results are consistent with earlier results based on surface prey remains, and confirm the importance of Chinook salmon in this population's summer diet.
Data from: Estimates of gene flow and dispersal in wild riverine Brook Trout (Salvelinus fontinalis) populations reveal ongoing migration and introgression from stocked fish
As anthropogenic impacts accelerate changes to landscapes across the globe, understanding how genetic population structure is influenced by habitat features and dispersal is key to preserving evolutionary potential at the species level. Furthermore, knowledge of these interactions is essential to identifying potential constraints on local adaptation and for the development of effective management strategies. We examined these issues in Brook Trout (Salvelinus fontinalis) populations residing in the Upper Hudson River watershed of New York State by investigating the spatial genetic structure of over 350 fish collected from 14 different sampling locations encompassing three river systems. Population genetic analyses of microsatellite data suggest that fish in the area exhibit varying degrees of introgression from nearby State-directed supplementation activities. Levels of introgression in these populations correlate with water-way distance to stocking sites, although genetic population structure at the level of individual tributaries as well as their larger, parent river systems is also detectable and is dictated by migration and influenced by habitat connectivity. These findings represent a significant contribution to the current literature surrounding Brook Trout migration and dispersal, especially as it relates to larger interconnected systems. This work also suggests that stocking activities may have far-reaching consequences that are not directly limited to the immediate area where stocking occurs. The framework and data presented here may aid in the development of other local aquatic species-focused conservation plans that incorporate molecular tools to answer complex questions regarding diversity mapping, and genetically important conservation units.
Data from: Estimating transient populations of unmarked individuals at a migratory stopover site using generalized N-mixture models
1. Migration counts are popular indices used to monitor population trends over time. Advanced analytical methods for estimating abundance of unmarked, open populations now incorporate population growth models and simultaneously test for covariate effects on abundance and detection probability. However, estimating population abundance at a staging site is complicated by daily immigration and emigration of unmarked individuals. 2. We applied a set of generalized N-mixture models to simulated count data to test their applicability for transient populations. Using simulated datasets, parameters were unbiased when the apparent survival rate varied within a season or was mis-specified in a model, but not when the immigration or detection probability was mis-specified. 3. With knowledge from the simulated data, we applied these models to daily counts of staging migratory shorebirds and estimated daily abundances accounting for variation in the detection and immigration rates. Daily counts of ruddy turnstones (Arenaria interpres) staging at Westhampton Island, New York, were collected during northward migration (1997–1999). We tested the effects of weather and tides on detection probability, and we modeled within-season variation in immigration rates as a function of time. 4. Covariates affecting the detection probability differed among years, but tide height consistently was correlated with detection probability. Accounting for detection and immigration rates, the predicted maximum single-day populations of ruddy turnstones were 172%, 165%, and 129% of the observed counts for each year. 5. Synthesis and applications. Management and conservation plans for migratory species require abundance estimates that are near the true population size though they are difficult to obtain. Our study is the first empirical application of the generalized N-mixture model that incorporates temporal trends in immigration and estimates daily abundance of a staging unmarked migratory population. Correct estimation of population sizes and the environmental factors affecting them can aid the conservation prioritization of species and staging sites. Moreover, the use of generalized N-mixture models can improve our understanding of the environmental factors that shape migratory movements.
Data from: Evaluating population receptive field estimation frameworks in terms of robustness and reproducibility
Within vision research retinotopic mapping and the more general receptive field estimation approach constitute not only an active field of research in itself but also underlie a plethora of interesting applications. This necessitates not only good estimation of population receptive fields (pRFs) but also that these receptive fields are consistent across time rather than dynamically changing. It is therefore of interest to maximize the accuracy with which population receptive fields can be estimated in a functional magnetic resonance imaging (fMRI) setting. This, in turn, requires an adequate estimation framework providing the data for population receptive field mapping. More specifically, adequate decisions with regard to stimulus choice and mode of presentation need to be made. Additionally, it needs to be evaluated whether the stimulation protocol should entail mean luminance periods and whether it is advantageous to average the blood oxygenation level dependent (BOLD) signal across stimulus cycles or not. By systematically studying the effects of these decisions on pRF estimates in an empirical as well as simulation setting we come to the conclusion that a bar stimulus presented at random positions and interspersed with mean luminance periods is generally most favorable. Finally, using this optimal estimation framework we furthermore tested the assumption of temporal consistency of population receptive fields. We show that the estimation of pRFs from two temporally separated sessions leads to highly similar pRF parameters.
