753 research outputs found

    Food web persistence in fragmented landscapes

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    Habitat destruction, characterized by patch loss and fragmentation, is a key driver of biodiversity loss. There has been some progress in the theory of spatial food webs; however, to date, practically nothing is known about how patch configurational fragmentation influences multi-trophic food web dynamics. We develop a spatially extended patch-dynamic model for different food webs by linking patch connectivity with trophic-dependent dispersal (i.e. higher trophic levels displaying longer-range dispersal). Using this model, we find that species display different sensitivities to patch loss and fragmentation, depending on their trophic position and the overall food web structure. Relative to other food webs, omnivory structure significantly increases system robustness to habitat destruction, as feeding on different trophic levels increases the omnivore’s persistence. Additionally, in food webs with a dispersal–competition trade-off between species, intermediate levels of habitat destruction can enhance biodiversity by creating refuges for the weaker competitor. This demonstrates that maximizing patch connectivity is not always effective for biodiversity maintenance, as in food webs containing indirect competition, doing so may lead to further species loss

    Development and testing of a database of NIH research funding of AAPM members: A report from the AAPM Working Group for the Development of a Research Database (WGDRD).

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    PURPOSE: To produce and maintain a database of National Institutes of Health (NIH) funding of the American Association of Physicists in Medicine (AAPM) members, to perform a top-level analysis of these data, and to make these data (hereafter referred to as the AAPM research database) available for the use of the AAPM and its members. METHODS: NIH-funded research dating back to 1985 is available for public download through the NIH exporter website, and AAPM membership information dating back to 2002 was supplied by the AAPM. To link these two sources of data, a data mining algorithm was developed in Matlab. The false-positive rate was manually estimated based on a random sample of 100 records, and the false-negative rate was assessed by comparing against 99 member-supplied PI_ID numbers. The AAPM research database was queried to produce an analysis of trends and demographics in research funding dating from 2002 to 2015. RESULTS: A total of 566 PI_ID numbers were matched to AAPM members. False-positive and -negative rates were respectively 4% (95% CI: 1-10%, N = 100) and 10% (95% CI: 5-18%, N = 99). Based on analysis of the AAPM research database, in 2015 the NIH awarded USD110MtomembersoftheAAPM.ThefourNIHinstituteswhichhistoricallyawardedthemostfundingtoAAPMmembersweretheNationalCancerInstitute,NationalInstituteofBiomedicalImagingandBioengineering,NationalHeartLungandBloodInstitute,andNationalInstituteofNeurologicalDisordersandStroke.In2015,over85USD 110M to members of the AAPM. The four NIH institutes which historically awarded the most funding to AAPM members were the National Cancer Institute, National Institute of Biomedical Imaging and Bioengineering, National Heart Lung and Blood Institute, and National Institute of Neurological Disorders and Stroke. In 2015, over 85% of the total NIH research funding awarded to AAPM members was via these institutes, representing 1.1% of their combined budget. In the same year, 2.0% of AAPM members received NIH funding for a total of 116M, which is lower than the historic mean of $120M (in 2015 USD). CONCLUSIONS: A database of NIH-funded research awarded to AAPM members has been developed and tested using a data mining approach, and a top-level analysis of funding trends has been performed. Current funding of AAPM members is lower than the historic mean. The database will be maintained by members of the Working group for the development of a research database (WGDRD) on an annual basis, and is available to the AAPM, its committees, working groups, and members for download through the AAPM electronic content website. A wide range of questions regarding financial and demographic funding trends can be addressed by these data. This report has been approved for publication by the AAPM Science Council

    Pediatric Patient Surface Model Atlas Generation and X-Ray Skin Dose Estimation

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    Fluoroscopy is used in a wide variety of examinations and procedures to diagnose or treat patients in modern pediatric medicine. Although these image guided interventions have many advantages in treating pediatric patients, understanding the deterministic and long term stochastic effects of ionizing radiation are of particular importance for this patient demographic. Therefore, quantitative estimation and visualization of radiation exposure distribution, and dose accumulation over the course of a procedure, is crucial for intra-procedure dose tracking and long term monitoring for risk assessment. Personalized pediatric models are necessary for precise determination of patient-X-ray interactions. One way to obtain such a model is to collect data from a population of pediatric patients, establish a population based generative pediatric model and use the latter for skin dose estimation. In this paper, we generate a population model for pediatric patient using data acquired by two RGB-D cameras from different views. A generative atlas was established using template registration. We evaluated the registered templates and generative atlas by computing the mean vertex error to the associated point cloud. The evaluation results show that the mean vertex error reduced from 25.2 ± 12.9 mm using an average surface model to 18.5 ± 9.4mm using specifically estimated pediatric surface model using the generated atlas. Similarly, the dose estimation error was halved from 10.6 ± 8.5% using the average surface model to 5.9 ± 9.3% using the personalized surface estimates

