Research Dataset Catalog and ShareScore Ratings | ScienceDex

zenodo44/100

Supplemental data and code for "Global patterns in water flux partitioning: Irrigated and rainfed agriculture drives asymmetrical flux to vegetation over runoff"

This dataset provides all data compiled and generated for the manuscript entitled "Global patterns in water flux partitioning: Irrigated and rainfed agriculture drives asymmetrical flux to vegetation over runoff" (https://doi.org/10.1016/j.oneear.2023.08.002). This includes the boundaries for 3614 hydrological catchments, the curated data used for analysis and modelling, the developed machine learning model, shapley values and area of applicability results, and data for global extrapolation It also contains a markdown file ('code.html') which shows how to access and use the data, and generic sample codes used to generate these results.

opencc-by-4.0May 2022View details →

zenodo44/100

Data for: Klein et al., Viscosity of aqueous ammonium nitrate--organic particles: Equilibrium partitioning may be a reasonable assumption for most tropospheric conditions, egusphere-2024-1459

Experimental data This folder contains the experimental and modelled data to the figures shown in the main manuscript and Appendix. Figure 3B AIOMFAC-VISC (AIOMFAC-VISC modelling of sucrose) Figure 3B Experimental (Viscosity measurements of sucrose) Figure 4 (Viscosity measurements of ammonium nitrate - sucrose - water mixtures) Figure 5 A and C (Viscosity estimations of ammonium nitrate - sucrose - water mixtures using mixing rules) Figure 5 B and D (Viscosity estimations of ammonium nitrate - sucrose - water mixtures using AIOMFAC-VISC) Figure 6 (Viscosity estimations of inorganic - sucrose - water mixtures using mixing rules) Figure 7 (Mixing times for ammonium nitrate - sucrose - water and Toluene SOA - sucrose - water aerosol particles for varies cities)  Figure A2 (Viscosity estimations of ammonium nitrate - sucrose - water mixtures using a mass fraction based mixing rules)

opencc-by-4.0May 2024View details →

dryad40/100

Anatomical partitioning has little influence in topologies from Bayesian phylogenetic analyses of morphological data

Morphological data is a fundamental source of evidence to reconstruct the Tree of Life, and Bayesian phylogenetic methods are increasingly being used for this task, along with, or instead of, traditional parsimony approaches. Bayesian phylogenetic analyses require the use of proper evolutionary models and their performance have been intensively studied in the past few years, with significant improvements to our knowledge regarding their performance. Notwithstanding, it was only recently that partitioned models for morphology received attention in studies of empirical data, but a systematic evaluation of its performances using simulations was never performed. Here we evaluate the influence of partitioned models defined by anatomical criterion in the precision and accuracy of consensus tree topologies, evaluating the possible negative effects of under and overpartitioning. For that, we analysed datasets simulated using parameters and properties of two empirical datasets, using Bayesian phylogenetic analyses in MrBayes. Additionally, we reanalysed 32 empirical datasets for diverse groups of vertebrates, applying unpartitioned and partitioned models. We found that in general, partitioning by anatomy has little to no influences in the performance of Bayesian phylogenetic methods in respect to the metrics studied here, with analyses under alternative partitioning schemes presenting very similar tree precision and accuracy. We discuss the possible reasons for the disagreement between the results obtained here and previous studies for empirical morphological data, and with empirical and simulation studies of molecular data, discussing the adequacy of anatomical partitioning relative to alternative methods to partition morphological datasets and how morphological and molecular partitioning are related.

opencc-zeroDec 2020View details →

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Data from: Seasonal diet partition among top predators of a small island, Iriomotejima island in the Ryukyu Archipelago, Japan

