Journal articles: 'Resource partitioning'

1

Ferrant, Coline. "Resource Partitioning Theory." Administración y Organizaciones 24, no. 46 (August 5, 2021): 107–15. http://dx.doi.org/10.24275/uam/xoc/dcsh/rayo/2021v24n46/ferrant.

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Walter, G. H. "What is resource partitioning?" Journal of Theoretical Biology 150, no. 2 (May 1991): 137–43. http://dx.doi.org/10.1016/s0022-5193(05)80327-3.

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Hertz, P. E. "Evaluating thermal resource partitioning." Oecologia 90, no. 1 (April 1992): 127–36. http://dx.doi.org/10.1007/bf00317818.

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Liu, Huiqun, Kai Zhu, and D. F. Wong. "FPGA Partitioning with Complex Resource Constraints." VLSI Design 11, no. 3 (January 1, 2000): 219–35. http://dx.doi.org/10.1155/2000/12198.

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In this paper, we present an algorithm for circuit partitioning with complex resource constraints in large FPGAs. Traditional partitioning methods estimate the capacity of an FPGA device by counting the number of logic blocks, however this is not accurate with the increasing diverse resource types in the new FPGA architectures. We first propose a network flow based method to optimally check whether a circuit or a subcircuit is feasible for a set of available heterogeneous resources. Then the feasibility checking procedure is integrated in the FM-based algorithm for circuit partitioning. Incremental flow technique is employed for efficient implementation. Experimental results on the MCNC benchmark circuits show that our partitioning algorithm not only yields good results, but also is efficient. Our algorithm for partitioning with complex resource constraints is applicable for both multiple FPGA designs (e.g., logic emulation systems) and partitioning-based placement algorithms for a single large hierarchical FPGA (e.g., Actel's ES6500 FPGA family).

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Yang, Maolin, Wen-Hung Huang, and Jian-Jia Chen. "Resource-Oriented Partitioning for Multiprocessor Systems with Shared Resources." IEEE Transactions on Computers 68, no. 6 (June 1, 2019): 882–98. http://dx.doi.org/10.1109/tc.2018.2889985.

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Okasha, Ahmed. "Resource Partitioning and Hospital Specialization." Journal of Health Management 21, no. 3 (September 2019): 337–50. http://dx.doi.org/10.1177/0972063419868543.

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Background: Organizational scholars have been debating over specialism and generalism, and which environment is better for specialists and for generalists. Methods: This study relies heavily on the work of Okasha (Okasha, 1995, Modeling the determinants of hospital services differentiation and specialization (Dissertation). Virginia Commonwealth University, Richmond) and enhances it with available current literature on the topic. Okasha’s ( Modeling the determinants of hospital services differentiation and specialization (Dissertation). Virginia Commonwealth University, Richmond) study tested the use of resource partitioning theory to explain the conversion of generalists to specialists under competitive environments. Results: The anticipated effect of buyers of care on hospital specialization was evident. Recent work on specialization (Eastaugh, 2014, Journal of Healthcare Finance) confirmed the trend. Conclusion: Buyer-related factors and organizational factors were the most important predictors of the positive change in hospital specialization between 1987 and 1993. High competition, the increased pressure from buyers of care, and organizational factors were the most important predictors of the positive change in the hospital specialization measures during that time period.

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Chandra, A., and K. Chakrabarty. "Test resource partitioning for SOCs." IEEE Design & Test of Computers 18, no. 5 (2001): 80–91. http://dx.doi.org/10.1109/54.953275.

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Carroll, Glenn R., Stanislav D. Dobrev, and Anand Swaminathan. "Organizational processes of resource partitioning." Research in Organizational Behavior 24 (January 2002): 1–40. http://dx.doi.org/10.1016/s0191-3085(02)24002-2.

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Malescio, G. "Broad distributions from resource partitioning." Physica A: Statistical Mechanics and its Applications 383, no. 2 (September 2007): 643–50. http://dx.doi.org/10.1016/j.physa.2007.05.016.

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10

Piet, G. J., J. S. Pet, WAHP Guruge, J. Vijverberg, and WLT Van Densen. "Resource partitioning along three niche dimensions in a size-structured tropical fish assemblage." Canadian Journal of Fisheries and Aquatic Sciences 56, no. 7 (July 1, 1999): 1241–54. http://dx.doi.org/10.1139/f99-033.

