Establishment Limitation Reduces Species Recruitment and Species Richness As Soil Resources Rise
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Energy Flow Through Marine Ecosystems: Confronting Transfer Efficiency
TREE 2756 No. of Pages 11 Trends in Ecology & Evolution Review Energy Flow Through Marine Ecosystems: Confronting Transfer Efficiency Tyler D. Eddy ,1,2,*,@ Joey R. Bernhardt ,3,4,5,@ Julia L. Blanchard,6,7 William W.L. Cheung,3 Mathieu Colléter,8 Hubert du Pontavice ,3,9 Elizabeth A. Fulton,6,10 Didier Gascuel ,9,@ Kelly A. Kearney ,11 Colleen M. Petrik ,12 Tilla Roy,13,14 Ryan R. Rykaczewski ,1,15 Rebecca Selden,16 Charles A. Stock ,17 Colette C.C. Wabnitz ,3,18,19 and Reg A. Watson 6,7 Transfer efficiency is the proportion of energy passed between nodes in food webs. Highlights It is an emergent, unitless property that is difficult to measure, and responds Transfer efficiency is a key parameter de- dynamically to environmental and ecosystem changes. Because the consequences scribing ecosystem structure and func- of changes in transfer efficiency compound through ecosystems, slight variations tion and is used to estimate fisheries production; however, it is also one of can have large effects on food availability for top predators. Here, we review the the most uncertain parameters. processes controlling transfer efficiency, approaches to estimate it, and known variations across ocean biomes. Both process-level analysis and observed macro- Questions remain about how habitats, fi scale variations suggest that ecosystem-scale transfer efficiency is highly variable, food resources, shing pressure, spatio- fi temporal scales, as well as temperature, impacted by shing, and will decline with climate change. It is important that we primary production, and other climate more fully resolve the processes controlling transfer efficiency in models to drivers impact transfer efficiency. -
"Species Richness: Small Scale". In: Encyclopedia of Life Sciences (ELS)
Species Richness: Small Advanced article Scale Article Contents . Introduction Rebecca L Brown, Eastern Washington University, Cheney, Washington, USA . Factors that Affect Species Richness . Factors Affected by Species Richness Lee Anne Jacobs, University of North Carolina, Chapel Hill, North Carolina, USA . Conclusion Robert K Peet, University of North Carolina, Chapel Hill, North Carolina, USA doi: 10.1002/9780470015902.a0020488 Species richness, defined as the number of species per unit area, is perhaps the simplest measure of biodiversity. Understanding the factors that affect and are affected by small- scale species richness is fundamental to community ecology. Introduction diversity indices of Simpson and Shannon incorporate species abundances in addition to species richness and are The ability to measure biodiversity is critically important, intended to reflect the likelihood that two individuals taken given the soaring rates of species extinction and human at random are of the same species. However, they tend to alteration of natural habitats. Perhaps the simplest and de-emphasize uncommon species. most frequently used measure of biological diversity is Species richness measures are typically separated into species richness, the number of species per unit area. A vast measures of a, b and g diversity (Whittaker, 1972). a Di- amount of ecological research has been undertaken using versity (also referred to as local or site diversity) is nearly species richness as a measure to understand what affects, synonymous with small-scale species richness; it is meas- and what is affected by, biodiversity. At the small scale, ured at the local scale and consists of a count of species species richness is generally used as a measure of diversity within a relatively homogeneous area. -
The Influence of Species Di7ersity on Ecosystem Producti7ity: How, Where
FORUM is intended for new ideas or new ways of interpreting existing information. It FORUM provides a chance for suggesting hypotheses and for challenging current thinking on FORUM ecological issues. A lighter prose, designed to attract readers, will be permitted. Formal research reports, albeit short, will not be accepted, and all contributions should be concise FORUM with a relatively short list of references. A summary is not required. The influence of species di7ersity on ecosystem producti7ity: how, where, and why? Jason D. Fridley, Dept of Biology, CB 3280, Uni7. of North Carolina, Chapel Hill, NC 27599-3280, USA ([email protected]). The effect of species diversity on ecosystem productivity is cism based upon their experimental methodology controversial, in large part because field experiments investigat- (Huston 1997, Hodgson et al. 1998, Wardle 1999), ing this relationship have been fraught with difficulties. Unfortu- analyses (Aarssen 1997, Huston et al. 2000), and gen- nately, there are few guidelines to aid researchers who must overcome these difficulties and determine whether global species eral conclusions (Grime 1998, Wardle et al. 2000). As a losses seriously threaten the ecological and economic bases of result, the nature of the relationship between species terrestrial ecosystems. In response, I offer a set of hypotheses diversity and ecosystem productivity remains unclear. that describe how diversity might influence productivity in plant communities based on three well-known mechanisms: comple- One cause of the diversity-productivity debate, and mentarity, facilitation, and the sampling effect. Emphasis on a reason that this relationship remains controversial, these mechanisms reveals the sensitivity of any diversity-produc- is the lack of clear hypotheses to guide experimental tivity relationship to ecological context (i.e., where this relation- ship should be found); ecological context includes characteristics hypothesis testing. -