In general, small islands lack predators because species at higher trophic levels often cannot survive. However, two predators—the Iriomote cat Prionailurus bengalensis iriomotensis, and the Crested Serpent Eagle Spilornis cheela perplexus—live on Iriomotejima Island in the Ryukyu Archipelago, which covers an area of approximately 284 square kilometers. To understand how these two top predators coexist on such a small island with limited resources, we focused on their seasonal feeding habits which are considered crucial for survival in such an island ecosystem. To compare the diets of the Iriomote cat and Crested Serpent Eagle, we used DNA metabarcoding analysis of their fecal samples. In the summer, we identified 16 prey items from Iriomote cat fecal samples, and 15 Crested Serpent Eagle fecal samples. In the winter, we identified 37 and 14 prey items, respectively. Using a non-metric multidimensional scaling (NMDS) and a permutational multivariate analysis of variance (PERMANOVA), our study reveals significant differences in the diet composition at the order level between the predators during both seasons. Furthermore, although some prey items at the species-to-order level overlapped between the two predators, the frequency of occurrence of most prey items differed between them in both seasons. These results suggest that this difference in diets was one of the reasons why the Iriomote cat and the Crested Serpent Eagle coexisted on such a small island.

opencc-zeroFeb 2024View details →

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Data for the publication "Too frequent and too light Arctic snowfall with incorrect precipitation phase partitioning in the MIROC6 GCM"

These data are a set of 1yr simulations using the MIROC6-SPRINTARS global aerosol-climate model with different treatments of precipitation (i.e., diagnostic and prognostic). The outputs include diagnostics from the satellite simulator COSP2. The data are used in the manuscript entitled "Too frequent and too light Arctic snowfall with incorrect precipitation phase partitioning in the MIROC6 GCM". All data used in this study are available from the corresponding author upon request.

opencc-by-4.0Feb 2022View details →

zenodo40/100

Data from: Drought and recovery effects on belowground respiration dynamics and the partitioning of recent carbon in managed and abandoned grassland

The supply of soil respiration with recent photoassimilates is an important and fast pathway for respiratory loss of carbon (C). To date it is unknown how drought and land-use change interactively influence the dynamics of recent C in soil respired CO2. In an in situ common-garden experiment, we exposed soil-vegetation monoliths from a managed and a nearby abandoned mountain grassland to an experimental drought. Based on two 13CO2 pulse-labelling campaigns, we traced recently assimilated C in soil respiration during drought, rewetting and early recovery. Independent of grassland management, drought reduced the absolute allocation of recent C to soil respiration. Rewetting triggered a respiration pulse, which was strongly fueled by C assimilated during drought. In comparison to the managed grassland, the abandoned grassland partitioned more recent C to belowground respiration than to root C storage under ample water supply. Interestingly, this pattern was reversed under drought. We suggest that these different response patterns reflect strategies of the managed and the abandoned grassland to enhance their respective resilience to drought, by fostering their resistance and recovery, respectively. We conclude that while severe drought can override the effects of abandonment of grassland management on the respiratory dynamics of recent C, abandonment alters strategies of belowground assimilate investment, with consequences for soil-CO2 fluxes during drought and drought-recovery.

opencc-by-4.0Apr 2020View details →

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Data from: Pop‐off data storage tags reveal niche partitioning between native and non‐native predators in a novel ecosystem

