The Diversity–Biomass–Productivity Relationships in Grassland Management and Restoration
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Freshwater Ecosystems and Biodiversity
Network of Conservation Educators & Practitioners Freshwater Ecosystems and Biodiversity Author(s): Nathaniel P. Hitt, Lisa K. Bonneau, Kunjuraman V. Jayachandran, and Michael P. Marchetti Source: Lessons in Conservation, Vol. 5, pp. 5-16 Published by: Network of Conservation Educators and Practitioners, Center for Biodiversity and Conservation, American Museum of Natural History Stable URL: ncep.amnh.org/linc/ This article is featured in Lessons in Conservation, the official journal of the Network of Conservation Educators and Practitioners (NCEP). NCEP is a collaborative project of the American Museum of Natural History’s Center for Biodiversity and Conservation (CBC) and a number of institutions and individuals around the world. Lessons in Conservation is designed to introduce NCEP teaching and learning resources (or “modules”) to a broad audience. NCEP modules are designed for undergraduate and professional level education. These modules—and many more on a variety of conservation topics—are available for free download at our website, ncep.amnh.org. To learn more about NCEP, visit our website: ncep.amnh.org. All reproduction or distribution must provide full citation of the original work and provide a copyright notice as follows: “Copyright 2015, by the authors of the material and the Center for Biodiversity and Conservation of the American Museum of Natural History. All rights reserved.” Illustrations obtained from the American Museum of Natural History’s library: images.library.amnh.org/digital/ SYNTHESIS 5 Freshwater Ecosystems and Biodiversity Nathaniel P. Hitt1, Lisa K. Bonneau2, Kunjuraman V. Jayachandran3, and Michael P. Marchetti4 1U.S. Geological Survey, Leetown Science Center, USA, 2Metropolitan Community College-Blue River, USA, 3Kerala Agricultural University, India, 4School of Science, St. -
Bacterial Production and Respiration
Organic matter production % 0 Dissolved Particulate 5 > Organic Organic Matter Matter Heterotrophic Bacterial Grazing Growth ~1-10% of net organic DOM does not matter What happens to the 90-99% of sink, but can be production is physically exported to organic matter production that does deep sea not get exported as particles? transported Export •Labile DOC turnover over time scales of hours to days. •Semi-labile DOC turnover on time scales of weeks to months. •Refractory DOC cycles over on time scales ranging from decadal to multi- decadal…perhaps longer •So what consumes labile and semi-labile DOC? How much carbon passes through the microbial loop? Phytoplankton Heterotrophic bacteria ?? Dissolved organic Herbivores ?? matter Higher trophic levels Protozoa (zooplankton, fish, etc.) ?? • Very difficult to directly measure the flux of carbon from primary producers into the microbial loop. – The microbial loop is mostly run on labile (recently produced organic matter) - - very low concentrations (nM) turning over rapidly against a high background pool (µM). – Unclear exactly which types of organic compounds support bacterial growth. Bacterial Production •Step 1: Determine how much carbon is consumed by bacteria for production of new biomass. •Bacterial production (BP) is the rate that bacterial biomass is created. It represents the amount of Heterotrophic material that is transformed from a nonliving pool bacteria (DOC) to a living pool (bacterial biomass). •Mathematically P = µB ?? µ = specific growth rate (time-1) B = bacterial biomass (mg C L-1) P= bacterial production (mg C L-1 d-1) Dissolved organic •Note that µ = P/B matter •Thus, P has units of mg C L-1 d-1 Bacterial production provides one measurement of carbon flow into the microbial loop How doe we measure bacterial production? Production (∆ biomass/time) (mg C L-1 d-1) • 3H-thymidine • 3H or 14C-leucine Note: these are NOT direct measures of biomass production (i.e. -
Fire and Nonnative Invasive Plants September 2008 Zouhar, Kristin; Smith, Jane Kapler; Sutherland, Steve; Brooks, Matthew L
United States Department of Agriculture Wildland Fire in Forest Service Rocky Mountain Research Station Ecosystems General Technical Report RMRS-GTR-42- volume 6 Fire and Nonnative Invasive Plants September 2008 Zouhar, Kristin; Smith, Jane Kapler; Sutherland, Steve; Brooks, Matthew L. 2008. Wildland fire in ecosystems: fire and nonnative invasive plants. Gen. Tech. Rep. RMRS-GTR-42-vol. 6. Ogden, UT: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. 355 p. Abstract—This state-of-knowledge review of information on relationships between wildland fire and nonnative invasive plants can assist fire managers and other land managers concerned with prevention, detection, and eradi- cation or control of nonnative invasive plants. The 16 chapters in this volume synthesize ecological and botanical principles regarding relationships between wildland fire and nonnative invasive plants, identify the nonnative invasive species currently of greatest concern in major bioregions of the United States, and describe emerging fire-invasive issues in each bioregion and throughout the nation. This volume can help increase understanding of plant invasions and fire and can be used in fire management and ecosystem-based management planning. The volume’s first part summarizes fundamental concepts regarding fire effects on invasions by nonnative plants, effects of plant invasions on fuels and fire regimes, and use of fire to control plant invasions. The second part identifies the nonnative invasive species of greatest concern and synthesizes information on the three topics covered in part one for nonnative inva- sives in seven major bioregions of the United States: Northeast, Southeast, Central, Interior West, Southwest Coastal, Northwest Coastal (including Alaska), and Hawaiian Islands. -
