Realistic Choice of Annual Matrices Contracts the Range of λS Estimates

In matrix population modeling the multi-year monitoring of a population structure results in a set of annual population projection matrices (PPMs), which gives rise to the stochastic growth rate λS, a quantitative measure of long-term population viability. This measure is usually found in the paradigm of population growth in a variable environment. The environment is represented by the set of PPMs, and λS ensues from a long sequence of PPMs chosen at random from the given set. because the known rules of random choice, such as the iid (independent and identically distributed) matrices, are generally artificial, the challenge is to find a more realistic rule. We achieve this with the a following a Markov chain that models, in a certain sense, the real variations in the environment. We develop a novel method to construct the ruling Markov chain from long-term weather data and to simulate, in a Monte Carlo mode, the long sequences of PPMs resulting in the estimates of λS. The stochastic nature of sequences causes the estimates to vary within some range, and we compare the range obtained by the “realistic choice” from 10 PPMs for a local population of a Red-Book species to those using the iid choice. As noted in the title of this paper, this realistic choice contracts the range of λS estimates, thus improving the estimation and confirming the Red-Book status of the species.

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“Realistic Choice of Annual Matrices Contracts the Range of λS Estimates” under Reproductive Uncertainty Too

Mathematics ◽

10.3390/math9233007 ◽

2021 ◽

Vol 9 (23) ◽

pp. 3007

Author(s):

Dmitrii O. Logofet ◽

Leonid L. Golubyatnikov ◽

Elena S. Kazantseva ◽

Nina G. Ulanova

Keyword(s):

Markov Chain ◽

Local Population ◽

Quantitative Measure ◽

Population Viability ◽

Matrix Population Models ◽

Random Choice ◽

Long Time ◽

Proper Modification ◽

Stochastic Growth Rate ◽

Realistic Choice

Our study is devoted to a subject popular in the field of matrix population models, namely, estimating the stochastic growth rate, λS, a quantitative measure of long-term population viability, for a discrete-stage-structured population monitored during many years. “Reproductive uncertainty” refers to a feature inherent in the data and life cycle graph (LCG) when the LCG has more than one reproductive stage, but when the progeny cannot be associated to a parent stage in a unique way. Reproductive uncertainty complicates the procedure of λS estimation following the defining of λS from the limit of a sequence consisting of population projection matrices (PPMs) chosen randomly from a given set of annual PPMs. To construct a Markov chain that governs the choice of PPMs for a local population of Eritrichium caucasicum, an short-lived perennial alpine plant species, we have found a local weather index that is correlated with the variations in the annual PPMs, and we considered its long time series as a realization of the Markov chain that was to be constructed. Reproductive uncertainty has required a proper modification of how to restore the transition matrix from a long realization of the chain, and the restored matrix has been governing random choice in several series of Monte Carlo simulations of long-enough sequences. The resulting ranges of λS estimates turn out to be more narrow than those obtained by the popular i.i.d. methods of random choice (independent and identically distributed matrices); hence, we receive a more accurate and reliable forecast of population viability.

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The implications of vehicle collisions for the Endangered endemic Zanzibar red colobus Piliocolobus kirkii

Oryx ◽

10.1017/s0030605320000605 ◽

2021 ◽

pp. 1-9

Author(s):

Harry Olgun ◽

Mzee Khamis Mohammed ◽

Abbas Juma Mzee ◽

M. E. Landry Green ◽

Tim R. B. Davenport ◽

...

Keyword(s):

Road Ecology ◽

Local Population ◽

Red Colobus ◽

Vehicle Collisions ◽

The Road ◽

Life History Data ◽

Natural Predation ◽

Historical Accounts ◽

The Impact

Abstract Roads affect wildlife in a variety of negative ways. Road ecology studies have mostly concentrated on areas in the northern hemisphere despite the potentially greater impact of roads on biodiversity in tropical habitats. Here, we examine 4 years (January 2016–December 2019) of opportunistic observations of mammalian roadkill along a road intersecting Jozani-Chwaka Bay National Park, Unguja, Zanzibar. In particular, we assess the impact of collisions on the population of an endemic primate, the Endangered Zanzibar red colobus Piliocolobus kirkii. Primates accounted for the majority of roadkill in this dataset. Monthly rainfall was not associated with roadkill frequency for mammals generally, nor for the Zanzibar red colobus. No single age–sex class of colobus was found dead more often than expected given their occurrence in the local population. The overall effect of roadkill on colobus populations in habitats fragmented by roads is unknown given the lack of accurate, long-term life history data for this species. Our findings suggest that mortality from collisions with vehicles in some groups of colobus is within the range of mortality rates other primates experience under natural predation. Unlike natural predators, however, vehicles do not kill selectively, so their impact on populations may differ. Although a comparison with historical accounts suggests that the installation of speedbumps along the road near the Park's entrance has led to a significant decrease in colobus roadkill, further actions to mitigate the impact of the road could bring substantial conservation benefits.

