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Madan K. Oli - One of the best experts on this subject based on the ideXlab platform.
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Survival, recruitment, and Population Growth Rate of an important mesopredator: the northern raccoon.
PLoS ONE, 2014Co-Authors: Elizabeth M. Troyer, Susan E. Cameron Devitt, Melvin E. Sunquist, Varun R. Goswami, Madan K. OliAbstract:Populations of mesopredators (mid-sized mammalian carnivores) are expanding in size and range amid declining apex predator Populations and ever-growing human presence, leading to significant ecological impacts. Despite their obvious importance, Population dynamics have scarcely been studied for most mesopredator species. Information on basic Population parameters and processes under a range of conditions is necessary for managing these species. Here we investigate survival, recruitment, and Population Growth Rate of a widely distributed and abundant mesopredator, the northern raccoon (Procyon lotor), using Pradel’s temporal symmetry models and >6 years of monthly capture-mark-recapture data collected in a protected area. Monthly apparent survival probability was higher for females (0.949, 95% CI = 0.936–0.960) than for males (0.908, 95% CI = 0.893–0.920), while monthly recruitment Rate was higher for males (0.091, 95% CI = 0.078–0.106) than for females (0.054, 95% CI = 0.042–0.067). Finally, monthly realized Population Growth Rate was 1.000 (95% CI = 0.996–1.004), indicating that our study Population has reached a stable equilibrium in this relatively undisturbed habitat. There was little evidence for substantial temporal variation in Population Growth Rate or its components. Our study is one of the first to quantify survival, recruitment, and realized Population Growth Rate of raccoons using long-term data and rigorous statistical models.
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Density dependence or climatic variation? Factors influencing survival, recruitment, and Population Growth Rate of Virginia opossums
Journal of Mammalogy, 2014Co-Authors: Elizabeth M. Troyer, Susan E. Cameron Devitt, Melvin E. Sunquist, Varun R. Goswami, Madan K. OliAbstract:Abstract Mesopredators play an increasingly important role in ecosystems where apex predators have been eliminated, but Population ecology of these midsized mammalian carnivores remains poorly understood. We applied Pradel's temporal symmetry models to > 6 years of monthly capture–mark–recapture data and investigated factors influencing apparent survival, recruitment, and realized Population Growth Rate of the Virginia opossum (Didelphis virginiana), an important mesopredator with unique life-history characteristics. Apparent survival did not vary temporally; monthly survival probabilities were 0.86 ± 0.01 (SE) for females and 0.76 ± 0.02 for males. Recruitment Rate varied monthly, with the highest recruitment in December (0.32 ± 0.12 for females and 0.57 ± 0.22 for males). Realized Population Growth Rate varied monthly and was also highest in December (1.30 ± 0.17). Both recruitment and Population Growth Rate were positively influenced by the monthly coefficient of variation of precipitation. There was n...
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relative importance of avian life history variables to Population Growth Rate
Ecological Modelling, 2006Co-Authors: Justyn T Stahl, Madan K. OliAbstract:Population Growth Rate is a function of several life-history variables, which differ in their potential influence on Population dynamics. Knowledge of the relative importance of these life-history variables can have implications for ecological and evolutionary theory as well as the conservation of endangered species. We used life-history data for 155 Populations of birds to estimate asymptotic Growth Rate (� ) and elasticity ofto changes in four life-history variables: age at maturity (˛), juvenile survival (Pj), adult survival (Pa), and mean fertility (F). Elasticities were used to quantify relative importance, and to test predictions regarding the pattern of relative importance. Neither ˛ nor any other single life-history variable was most influential in all Populations, but Pa had the largest relative influence onin 53.5% of the Populations. Several metrics (� /˛, � /Pa, F/˛, m/˛, and two estimates of generation time: ¯ A and T) were strongly correlated with elasticities, suggesting that these metrics may be useful predictors of the pattern of relative importance. In general, reproductive parameters (˛ and F) were most important in Populations that matured early and had high reproductive Rates, whereas survival parameters (Pj and Pa) were most important in Populations that matured late and had low reproductive Rates, consistent with earlier research in other taxa. Metrics that require minimal data and have strong predictive power (e.g. the m/˛ ratio) should be useful in devising conservation plans for those species that lack detailed demographic data.