    Mechanisms affecting population density in fragmented habitat

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    We conducted a factorial simulation experiment to analyze the relative importance of movement pattern, boundary-crossing probability, and mortality in habitat and matrix on population density, and its dependency on habitat fragmentation, as well as inter-patch distance. We also examined how the initial response of a species to a fragmentation event may affect our observations of population density in post-fragmentation experiments. We found that the boundary-crossing probability from habitat to matrix, which partly determines the emigration rate, is the most important determinant for population density within habitat patches. The probability of crossing a boundary from matrix to habitat had a weaker, but positive, effect on population density. Movement behavior in habitat had a stronger effect on population density than movement behavior in matrix. Habitat fragmentation and inter-patch distance may have a positive or negative effect on population density. The direction of both effects depends on two factors. First, when the boundary-crossing probability from habitat to matrix is high, population density may decline with increasing habitat fragmentation. Conversely, for species with a high matrix-to-habitat boundary-crossing probability, population density may increase with increasing habitat fragmentation. Second, the initial distribution of individuals across the landscape: we found that habitat fragmentation and inter-patch distance were positively correlated with population density when individuals were distributed across matrix and habitat at the beginning of our simulation experiments. The direction of these relationships changed to negative when individuals were initially distributed across habitat only. Our findings imply that the speed of the initial response of organisms to habitat fragmentation events may determine the direction of observed relationships between habitat fragmentation and population density. The time scale of post-fragmentation studies must, therefore, be adjusted to match the pace of post-fragmentation movement responses

    Stochastic population growth in spatially heterogeneous environments

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    Classical ecological theory predicts that environmental stochasticity increases extinction risk by reducing the average per-capita growth rate of populations. To understand the interactive effects of environmental stochasticity, spatial heterogeneity, and dispersal on population growth, we study the following model for population abundances in nn patches: the conditional law of Xt+dtX_{t+dt} given Xt=xX_t=x is such that when dtdt is small the conditional mean of Xt+dtiXtiX_{t+dt}^i-X_t^i is approximately [xiμi+j(xjDjixiDij)]dt[x^i\mu_i+\sum_j(x^j D_{ji}-x^i D_{ij})]dt, where XtiX_t^i and μi\mu_i are the abundance and per capita growth rate in the ii-th patch respectivly, and DijD_{ij} is the dispersal rate from the ii-th to the jj-th patch, and the conditional covariance of Xt+dtiXtiX_{t+dt}^i-X_t^i and Xt+dtjXtjX_{t+dt}^j-X_t^j is approximately xixjσijdtx^i x^j \sigma_{ij}dt. We show for such a spatially extended population that if St=(Xt1+...+Xtn)S_t=(X_t^1+...+X_t^n) is the total population abundance, then Yt=Xt/StY_t=X_t/S_t, the vector of patch proportions, converges in law to a random vector YY_\infty as tt\to\infty, and the stochastic growth rate limtt1logSt\lim_{t\to\infty}t^{-1}\log S_t equals the space-time average per-capita growth rate \sum_i\mu_i\E[Y_\infty^i] experienced by the population minus half of the space-time average temporal variation \E[\sum_{i,j}\sigma_{ij}Y_\infty^i Y_\infty^j] experienced by the population. We derive analytic results for the law of YY_\infty, find which choice of the dispersal mechanism DD produces an optimal stochastic growth rate for a freely dispersing population, and investigate the effect on the stochastic growth rate of constraints on dispersal rates. Our results provide fundamental insights into "ideal free" movement in the face of uncertainty, the persistence of coupled sink populations, the evolution of dispersal rates, and the single large or several small (SLOSS) debate in conservation biology.Comment: 47 pages, 4 figure

    The conservation value of human-modified landscapes for the world's primates

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    Land-use change pushes biodiversity into human-modified landscapes, where native ecosystems are surrounded by anthropic land covers (ALCs). Yet, the ability of species to use these emerging covers remains poorly understood. We quantified the use of ALCs by primates worldwide, and analyzed species' attributes that predict such use. Most species use secondary forests and tree plantations, while only few use human settlements. ALCs are used for foraging by at least 86 species with an important conservation outcome: those that tolerate heavily modified ALCs are 26% more likely to have stable or increasing populations than the global average for all primates. There is no phylogenetic signal in ALCs use. Compared to all primates on Earth, species using ALCs are less often threatened with extinction, but more often diurnal, medium or large-bodied, not strictly arboreal, and habitat generalists. These findings provide valuable quantitative information for improving management practices for primate conservation worldwide

    Immigration Rates in Fragmented Landscapes – Empirical Evidence for the Importance of Habitat Amount for Species Persistence

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    BACKGROUND: The total amount of native vegetation is an important property of fragmented landscapes and is known to exert a strong influence on population and metapopulation dynamics. As the relationship between habitat loss and local patch and gap characteristics is strongly non-linear, theoretical models predict that immigration rates should decrease dramatically at low levels of remaining native vegetation cover, leading to patch-area effects and the existence of species extinction thresholds across fragmented landscapes with different proportions of remaining native vegetation. Although empirical patterns of species distribution and richness give support to these models, direct measurements of immigration rates across fragmented landscapes are still lacking. METHODOLOGY/PRINCIPAL FINDINGS: Using the Brazilian Atlantic forest marsupial Gray Slender Mouse Opossum (Marmosops incanus) as a model species and estimating demographic parameters of populations in patches situated in three landscapes differing in the total amount of remaining forest, we tested the hypotheses that patch-area effects on population density are apparent only at intermediate levels of forest cover, and that immigration rates into forest patches are defined primarily by landscape context surrounding patches. As expected, we observed a positive patch-area effect on M. incanus density only within the landscape with intermediate forest cover. Density was independent of patch size in the most forested landscape and the species was absent from the most deforested landscape. Specifically, the mean estimated numbers of immigrants into small patches were lower in the landscape with intermediate forest cover compared to the most forested landscape. CONCLUSIONS/SIGNIFICANCE: Our results reveal the crucial importance of the total amount of remaining native vegetation for species persistence in fragmented landscapes, and specifically as to the role of variable immigration rates in providing the underlying mechanism that drives both patch-area effects and species extinction thresholds
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