Delineating Probabilistic Species Pools in Ecology and Biogeography
GlobalGlobal Ecology Ecology and and Biogeography, Biogeography, (Global (Global Ecol. Ecol. Biogeogr.) Biogeogr.)(2016)(2016)25, 489–501 MACROECOLOGICAL Delineating probabilistic species pools in METHODS ecology and biogeography Dirk Nikolaus Karger1,2*, Anna F. Cord3, Michael Kessler2, Holger Kreft4, Ingolf Kühn5,6,7,SvenPompe5,8, Brody Sandel9, Juliano Sarmento Cabral4,7, Adam B. Smith10, Jens-Christian Svenning9, Hanna Tuomisto1, Patrick Weigelt4,11 and Karsten Wesche12,7 1Department of Biology, University of Turku, ABSTRACT Turku, Finland, 2Institute of Systematic Aim To provide a mechanistic and probabilistic framework for defining the Botany, University of Zurich, Zurich, Switzerland, 3Department of Computational species pool based on species-specific probabilities of dispersal, environmental Landscape Ecology, Helmholtz Centre for suitability and biotic interactions within a specific temporal extent, and to show Environmental Research – UFZ, Leipzig, how probabilistic species pools can help disentangle the geographical structure of Germany, 4Biodiversity, Macroecology and different community assembly processes. Conservation Biogeography Group, University Innovation Probabilistic species pools provide an improved species pool defini- of Göttingen, Göttingen, Germany, tion based on probabilities in conjunction with the associated species list, which 5Department of Community Ecology, explicitly recognize the indeterminate nature of species pool membership for a Helmholtz Centre for Environmental Research given focal unit of interest and -
The New Talent Landscape: Recruiting Difficulty and Skills Shortages (SHRM, 2016)
THE NEW TALENT LANDSCAPE RECRUITING DIFFICULTY AND SKILLS SHORTAGES THE NEW TALENT LANDSCAPE Recruiting Difficulty and Skills Shortages A RESEARCH REPORT BY THE SOCIETY FOR HUMAN RESOURCE MANAGEMENT Media Contact USA Kate Kennedy SHRM Headquarters Phone: + 1.703.535.6260 Alexandria, VA 22314 The Society for Human Resource Management E-mail: [email protected] Phone +1.800.283.7476 (SHRM) is the world’s largest HR professional society, E-mail [email protected] representing 285,000 members in more than 165 Vanessa Hill countries. For nearly seven decades, the Society Phone: +1.703.535.6072 China has been the leading provider of resources serving E-mail: [email protected] Gateway Plaza the needs of HR professionals and advancing the Chaoyang District Online practice of human resource management. SHRM Beijing, 100027 SHRM Online: shrm.org has more than 575 affiliated chapters within the Phone +86.10.59231033 United States and subsidiary offices in China, India SHRM Research & Surveys: shrm.org/research E-mail [email protected] and United Arab Emirates. Visit us at shrm.org. SHRM Research on Twitter: @SHRM_Research India SHRM Research on LinkedIn: LinkedIn.com Gurgaon, Sector 26 SHRM Research on SHRM Connect: Haryana 122002 community.shrm.org Phone +91.12.44200243 E-mail [email protected] United Arab Emirates Dubai Knowledge Village Dubai, UAE Phone +971.050.104.6330 E-mail [email protected] 16-0156 To order printed copies of this report, visit shrmstore.shrm.org or call 1-800-444-5006. 2 About This Research Report 5 Executive Summary -
Life History Strategies, Population Regulation, and Implications for Fisheries Management1
872 PERSPECTIVE / PERSPECTIVE Life history strategies, population regulation, and implications for fisheries management1 Kirk O. Winemiller Abstract: Life history theories attempt to explain the evolution of organism traits as adaptations to environmental vari- ation. A model involving three primary life history strategies (endpoints on a triangular surface) describes general pat- terns of variation more comprehensively than schemes that examine single traits or merely contrast fast versus slow life histories. It provides a general means to predict a priori the types of populations with high or low demographic resil- ience, production potential, and conformity to density-dependent regulation. Periodic (long-lived, high fecundity, high recruitment variation) and opportunistic (small, short-lived, high reproductive effort, high demographic resilience) strat- egies should conform poorly to models that assume density-dependent recruitment. Periodic-type species reveal greatest recruitment variation and compensatory reserve, but with poor conformity to stock–recruitment models. Equilibrium- type populations (low fecundity, large egg size, parental care) should conform better to assumptions of density- dependent recruitment, but have lower demographic resilience. The model’s predictions are explored relative to sustain- able harvest, endangered species conservation, supplemental stocking, and transferability of ecological indices. When detailed information is lacking, species ordination according to the triangular model provides qualitative -
Recruitment, Dispersal, and Demographic Rescue in Spatially-Structured White-Tailed Ptarmigan Populations ’