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In Tissawewa, a tropical reservoir, the size-specific resource use of the 10 most important fish species was determined along three dimensions: trophic, spatial, and temporal. During this study, a drought occurred distinguishing two periods before and after the drought that differed markedly in availability of resources and fish biomass. In this study, differences in resource use between the two periods are presented together with their consequence on the partitioning of resources. A different approach is introduced into the calculation of niche breadth and niche overlap incorporating size-specific differences in resource use and interactions between resource dimensions. Comparison with conventional measures of niche breadth and niche overlap shows that conventional measures often misrepresent interactions between species. Condition and biomass were used as indicators of a species' fitness, and it is shown that fitness of most species is governed by the availability of resources and partitioning of these resources is an important mechanism allowing potential competitors to coexist. Resource partitioning along the trophic dimension was more important than along the spatial or temporal dimension.

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Toft, Catherine A. "Resource Partitioning in Amphibians and Reptiles." Copeia 1985, no. 1 (February 11, 1985): 1. http://dx.doi.org/10.2307/1444785.

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12

Pringle, Robert M. "Ecology: A revolution in resource partitioning." Current Biology 31, no. 22 (November 2021): R1474—R1476. http://dx.doi.org/10.1016/j.cub.2021.10.001.

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13

Gupta, A., and D. Ferrari. "Resource partitioning for real-time communication." IEEE/ACM Transactions on Networking 3, no. 5 (1995): 501–8. http://dx.doi.org/10.1109/90.469956.

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Belant, Jerrold L., Knut Kielland, Erich H. Follmann, and Layne G. Adams. "INTERSPECIFIC RESOURCE PARTITIONING IN SYMPATRIC URSIDS." Ecological Applications 16, no. 6 (December 2006): 2333–43. http://dx.doi.org/10.1890/1051-0761(2006)016[2333:irpisu]2.0.co;2.

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15

Liu, Min. "New Form Emergence and Resource Partitioning." Academy of Management Proceedings 2015, no. 1 (January 2015): 12211. http://dx.doi.org/10.5465/ambpp.2015.12211abstract.

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Browning, Nicole E., Victor G. Cockcroft, and Graham A. J. Worthy. "Resource partitioning among South African delphinids." Journal of Experimental Marine Biology and Ecology 457 (August 2014): 15–21. http://dx.doi.org/10.1016/j.jembe.2014.03.016.

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17

Kingston, T., G. Jones, A. Zubaid, and T. H. Kunz. "Resource partitioning in rhinolophoid bats revisited." Oecologia 124, no. 3 (August 23, 2000): 332–42. http://dx.doi.org/10.1007/pl00008866.

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18

Andersen, Johan. "Resource Partitioning and Interspecific Interactions among Riparian Bembidion species (Coleoptera: Carabidae)." Entomologia Generalis 13, no. 1-2 (May 1, 1988): 47–60. http://dx.doi.org/10.1127/entom.gen/13/1988/47.

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19

Mahendiran, Mylswamy. "Coexistence of three sympatric cormorants ( Phalacrocorax spp.); partitioning of time as an ecological resource." Royal Society Open Science 3, no. 5 (May 2016): 160175. http://dx.doi.org/10.1098/rsos.160175.

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Resource partitioning is well known along food and habitat for reducing competition among sympatric species, yet a study on temporal partitioning as a viable basis for reducing resource competition is not empirically investigated. Here, I attempt to identify the mechanism of temporal partitioning by intra- and interspecific diving analyses of three sympatric cormorant species at different freshwater wetlands around the Delhi region. Diving results indicated that cormorants opted for a shallow diving; consequently, they did not face any physiological stress. Moreover, diving durations were linked with seasons, foraging time and foraging habitats. Intraspecific comparison suggested that cormorants spent a longer time underwater in early hours of the day. Therefore, time spent for dive was higher in the forenoon than late afternoon, and the interspecific analysis also yielded a similar result. When Phalacrocorax niger and Phalacrocorax fuscicollis shared the same foraging habitat, they tended to differ in their foraging time (forenoon/afternoon). However, when P. niger and Phalacrocorax carbo shared the same foraging time, they tended to use different foraging habitats (lentic/lotic) leading to a mechanism of resource partitioning. Thus, sympatric cormorants effectively use time as a resource to exploit the food resources and successful coexistence.

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20

Walters, Michael B., John L. Willis, and Kurt W. Gottschalk. "Seedling growth responses to light and mineral N form are predicted by species ecologies and can help explain tree diversity." Canadian Journal of Forest Research 44, no. 11 (November 2014): 1356–68. http://dx.doi.org/10.1139/cjfr-2013-0400.