1. Niche partitioning might be predicted to be particularly dynamic in 'novel ecosystems' characterized by human-altered environmental conditions and biological invasions. Restoration efforts for native species in such systems can be informed by detailed characterization of niche partitioning. 2. In Lake Ontario, fishery management agencies have been engaged in a long-term struggle to restore native top predators including lake trout (Salvelinus namaycush). Meanwhile, management agencies continue to stock non-native species like Chinook salmon (Oncorhynchus tshawytscha) into the lake to support a recreational fishery and to help control the abundance of a non-native forage fish, the alewife (Alosa pseudoharengus). 3. We used pop-off data storage tags to study fine scale (9.1M lines of data from 22 animals) behaviour and habitat use by lake trout (native) and Chinook salmon (non-native) in Lake Ontario in terms of depth and temperature, recorded at ≤70 s intervals for periods of up to 12 months. 4. Chinook salmon occupied warmer and shallower waters during summer than did lake trout, and their niche breadth was wider. They achieved greater niche breadth in part because they were much more active vertically, cumulatively traveling 103±1 m hour-1 during summer (model-estimated median), whereas most lake trout were relatively inactive vertically (7±1 m hour-1). In each of our analyses, there was more inter-individual variation among lake trout than among Chinook salmon, driven by some lake trout that spent considerable time making forays into warmer, shallower waters. 5. Synthesis and applications. Our results illustrate the different foraging tactics used by two species in the Great Lakes and reflect their distinct life histories. Vertical and thermal niche partitioning between Chinook salmon and lake trout helps to explain how these species can co-exist in a multi-species fishery even while having substantial overlap in diet. The diversity of behaviours exhibited here by native lake trout have likely helped them persist during dramatic changes to the forage base in recent decades; that flexibility could help underlie their long-term prospects for restoration during future changes to the ecosystem.

opencc-zeroNov 2019View details →

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Niche partitioning between planktivorous fish in the pelagic Baltic Sea assessed by DNA metabarcoding, qPCR and microscopy: Data and Analyses

Marine communities undergo rapid changes because of human-induced ecosystem pressures. The Baltic Sea pelagic food web has experienced several regime shifts during the past century, resulting in a system where competition between planktivorous mesopredators is assumed to be high. While the two clupeids sprat and herring reveal signs of competition, the stickleback population has increased drastically during the past decades. Here, we investigate diet overlap between the three dominating planktivorous fish in the Baltic Sea, utilizing DNA metabarcoding on the 18S rRNA gene and the COI gene, targeted qPCR, and microscopy. Our results show niche differentiation between clupeids and stickleback and that rotifers play an important function in niche partitioning of stickleback, as a resource that is not being used, neither by the clupeids nor by other zooplankton. We further show that all the diet assessment methods used in this study are consistent but DNA metabarcoding describes the plankton-fish link at the highest taxonomic resolution. This study suggests that rotifers and other understudied soft-bodied prey may have an important function in the pelagic food web and that the growing population of pelagic stickleback is supported by the unutilized feeding niche offered by the rotifers.

opencc-zeroJul 2022View details →

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Data - Effect of electrolytes as adjuvants in GFP and LPS partitioning on aqueous two-phase systems: 1. Polymer-polymer systems