The Condor 102:503-516 D The Cooper Ornithological Society Zoo0 RECRUITMENT, DISPERSAL, AND DEMOGRAPHIC RESCUE IN SPATIALLY-STRUCTURED WHITE-TAILED PTARMIGAN POPULATIONS ’ KATHY MARTIN Canadian Wildlife Service, 5421 Robertson Rd, RR I Delta, British Columbia, Canada, V4K 3N2, and Department of Forest Sciences, 2424 Main Mall, University of British Columbia, Vancouver, British Columbia, Canada, V6T 124, e-mail: [email protected] PETER B. STACEY Department of Biology, University of New Mexico, Albuquerque, NM 87131, e-mail: [email protected] CLAIT E. BRAUN* Colorado Division of Wildlife, 317 West Prospect Rd., Fort Collins, CO 80526, e-mail: [email protected] Abstract. We studiedrecruitment and dispersalof White-tailed Ptarmigan (Lagopus leu- curus) breeding in naturally fragmented alpine habitatsat four study sites in Colorado from 1987-1998. Almost all recruitment for both sexes, particularly females, was of birds pro- duced outside local populationsand also external to nearby studiedpopulations. Populations were more dependent on female recruitment than on male recruitment to sustainthem, and patterns of recruitment were not correlated with local survival of adults or production of young the previous year, except at one site for females. Over 95% of recruitswere yearlings. Breeding dispersal of adults, an infrequent but regular event, was also important to inter- population connectivity. Our data for multiple populationsallowed us to describemovement patterns among populations to assess consistency with conditions required for a -
Talent Acquisition Technology Ecosystem
Global Staffing and Recruitment Technology Talent Acquisition Technology Ecosystem February 15, 2018 | David Francis, Research Manager | [email protected] Talent Acquisition Technology Ecosystem | February 15, 2017 Contents Talent Acquisition Technology Ecosystem ........................................................................................................................................................... 2 Overview of an Ecosystem .................................................................................................................................................................................... 3 Systems of Record ................................................................................................................................................................................................ 8 Candidate Discovery ........................................................................................................................................................................................... 10 Candidate Assessment ........................................................................................................................................................................................ 14 Candidate Engagement ....................................................................................................................................................................................... 15 Candidate Verification ....................................................................................................................................................................................... -
Recruitment of Marine Invertebrates: the Role of Active Larval Choices and Early Mortality
Oecologia (Berl) (1982) 54:348-352 Oer Springer-Verlag 1982 Recruitment of Marine Invertebrates: the Role of Active Larval Choices and Early Mortality Michael J. Keough and Barbara J. Downes Department of Biological Sciences, University of California, Santa Barbara, Ca 93106, USA Summary. Spatial variation in the recruitment of sessile a reflection of the limitations of the observer. The number marine invertebrates with planktonic larvae may be derived of organisms passing through the fourth phase is termed from a number of sources: events within the plankton, recruitment, while the number passing to the third phase choices made by larvae at the time of settlement, and mor- is termed settlement. Recruitment is a composite of larval tality of juvenile organisms after settlement, but before a and juvenile stages, while settlement involves only larval census by an observer. These sources usually are not distin- stages. guished. It is important to distinguish between settlement and A study of the recruitment of four species of sessile recruitment. Non-random patterns of recruitment, such as invertebrates living on rock walls beneath a kelp canopy differences in the density of recruitment with height on the showed that both selection of microhabitats by settling shore (Underwood 1979) or differences in the density of larvae and predation by fish may be important. Two micro- recruitment with patch size (Jackson 1977; Keough 1982a), habitats were of interest; open, flat rock surfaces, and small or with microhabitat, may have two causes: (1) differential pits and crevices that act as refuges from fish predators. settlement, and (2), different probabilities of early mortality The polychaete Spirorbis eximus and the cyclostome in different parts of an organism's habitat. -
The Relationship Between Productivity and Species Richness
