Spatial Ecology of Territorial Populations

Total Page:16

File Type:pdf, Size:1020Kb

Spatial Ecology of Territorial Populations Spatial ecology of territorial populations Benjamin G. Weinera, Anna Posfaib, and Ned S. Wingreenc,1 aDepartment of Physics, Princeton University, Princeton, NJ 08544; bSimons Center for Quantitative Biology, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724; and cLewis–Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544 Edited by Nigel Goldenfeld, University of Illinois at Urbana–Champaign, Urbana, IL, and approved July 30, 2019 (received for review July 9, 2019) Many ecosystems, from vegetation to biofilms, are composed of and penalize niche overlap (25), but did not otherwise struc- territorial populations that compete for both nutrients and phys- ture the spatial interactions. All these models allow coexistence ical space. What are the implications of such spatial organization when the combination of spatial segregation and local interac- for biodiversity? To address this question, we developed and ana- tions weakens interspecific competition relative to intraspecifc lyzed a model of territorial resource competition. In the model, competition. However, it remains unclear how such interactions all species obey trade-offs inspired by biophysical constraints on relate to concrete biophysical processes. metabolism; the species occupy nonoverlapping territories, while Here, we study biodiversity in a model where species interact nutrients diffuse in space. We find that the nutrient diffusion through spatial resource competition. We specifically consider time is an important control parameter for both biodiversity and surface-associated populations which exclude each other as they the timescale of population dynamics. Interestingly, fast nutri- compete for territory. This is an appropriate description for ent diffusion allows the populations of some species to fluctuate biofilms, vegetation, and marine ecosystems like mussels (28) or to zero, leading to extinctions. Moreover, territorial competition coral (29), in contrast with models that represent populations as spontaneously gives rise to both multistability and the Allee overlapping densities and better describe motile or planktonic effect (in which a minimum population is required for survival), so populations (9, 30). The well-mixed environment is an explicit that small perturbations can have major ecological effects. While limit of our model, so we are able to isolate the unique effects of the assumption of trade-offs allows for the coexistence of more spatial structure. species than the number of nutrients—thus violating the prin- We find that, contrary to expectations, introducing population ciple of competitive exclusion—overall biodiversity is curbed by territories into a model with metabolic trade-offs reduces bio- the domination of “oligotroph” species. Importantly, in contrast diversity relative to the well-mixed case. Extinctions occur over to well-mixed models, spatial structure renders diversity robust to a new timescale inversely related to the nutrient mixing time. inequalities in metabolic trade-offs. Our results suggest that terri- Spatial structure also leads to the emergence of multiple steady torial ecosystems can display high biodiversity and rich dynamics states and the Allee effect, so that small perturbations may have simply due to competition for resources in a spatial community. drastic consequences. Finally, we find that overall biodiversity is curbed by the domination of “oligotroph” species but is robust to spatial ecology j biodiversity j trade-offs j microbial ecology j modeling inequalities in metabolic trade-offs. Results iving things exist not in isolation but in communities, many Lof which are strikingly diverse. Tropical rainforests can have Model. We developed a model of territorial populations compet- more than 300 tree species in a single hectare (1), and it has ing for diffusing resources to clarify the relationship between been estimated that 1 g of soil contains 2,000–30,000+ dis- tinct microbial genomes (2, 3). Understanding the relationship Significance between biodiversity and the environment remains a major chal- lenge, particularly in light of the competitive exclusion principle: All organisms live in spatial communities. In many cases, such In simple models of resource competition, no more species can as vegetation or bacterial biofilms, dense surface-bound