Overview The production of recombinant biopharmaceuticals is highly dependent of a proper choice of the downstream processing stages. Particularly, the purification that must ensure that all the endotoxins (lipopolysaccharide - LPS) are efficiently removed from the final product. This dataset contains the raw data and statistical analysis for the research entitled - "Effect of electrolytes as adjuvants in GFP and LPS partitioning on aqueous two-phase systems: 1. Polymer-polymer systems".  Info ANOVA_Turkey_Sub.R <- code for ANOVA analysis in R statistic 3.3.3     glm.R <- code for GLM analysis in R statistic 3.3.3 K&REC_LPS_PEG_NaPA.xlsx <- File with raw values organized in a spreadsheet of GFP partition coefficient (K) and recover (REC) for ANOVA analysis K&REC_LPS_PEG_NaPA_K.docx <- File with ANOVA result of partition coefficient (K) for GFP K&REC_LPS_PEG_NaPA_REC.docx <- File with ANOVA result of recover (REC) for GFP          K_GFP_Pol_005.csv <- File with raw values organized in a spreadsheet of GFP partition coefficient (K) for GLM analysis in 0.05M salt assays     K_GFP_Pol_005.doc <- File with GLM analysis of GFP partition coefficient (K) in 0.05M salt assays   K_GFP_Pol_005_QQ.png <- Residual quantile plot of GLM analysis for partition coefficient (K) in 0.05M salt assays   K_GFP_Pol_025.csv <- File with raw values organized in a spreadsheet of GFP partition coefficient (K) for GLM analysis in 0.25M salt assays   K_GFP_Pol_025.doc  <- File with GLM analysis of GFP partition coefficient (K) in 0.25M salt assays   K_GFP_Pol_025_QQ.png <- Residual quantile plot of GLM analysis for partition coefficient (K) in 0.25M salt assays          REC_GFP_Pol_005.csv <- File with raw values organized in a spreadsheet of GFP recover (REC) for GLM analysis in 0.05M salt assays          REC_GFP_Pol_005.doc  <- File with GLM analysis of GFP recover (REC) in 0.05M salt assays     REC_GFP_Pol_005_QQ.png <- Residual quantile plot of GLM analysis of GFP recover (REC) in 0.05M salt assays    REC_GFP_Pol_025.csv <- File with raw values organized in a spreadsheet of GFP recover (REC) for GLM analysis in 0.25M salt assays           REC_GFP_Pol_025.doc  <- File with GLM analysis of GFP recover (REC) in 0.25M salt assays  REC_GFP_Pol_025_QQ.png <- Residual quantile plot of GLM analysis of GFP recover (REC) in 0.25M salt assays         REM_LPS_PEG_NaPA.docx  <- File with ANOVA result of LPS removal           REM_LPS_PEG_NaPA.xlsx <- File with raw values organized in a spreadsheet of LPS removal for ANOVA analysis Stability_GFP_PEG_NaPA.docx <- File with ANOVA result of GFP stability Stability_GFP_PEG_NaPA.xlsx <- File with raw values organized in a spreadsheet of GFP stability results for ANOVA analysis REM_LPS_Pol_005.csv  <- File with raw values organized in a spreadsheet of LPS removal (REM) for GLM analysis in 0.05M salt assays          REM_LPS_Pol_005.doc  <- File with GLM analysis of LPS removal (REM) in 0.05M salt assays     REM_LPS_Pol_005_QQ.png <- Residual quantile plot of GLM analysis of LPS removal (REM) in 0.05M salt assays   REM_LPS_Pol_025.csv  <- File with raw values organized in a spreadsheet of LPS removal (REM) for GLM analysis in 0.25M salt assays          REM_LPS_Pol_025.doc   <- File with GLM analysis of LPS removal (REM) in 0.25M salt assays     REM_LPS_Pol_025_QQ.png <- Residual quantile plot of GLM analysis of LPS removal (REM) in 