P1: FNE/FGO P2: FLI/FDR September 15, 1999 17:9 Annual Reviews AR093-10 Annu. Rev. Ecol. Syst. 1999. 30:257–300 Copyright c 1999 by Annual Reviews. All rights reserved THE RELATIONSHIP BETWEEN PRODUCTIVITY AND SPECIES RICHNESS R. B. Waide1,M.R.Willig2, C. F. Steiner3, G. Mittelbach4, L. Gough5,S.I.Dodson6,G.P.Juday7, and R. Parmenter8 1LTER Network Office, Department of Biology, University of New Mexico, Albuquerque, New Mexico 87131-1091; e-mail: [email protected]; 2Program in Ecology and Conservation Biology, Department of Biological Sciences & The Museum, Texas Tech University, Lubbock, Texas 79409-3131; e-mail: [email protected]; 3Kellogg Biological Station and the Department of Zoology, Michigan State University, Hickory Corners, Michigan 49060; e-mail: [email protected]; 4Kellogg Biological Station and the Department of Zoology, Michigan State University, Hickory Corners, Michigan 49060; e-mail: [email protected]; 5Department of Biological Sciences, University of Alabama, Tuscaloosa, Alabama 35487-0344; e-mail: [email protected]; 6Department of Zoology, University of Wisconsin, Madison, Wisconsin 53706; e-mail: [email protected]; 7Forest Sciences Department, University of Alaska, Fairbanks, Alaska 99775-7200; e-mail: [email protected]; 8Department of Biology, University of New Mexico, Albuquerque, New Mexico 87131-1091; e-mail: [email protected] Key Words primary productivity, biodiversity, functional groups, ecosystem processes ■ Abstract Recent overviews have suggested that the relationship between species richness and productivity (rate of conversion of resources to biomass per unit area per unit time) is unimodal (hump-shaped). Most agree that productivity affects species richness at large scales, but unanimity is less regarding underlying mechanisms. -
The Relative Importance of the Species Pool
Journal of Ecology 2008, 96, 937–946 doi: 10.1111/j.1365-2745.2008.01420.x TheBlackwell Publishing Ltd relative importance of the species pool, productivity and disturbance in regulating grassland plant species richness: a field experiment Timothy L. Dickson* and Bryan L. Foster Ecology and Evolutionary Biology; The University of Kansas; Lawrence, KS 66045; USA Summary 1. Ecologists have generally focused on how species interactions and available niches control species richness. However, the number of species in the regional species pool may also control richness. Moreover, the relative influence of the species pool and species interactions on plant richness may change along productivity and disturbance gradients. 2. We test the hypothesis that many species from the propagule pool will colonize into habitats of moderate productivity and moderate disturbance, and the number of species in the pool will, therefore, primarily control plant species richness in such habitats. The hypothesis also states that few species from the propagule pool will colonize into habitats of high productivity and minimal disturbance because competitive species interactions primarily control plant richness in such habitats. 3. To test this hypothesis, we experimentally varied resource availability via fertilization and irrigation, the size of the available propagule pool via sowing the seeds of 49 species and disturbance via vegetation clipping. 4. A larger propagule pool increased species richness 80% in the absence of fertilization and the presence of clipping but had no significant effect on richness in the presence of fertilization and the absence of clipping (significant fertilization × clipping × seed addition interaction). Irrigation increased species richness primarily in the absence of fertilization and the presence or clipping (significant fertilization × clipping × irrigation interaction). -
Long-Term Nutrient Enrichment Decouples Predator and Prey Production
Long-term nutrient enrichment decouples predator and prey production John M. Davisa,1,2, Amy D. Rosemonda, Susan L. Eggertb, Wyatt F. Crossa,3, and J. Bruce Wallacec aOdum School of Ecology, University of Georgia, Athens, GA 30602; bUS Department of Agriculture Forest Service, Northern Research Station, Grand Rapids, MN 55744; and cDepartment of Entomology, University of Georgia, Athens, GA 30602 Edited by William Bowden, University of Vermont, and accepted by the Editorial Board November 23, 2009 (received for review July 28, 2009) Increased nutrient mobilization by human activities represents one amplify variability in predator–prey cycles and even extirpate of the greatest threats to global ecosystems, but its effects on predator populations (i.e., “the paradox of enrichment”) (9). ecosystem productivity can differ depending on food web structure. More recent models predict that nutrient enrichment can fur- When this structure facilitates efficient energy transfers to higher ther alter predator–prey interactions by increasing the dominance trophic levels, evidence from previous large-scale enrichments of predator-resistant primary consumers, diverting energy flow to suggests that nutrients can stimulate the production of multiple predator-resistant pathways that are relatively inaccessible to top trophic levels. Here we report results from a 5-year continuous predators (10, 11). Small-scale mesocosm experiments have nutrient enrichment of a forested stream that increased primary shown that such a reduction in trophic efficiency can ultimately consumer production, but not predator production. Because of decrease predator production, even with sustained increases in strong positive correlations between predator and prey production primary consumer productivity (i.e., resulting in a trophic decou- (evidence of highly efficient trophic transfers) under reference pling) (12, 13).