Data from: Counting cats: spatially explicit population estimates of cheetah (Acinonyx jubatus) using unstructured sampling data
Many ecological theories and species conservation programmes rely on accurate estimates of population density. Accurate density estimation, especially for species facing rapid declines, requires the application of rigorous field and analytical methods. However, obtaining accurate density estimates of carnivores can be challenging as carnivores naturally exist at relatively low densities and are often elusive and wide-ranging. In this study, we employ an unstructured spatial sampling field design along with a Bayesian sex-specific spatially explicit capture-recapture (SECR) analysis, to provide the first rigorous population density estimates of cheetahs (Acinonyx jubatus) in the Maasai Mara, Kenya. We estimate adult cheetah density to be between 1.22 ± 0.301 and 1.28 ± 0.322 individuals/100km2 across four candidate models specified in our analysis. Our spatially explicit approach revealed 'hotspots' of cheetah density, highlighting that cheetah are distributed heterogeneously across the landscape. The SECR models incorporated a movement range parameter which indicated that male cheetah moved four times as much as females, possibly because female movement was restricted by their reproductive status and/or the spatial distribution of prey. We show that SECR can be used for spatially unstructured data to successfully characterise the spatial distribution of a low density species and also estimate population density when sample size is small. Our sampling and modelling framework will help determine spatial and temporal variation in cheetah densities, providing a foundation for their conservation and management. Based on our results we encourage other researchers to adopt a similar approach in estimating densities of individually recognisable species.
Data from: Estimating quantitative genetic parameters in wild populations: a comparison of pedigree and genomic approaches
The estimation of quantitative genetic parameters in wild populations is generally limited by the accuracy and completeness of the available pedigree information. Using relatedness at genome-wide markers can potentially remove this limitation and lead to less biased and more precise estimates. We estimated heritability, maternal genetic effects and genetic correlations for body size traits in an unmanaged long-term study population of Soay sheep on St Kilda using three increasingly complete and accurate estimates of relatedness: (1) Pedigree 1, using observation-derived maternal links and microsatellite-derived paternal links; (2) Pedigree 2, using SNP-derived assignment of both maternity and paternity; and (3) whole-genome relatedness at 37,037 autosomal SNPs. In initial analyses, heritability estimates were strikingly similar for all three methods while standard errors were systematically lower in analyses based on Pedigree 2 and genomic relatedness. Genetic correlations were generally strong, differed little between the three estimates of relatedness and the standard errors declined only very slightly with improved relatedness information. When partitioning maternal effects into separate genetic and environmental components, maternal genetic effects found in juvenile traits increased substantially across the three relatedness estimates. Heritability declined compared to parallel models where only a maternal environment effect was fitted, suggesting that maternal genetic effects are confounded with direct genetic effects and that more accurate estimates of relatedness were better able to separate maternal genetic effects from direct genetic effects. We found that the heritability captured by SNP markers asymptoted at about half the SNPs available, suggesting that denser marker panels are not necessarily required for precise and unbiased heritability estimates. Finally, we present guidelines for the use of genomic relatedness in future quantitative genetics studies in natural populations.
Data from: Comparing direct and indirect selfing rate estimates: when are population-structure estimates reliable?