Microbial Loop' in Stratified Systems
MARINE ECOLOGY PROGRESS SERIES Vol. 59: 1-17, 1990 Published January 11 Mar. Ecol. Prog. Ser. 1 A steady-state analysis of the 'microbial loop' in stratified systems Arnold H. Taylor, Ian Joint Plymouth Marine Laboratory, Prospect Place, West Hoe, Plymouth PLl 3DH, United Kingdom ABSTRACT. Steady state solutions are presented for a simple model of the surface mixed layer, which contains the components of the 'microbial loop', namely phytoplankton, picophytoplankton, bacterio- plankton, microzooplankton, dissolved organic carbon, detritus, nitrate and ammonia. This system is assumed to be in equilibrium with the larger grazers present at any time, which are represented as an external mortality function. The model also allows for dissolved organic nitrogen consumption by bacteria, and self-grazing and mixotrophy of the microzooplankton. The model steady states are always stable. The solution shows a number of general properties; for example, biomass of each individual component depends only on total nitrogen concentration below the mixed layer, not whether the nitrogen is in the form of nitrate or ammonia. Standing stocks and production rates from the model are compared with summer observations from the Celtic Sea and Porcupine Sea Bight. The agreement is good and suggests that the system is often not far from equilibrium. A sensitivity analysis of the model is included. The effect of varying the mixing across the pycnocline is investigated; more intense mixing results in the large phytoplankton population increasing at the expense of picophytoplankton, micro- zooplankton and DOC. The change from phytoplankton to picophytoplankton dominance at low mixing occurs even though the same physiological parameters are used for both size fractions. -
Assessing Habitat Quality for Conservation Using an Integrated
Journal of Applied Ecology 2009, 46, 600–609 doi: 10.1111/j.1365-2664.2009.01634.x AssessingBlackwell Publishing Ltd habitat quality for conservation using an integrated occurrence-mortality model Alessandra Falcucci1*, Paolo Ciucci1, Luigi Maiorano1, Leonardo Gentile2 and Luigi Boitani1 1Department of Animal and Human Biology, Sapienza Università di Roma, Viale dell’Università 32, 00185 Rome, Italy and 2Servizio Veterinario, Ente Parco Nazionale d’Abruzzo Lazio e Molise, Viale S. Lucia, 67032 Pescasseroli (l’Aquila), Italy Summary 1. Habitat suitability models are usually produced using species presence or habitat selection, with- out taking into account the demographic performance of the population considered. These models cannot distinguish between sink and source habitats, causing problems especially for species with low reproductive rates and high susceptibility to low levels of mortality as in the case of the critically endangered Apennine brown bear Ursus arctos marsicanus. 2. We developed a spatial model based on bear presence (2544 locations) and mortality data (37 locations) used as proxies for demographic performance. We integrated an occurrence and a mortality-risk Ecological Niche Factor Analysis model into a final two-dimensional model that can be used to distinguish between attractive sink-like and source-like habitat. 3. Our integrated model indicates that a traditional habitat suitability model can provide misleading management and conservation indications, as 43% of the area suitable for the occurrence model is associated with high mortality risk. Areas of source-like habitat for the Apennine bears (highly elevated areas rich in beech forests, far from roads, and with low human density and cultivated fields) are still present, including outside the currently occupied range. -
"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. -
Master Thesis Development and Characteristics of Applied Ecology
1 Faculty of Applied Ecology and Agricultural Sciences Farina Sooth Master thesis Development and characteristics of applied ecology Master in Applied Ecology 2014 2 __________ _________________ _____________________ Date Place Signature I agree that this thesis is for loan in the library YES ☐ NO ☐ I agree that this thesis is open accessible in Brage YES ☐ NO ☐ 3 Abstract The science of applied ecology is lacking a general theory and a commonly acknowledged definition. Additionally, information about the development of applied ecology over the past years, the relation to other disciplines and the importance of applied ecology in different continents are scarce. This is problematic because applied ecology is confronted with growing problems and the society demands more and more that it fulfils its promise of solving practical problems related to the environment. In the past applied ecology regularly failed to keep this promise and is faced with the future challenge of eliminating this problem. Based on communication theory I assume that for a fruitful discussion about the future of applied ecology, the development and the understanding of ecology have to be clarified first to avoid to talk at cross. Therefore, I conducted different qualitative and quantitative content analyses based on material from books and papers dealing with the subject of applied ecology or related disciplines to find out how applied ecology developed over time and what is understood under the term applied ecology. I found out that applied ecology is a young and interdisciplinary oriented science. Its origin lays in the science of ecology and since the 1960s applied ecology developed from a discipline focussed on productivity and utilisation over conservation related topics to a stronger focus on social aspects today. -