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Tree species distributions and diversity could be explained by rank changes in performance over multiple spatiotemporal resource gradients, i.e., resource partitioning. For 14 species planted in 45 harvest gap and closed canopy locations in a mesic northern hardwood forest community, Michigan, USA, we asked the following questions: (i) are species growth responses to light, nitrogen (N), or N form (ammonium vs. nitrate) related to their ecological distributions and phylogenies? and (ii) is there evidence of growth-based resource partitioning over measured resource gradients? Growth responses to the N form were consistent with both differences in uptake energy requirements between N forms and their availability through succession and across fertility gradients; height growth was negatively related to the species shade-tolerance score, especially in high light, i.e., shade-intolerant species responded to soil nitrate-N and shade-tolerant species responded to ammonium-N; fertile soil associated species responded to nitrate-N and infertile soil associated species to ammonium-N; and gymnosperms responded to ammonium-N and angiosperm responses varied. Modeled growth responses to resources showed only modest evidence for rank changes over resource gradients, with N contributing less to rank changes than light. Thus, growth responses to resources were accurately predicted by species ecology and (or) phylogeny; however, there was only modest support for the notion that growth-based resource partitioning underlies community-scale diversity in a northern hardwood forest.

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21

Shen, Yongming, Michael Ferdman, and Peter Milder. "Maximizing CNN Accelerator Efficiency Through Resource Partitioning." ACM SIGARCH Computer Architecture News 45, no. 2 (September 14, 2017): 535–47. http://dx.doi.org/10.1145/3140659.3080221.

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22

Dobrev, Stanislav D., Tai‐Young Kim, and Michael T. Hannan. "Dynamics of Niche Width and Resource Partitioning." American Journal of Sociology 106, no. 5 (March 2001): 1299–337. http://dx.doi.org/10.1086/320821.

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23

Northfield, Tobin D., Gretchen B. Snyder, Anthony R. Ives, and William E. Snyder. "Niche saturation reveals resource partitioning among consumers." Ecology Letters 13, no. 3 (March 2010): 338–48. http://dx.doi.org/10.1111/j.1461-0248.2009.01428.x.

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24

PAPPANTONIOU, ANTONIOS, JOSEPH W. RACHLIN, and BARBARA E. WARKENTINE. "Resource Partitioning in a Stream Fish Community." Annals of the New York Academy of Sciences 529, no. 1 Fourth Colloq (June 1988): 152–56. http://dx.doi.org/10.1111/j.1749-6632.1988.tb51446.x.

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25

Turner, Benjamin L. "Resource partitioning for soil phosphorus: a hypothesis." Journal of Ecology 96, no. 4 (July 2008): 698–702. http://dx.doi.org/10.1111/j.1365-2745.2008.01384.x.

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26

Kronfeld-Schor, Noga, and Tamar Dayan. "Partitioning of Time as an Ecological Resource." Annual Review of Ecology, Evolution, and Systematics 34, no. 1 (November 2003): 153–81. http://dx.doi.org/10.1146/annurev.ecolsys.34.011802.132435.

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27

Boone, Christophe, Roger Meuwissen, and Arjen van Witteloostuijn. "Resource-partitioning processes in the audit industry." Strategic Organization 7, no. 3 (August 2009): 307–38. http://dx.doi.org/10.1177/1476127009343265.

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28

Waller, Deborah A. "Termite Resource Partitioning Related to Log Diameter." Northeastern Naturalist 14, no. 1 (March 2007): 139–44. http://dx.doi.org/10.1656/1092-6194(2007)14[139:trprtl]2.0.co;2.

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29

Emrich, Matthew A., Elizabeth L. Clare, William O. C. Symondson, Susan E. Koenig, and Melville Brock Fenton. "Resource partitioning by insectivorous bats in Jamaica." Molecular Ecology 23, no. 15 (October 25, 2013): 3648–56. http://dx.doi.org/10.1111/mec.12504.

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30

McDonald, Robbie A. "Resource partitioning among British and Irish mustelids." Journal of Animal Ecology 71, no. 2 (March 2002): 185–200. http://dx.doi.org/10.1046/j.1365-2656.2002.00588.x.

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31

Waddington, D. G., and D. Hutchison. "Resource partitioning in general purpose operating systems." ACM SIGOPS Operating Systems Review 33, no. 4 (October 1999): 52–74. http://dx.doi.org/10.1145/334598.334609.