0.25M salt assays K_GFP_Pol_025_NaCl_Li2SO4.csv <- File with raw values organized in a spreadsheet of GFP partition coefficient (K) for GLM analysis in 0.25M salt assays comparing NaCl and Li2SO4 effect  K_GFP_Pol_025_NaCl_Li2SO4.doc  <- File with GLM analysis of GFP partition coefficient (K) in 0.25M salt assays comparing NaCl and Li2SO4 effect  K_GFP_Pol_025_NaCl_Li2SO4_QQ.png <- Residual quantile plot of GLM analysis of GFP recover (REC) in 0.25M salt assays comparing NaCl and Li2SO4 effect    REM_LPS_Pol_KI_0.05_vs_0.25.csv <- File with raw values organized in a spreadsheet of GFP partition coefficient (K) for GLM analysis in KI assays comparing salt concentration effect   REM_LPS_Pol_KI_0.05_vs_0.25.doc <- File with GLM analysis of GFP partition coefficient (K) in KI assays comparing salt concentration effect REM_LPS_Pol_KI_0.05_vs_0.25_QQ.png <- Residual quantile plot of GLM analysis of GFP recover (REC) in KI assays comparing salt concentration effect REM_LPS_Pol_KNO3_0.05_vs_0.25.csv  <- File with raw values organized in a spreadsheet of GFP partition coefficient (K) for GLM analysis in KNO3 assays comparing salt concentration effect   REM_LPS_Pol_KNO3_0.05_vs_0.25.doc <- File with GLM analysis of GFP partition coefficient (K) in KNO3 assays comparing salt concentration effect REM_LPS_Pol_KNO3_0.05_vs_0.25_QQ.png <- Residual quantile plot of GLM analysis of GFP recover (REC) in KNO3 assays comparing salt concentration effect REM_LPS_Pol_Li2SO4_0.05_vs_0.25.csv <- File with raw values organized in a spreadsheet of GFP partition coefficient (K) for GLM analysis in Li2SO4 assays comparing salt concentration effect   REM_LPS_Pol_Li2SO4_0.05_vs_0.25.doc <- File with GLM analysis of GFP partition coefficient (K) in Li2SO4 assays comparing salt concentration effect REM_LPS_Pol_Li2SO4_0.05_vs_0.25_QQ.png <- Residual quantile plot of GLM analysis of GFP recover (REC) in Li2SO4 assays comparing salt concentration effect REM_LPS_Pol_NaCl_0.05_vs_0.25.csv <- File with raw values organized in a spreadsheet of GFP partition coefficient (K) for GLM analysis in NaCl assays comparing salt concentration effect   REM_LPS_Pol_NaCl_0.05_vs_0.25.doc <- File with GLM analysis of GFP partition coefficient (K) in NaCl assays comparing salt concentration effect  REM_LPS_Pol_NaCl_0.05_vs_0.25_QQ.png <- Residual quantile plot of GLM analysis of GFP recover (REC) in NaCl assays comparing salt concentration effect   Annotation 12/12 - Concentration of 12% of each polymer PEG/NaPA 16/16 - Concentration of 16% of each polymer PEG/NaPA P/N -  PEG/NaPA 10e4, 10e5, 10e6 - Concentration of LPS in scientific notation - 10000, 100000, 100000 EU/mL poly - Polymer salt - Salt concentration in the assay tsalt - Type of salt in the assay (NaCl, KNO3, KI and Li2SO4) lps - lipopolysaccharide K - GFP partition coefficient REM - LPS removal REC - GFP recover wo_salt - Assay without salt addition Acknowledgements The authors are grateful for financial support from FAPESP (São Paulo Research Foundation, Brazil) through the following projects: 2005/60159-7; 2007/51978-0; 2014/16424-7; and 2014/19793-3. The authors also acknowledge the support from CAPES (Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, Brazil) through the process #0366/09-9 and CNPq (Conselho Nacional de Desenvolvimento Científico e Tecnológico, Brazil). Consider citing our work.  1. Work in progress...