pop- coexist indefinitely than the number of limiting resources (4, 5). ulations compete for both resources and physical space. How In modern niche theory, competitive exclusion is circumvented do these territorial interactions impact ecosystem behavior by mechanisms which reduce niche overlaps and/or intrinsic fit- and biodiversity? We study a theoretical model of terri- ness differences (6, 7), suggesting that trade-offs may play an torial resource competition with trade-offs and show that important role in the maintenance of biodiversity. Intriguingly, many features of real ecosystems emerge naturally, including diversity beyond the competitive-exclusion limit was recently slow population dynamics that render community composi- demonstrated in a resource-competition model with a well-mixed tion susceptible to demographic and other noise. We also environment and exact metabolic trade-offs (8). However, many observe alternate steady states, including the Allee effect in ecosystems are spatially structured, and metabolic trade-offs are which survival requires a minimum population. Importantly, unlikely to be exact. While some spatial structure is externally we demonstrate that biodiversity occurs robustly and can imposed, it also arises from the capacity of organisms to shape arise in territorial communities simply due to competition for their environment. How does self-generated spatial structure, resources. along with realistic metabolic constraints, impact diversity? Various studies have clarified how intrinsic environmental het- Author contributions: B.G.W., A.P., and N.S.W. designed research; B.G.W., A.P., and N.S.W. erogeneity (e.g., an external resource gradient) fosters biodiver- performed research; B.G.W. analyzed data; and B.G.W. and N.S.W. wrote the paper.y sity by creating spatial niches (9–13). Others have demonstrated The authors declare no conflict of interest.y that migration between low-diversity local environments can lead This article is a PNAS Direct Submission.y to “metacommunities” with high global diversity (14–19). But This open access article is distributed under Creative Commons Attribution License 4.0 how is diversity impacted by local spatial structure? Recent (CC BY).y models suggest that spatial environments without intrinsic het- Data deposition: The code used in this paper has been deposited in GitHub (https:// erogeneity can support higher diversity than the well-mixed case github.com/BenjaminWeiner/ecology-territorial-populations).y (20–25), although the effect depends on the interactions and 1 To whom correspondence may be addressed. Email: [email protected] details of spatial structure (26, 27). In these models, competi- This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10. tion follows phenomenological interaction rules. In some cases, 1073/pnas.1911570116/-/DCSupplemental.y trade-offs have been invoked to limit fitness differences (21) Published online August 21, 2019. 17874–17879 j PNAS j September 3, 2019 j vol. 116 j no. 36 www.pnas.org/cgi/doi/10.1073/pnas.1911570116 Downloaded by guest on September 27, 2021 spatial structure, metabolic trade-offs, and biodiversity. The regime where population growth is nutrient-limited, so the rate model is spatially explicit and relates the mechanistic dynam- of uptake of each nutrient is linear in its concentration. Thus, ics of competition to parameters with clear biological meaning. within each region occupied by a single species σ, the nutrient Crucially, competing populations are not interpenetrating, so concentrations cσi obey populations are competing for both nutrients and territory. 2 m p @cσi @ cσi Specifically, we consider species competing for nutri- = S − α c + D , [1] ents in a 1-dimensional space of size L with periodic boundary @t i σi σi @x 2 conditions (a ring). The rate of supply of nutrients is speci- P where D is the diffusion coefficient for all nutrients. As nutri- fied by the supply vector S~ = (S1, S2 ::: Sp ) such that Si = S, i ent processing is generally much faster than growth, we assume S where is the total nutrient supply rate in units of concentra- a separation of timescales, such that nutrient concentrations tion/time. The nutrient supply is spatially uniform, so there is no equilibrate before populations change. Then, @c = 0, and external environmental heterogeneity. Each species σ 2 [1 ::: m] @t is defined by its metabolic strategy ~ασ = (ασ1, ασ2 : : : ασp ), r r Si ασi ασi