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32

Capula, Massimo, and Luca Luiselli. "Resource partitioning in a Mediterranean lizard community." Bolletino di zoologia 61, no. 2 (January 1994): 173–77. http://dx.doi.org/10.1080/11250009409355879.

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33

Volckaert, Bruno, Pieter Thysebaert, Marc De Leenheer, Filip De Turck, Bart Dhoedt, and Piet Demeester. "Flexible Grid service management through resource partitioning." Journal of Supercomputing 38, no. 3 (December 2006): 279–305. http://dx.doi.org/10.1007/s11227-006-8752-9.

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34

Dixon, A. F. G. "Body size and resource partitioning in ladybirds." Population Ecology 49, no. 1 (November 14, 2006): 45–50. http://dx.doi.org/10.1007/s10144-006-0019-z.

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35

Rebout, Nancy, Christine Desportes, and Bernard Thierry. "Resource partitioning in tolerant and intolerant macaques." Aggressive Behavior 43, no. 5 (April 27, 2017): 513–20. http://dx.doi.org/10.1002/ab.21709.

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36

Xi, Xinqiang, Yangheshan Yang, Yonghua Yang, Michal Segoli, and Shucun Sun. "Plant-mediated resource partitioning by coexisting parasitoids." Ecology 98, no. 6 (May 15, 2017): 1660–70. http://dx.doi.org/10.1002/ecy.1834.

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37

Hageman, Amber N., Milan O. Urban, and Elizabeth Van Volkenburgh. "Sensitivity of leaflet growth rate to drought predicts yield in common bean (Phaseolus vulgaris)." Functional Plant Biology 47, no. 9 (2020): 792. http://dx.doi.org/10.1071/fp19332.

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Although drought limits yield by decreasing photosynthesis and therefore biomass accumulation, biomass is not the strongest predictor of yield under drought in common beans (Phaseolus vulgaris L.). Instead, resource partitioning from pod walls into seeds is a stronger correlate. Our aim was to determine whether growth rates of developing leaflets and pods, as independent indicators of sink strength, predict resource partitioning into seeds. Using 20 field-grown genotypes, we paired biomass, yield, and resource partitioning data with leaflet and pod growth rates under well-watered and droughted conditions. We hypothesised that genotypes with faster growing leaflets and pods under drought would fill seeds better. However, we found that leaflet and pod growth rates did not predict partitioning to seeds; rather, sensitivity of leaflet growth rate to drought was a good predictor of yield reduction. Further, plants with rapidly growing leaves under well-watered conditions were most vulnerable to decreases in leaflet growth rate under drought. This suggests that lines that inherited a conservative growth strategy were better able to maintain yield by allocating resources to seeds. Our findings indicate that inherent sensitivity of leaflet growth rate to drought may be used as a predictor of partitioning and yield in common beans.

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38

Chen, Ze-Wei, Hang Lei, Mao-Lin Yang, Yong Liao, and Jia-Li Yu. "Improved Task and Resource Partitioning Under the Resource-Oriented Partitioned Scheduling." Journal of Computer Science and Technology 34, no. 4 (July 2019): 839–53. http://dx.doi.org/10.1007/s11390-019-1945-5.

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39

Koperski, Pawel. "Feeding in epiphytic, carnivorous insects: resource partitioning and the avoidance of intraguild predation." Fundamental and Applied Limnology 142, no. 4 (July 30, 1998): 467–83. http://dx.doi.org/10.1127/archiv-hydrobiol/142/1998/467.

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40

Zanne, Amy E., Steven S. Lower, Zoe G. Cardon, and Colin M. Orians. "15N partitioning in tomato: vascular constraints versus tissue demand." Functional Plant Biology 33, no. 5 (2006): 457. http://dx.doi.org/10.1071/fp05299.

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Allocation of root-derived resources is influenced by tissue demand; however, vascular pathways mediate resource flow from roots to shoots. In vascularly constrained plants (i.e. sectored plants), effects of vascular connections likely limit homogenous resource delivery, especially when environmental resource distribution is patchy. Here, we quantify relative roles of vascular connections, demands by different leaves (i.e. by leaf age and size), and molecule size of transported N compounds (effective sectoriality: nitrate v. ammonium) on allocation of 15N in the sectored tomato (Solanum lycopersicum L.). Vascular connections were the strongest predictor of both accumulation (amount per leaf; P<0.0001) and δ (estimate of concentration; P<0.0001) 15N values in mature leaves, but young expanding leaves did not show such dramatically sectored uptake (accumulation: P=0.0685; δ: P=0.0455), suggesting that sectoriality is less strong in young expanding tissue, especially in the youngest leaf. In patchy environments sectoriality, then, should have large consequences for the ability of a plant to allocate resources in mature tissue; however, young leaves do not appear to experience such strong vascular constraints when building new tissue.