The rate of self-fertilization (that is, selfing) is a key evolutionary parameter in hermaphroditic species, yet obtaining accurate estimates of selfing rates in natural populations can be technically challenging. Most published estimates are derived from population-level heterozygote deficiency (that is, FIS) or identity disequilibria (for example, the software RMES (robust multilocus estimate of selfing)). These indirect methods can be applied to population genetic survey data, whereas direct methods using progeny arrays require much larger data sets that are often difficult to collect in natural populations or even require captive breeding. Unfortunately, indirect methods rely on assumptions that can be problematic, such as negating biparental inbreeding, inbreeding disequilibrium and (for FIS) the presence of null alleles. The performance of indirect estimates against progeny-array estimates is still largely unknown. Here we used both direct progeny-array and indirect population-level methods to estimate the selfing rate in a single natural population of the simultaneously hermaphroditic freshwater snail Radix balthica throughout its reproductive lifespan using 10 highly polymorphic microsatellites. We found that even though progeny arrays (n=1034 field-collected embryos from 60 families) did not reveal a single selfed embryo, FIS-based selfing rates (n=316 adults) were significantly positive in all 6 sequential population samples. Including a locus with a high frequency of null alleles further biased FIS-based estimates. Conversely, RMES-based estimates were very similar to progeny-array estimates and proved insensitive to null alleles. The assumptions made by RMES were thus either met or irrelevant in this particular population, making RMES a valid, cost-efficient alternative to progeny arrays.
Data from: The program STRUCTURE does not reliably recover the correct population structure when sampling is uneven: sub-sampling and new estimators alleviate the problem
Inferences of population structure and more precisely the identification of genetically homogeneous groups of individuals are essential to the fields of ecology, evolutionary biology, and conservation biology. Such population structure inferences are routinely investigated via the program STRUCTURE implementing a Bayesian algorithm to identify groups of individuals at Hardy-Weinberg and linkage equilibrium. While the method is performing relatively well under various population models with even sampling between subpopulations, the robustness of the method to uneven sample size between subpopulations and/or hierarchical levels of population structure has not yet been tested despite being commonly encountered in empirical datasets. In this study, I used simulated and empirical microsatellite datasets to investigate the impact of uneven sample size between subpopulations and/or hierarchical levels of population structure on the detected population structure. The results demonstrated that uneven sampling often leads to wrong inferences on hierarchical structure and downward biased estimates of the true number of subpopulations. Distinct subpopulations with reduced sampling tended to be merged together, whilst at the same time, individuals from extensively sampled subpopulations were generally split, despite belonging to the same panmictic population. Four new supervised methods to detect the number of clusters were developed and tested as part of this study and were found to outperform the existing methods using both evenly and unevenly sampled datasets. Additionally, a sub-sampling strategy aiming to reduce sampling unevenness between subpopulations is presented and tested. These results altogether demonstrate that when sampling evenness is accounted for, the detection of the correct population structure is greatly improved.
Data from: Bayesian estimates of male and female African lion mortality for future use in population management
The global population size of African lions is plummeting, and many small fragmented populations face local extinction. Extinction risks are amplified through the common practice of trophy hunting for males, which makes setting sustainable hunting quotas a vital task. Various demographic models evaluate consequences of hunting on lion population growth. However, none of the models use unbiased estimates of male age-specific mortality because such estimates do not exist. Until now, estimating mortality from resighting records of marked males has been impossible due to the uncertain fates of disappeared individuals: dispersal or death. We develop a new method and infer mortality for male and female lions from two populations that are typical with respect to their experienced levels of human impact. We found that mortality of both sexes differed between the populations and that males had higher mortality across all ages in both populations. We discuss the role that different drivers of lion mortality may play in explaining these differences and whether their effects need to be included in lion demographic models. Synthesis and applications. Our mortality estimates can be used to improve lion population management and, in addition, the mortality model itself has potential applications in demographically informed approaches to the conservation of species with sex-biased dispersal.
