A Test of Foraging Models Using Dietary Diversity Indices for the Lomako Forest Bonobos

2021 ◽  
Vol 92 (4) ◽  
pp. 211-226
Author(s):  
Alexana J. Hickmott ◽  
Michel T. Waller ◽  
Monica L. Wakefield ◽  
Nicholas Malone ◽  
Colin M. Brand ◽  
...  

Optimal diet and functional response models are used to understand the evolution of primate foraging strategies. The predictions of these models can be tested by examining the geographic and seasonal variation in dietary diversity. Dietary diversity is a useful tool that allows dietary comparisons across differing sampling locations and time periods. Bonobos (<i>Pan paniscus</i>) are considered primarily frugivorous and consume fruits, leaves, insects, vertebrates, terrestrial herbaceous vegetation, and flowers. Frugivores, like bonobos, are valuable for examining dietary diversity and testing foraging models because they eat a variety of species and are subject to seasonal shifts in fruit availability. Frugivorous primate species thus allow for tests of how variation in dietary diversity is correlated with variation in ecological factors. We investigated measures of dietary diversity in bonobos at two research camps across field seasons within the same protected area (N’dele and Iyema) in Lomako Forest, Democratic Republic of the Congo. We compared the results of behavioral observation (1984/1985, 1991, 1995, 2014, and 2017) and fecal washing analysis (2007 and 2009) between seasons and study period using three diversity indices (Shannon’s, Simpson’s, and SW evenness). The average yearly dietary diversity indices at N’dele were Shannon’s <i>Hʹ</i> = 2.04, Simpson’s D = 0.82, and SW evenness = 0.88 while at Iyema, the indices were Shannon’s <i>Hʹ</i> = 2.02, Simpson’s D = 0.82, and SW evenness = 0.88. Behavioral observation data sets yielded significantly higher dietary diversity indices than fecal washing data sets. We found that food item (fruit, leaf, and flower) consumption was not associated with seasonal food availability for the 2017 behavioral observation data set. Shannon’s index was lower during periods when fewer bonobo dietary items were available to consume and higher when fruit was abundant. Finally, we found that optimal diet models best-explained patterns of seasonal food availability and dietary diversity. Dietary diversity is an essential factor to consider when understanding primate diets and can be a tool in understanding variation in primate diets, particularly among frugivores. Dietary diversity varies across populations of the same species and across time, and it is critical in establishing a complete understanding of how primate diets change over time.

2016 ◽  
Vol 53 (4) ◽  
pp. 405 ◽  
Author(s):  
D. J. Nithya ◽  
R. V. Bhavani

Dietary Diversity, with foods from all food groups is necessary to meet the requirements for essential nutrients which lead to good health. This study examines whether different dietary diversity indices have relationship with the nutritional status of school children aged 6 to 12 years, in two different regions of India: Wardha district, Maharashtra and Koraput district, Odisha. Dietary diversity was calculated using three methods: Individual food scores calculated using 24 hour diet recall (FS<sub>24hr</sub>) data; household dietary diversity using Berry's index (DDI) and food scores calculated using food frequency data (FS<sub>FFQ</sub>). Anthropometric indices were used to assess the nutritional status of school aged children. The Nutrient Adequacy Ratio (NAR) and the Mean Adequacy Ratio (MAR) were calculated as indicators of nutrient adequacy. The relationship between NAR, MAR and three different diversity indices, dietary diversity and anthropometric indices were analyzed. Overall, 38% of 6 to 12 year school aged children were found to be undernourished. The NAR was &lt;70% for all nutrients except protein, energy, thiamine and niacin and MAR was found to be &lt;70% of requirement with mean of 60.5% in both locations. The dietary diversity was found to be relatively better in Wardha when compared with Koraput. The mean diversity indices in both the locations were FS<sub>24hr</sub> 7.56, DDI 89 and FS<sub>FFQ</sub> 62.9. Overall most of the nutrient adequacy and mean adequacy were correlated with all three dietary diversity indices when both locations were studied together. However all three dietary diversity indices failed to show any relationship with nutritional status of school children aged 6-12 years from both locations taken together.


Author(s):  
Fatai Abiola Sowunmi ◽  
Funmi Lydia Adeduntan

The study examined the impact of rural-urban migration on the food consumption pattern of farming households. The study revealed that 73.8% of the households had migrants, while 80.2% of the migrants were male. The highest level of education of most of the migrants was secondary school (71.4%). The study showed that the major reason (63.3%) for migration was for job. The average remittance sent per year was ₦108,119.14. The study revealed that household expenditure on carbohydrate food group accounted for 54.4% of the total households' expenditure on food. The average dietary diversity indices for the migrant (0.345) and non-migrant (0.346) households were low. The study revealed that migration (short and long term) positively influenced per capita food expenditure of respondent. Despite the remittance from some of the migrants, the need to develop the rural areas in terms of provision of basic infrastructures by government is imperative in order to reduce rural-urban migration.