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Evaluation of the CERES-Rice Model for Precision Nitrogen Management for Rice in Northeast China

Advances in Animal Biosciences ◽

10.1017/s2040470017000024 ◽

2017 ◽

Vol 8 (2) ◽

pp. 328-332

Author(s):

J. Zhang ◽

Y. Miao ◽

W.D. Batchelor

Keyword(s):

Northeast China ◽

Weather Data ◽

Cool Season ◽

Use Efficiency ◽

Optimum N Rate ◽

Management Recommendations ◽

N Management ◽

N Rates ◽

N Use

Over-application of nitrogen (N) in rice (Oryza sativaL.) production in China is common, leading to low N use efficiency (NUE) and high environmental risks. The objective of this work was to evaluate the ability of the CERES-Rice crop growth model to simulate N response in the cool climate of Northeast China, with the long term goal of using the model to develop optimum N management recommendations. Nitrogen experiments were conducted from 2011–2015 in Jiansanjiang, Heilongjiang Province in Northeast China. The CERES-Rice model was calibrated for 2014 and 2015 and evaluated for 2011 and 2013 experiments. Overall, the model gave good estimations of yield across N rates for the calibration years (R2=0.89) and evaluation years (R2=0.73). The calibrated model was then run using weather data from 2001–2015 for 20 different N rates to determine the N rate that maximized the long term marginal net return (MNR) for different N prices. The model results indicated that the optimum mean N rate was 120–130 kg N ha–1, but that the simulated optimum N rate varied each year, ranging from 100 to 200 kg N ha–1. Results of this study indicated that the CERES-Rice model was able to simulate cool season rice growth and provide estimates of optimum regional N rates that were consistent with field observations for the area.

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A method for simulating risk profiles of wheat yield in data-sparse conditions

The Journal of Agricultural Science ◽

10.1017/s0021859621000253 ◽

2021 ◽

pp. 1-12

Author(s):

G. Bracho-Mujica ◽

P.T. Hayman ◽

V.O. Sadras ◽

B. Ostendorf

Keyword(s):

Reference Site ◽

Climate Impacts ◽

Weather Data ◽

Climate Data ◽

High Quality ◽

Risk Profiles ◽

Record Length ◽

Daily Weather Data ◽

Study Sites

Abstract Process-based crop models are a robust approach to assess climate impacts on crop productivity and long-term viability of cropping systems. However, these models require high-quality climate data that cannot always be met. To overcome this issue, the current research tested a simple method for scaling daily data and extrapolating long-term risk profiles of modelled crop yields. An extreme situation was tested, in which high-quality weather data was only available at one single location (reference site: Snowtown, South Australia, 33.78°S, 138.21°E), and limited weather data was available for 49 study sites within the Australian grain belt (spanning from 26.67 to 38.02°S of latitude, and 115.44 to 151.85°E of longitude). Daily weather data were perturbed with a delta factor calculated as the difference between averaged climate data from the reference site and the study sites. Risk profiles were built using a step-wise combination of adjustments from the most simple (adjusted series of precipitation only) to the most detailed (adjusted series of precipitation, temperatures and solar radiation), and a variable record length (from 10 to 100 years). The simplest adjustment and shortest record length produced bias of modelled yield grain risk profiles between −10 and 10% in 41% of the sites, which increased to 86% of the study sites with the most detailed adjustment and longest record (100 years). Results indicate that the quality of the extrapolation of risk profiles was more sensitive to the number of adjustments applied rather than the record length per se.

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Calibration of Transition Intensities for a Multistate Model: Application to Long-Term Care

Risks ◽

10.3390/risks9020037 ◽

2021 ◽

Vol 9 (2) ◽

pp. 37

Author(s):

Manuel L. Esquível ◽

Gracinda R. Guerreiro ◽

Matilde C. Oliveira ◽

Pedro Corte Real

Keyword(s):

Markov Chain ◽

Continuous Time ◽

Long Term Care ◽

Transition Probabilities ◽

Markov Chain Model ◽

Chain Model ◽

Chain Process ◽

Term Care ◽

National Network

We consider a non-homogeneous continuous time Markov chain model for Long-Term Care with five states: the autonomous state, three dependent states of light, moderate and severe dependence levels and the death state. For a general approach, we allow for non null intensities for all the returns from higher dependence levels to all lesser dependencies in the multi-state model. Using data from the 2015 Portuguese National Network of Continuous Care database, as the main research contribution of this paper, we propose a method to calibrate transition intensities with the one step transition probabilities estimated from data. This allows us to use non-homogeneous continuous time Markov chains for modeling Long-Term Care. We solve numerically the Kolmogorov forward differential equations in order to obtain continuous time transition probabilities. We assess the quality of the calibration using the Portuguese life expectancies. Based on reasonable monthly costs for each dependence state we compute, by Monte Carlo simulation, trajectories of the Markov chain process and derive relevant information for model validation and premium calculation.

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Timing and severity of immunizing diseases in rabbits is controlled by seasonal matching of host and pathogen dynamics

Journal of The Royal Society Interface ◽

10.1098/rsif.2014.1184 ◽

2015 ◽

Vol 12 (103) ◽

pp. 20141184 ◽

Cited By ~ 20

Author(s):

Konstans Wells ◽

Barry W. Brook ◽

Robert C. Lacy ◽

Greg J. Mutze ◽

David E. Peacock ◽

...