which specifies the proportion of its metabolic resources (e.g., cσi (x) = + Aσi exp x + Bσi exp −x : enzymes) it allocates to the consumption of each nutrient. ασi D D Metabolic trade-offs are implemented via a constraint on the [2] P The constants of integration Aσi and Bσi are fixed by the phys- enzyme budget—namely, i ασi = E for all species (except where noted). Metabolic strategies and the supply can be rep- ical requirement that ci (x) be continuous and differentiable at resented as points on a simplex of dimension p − 1 (see Figs. 1A the population boundaries. Fig. 1D shows the concentrations of and 2 A, Inset, for example). Each species occupies a segment the 3 nutrients after the populations shown in Fig. 1
Recommended publications
  • Consistent Responses of Soil Microbial Communities to Elevated Nutrient Inputs in Grasslands Across the Globe
    Consistent responses of soil microbial communities to elevated nutrient inputs in grasslands across the globe Jonathan W. Leffa,b, Stuart E. Jonesc, Suzanne M. Proberd, Albert Barberána, Elizabeth T. Borere, Jennifer L. Firnf, W. Stanley Harpoleg,h,i, Sarah E. Hobbiee, Kirsten S. Hofmockelj, Johannes M. H. Knopsk, Rebecca L. McCulleyl, Kimberly La Pierrem, Anita C. Rischn, Eric W. Seabloomo, Martin Schützn, Christopher Steenbockb, Carly J. Stevensp, and Noah Fierera,b,1 aCooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, CO 80309; bDepartment of Ecology and Evolutionary Biology, University of Colorado, Boulder, CO 80309; cDepartment of Biological Sciences, University of Notre Dame, Notre Dame, IN 46556; dCommonwealth Scientific and Industrial Research Organisation Land and Water Flagship, Wembley, WA 6913, Australia; eDepartment of Ecology, Evolution and Behavior, University of Minnesota, St. Paul, MN 55108; fSchool of Earth, Environmental and Biological Sciences, Queensland University of Technology, Brisbane, QLD 4001, Australia; gDepartment of Physiological Diversity, Helmholtz Center for Environmental Research UFZ, 04318 Leipzig, Germany; hGerman Centre for Integrative Biodiversity Research Halle-Jena-Leipzig, D-04103 Leipzig, Germany; iInstitute of Biology, Martin Luther University Halle-Wittenberg, 06108 Halle (Saale), Germany; jEcology, Evolution, and Organismal Biology Department, Iowa State University, Ames, IA 50011; kSchool of Biological Sciences, University of Nebraska, Lincoln, NE 68588; lDepartment of Plant and Soil Sciences, University of Kentucky, Lexington, KY 40546; mDepartment of Integrative Biology, University of California, Berkeley, CA 94720; nCommunity Ecology, Swiss Federal Institute for Forest, Snow and Landscape Research, 8903 Birmensdorf, Switzerland; oDepartment of Ecology, Evolution, and Behavior, University of Minnesota, St. Paul, MN 55108; and pLancaster Environment Centre, Lancaster University, Lancaster, LA1 4YQ, United Kingdom Edited by Peter M.
    [Show full text]
  • The Trophic-Dynamic Aspect of Ecology Author(S): Raymond L
    The Trophic-Dynamic Aspect of Ecology Author(s): Raymond L. Lindeman Reviewed work(s): Source: Ecology, Vol. 23, No. 4 (Oct., 1942), pp. 399-417 Published by: Ecological Society of America Stable URL: http://www.jstor.org/stable/1930126 . Accessed: 30/01/2012 10:50 Your use of the JSTOR archive indicates your acceptance of the Terms & Conditions of Use, available at . http://www.jstor.org/page/info/about/policies/terms.jsp JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about JSTOR, please contact [email protected]. Ecological Society of America is collaborating with JSTOR to digitize, preserve and extend access to Ecology. http://www.jstor.org THE TROPHIC-DYNAMIC ASPECT OF ECOLOGY RAYMOND L. LINDEMAN OsbornZoological Laboratory,Yale University Recent progressin the studyof aquatic community. A more "bio-ecological" food-cycle relationships invites a re- species-distributionalapproach would appraisal of certain ecological tenets. recognize both the plants and animals Quantitative productivitydata provide as co-constituentsof restricted"biotic" a basis for enunciating certain trophic communities,such as "plankton com- principles, which, when applied to a munities," "benthic communities,"etc., series of successional stages, shed new in which membersof the living commu- light on the dynamics of ecological nity "co-act" with each other and "re- succession. act" with the non-livingenvironment (Clementsand Shelford,'39; Carpenter, "COMMUNITY" CONCEPTS '39, '40; T. Park, '41).