2020 ◽  
Vol 13 (5) ◽  
pp. 2169-2184
Author(s):  
Li Pan ◽  
HyunCheol Kim ◽  
Pius Lee ◽  
Rick Saylor ◽  
YouHua Tang ◽  
...  

Abstract. Multiple observation data sets – Interagency Monitoring of Protected Visual Environments (IMPROVE) network data, the Automated Smoke Detection and Tracking Algorithm (ASDTA), Hazard Mapping System (HMS) smoke plume shapefiles and aircraft acetonitrile (CH3CN) measurements from the NOAA Southeast Nexus (SENEX) field campaign – are used to evaluate the HMS–BlueSky–SMOKE (Sparse Matrix Operator Kernel Emission)–CMAQ (Community Multi-scale Air Quality Model) fire emissions and smoke plume prediction system. A similar configuration is used in the US National Air Quality Forecasting Capability (NAQFC). The system was found to capture most of the observed fire signals. Usage of HMS-detected fire hotspots and smoke plume information was valuable for deriving both fire emissions and forecast evaluation. This study also identified that the operational NAQFC did not include fire contributions through lateral boundary conditions, resulting in significant simulation uncertainties. In this study we focused both on system evaluation and evaluation methods. We discussed how to use observational data correctly to retrieve fire signals and synergistically use multiple data sets. We also addressed the limitations of each of the observation data sets and evaluation methods.


2019 ◽  
Vol 22 (11) ◽  
pp. 2110-2119 ◽  
Author(s):  
Ramya Ambikapathi ◽  
Nilupa S Gunaratna ◽  
Isabel Madzorera ◽  
Simone Passarelli ◽  
Chelsey R Canavan ◽  
...  

AbstractObjectiveIn Ethiopia, women’s dietary diversity is low, primarily due to poor food availability and access, both at home and market level. The present study aimed to describe market access using a new definition called market food diversity (MFD) and estimate the impact of MFD, crop and livestock diversity on dietary diversity among women enrolled in the Agriculture to Nutrition (ATONU) trial.DesignBaseline cross-sectional data collected from November 2016 to January 2017 were used for the analysis. Availability of foods in markets was assessed at the village level and categorized into nine food groups similar to the dietary diversity index for women. Bivariate and multivariate mixed-effects regression analyses were conducted, adjusted for clustering at the village level.SettingChicken-producing farmers in rural Ethiopia.ParticipantsWomen (n 2117) aged 15–49 years.ResultsOverall, less than 6 % of women met the minimum dietary diversity (≥5 food groups) and the most commonly consumed food groups were staples and legumes. Median MFD was 4 food groups (interquartile range: 2–8). Multivariate models indicated that women’s dietary diversity differed by livestock diversity, food crop diversity and agroecology, with significant interaction effects between agroecology and MFD.ConclusionsWomen’s dietary diversity is poor in Ethiopia. Local markets are variable in food availability across seasons and agroecological zones. The MFD indicator captures this variability, and women who have access to higher MFD in the highland agroecological zone have better dietary diversity. Thus, MFD has the potential to mitigate the effects of environment on women’s dietary diversity.


1988 ◽  
Vol 32 (17) ◽  
pp. 1183-1187
Author(s):  
J. G. Kreifeldt ◽  
S. H. Levine ◽  
M. C. Chuang

Sensory modalities exhibit a characteristic known as Weber's ratio which remarks that when two stimuli are compared for a difference: (1) there is some minimal nonzero difference which can be differentiated and (2) this minimal difference is a nearly constant proportion of the magnitude of the stimuli. Both of these would, in a typical measurement context, appear to be system defects. We have found through simulation explorations that in fact these are apparently the characteristics required by a system designed to extract an adequate amount of information from an incomplete observation data set according to a new approach to measurement.


2020 ◽  
Vol 496 (1) ◽  
pp. 629-637
Author(s):  
Ce Yu ◽  
Kun Li ◽  
Shanjiang Tang ◽  
Chao Sun ◽  
Bin Ma ◽  
...  

ABSTRACT Time series data of celestial objects are commonly used to study valuable and unexpected objects such as extrasolar planets and supernova in time domain astronomy. Due to the rapid growth of data volume, traditional manual methods are becoming extremely hard and infeasible for continuously analysing accumulated observation data. To meet such demands, we designed and implemented a special tool named AstroCatR that can efficiently and flexibly reconstruct time series data from large-scale astronomical catalogues. AstroCatR can load original catalogue data from Flexible Image Transport System (FITS) files or data bases, match each item to determine which object it belongs to, and finally produce time series data sets. To support the high-performance parallel processing of large-scale data sets, AstroCatR uses the extract-transform-load (ETL) pre-processing module to create sky zone files and balance the workload. The matching module uses the overlapped indexing method and an in-memory reference table to improve accuracy and performance. The output of AstroCatR can be stored in CSV files or be transformed other into formats as needed. Simultaneously, the module-based software architecture ensures the flexibility and scalability of AstroCatR. We evaluated AstroCatR with actual observation data from The three Antarctic Survey Telescopes (AST3). The experiments demonstrate that AstroCatR can efficiently and flexibly reconstruct all time series data by setting relevant parameters and configuration files. Furthermore, the tool is approximately 3× faster than methods using relational data base management systems at matching massive catalogues.