A large-scale artificial forest tree population for sampling and estimation methods simulations
<p>The dataset utilized in the Simulation Study section of the article is generated for a 10 km x 10 km area. This artificial dataset is constructed by populating polygons with trees sourced from the NFI database, representing the stands of the associated Vosges polygon. The aim is to create a sizable dataset that closely resembles a real forest by incorporating authentic information. As the Vosges dataset consists of a set of polygons, the artificial dataset is formed using voronoi polygons, each randomly linked to a Vosges dataset polygon. The Vosges dataset contributes basal area information to the voronoi polygons. These voronoi polygons are then filled with trees from the NFI database, corresponding to the stands of the Vosges polygon. The dataset comprises 1,174,227 trees, each with specified attributes such as circumference at a height of 130cm, top height, volume, species, and status (dead/alive).<br> </p>
Correlation between estimated pulse wave velocity values from two equations in healthy and under cardiovascular risk populations
<p><strong>Introduction </strong><strong>: </strong>Equations can calculate pulse wave velocity (ePWV) from blood pressure values (BP) and age. The ePWV predicts cardiovascular events beyond carotid-femoral PWV. We aimed to evaluate the correlation between four different equations to calculate ePWV.</p> <p><strong>Methods: </strong>The ePWV was estimated utilizing mean BP (MBP) from office BP (MBP<sub>OBP</sub>) or 24-hour ambulatory BP (MBP<sub>24-hBP</sub>). We separated the whole sample into two groups: individuals with risk factors and healthy individuals. The e-PWV was calculated as follows: </p> <p>We calculated the concordance correlation coefficient (Pc) between e1-PWV<sub>OBP</sub> vs e2-PWV<sub>OBP</sub>, e1-PWV<sub>24-hBP</sub> vs e2-PWV<sub>24-hBP</sub>, and mean values of e1-PWV<sub>OBP</sub>, e2-PWV<sub>OBP</sub>, e1-PWV<sub>24-hBP, </sub>and e2-PWV<sub>24-hBP </sub>. The multilevel regression model determined how much the ePWVs are influenced by age and MBP values.</p> <p><strong>Results:</strong> We analyzed data from 1541 individuals; 1374 ones with risk factors and 167 healthy ones. The values are presented for the entire sample, for risk-factor patients and for healthy individuals, respectively. The correlation between e1-PWV<sub>OBP</sub> with e2-PWV<sub>OBP</sub> and e1-PWV<sub>24-hBP </sub>with e2-PWV<sub>24-hBP</sub> was almost perfect. The Pc for e1-PWV<sub>OBP</sub> vs e2-PWV<sub>OBP</sub> was 0.996 (0.995-0.996), 0.996 (0.995-0.996), and 0.994 (0.992-0.995); furthermore, it was 0.994 (0.993-0.995), 0.994 (0.994-0.995), 0.987 (0.983-0.990) to the e1-PWV<sub>24-hBP </sub>vs e2-PWV<sub>24-hBP</sub>. There were no significant differences between mean values (m/s) for e1-PWV<sub>OBP</sub> vs e2-PWV<sub>OBP</sub> 8.98±1.9 vs 8.97±1.8; p=0.88, 9.14±1.8 vs 9.13±1.8; p=0.88, and 7.57±1.3 vs 7.65±1.3; p=0.5; mean values are also similar for e1-PWV<sub>24-hBP </sub>vs e2-PWV<sub>24-hBP</sub>, 8.36±1.7 vs 8.46±1.6; p=0.09, 8.50±1.7 vs 8.58±1.7; p=0.21 and 7.26±1.3 vs 7.39±1.2; p=0.34. The multiple linear regression showed that age, MBP, and age² predicted more than 99.5% of all four e-PWV.</p> <p><strong>Conclusion: </strong>Our data presents a nearly perfect correlation between the values of two equations to calculate the estimated PWV, whether utilizing office or ambulatory blood pressure.</p>
How to better count elusive birds? Comparing non-invasive monitoring methods to estimate population size of the endangered Pin-tailed sandgrouse (Pterocles alchata)
<p>Data to run analyses for manuscript comparing non-invasive monitoring methods to estimate Pin-tailed sandgrouse abundance</p>
Distribution. Sub-Saharan Africa; virtually eradicated from W Africa, and greatly reduced in C and NE Africa. The largest populations exist in Botswana, Tanzania, and Zimbabwe, which account for approximately half of the estimated number of African Wild Dogs remaining in the wild. Other populations occur in Central African Republic, Ethiopia, Kenya, Mozambique, Namibia, South Africa, Sudan, and Zambia. Potential small populations (less than 100 individuals) may exist in Cameroon, Chad, Senegal, and Somalia. in Canidae
Distribution. Sub-Saharan Africa; virtually eradicated from W Africa, and greatly reduced in C and NE Africa. The largest populations exist in Botswana, Tanzania, and Zimbabwe, which account for approximately half of the estimated number of African Wild Dogs remaining in the wild. Other populations occur in Central African Republic, Ethiopia, Kenya, Mozambique, Namibia, South Africa, Sudan, and Zambia. Potential small populations (less than 100 individuals) may exist in Cameroon, Chad, Senegal, and Somalia.