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the relative importance of life history variables to Population Growth Rate in mammals cole s prediction revisited
The American Naturalist, 2003Co-Authors: Madan K. Oli, Stephen F DobsonAbstract:Abstract: The relative importance of life‐history variables to Population Growth Rate (λ) has substantial consequences for the study of life‐history evolution and for the dynamics of biological Populations. Using life‐history data for 142 natural Populations of mammals, we estimated the elasticity of λ to changes in age at maturity (α), age at last reproduction (ω), juvenile survival (Pj), adult survival (Pa), and fertility (F). Elasticities were then used to quantify the relative importance of α, ω, Pj, Pa, and F to λ and to test theoretical predictions regarding the relative influence on λ of changes in life‐history variables. Neither α nor any other single life‐history variable had the largest relative influence on λ in the majority of the Populations, and this pattern did not change substantially when effects of phylogeny and body size were statistically removed. Empirical support for theoretical predictions was poor at best. However, analyses of elasticities on the basis of the magnitude (F) and onse...
David Mouillot - One of the best experts on this subject based on the ideXlab platform.
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Extending networks of protected areas to optimize connectivity and Population Growth Rate
Ecography, 2015Co-Authors: Marco Andrello, Martin Nilsson Jacobi, Stéphanie Manel, Wilfried Thuiller, David MouillotAbstract:Protected areas (PAs) are recognized as the flagship tool to offset biodiversity loss on Earth. Spatial conservation planning seeks optimal designs of PAs that meet multiple targets such as biodiversity representation and Population persistence. Since connectivity between PAs is a fundamental requirement for Population persistence, several methods have been developed to include connectivity into PA design algorithms. Among these, the eigenvalue decomposition of the connectivity matrix allows for identifying clusters of strongly connected sites and selecting the sites contributing the most to Population persistence. So far, this method was only suited to optimize an entire network of PAs without considering existing PAs in the new design. However, a more cost-effective and realistic approach is to optimize the design of an extended network to improve its connectivity and thus Population persistence. Here, we develop a flexible algorithm based on eigenvalue decomposition of connectivity matrices to extend existing networks of PAs while optimizing connectivity and Population Growth Rate. We also include a splitting algorithm to improve cluster identification. The new algorithm accounts for the change in connectivity due to the increased biological productivity often observed in existing PAs. We illustRate the potential of our algorithm by proposing an extension of the network of ∼100 Mediterranean marine PAs to reach the targeted 10% surface area protection from the current 1.8%. We identify differences between the clean slate scenario, where all sites are available for protection, irrespective of their current protection status, and the scenario where existing PAs are forced to be included into the optimized solution. By integrating this algorithm to existing multi-objective and multi-specific algorithms of PA selection, the demographic effects of connectivity can be explicitly included into conservation planning.
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extending networks of protected areas to optimize connectivity and Population Growth Rate
Ecography, 2015Co-Authors: Marco Andrello, Martin Nilsson Jacobi, Stéphanie Manel, Wilfried Thuiller, David MouillotAbstract:Protected areas (PAs) are recognized as the flagship tool to offset biodiversity loss on Earth. Spatial conservation planning seeks optimal designs of PAs that meet multiple targets such as biodiversity representation and Population persistence. Since connectivity between PAs is a fundamental requirement for Population persistence, several methods have been developed to include connectivity into PA design algorithms. Among these, the eigenvalue decomposition of the connectivity matrix allows for identifying clusters of strongly connected sites and selecting the sites contributing the most to Population persistence. So far, this method was only suited to optimize an entire network of PAs without considering existing PAs in the new design. However, a more cost-effective and realistic approach is to optimize the design of an extended network to improve its connectivity and thus Population persistence. Here, we develop a flexible algorithm based on eigenvalue decomposition of connectivity matrices to extend existing networks of PAs while optimizing connectivity and Population Growth Rate. We also include a splitting algorithm to improve cluster identification. The new algorithm accounts for the change in connectivity due to the increased biological productivity often observed in existing PAs. We illustRate the potential of our algorithm by proposing an extension of the network of approximate to 100 Mediterranean marine PAs to reach the targeted 10% surface area protection from the current 1.8%. We identify differences between the clean slate scenario, where all sites are available for protection, irrespective of their current protection status, and the scenario where existing PAs are forced to be included into the optimized solution. By integrating this algorithm to existing multi-objective and multi-specific algorithms of PA selection, the demographic effects of connectivity can be explicitly included into conservation planning.
Pablo E Villagra - One of the best experts on this subject based on the ideXlab platform.