opencc-by-4.0Mar 2018View details →

zenodo40/100

Data - Effect of electrolytes as adjuvants in GFP and LPS partitioning on aqueous two-phase systems: 2. Nonionic micellar systems

Overview The production of recombinant biopharmaceuticals is highly dependent of a proper choice of the downstream processing stages. Particularly, the purification that must ensure that all the endotoxins (lipopolysaccharide - LPS) are efficiently removed from the final product. This dataset contains the raw data and statistical analysis for the research entitled - "Effect of electrolytes as adjuvants in GFP and LPS partitioning on aqueous two-phase systems: 2. Nonionic micellar systems".  Info ANOVA_Turkey_Sub.R <- code for ANOVA analysis in R statistic 3.3.3     glm.R <- code for GLM analysis in R statistic 3.3.3 K&REC_ORG_ANOVA.csv  <- File with raw values organized in a spreadsheet of GFP partition coefficient (K) and recover (REC) for ANOVA analysis K_ORG_ANOVA.docx <-  File with ANOVA result of partition coefficient (K) for GFP REC_ORG_ANOVA.docx  <- File with ANOVA result of partition coefficient (REC) for GFP REM_LPS_ORG_ANOVA.csv  <- File with raw values organized in a spreadsheet of LPS removal for ANOVA analysis REM_LPS_ORG_ANOVA.docx  <- File with ANOVA result of removal of LPS Stability__ORG_ANOVA.csv <- File with raw values organized in a spreadsheet of GFP stability for ANOVA analysis Stability__ORG_ANOVA.docx  <- File with ANOVA result of GFP stability K_ORG_glm_005.csv  <- File with raw values organized in a spreadsheet of GFP partition coefficient (K) for GLM analysis in 0.05M salt assays     K_ORG_glm_005.doc <- File with GLM analysis of GFP partition coefficient (K) in 0.05M salt assays   K_ORG_glm_005_QQ.png <- Residual quantile plot of GLM analysis for partition coefficient (K) in 0.05M salt assays   K_ORG_glm_025.csv  <- File with raw values organized in a spreadsheet of GFP partition coefficient (K) for GLM analysis in 0.25M salt assays     K_ORG_glm_025.doc <- File with GLM analysis of GFP partition coefficient (K) in 0.25M salt assays   K_ORG_glm_025_QQ.png <- Residual quantile plot of GLM analysis for partition coefficient (K) in 0.25M salt assays   REC_ORG_glm_005.csv <- File with raw values organized in a spreadsheet of GFP recover (REC) for GLM analysis in 0.05M salt assays REC_ORG_glm_005.doc <-  File with GLM analysis of GFP recover (REC) in 0.05M salt assays     REC_ORG_glm_005_QQ.png <- Residual quantile plot of GLM analysis of GFP recover (REC) in 0.05M salt assays    REC_ORG_glm_025.csv <- File with raw values organized in a spreadsheet of GFP recover (REC) for GLM analysis in 0.25M salt assays REC_ORG_glm_025.doc <-  File with GLM analysis of GFP recover (REC) in 0.25M salt assays     REC_ORG_glm_025_QQ.png <- Residual quantile plot of GLM analysis of GFP recover (REC) in 0.25M salt assays    REM_ORG_glm_005.csv <- File with raw values organized in a spreadsheet of LPS removal (REM) for GLM analysis in 0.05M salt assays REM_ORG_glm_005.doc <-  File with GLM analysis of LPS removal (REM) in 0.05M salt assays   REM_ORG_glm_005_QQ.png <-  Residual quantile plot of GLM analysis of LPS removal (REM) in 0.25M salt assays REM_ORG_glm_025.csv <- File with raw values organized in a spreadsheet of LPS removal (REM) for GLM analysis in 0.25M salt assays REM_ORG_glm_025.doc <-  File with GLM analysis of LPS removal (REM) in 0.25M salt assays  REM_ORG_glm_025_QQ.png <-  Residual quantile plot of GLM analysis of LPS removal (REM) in 0.25M salt assays   Annotation 12/12 - Concentration of 12% of each polymer PEG/NaPA 16/16 - Concentration of 16% of each polymer PEG/NaPA P/N -  PEG/NaPA 10e4, 10e5, 10e6 - Concentration of LPS in scientific notation - 10000, 100000, 100000 EU/mL poly - Polymer salt - Salt concentration in the assay tsalt - Type of salt in the assay (NaCl, KNO3, KI and Li2SO4) lps - lipopolysaccharide K - GFP partition coefficient REM - LPS removal REC - GFP recover wo_salt - Assay without salt addition Acknowledgements The authors are grateful for financial support from FAPESP (São Paulo Research Foundation, Brazil) through the following projects: 2005/60159-7; 2007/51978-0; 2014/16424-7; and 2014/19793-3. The authors also acknowledge the support from CAPES (Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, Brazil) through the process #0366/09-9 and CNPq (Conselho Nacional de Desenvolvimento Científico e Tecnológico, Brazil). Consider citing our work.  1. Work in progress...

opencc-by-4.0Apr 2018View details →

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Partitioned Image Data for Machine Learning Analysis of Molecular Biology Figures