    [Show full text]
  • Meta-Ecosystems: a Theoretical Framework for a Spatial Ecosystem Ecology
    Ecology Letters, (2003) 6: 673–679 doi: 10.1046/j.1461-0248.2003.00483.x IDEAS AND PERSPECTIVES Meta-ecosystems: a theoretical framework for a spatial ecosystem ecology Abstract Michel Loreau1*, Nicolas This contribution proposes the meta-ecosystem concept as a natural extension of the Mouquet2,4 and Robert D. Holt3 metapopulation and metacommunity concepts. A meta-ecosystem is defined as a set of 1Laboratoire d’Ecologie, UMR ecosystems connected by spatial flows of energy, materials and organisms across 7625, Ecole Normale Supe´rieure, ecosystem boundaries. This concept provides a powerful theoretical tool to understand 46 rue d’Ulm, F–75230 Paris the emergent properties that arise from spatial coupling of local ecosystems, such as Cedex 05, France global source–sink constraints, diversity–productivity patterns, stabilization of ecosystem 2Department of Biological processes and indirect interactions at landscape or regional scales. The meta-ecosystem Science and School of perspective thereby has the potential to integrate the perspectives of community and Computational Science and Information Technology, Florida landscape ecology, to provide novel fundamental insights into the dynamics and State University, Tallahassee, FL functioning of ecosystems from local to global scales, and to increase our ability to 32306-1100, USA predict the consequences of land-use changes on biodiversity and the provision of 3Department of Zoology, ecosystem services to human societies. University of Florida, 111 Bartram Hall, Gainesville, FL Keywords 32611-8525,
    [Show full text]
  • Spatial Ecology and Modeling of Fish Populations - FAS 6416
    Spatial Ecology and Modeling of Fish Populations - FAS 6416 1 Overview Spatial approaches to fisheries management are increasingly of interest the conservation and management of fish populations; and spatial research on fish populations and fish ecology is becoming a cornerstone of fisheries research. This course explores spatial ecology concepts, population dynamics models, examples of field data, and computer simulation tools to understand the ecological origin of spatial fish populations and their importance for fisheries management and conservation. The course is suitable for students who are interested in an interdisciplinary research field that draws as much from ecology as from fisheries management. 2 credits Spring Semester Face-to-face Location TBD with course website: http://elearning.ufl.edu/ The course is intended to provide students with different types of models and concepts that explain the spatial distribution of fish at different spatial and temporal scales. The course is new and evolving, and contains structured elements as well as exploratory exercises and discussions that are aimed at providing students with new perspectives on the dynamics of fish populations. Course Prerequisites: Graduate student status in Fisheries and Aquatic Sciences (or related, as determined by instructor). Interested graduate students in Wildlife Ecology are welcome. Instructor: Dr. Juliane Struve, [email protected]. SFRC Fisheries and Aquatic Sciences Rm. 34, Building 544. Telephone: 352-273-3632. Cell Phone: 352-213-5108 Please use the Canvas message/Inbox feature for fastest response. Office hours: Tuesdays, 3-5pm or online by appointment Textbook(s) and/or readings: The course does not have a designated text book. Reading materials will be assigned for every session and typical consist of 1-2 classic and recent papers.