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demography and Population Growth Rate of the tree prosopis flexuosa with contrasting grazing regimes in the central monte desert
Forest Ecology and Management, 2016Co-Authors: Valeria Aschero, William F Morris, Diego P Vazquez, Juan A Alvarez, Pablo E VillagraAbstract:Abstract One of the most important current challenges for ecologists is to evaluate how human-induced changes in ecosystems would impact viability of Populations. Demographic response to anthropogenic impact could help us to understand how to manage those impacts. Using demographic techniques and Population projection models, here we assess if demography and Population dynamics of the tree Prosopis flexuosa change in cattle grazed areas compared to ungrazed areas in the Central Monte desert, Mendoza, Argentina. To this end, we quantified vital Rates and constructed a Population projection matrix model to compare the deterministic Population Growth Rate ( λ ) between grazed and ungrazed areas. We also estimated elasticities of vital Rates to evaluate their potential importance for future changes in λ and performed a life table response experiment (LTRE) to identify the life cycle transitions that contribute the most to the observed differences in λ between the two treatments. Although we found differences in demographic processes, such as lower seed production and higher probability of reversion to smaller size classes in young individuals when cattle were present, our results indicate that cattle grazing had no significant effect on λ for this species. According to the elasticity analysis, survival of large trees is the main driver of the Population Growth Rate ( λ ) of P. flexuosa , and the vital Rates related to tree reproduction, such as seed production and germination, have a poor contribution to λ . Therefore, limitations of activities that can affect survival of large trees should be considered as part of the conservation stRategy for this species. Our study provides a compilation of demographic information that can be useful to set policies connecting the conservation objectives for this woodlands with that of ranch managers of the area.
John P. Delong - One of the best experts on this subject based on the ideXlab platform.
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scaling from metabolism to Population Growth Rate to understand how acclimation temperature alters thermal performance
Integrative and Comparative Biology, 2017Co-Authors: Thomas M. Luhring, John P. DelongAbstract:SYNOPSIS The mean and variance of environmental temperature are changing as a consequence of human activities. Ectotherms are sensitive to these temperature changes in the short term, typically displaying a unimodal response of most biological Rates to temperature (thermal performance curves; TPCs). Many organisms, however, may acclimate or evolve in response to new temperature regimes. In particular, Population Growth Rate TPCs (r TPCs) reflect the ability to maintain positive Growth under a range of temperatures, and therefore shifts in r TPCs due to acclimation are fundamental to our understanding of how ectotherms will respond to changes in climate. Here, we derive a model for r TPCs rooted in temperature dependent metabolic Rate (through enzyme kinetics and activity). We then use this model to interpret the effects of acclimation to different temperatures on r TPCs of the protist Paramecium bursaria. Intermediate acclimation temperatures generally resulted in higher upper critical thermal limits, thermal optima, maximum Population Growth Rate, and the area under the TPC. Lower critical thermal limits increased linearly with acclimation temperature, causing a decrease in thermal breadth with increased acclimation temperature. Thus, rather than showing improved performance at the acclimation temperature, P. bursaria appeared to pay a price at all temperatures for acclimating to higher temperatures. The fits of our data to our model also suggest that changes in the structure and function of metabolic enzymes may underlie the changes in the TPCs. Specifically, our results suggest that both the delta heat capacity and delta enthalpy of formation of metabolic enzymes may have increased with acclimation. Since these two factors are correlated across acclimation temperatures, our data also suggest potential trade-offs that may constrain changes in TPCs.
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Predation changes the shape of thermal performance curves for Population Growth Rate.
Current Zoology, 2016Co-Authors: Thomas M. Luhring, John P. DelongAbstract:Ectotherms generally demonstRate nonlinear changes in performance (e.g., movement speed, individual Growth, Population Growth) as a function of temperature that are characterized by thermal performance curves (TPC). Predation risk elicits phenotypic and behavioral changes that likewise impact performance measures. We tested whether exposure to predation Orthocyclops modestus impacts the maximum Population Growth Rate ( r max) TPC of the protist Paramecium aurelia . We fit predator and non-predator exposed P. aurelia Population Growth Rates to a function previously shown to best describe Paramecium Population Growth Rate TPC’s (Lactin-2) and compared subsequent parameter estimates between curves. For Paramecium exposed to predation risk, maximum Population Growth increased more rapidly as temperatures rose and decreased more rapidly as temperatures fell compared to the initial temperature. The area under each TPC curve remained approximately the same, consistent with the idea of a trade-off in performance across temperatures. Our results indicate TPCs are flexible given variation in food web context and that trophic interactions may play an important role in shaping TPCs. Furthermore, this and other studies illustRate the need for a mechanistic model of TPCs with parameters tied to biologically meaningful properties.