Ocean Science ◽  
2019 ◽  
Vol 15 (3) ◽  
pp. 779-808 ◽  
Author(s):  
Hao Zuo ◽  
Magdalena Alonso Balmaseda ◽  
Steffen Tietsche ◽  
Kristian Mogensen ◽  
Michael Mayer

Abstract. The ECMWF OCEAN5 system is a global ocean and sea-ice ensemble of reanalysis and real-time analysis. This paper gives a full description of the OCEAN5 system, with the focus on upgrades of system components with respect to its predecessors, ORAS4 and ORAP5. An important novelty in OCEAN5 is the ensemble generation strategy that includes perturbation of initial conditions and a generic perturbation scheme for observations and forcing fields. Other upgrades include revisions to the a priori bias correction scheme, observation quality control and assimilation method for sea-level anomalies. The OCEAN5 historical reconstruction of the ocean and sea-ice state is the ORAS5 reanalysis, which includes five ensemble members and covers the period from 1979 onwards. Updated versions of observation data sets are used in ORAS5 production, with special attention devoted to the consistency of sea surface temperature (SST) and sea-ice observations. Assessment of ORAS5 through sensitivity experiments suggests that all system components contribute to an improved fit to observation in reanalyses, with the most prominent contribution from direct assimilation of ocean in situ observations. Results of observing system experiments further suggest that the Argo float is the most influential observation type in our data assimilation system. Assessment of ORAS5 has also been carried out for several key ocean state variables and verified against reference climate data sets from the ESA CCI (European Space Agency Climate Change Initiative) project. With respect to ORAS4, ORAS5 has improved ocean climate state and variability in terms of SST and sea level, mostly due to increased model resolution and updates in assimilated observation data sets. In spite of the improvements, ORAS5 still underestimates the temporal variance of sea level and continues exhibiting large SST biases in the Gulf Stream and its extension regions which are possibly associated with misrepresentation of front positions. Overall, the SST and sea-ice uncertainties estimated using five ORAS5 ensemble members have spatial patterns consistent with those of analysis error. The ensemble spread of sea ice is commensurable with the sea-ice analysis error. On the contrary, the ensemble spread is under-dispersive for SST.


2016 ◽  
Vol 3 (1) ◽  
pp. 67
Author(s):  
Sangeeta Maharjan ◽  
Ram P. Regmi

<p>As part of the ongoing research activities at National Atmospheric Resource and Environmental Research Laboratory (NARERL) to realize high spatial and temporal resolution weather forecasts for Nepal, the Weather Research and Forecasting (WRF) modeling system performance with the National Center for Environmental Protection (NCEP) and National Center for Medium Range Weather Forecast (NCMRWF) initialization global meteorological data sets and the effect of surface observation data assimilation have been examined. The study shows that WRF modeling system reasonably well predicts the diurnal variation of upcoming weather events with both the data sets. The observation data assimilation from entire weather station distributed over the country may lead to the significant improvement in the accuracy and reliability of extended period of forecast. However, upper air observation data assimilation would be necessary to achieve desired precision and reliability of extended weather forecast.</p><p>Journal of Nepal Physical Society Vol.3(1) 2015: 67-72</p>


Author(s):  
SHINJI FUKUDA ◽  
BERNARD DE BAETS

Information on species distributions is of key importance when designing management plans for a target species or ecosystem. This paper illustrates the effects of absence data on fish habitat prediction and habitat preference evaluation using a genetic Takagi-Sugeno fuzzy model. Three independent data sets were prepared from a series of fish habitat surveys conducted in an agricultural canal in Japan. To quantify the effects of absence data, two kinds of abundance data (entire data and presence data) were used for developing a fuzzy habitat preference model (FHPM). As a result, habitat preference curves (HPCs) obtained from presence data resulted in similar HPCs between the three data sets, while those obtained from entire data slightly differed according to the data sets. The higher generalization ability of the FHPMs obtained from presence data supports the usefulness of presence data for better extracting the habitat preference information of a target species from field observation data.


1995 ◽  
Vol 43 (3) ◽  
pp. 189-196 ◽  
Author(s):  
E. Hosoi ◽  
L.R. Rittenhouse ◽  
D.M. Swift ◽  
R.W. Richards

Sign in / Sign up

Export Citation Format

Share Document