Keyword(s):

Local Population ◽

Disease Outbreaks ◽

Maternal Antibodies ◽

Timing Of Reproduction ◽

Demographic Rates ◽

Pathogen Dynamics ◽

Rabbit Haemorrhagic Disease ◽

Seasonal Epidemics ◽

Haemorrhagic Disease

Infectious diseases can exert a strong influence on the dynamics of host populations, but it remains unclear why such disease-mediated control only occurs under particular environmental conditions. We used 16 years of detailed field data on invasive European rabbits ( Oryctolagus cuniculus ) in Australia, linked to individual-based stochastic models and Bayesian approximations, to test whether (i) mortality associated with rabbit haemorrhagic disease (RHD) is driven primarily by seasonal matches/mismatches between demographic rates and epidemiological dynamics and (ii) delayed infection (arising from insusceptibility and maternal antibodies in juveniles) are important factors in determining disease severity and local population persistence of rabbits. We found that both the timing of reproduction and exposure to viruses drove recurrent seasonal epidemics of RHD. Protection conferred by insusceptibility and maternal antibodies controlled seasonal disease outbreaks by delaying infection; this could have also allowed escape from disease. The persistence of local populations was a stochastic outcome of recovery rates from both RHD and myxomatosis. If susceptibility to RHD is delayed, myxomatosis will have a pronounced effect on population extirpation when the two viruses coexist. This has important implications for wildlife management, because it is likely that such seasonal interplay and disease dynamics has a strong effect on long-term population viability for many species.

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Protected Areas: offering security to whom, when and where?

Environmental Conservation ◽

10.1017/s0376892915000375 ◽

2016 ◽

Vol 43 (2) ◽

pp. 172-180 ◽

Cited By ~ 7

Author(s):

ALICE B. KELLY ◽

A. CLARE GUPTA

Keyword(s):

Protected Areas ◽

Environmental Conditions ◽

Protected Area ◽

Spatial Scales ◽

Local Population ◽

Well Being ◽

Economic Context ◽

Term Management ◽

Over Time

SUMMARYThis study considers the issue of security in the context of protected areas in Cameroon and Botswana. Though the literature on issues of security and well-being in relation to protected areas is extensive, there has been less discussion of how and in what ways these impacts and relationships can change over time, vary with space and differ across spatial scales. Looking at two very different historical trajectories, this study considers the heterogeneity of the security landscapes created by Waza and Chobe protected areas over time and space. This study finds that conservation measures that various subsets of the local population once considered to be ‘bad’ (e.g. violent, exclusionary protected area creation) may be construed as ‘good’ at different historical moments and geographical areas. Similarly, complacency or resignation to the presence of a park can be reversed by changing environmental conditions. Changes in the ways security (material and otherwise) has fluctuated within these two protected areas has implications for the long-term management and funding strategies of newly created and already existing protected areas today. This study suggests that parks must be adaptively managed not only for changing ecological conditions, but also for shifts in a protected area's social, political and economic context.

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Thermogenesis of white adipocytes: a novel method allowing long-term microcalomrimetric investigations

Journal of Biochemical and Biophysical Methods ◽

10.1016/0165-022x(91)90065-5 ◽

1991 ◽

Vol 23 (2) ◽

pp. 181-187 ◽

Cited By ~ 6

Author(s):

Hartfried Böttcher ◽

Jürgen Nittinger ◽

Sabine Engel ◽

Peter Fürst

Keyword(s):

White Adipocytes ◽

Novel Method

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Continuous automatic measurement of rhythms in fungal respiration using a gas chromatograph

Canadian Journal of Botany ◽

10.1139/b73-087 ◽

1973 ◽

Vol 51 (4) ◽

pp. 701-710 ◽

Cited By ~ 5

Author(s):

Roger S. Smith

Keyword(s):

Carbon Dioxide ◽

Agar Medium ◽

Quantitative Measure ◽

Automatic Measurement ◽

Carbon Dioxide Production ◽

Chromatographic Technique ◽

Gas Chromatograph ◽

Growth Chambers ◽

Long Term Measurement

The long-term measurement of aerobic fungal respiration, both on an agar medium and on wood blocks, was possible using a gas-chromatographic technique for the detection of the carbon dioxide. This method was fully automated to analyze gas samples sequentially from eight or more growth chambers, after variable but determined time periods. It provided a precise quantitative measure of the respired carbon dioxide, presented both in the form of punched computer tape and normal printed teleprinter output. This apparatus worked continuously for several years without serious breakdown.The fungi Lentinus lepideus, Lenzites trabea, Poria monticola, and several strains of Coniophora puteana all showed a rhythm in their respiration which was not controlled by temperature or light. The magnitude and frequency of the rhythmical peaks in carbon dioxide production varied between fungi and, although there was considerable variation between different isolates of the same species, the separation of these species of fungi based on their different patterns of respiration was possible.

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