Distribution. Sub-Saharan Africa; virtually eradicated from W Africa, and greatly reduced in C and NE Africa. The largest populations exist in Botswana, Tanzania, and Zimbabwe, which account for approximately half of the estimated number of African Wild Dogs remaining in the wild. Other populations occur in Central African Republic, Ethiopia, Kenya, Mozambique, Namibia, South Africa, Sudan, and Zambia. Potential small populations (less than 100 individuals) may exist in Cameroon, Chad, Senegal, and Somalia. in Canidae
Distribution. Sub-Saharan Africa; virtually eradicated from W Africa, and greatly reduced in C and NE Africa. The largest populations exist in Botswana, Tanzania, and Zimbabwe, which account for approximately half of the estimated number of African Wild Dogs remaining in the wild. Other populations occur in Central African Republic, Ethiopia, Kenya, Mozambique, Namibia, South Africa, Sudan, and Zambia. Potential small populations (less than 100 individuals) may exist in Cameroon, Chad, Senegal, and Somalia.
Data from: Effective population size of natural populations of Drosophila buzzatii, with a comparative evaluation of nine methods of estimation
Allozyme and microsatellite data from numerous populations of Drosophila buzzatii have been used (i) to determine to what degree Ne varies among generations within populations, and among populations, and (ii) to evaluate the congruence of four temporal and five single sample estimators of Ne. Effective size of different populations varied over two orders of magnitude, most populations are not temporally stable in genetic composition, and Ne showed large variation over generations in some populations. Short term Ne estimates from the temporal methods were highly correlated, but the smallest estimates were the most precise for all four methods, and the most consistent across methods. Except for one population, Ne estimates were lower when assuming gene flow than when assuming populations were closed. However, attempts to jointly estimate Ne and immigration rate were of little value because the source of migrants was unknown. Correlations among the estimates from the single sample methods generally were not significant although, as for the temporal methods, estimates were most consistent when they were small. These single sample estimates of current Ne are generally smaller than the short term temporal estimates. Nevertheless, population genetic variation is not being depleted, presumably due to past or ongoing migration. A clearer picture of current and short term effective population sizes will only follow with better knowledge of migration rates between populations. Different methods are not necessarily estimating the same Ne, they are subject to different bias, and the biology, demography and history of the population(s) may affect different estimators differently.