    [Show full text]
  • (Antarctica) Glacial, Basal, and Accretion Ice
    CHARACTERIZATION OF ORGANISMS IN VOSTOK (ANTARCTICA) GLACIAL, BASAL, AND ACCRETION ICE Colby J. Gura A Thesis Submitted to the Graduate College of Bowling Green State University in partial fulfillment of the requirements for the degree of MASTER OF SCIENCE December 2019 Committee: Scott O. Rogers, Advisor Helen Michaels Paul Morris © 2019 Colby Gura All Rights Reserved iii ABSTRACT Scott O. Rogers, Advisor Chapter 1: Lake Vostok is named for the nearby Vostok Station located at 78°28’S, 106°48’E and at an elevation of 3,488 m. The lake is covered by a glacier that is approximately 4 km thick and comprised of 4 different types of ice: meteoric, basal, type 1 accretion ice, and type 2 accretion ice. Six samples were derived from the glacial, basal, and accretion ice of the 5G ice core (depths of 2,149 m; 3,501 m; 3,520 m; 3,540 m; 3,569 m; and 3,585 m) and prepared through several processes. The RNA and DNA were extracted from ultracentrifugally concentrated meltwater samples. From the extracted RNA, cDNA was synthesized so the samples could be further manipulated. Both the cDNA and the DNA were amplified through polymerase chain reaction. Ion Torrent primers were attached to the DNA and cDNA and then prepared to be sequenced. Following sequencing the sequences were analyzed using BLAST. Python and Biopython were then used to collect more data and organize the data for manual curation and analysis. Chapter 2: As a result of the glacier and its geographic location, Lake Vostok is an extreme and unique environment that is often compared to Jupiter’s ice-covered moon, Europa.
    [Show full text]
  • Landscapes of Fear: Spatial Patterns of Risk
    TREE 2486 No. of Pages 14 Review Landscapes of Fear: Spatial Patterns of Risk Perception and Response 1, ,@ 2,3,5 1,5 4,5 Kaitlyn M. Gaynor , * Joel S. Brown, Arthur D. Middleton, Mary E. Power, and 1 Justin S. Brashares Animals experience varying levels of predation risk as they navigate heteroge- Highlights neous landscapes, and behavioral responses to perceived risk can structure Recent technological advances have provided unprecedented insights into ecosystems. The concept of the landscape of fear has recently become central the movement and behavior of animals to describing this spatial variation in risk, perception, and response. We present on heterogeneous landscapes. Some studies have indicated that spatial var- a framework linking the landscape of fear, defined as spatial variation in prey iation in predation risk plays a major perception of risk, to the underlying physical landscape and predation risk, and role in prey decision making, which can to resulting patterns of prey distribution and antipredator behavior. By disam- ultimately structure ecosystems. biguating the mechanisms through which prey perceive risk and incorporate The concept of the ‘landscape of fear’ fear into decision making, we can better quantify the nonlinear relationship was introduced in 2001 and has been between risk and response and evaluate the relative importance of the land- widely adopted to describe spatial var- iation predation risk, risk perception, scape of fear across taxa and ecosystems. and response. However, increasingly divergent interpretations of its meaning Introduction and application now cloud under- The risk of predation plays a powerful role in shaping behavior of fearful prey, with conse- standing and synthesis, and at least 15 distinct processes and states have quences for individual physiology, population dynamics, and community interactions [1,2].
    [Show full text]
  • Introduction to the Special Issue on Spatial Ecology
    International Journal of Geo-Information Editorial Space-Ruled Ecological Processes: Introduction to the Special Issue on Spatial Ecology Duccio Rocchini 1,2,3 1 University of Trento, Center Agriculture Food Environment, Via E. Mach 1, 38010 S. Michele all’Adige (TN), Italy; [email protected] 2 University of Trento, Centre for Integrative Biology, Via Sommarive, 14, 38123 Povo (TN), Italy 3 Fondazione Edmund Mach, Department of Biodiversity and Molecular Ecology, Research and Innovation Centre, Via E. Mach 1, 38010 S. Michele all’Adige (TN), Italy Received: 12 December 2017; Accepted: 23 December 2017; Published: 2 January 2018 This special issue explores most of the scientific issues related to spatial ecology and its integration with geographical information at different spatial and temporal scales. Papers are mainly related to challenging aspects of species variability over space and landscape dynamics, providing a benchmark for future exploration on this theme. The need for a spatial view in Ecology is a fact. Dealing with ecological changes over space and time represents a long-lasting theme, now faced by means of innovative techniques and modelling approaches (e.g., Chaudhary et al. [1], Palmer [2], Rocchini [3]). This special issue explores some of them, with challenging ideas facing different components of spatial patterns related to ecological processes, such as: (i) species variability over space [4–11]; and (ii) landscape dynamics [12,13]. Concerning biodiversity variability over space, key spatial datasets are needed to fully investigate biodiversity change in space and time, as shown by Geri et al. [7], who carried out innovative procedures to recover and properly map historical floristic and vegetation data for biodiversity monitoring.