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Population Growth Rate
2016Co-Authors: Thomas M. Luhring, John P. DelongAbstract:Ectotherms generally demonstRate non-linear changes in performance (e.g., movement speed, individual Growth, Population Growth) as a function of temperature that are characterized by thermal performance curves (TPC). Predation risk elicits phenotypic and behavioral changes that likewise impact performance measures. We tested whether exposure to predation Orthocyclops modestus impacts the maximum Population Growth Rate (rmax) TPC of the protist Paramecium aurelia. We fit predator and non-predator exposed P. aurelia Population Growth Rates to a function previously shown to best describe Paramecium Population Growth Rate TPC’s (Lactin-2) and compared subsequent parameter estimates between curves. For Paramecium exposed to predation risk, maximum Population Growth increased more rapidly as temperatures rose and decreased more rapidly as temperatures fell compared to the initial temperature. The area under each TPC curve remained approximately the same, consistent with the idea of a trade-off in performance across temperatures. Our results indicate TPCs are flexible given variation in food-web context and that trophic interactions may play an important role in shaping TPCs. Furthermore, this and other studies illustRate the need for a mechanistic model of TPCs with parameters tied to
Marco Andrello - One of the best experts on this subject based on the ideXlab platform.
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Extending networks of protected areas to optimize connectivity and Population Growth Rate
Ecography, 2015Co-Authors: Marco Andrello, Martin Nilsson Jacobi, Stéphanie Manel, Wilfried Thuiller, David MouillotAbstract:Protected areas (PAs) are recognized as the flagship tool to offset biodiversity loss on Earth. Spatial conservation planning seeks optimal designs of PAs that meet multiple targets such as biodiversity representation and Population persistence. Since connectivity between PAs is a fundamental requirement for Population persistence, several methods have been developed to include connectivity into PA design algorithms. Among these, the eigenvalue decomposition of the connectivity matrix allows for identifying clusters of strongly connected sites and selecting the sites contributing the most to Population persistence. So far, this method was only suited to optimize an entire network of PAs without considering existing PAs in the new design. However, a more cost-effective and realistic approach is to optimize the design of an extended network to improve its connectivity and thus Population persistence. Here, we develop a flexible algorithm based on eigenvalue decomposition of connectivity matrices to extend existing networks of PAs while optimizing connectivity and Population Growth Rate. We also include a splitting algorithm to improve cluster identification. The new algorithm accounts for the change in connectivity due to the increased biological productivity often observed in existing PAs. We illustRate the potential of our algorithm by proposing an extension of the network of ∼100 Mediterranean marine PAs to reach the targeted 10% surface area protection from the current 1.8%. We identify differences between the clean slate scenario, where all sites are available for protection, irrespective of their current protection status, and the scenario where existing PAs are forced to be included into the optimized solution. By integrating this algorithm to existing multi-objective and multi-specific algorithms of PA selection, the demographic effects of connectivity can be explicitly included into conservation planning.
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extending networks of protected areas to optimize connectivity and Population Growth Rate
Ecography, 2015Co-Authors: Marco Andrello, Martin Nilsson Jacobi, Stéphanie Manel, Wilfried Thuiller, David MouillotAbstract:Protected areas (PAs) are recognized as the flagship tool to offset biodiversity loss on Earth. Spatial conservation planning seeks optimal designs of PAs that meet multiple targets such as biodiversity representation and Population persistence. Since connectivity between PAs is a fundamental requirement for Population persistence, several methods have been developed to include connectivity into PA design algorithms. Among these, the eigenvalue decomposition of the connectivity matrix allows for identifying clusters of strongly connected sites and selecting the sites contributing the most to Population persistence. So far, this method was only suited to optimize an entire network of PAs without considering existing PAs in the new design. However, a more cost-effective and realistic approach is to optimize the design of an extended network to improve its connectivity and thus Population persistence. Here, we develop a flexible algorithm based on eigenvalue decomposition of connectivity matrices to extend existing networks of PAs while optimizing connectivity and Population Growth Rate. We also include a splitting algorithm to improve cluster identification. The new algorithm accounts for the change in connectivity due to the increased biological productivity often observed in existing PAs. We illustRate the potential of our algorithm by proposing an extension of the network of approximate to 100 Mediterranean marine PAs to reach the targeted 10% surface area protection from the current 1.8%. We identify differences between the clean slate scenario, where all sites are available for protection, irrespective of their current protection status, and the scenario where existing PAs are forced to be included into the optimized solution. By integrating this algorithm to existing multi-objective and multi-specific algorithms of PA selection, the demographic effects of connectivity can be explicitly included into conservation planning.