Distribution. Now restricted to the Channel Country of SW Queensland and the Lake Eyre Basin in NE South Australia. Descriptive notes. Head-body 95-120 mm, tail 105-160 mm, ear 23-29 mm, hindfoot 32-37 mm; weight 30-50 g. The Fawn Hopping Mouse has body form typical of hopping mice, with very long hindfeet, long tail with distal brush of longer hairs, very long ears, and large protruberant eyes. Dorsal fur is of variable color, from pale pinkish fawn to gray; ventral fur white. Unlike most other hopping mice, it has no throat pouch, but males have a glandular area of naked skin on the chest. Habitat. Occurs in low shrublands and tussock grasslands on stony ("gibber") plains and claypans. Shows marked habitat segregation from the Dusky Hopping Mouse (N. fuscus), which is closely associated with sandy substrates. Food and Feeding. The Fawn Hopping Mouse is mostly granivorous, but also eats other plant material (stems, leaves) and occasionally invertebrates. It uses succulent, salt-adapted plants around edges of claypans as a source of water. Breeding. Reproduction is probably largely opportunistic and aseasonal, with high reproductive output from near-continuous breeding after periods of high rainfall; reported littersize is 1-5, most commonly three; gestation period 38-43 days for nonlactating females. Females may mature later than other hopping mice, with reproductive maturity reached at about six months. Activity patterns. Terrestrial and nocturnal. Fawn Hopping Mice shelter during day in burrow systems that are typically simpler and shallower than those of other hopping mice. Movements, Home range and Social organization. Fawn Hopping Mice generally live singly or in small groups; typically uncommon within range, but population density may increase by an order of magnitude following periods of high rainfall. Status and Conservation. Classified as Near Threatened on The IUCN Red List. The Fawn Hopping Mouse has shown marked decline in range (estimated at greater than 50%), and presumably population size, since European settlement of Australia. This is mostlikely due to predation by the introduced house cat and Red Fox (Vulpes vulpes), and to habitat degradation associated with pastoralism. Bibliography. Brazenor (1934), Burbidge et al. (2008), Finlayson (1939), Gould (1853), Jackson & Groves (2015), Murray et al. (1999), Ogilby (1892), Thomas (1921h), Van Dyck & Strahan (2008), Waite (1898), Watts & Aslin (1981), Woinarski et al. (2014), Wood Jones (1925). in Muridae
Distribution. Now restricted to the Channel Country of SW Queensland and the Lake Eyre Basin in NE South Australia. Descriptive notes. Head-body 95-120 mm, tail 105-160 mm, ear 23-29 mm, hindfoot 32-37 mm; weight 30-50 g. The Fawn Hopping Mouse has body form typical of hopping mice, with very long hindfeet, long tail with distal brush of longer hairs, very long ears, and large protruberant eyes. Dorsal fur is of variable color, from pale pinkish fawn to gray; ventral fur white. Unlike most other hopping mice, it has no throat pouch, but males have a glandular area of naked skin on the chest. Habitat. Occurs in low shrublands and tussock grasslands on stony ("gibber") plains and claypans. Shows marked habitat segregation from the Dusky Hopping Mouse (N. fuscus), which is closely associated with sandy substrates. Food and Feeding. The Fawn Hopping Mouse is mostly granivorous, but also eats other plant material (stems, leaves) and occasionally invertebrates. It uses succulent, salt-adapted plants around edges of claypans as a source of water. Breeding. Reproduction is probably largely opportunistic and aseasonal, with high reproductive output from near-continuous breeding after periods of high rainfall; reported littersize is 1-5, most commonly three; gestation period 38-43 days for nonlactating females. Females may mature later than other hopping mice, with reproductive maturity reached at about six months. Activity patterns. Terrestrial and nocturnal. Fawn Hopping Mice shelter during day in burrow systems that are typically simpler and shallower than those of other hopping mice. Movements, Home range and Social organization. Fawn Hopping Mice generally live singly or in small groups; typically uncommon within range, but population density may increase by an order of magnitude following periods of high rainfall. Status and Conservation. Classified as Near Threatened on The IUCN Red List. The Fawn Hopping Mouse has shown marked decline in range (estimated at greater than 50%), and presumably population size, since European settlement of Australia. This is mostlikely due to predation by the introduced house cat and Red Fox (Vulpes vulpes), and to habitat degradation associated with pastoralism. Bibliography. Brazenor (1934), Burbidge et al. (2008), Finlayson (1939), Gould (1853), Jackson & Groves (2015), Murray et al. (1999), Ogilby (1892), Thomas (1921h), Van Dyck & Strahan (2008), Waite (1898), Watts & Aslin (1981), Woinarski et al. (2014), Wood Jones (1925).
Data for Storeria dekayi population estimation study
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Allen Brain Atlas
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Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
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OpenNeuro
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