    [Show full text]
  • Pattern and Process Second Edition Monica G. Turner Robert H. Gardner
    Monica G. Turner Robert H. Gardner Landscape Ecology in Theory and Practice Pattern and Process Second Edition L ANDSCAPE E COLOGY IN T HEORY AND P RACTICE M ONICA G . T URNER R OBERT H . G ARDNER LANDSCAPE ECOLOGY IN THEORY AND PRACTICE Pattern and Process Second Edition Monica G. Turner University of Wisconsin-Madison Department of Zoology Madison , WI , USA Robert H. Gardner University of Maryland Center for Environmental Science Frostburg, MD , USA ISBN 978-1-4939-2793-7 ISBN 978-1-4939-2794-4 (eBook) DOI 10.1007/978-1-4939-2794-4 Library of Congress Control Number: 2015945952 Springer New York Heidelberg Dordrecht London © Springer-Verlag New York 2015 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifi cally the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfi lms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specifi c statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made.
    [Show full text]
  • The Structure of Community Ecology
    The structure of community ecology Mark Vellend Departments of Botany & Zoology Biodiversity Research Centre University of British Columbia Is community ecology a mess? 1 …with a key difference in how process is treated Population Community Genetics Ecology Patterns we Diversity and Diversity and want to composition of composition of understand alleles/genotypes species Competition Processes to Mutation Predation Niches Neutrality explain Drift Island biogeography Resource-use trade-offs patterns Colonization-competition trade-offs Migration Disturbance Productivity Evolutionary history Selection Etc. But is the difference real or necessary? Population Community Genetics Ecology Patterns we Diversity and Diversity and want to composition of composition of understand alleles/genotypes species Processes to Mutation Speciation explain Drift Drift patterns Migration Dispersal Selection Selection 2 Question on Ecology 101 final exam: What processes influence species composition and diversity? Answer: Question on Evolution 101 final exam: What processes influence genetic variation? Answer: Mutation Drift Migration Selection 3 Processes that influence community composition and diversity Speciation: The creation of new species. Drift: Random changes in the relative frequencies of species. Dispersal: Movement of organisms/propagules among communities. Selection: Deterministic differential survival or reproduction of species. THE LAST 40 The MacArthur school (Marlboro Circle) YEARS OF COMMUNITY Island Biogeography Simple, general, deterministic
    [Show full text]
  • Spatial Ecology of Territorial Populations
    bioRxiv preprint doi: https://doi.org/10.1101/694257; this version posted July 5, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. Spatial Ecology of Territorial Populations Benjamin G. Weiner Department of Physics, Princeton University, Princeton, NJ 08544 Anna Posfai Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724 Ned S. Wingreen∗ Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544 (Dated: July 5, 2019) Many ecosystems, from vegetation to biofilms, are composed of territorial populations that com- pete for both nutrients and physical space. What are the implications of such spatial organization for biodiversity? To address this question, we developed and analyzed a model of territorial re- source competition. In the model, all species obey trade-offs inspired by biophysical constraints on metabolism; the species occupy non-overlapping territories while nutrients diffuse in space. We find that the nutrient diffusion time is an important control parameter for both biodiversity and the timescale of population dynamics. Interestingly, fast nutrient diffusion allows the populations of some species to fluctuate to zero, leading to extinctions. Moreover, territorial competition spon- taneously gives rise to both multistability and the Allee effect (in which a minimum population is required for survival), so that small perturbations can have major ecological effects. While the as- sumption of trade-offs allows for the coexistence of more species than the number of nutrients – thus violating the principle of competitive exclusion – overall biodiversity is curbed by the domination of “oligotroph” species.