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41

Davis, Naomi E., Ian R. Gordon, and Graeme Coulson. "The influence of evolutionary history and body size on partitioning of habitat resources by mammalian herbivores in south-eastern Australia." Australian Journal of Zoology 65, no. 4 (2017): 226. http://dx.doi.org/10.1071/zo16075.

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Habitat use is the most common dimension along which sympatric species partition resources to reduce competition. We conducted faecal pellet counts at Wilsons Promontory National Park, Victoria, to examine habitat use by an assemblage of mammalian herbivores with disparate evolutionary histories and varying body size: introduced European rabbit (Oryctolagus cuniculus) and hog deer (Axis porcinus), and native eastern grey kangaroo (Macropus giganteus), swamp wallaby (Wallabia bicolor) and common wombat (Vombatus ursinus). Overlap in habitat use was low between four pairs of species, suggesting spatial partitioning of resources to reduce the potential for interspecific competition. More generally, however, overlap in habitat use was high, particularly between native and introduced grazers. These results indicate the potential for competition if resources were limiting and suggest that assemblages of species with independent evolutionary histories have inherently less resource partitioning to facilitate coexistence than assemblages of species with common evolutionary histories. Despite evidence of high overlap in habitat use between native and introduced species at a broad scale, and variation in the competitive ability of species, coexistence was likely facilitated by niche complementarity, including temporal and fine-scale partitioning of spatial resources. There was no relationship between body size and the diversity of habitats used. In contemporary assemblages of native and introduced species, evolutionary history is likely to have a strong influence on resource partitioning.

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42

Kappes, MA, H. Weimerskirch, D. Pinaud, and M. Le Corre. "Variability of resource partitioning in sympatric tropical boobies." Marine Ecology Progress Series 441 (November 15, 2011): 281–94. http://dx.doi.org/10.3354/meps09376.

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43

Duncan, P., and R. J. Putman. "Competition and Resource Partitioning in Temperature Ungulate Assemblies." Journal of Applied Ecology 34, no. 6 (December 1997): 1510. http://dx.doi.org/10.2307/2405268.

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44

Gordon, Iain, and R. J. Putman. "Competition and Resource Partitioning In Temperate Ungulate Assemblies." Journal of Animal Ecology 66, no. 4 (July 1997): 603. http://dx.doi.org/10.2307/5954.

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45

Van Snik Gray, Ellen, Jeff M. Boltz, Karen A. Kellogg, and Jay R. Stauffer. "Food Resource Partitioning by Nine Sympatric Darter Species." Transactions of the American Fisheries Society 126, no. 5 (September 1997): 822–40. http://dx.doi.org/10.1577/1548-8659(1997)126<0822:frpbns>2.3.co;2.

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46

Mcdonald, R. A. "Resource partitioning in the diet of British mustelids." Mammal Review 30, no. 3-4 (December 2000): 229. http://dx.doi.org/10.1046/j.1365-2907.2000.0075f.x.

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47

Adams, R. A., and K. M. Thibault. "Temporal resource partitioning by bats at water holes." Journal of Zoology 270, no. 3 (November 2006): 466–72. http://dx.doi.org/10.1111/j.1469-7998.2006.00152.x.

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48

McCullough, Dale R., David H. Hirth, and Stephen J. Newhouse. "Resource Partitioning between Sexes in White-Tailed Deer." Journal of Wildlife Management 53, no. 2 (April 1989): 277. http://dx.doi.org/10.2307/3801123.

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49

Aldridge, H. D. J. N., and I. L. Rautenbach. "Morphology, Echolocation and Resource Partitioning in Insectivorous Bats." Journal of Animal Ecology 56, no. 3 (October 1987): 763. http://dx.doi.org/10.2307/4947.

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50

Würtenberger, A., P. Rosinger, B. M. Al-Hashimi, and K. Chakrabarty. "Cost model driven test resource partitioning for SoCs." Electronics Letters 42, no. 16 (2006): 915. http://dx.doi.org/10.1049/el:20061556.

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Journal articles on the topic 'Resource partitioning'

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