Corpus Composition This data collection provides four types of hand-curated images from open access research articles images. The types are: <ol> <li>chart (n=811): data displays such as bar charts, scatterplots, line graphs, etc.</li> <li>diagram (n=816): any general conceptual diagram</li> <li>gel (n=1182): the output of electrophoresis experiments in Northern, Western, or Southern Blot experiments. </li> <li>histology (n=3458): microscope images of tissue with histological staining</li> </ol> The images are simply organized in subdirectories as individual files. File names are based on PubMed Id and Figure number.

opencc-by-4.0Jul 2018View details →

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Mechanical data in support of "Permeability Partitioning through the Brittle-to-Ductile Transition and its Implications for Supercritical Geothermal Reservoirs"

This folder contains 4 files with the nechanicakl data produced during the study titled "Mechanical data in support of "Permeability Partitioning through the Brittle-to-Ductile Transition and its Implications for Supercritical Geothermal Reservoirs". Each file correspond to an experiment ran at a different temperature: LG200C.txt: Lanhelin Granite, T = 200C, strain rate 10-6, Initial length = 42.32 mm LG400C.txt: Lanhelin Granite, T = 400C, strain rate 10-6, Initial length = 41.68 mm LG600C.txt: Lanhelin Granite, T = 600C, strain rate 10-6, Initial length = 41.78 mm LG800C.txt: Lanhelin Granite, T = 800C, strain rate 10-6, Initial length = 41.77 mm All data files contain the following columns: time (s), confining pressure (bar), displacement (mm), vertical load (kN), temperature (C), upstream pore pressure (bar), downstream porepressure (bar).

opencc-by-4.0Aug 2024View details →

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Data Related to Osorio-Forero, Foustoukos, Cardis et al., "Noradrenergic locus coeruleus activity functionally partitions NREMS to gatekeep the NREM-REM cycle"

This Zenodo Upload contains the Transparent Data Files for an updated version of the manuscript currently published in Nature Neuroscience and entitled  'Infraslow noradrenergic locus coeruleus activity fluctuations control are gatekeepers of the NREM–REM sleep cycle'   published by the authors as indicated in the author list.

opencc-by-4.0Nov 2024View details →

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Data from: Partitioning variance in population growth for models with environmental and demographic stochasticity

<ol> <li>How demographic factors lead to variation or change in growth rates can be investigated using life table response experiments (LTRE) based on structured population models. Traditionally, LTREs focused on decomposing the asymptotic growth rate, but more recently decompositions of annual 'realized' growth rates have gained in popularity.</li> <li>Realized LTREs have been used particularly to understand how variation in vital rates translates into variation in growth for populations under long-term study. For these, complete population models may be constructed by combining data in an integrated population model (IPM). IPMs are also used to investigate how temporal variation in environmental drivers affect vital rates. Such investigations have usually come down to estimating covariate coefficients for the effects of environmental variables on vital rates, but formal ways of assessing how they lead to variation in growth rates have been lacking. </li> <li>We extend realized LTREs in two ways. First, we further partition the contributions from vital rates into contributions from temporally varying factors that affect them. The decomposition allows us to compare the resultant effect on the growth rate of different environmental factors that may each act via multiple vital rates. Second, we show how realized growth rates can be decomposed into separate components from environmental and demographic stochasticity. The latter is typically omitted in LTRE analyses.</li> <li>We illustrate how to use the approach in an IPM for data from a 26-year study on northern wheatears (Oenanthe oenanthe), a migratory passerine bird breeding in an agricultural landscape. For this population, consisting of around 50–120 breeding pairs per year, we partition variation in realized growth rates into environmental contributions from temperature, rainfall, population density, and unexplained random variation via multiple vital rates, and from demographic stochasticity.</li> <li>The case study suggests that variation in first-year survival via the random component, and adult survival via temperature are two main factors behind environmental variation in growth rates. More than half of the variation in growth rates is suggested to come from demographic stochasticity, demonstrating the importance of this factor for populations of moderate size.</li> </ol>

opencc-zeroJul 2023View details →

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