    [Show full text]
  • Chapter 4: PROKARYOTIC DIVERSITY
    Chapter 4: PROKARYOTIC DIVERSITY 1. Prokaryote Habitats, Relationships & Biomes 2. Proteobacteria 3. Gram-negative and Phototropic Non-Proteobacteria 4. Gram-Positive Bacteria 5. Deeply Branching Bacteria 6. Archaea 1. Prokaryote Habitats, Relationships & Biomes Important Metabolic Terminology Oxygen tolerance/usage: aerobic – requires or can use oxygen (O2) anaerobic – does not require or cannot tolerate O2 Energy usage: phototroph – uses light as an energy source • all photosynthetic organisms chemotroph – acquires energy from organic or inorganic molecules • organotrophs – get energy from organic molecules • lithotrophs – get energy from inorganic molecules …more Important Terminology Carbon Source: autotroph – uses CO2 as a carbon source • e.g., photoautotrophs or chemoautotrophs heterotroph – requires an organic carbon source • e.g., chemoheterotroph – gets energy & carbon from organic molecules Oligotrophs require few nutrients, the opposite of eutrophs or copiotrophs Facultative vs Obligate (or Strict): facultative – “able to, but not requiring” • e.g., facultative anaerobes can survive w/ or w/o O2 obligate – “absolutely requires” • e.g., obligate anaerobes cannot survive in O2 Symbiotic Relationships Symbiotic relationships (close, direct interactions) between different organisms in nature are of several types: • e.g., humans have beneficial bacteria in their digestive tracts that also benefit from the food we eat (mutualism) Microbiomes All the microorganisms that inhabit a particular organism or environment (e.g., human or
    [Show full text]
  • Wu-2012-LE-Encyclopedia TE.Pdf
    L in real landscapes, and because it facilitates theoretical and methodological developments by recognizing the LANDSCAPE ECOLOGY importance of micro-, meso-, macro-, and cross-scale approaches. JIANGUO WU The term landscape ecology was coined in 1939 by Arizona State University the German geographer Carl Troll, who was inspired by the spatial patterning of landscapes revealed in aer- ial photographs and the ecosystem concept developed Spatial heterogeneity is ubiquitous in all ecological sys- in 1935 by the British ecologist Arthur Tansley. Troll tems, underlining the signifi cance of the pattern–process originally defi ned landscape ecology as the study of the relationship and the scale of observation and analysis. relationship between biological communities and their Landscape ecology focuses on the relationship between environment in a landscape mosaic. Today, landscape spatial pattern and ecological processes on multiple scales. ecology is widely recognized as the science of studying On the one hand, it represents a spatially explicit per- and improving the relationship between spatial pattern spective on ecological phenomena. On the other hand, and ecological processes on a multitude of scales and or- it is a highly interdisciplinary fi eld that integrates bio- ganizational levels. Heterogeneity, scale, pattern–process physical and socioeconomic perspectives to understand relationships, disturbance, hierarchy, and sustainability and improve the ecology and sustainability of landscapes. are among the key concepts in contemporary landscape Landscape ecology is still rapidly evolving, with a diver- ecology. Landscape ecological studies typically involve sity of emerging ideas and a plurality of methods and the use of geospatial data from various sources (e.g., applications. fi eld survey, aerial photography, and remote sensing) and spatial analysis of different kinds (e.g., pattern indi- DEFINING LANDSCAPE ECOLOGY ces and spatial statistics).
    [Show full text]