Ecosystem Indicatorsfor Variability in Species'trophic Levels
Ecosystem indicatorsfor variability in species’trophic levels Jodie Reed, Lynne Shannon, Laure Velez, Ekin Akoglu, Alida Bundy, Marta Coll, Caihong Fu, Elizabeth A. Fulton, Arnaud Grüss, Ghassen Halouani, et al. To cite this version: Jodie Reed, Lynne Shannon, Laure Velez, Ekin Akoglu, Alida Bundy, et al.. Ecosystem indicatorsfor variability in species’trophic levels. ICES Journal of Marine Science, Oxford University Press (OUP), 2017, 74 (1), pp.158-169. 10.1093/icesjms/fsw150. hal-01927070 HAL Id: hal-01927070 https://hal.archives-ouvertes.fr/hal-01927070 Submitted on 22 Nov 2018 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. ICES Journal of Marine Science (2017), 74(1), 158–169. doi:10.1093/icesjms/fsw150 Original Article Downloaded from https://academic.oup.com/icesjms/article-abstract/74/1/158/2669566 by guest on 19 November 2018 Ecosystem indicators—accounting for variability in species’ trophic levels Jodie Reed1,2,3,4, Lynne Shannon1, Laure Velez3,4, Ekin Akoglu5, Alida Bundy6, Marta Coll1,2,3,7, Caihong Fu8, Elizabeth A. Fulton9, Arnaud -
Land Use, Landscapes, and Biological Invasions
University of Nebraska - Lincoln DigitalCommons@University of Nebraska - Lincoln Nebraska Cooperative Fish & Wildlife Research Nebraska Cooperative Fish & Wildlife Research Unit -- Staff Publications Unit 1-2012 Land Use, Landscapes, and Biological Invasions Karie L. Decker USGS Nebraska Cooperative Fish and Wildlife Research Unit, [email protected] Craig R. Allen USGS Nebraska Cooperative Fish and Wildlife Research Unit, University of Nebraska, [email protected] Leonardo Acosta University of Nebraska-Lincoln Michelle L. Hellman University of Nebraska-Lincoln Christopher F. Jorgensen University of Nebraska-Lincoln See next page for additional authors Follow this and additional works at: https://digitalcommons.unl.edu/ncfwrustaff Part of the Other Environmental Sciences Commons Decker, Karie L.; Allen, Craig R.; Acosta, Leonardo; Hellman, Michelle L.; Jorgensen, Christopher F.; Stutzman, Ryan J.; Unstad, Kody M.; Williams, Amy; and Yans, Matthew, "Land Use, Landscapes, and Biological Invasions" (2012). Nebraska Cooperative Fish & Wildlife Research Unit -- Staff Publications. 99. https://digitalcommons.unl.edu/ncfwrustaff/99 This Article is brought to you for free and open access by the Nebraska Cooperative Fish & Wildlife Research Unit at DigitalCommons@University of Nebraska - Lincoln. It has been accepted for inclusion in Nebraska Cooperative Fish & Wildlife Research Unit -- Staff Publications by an authorized administrator of DigitalCommons@University of Nebraska - Lincoln. Authors Karie L. Decker, Craig R. Allen, Leonardo Acosta, Michelle L. Hellman, Christopher F. Jorgensen, Ryan J. Stutzman, Kody M. Unstad, Amy Williams, and Matthew Yans This article is available at DigitalCommons@University of Nebraska - Lincoln: https://digitalcommons.unl.edu/ ncfwrustaff/99 Invasive Plant Science and Management 2012 5:108–116 Land Use, Landscapes, and Biological Invasions Karie L. -
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 -
Supplement A: Assumptions and Equations in Ecopath with Ecosim Governing Equations
Transactions of the American Fisheries Society 145:136–162, 2016 © American Fisheries Society 2016 DOI: 10.1080/00028487.2015.1069211 Supplement A: Assumptions and Equations in Ecopath with Ecosim Governing Equations The Ecopath module of EwE is a static, mass-balance ecosystem model that uses two governing equations for each species and age group (Christensen and Walters 2004). The first governing equation describes each species group’s production for a time period, i.e., production (P) is the sum of fishery catch (F), predation (M2), net migration (immigration, I, and emigration, E), biomass accumulation (BA), and mortality from other sources (‘other mortality’, M0): P = F + M2 + (I - E) + BA - M0 The second governing equation is based on the principle of conservation of matter within a group, and is designed to balance the energy flows of a biomass pool, i.e., consumption (C) equals the sum of production (P), respiration (R), and unassimilated food (U): C = P + R + U At a minimum, Ecopath requires inputs of diet composition (DCi,j, where i is predator and j is prey), fishery catch (Yi), and three of the following four parameters for each model group (i): biomass (Bi), production-to-biomass ratio (Pi/Bi), consumption-to-biomass ratio (Qi/Bi), and the ecotrophic efficiency (EEi, the fraction of the production that is used in the system and does not move directly to the detritus pool). Mass-balance principles are then used to estimate the fourth parameter. P/B is the annual production rate of the population in Ecopath. Under equilibrium conditions, the P/B ratio of fish is equivalent to its total annual instantaneous mortality (Z) (Allen 1971).