A quantitative framework for selecting and validating food web indicators

Abstract Finding suitable state indicators is challenging and cumbersome in stochastic and complex ecological systems. Typically, a great focus is given to criteria such as data availability, scientific basis, or measurability. Features associated with the indicator's performance such as sensitivity or robustness are often neglected due to the lack of quantitative validation tools. In this paper, we present a simple but flexible framework for selecting and validating the performance of food web indicators. In specific, we suggest a 7-step process in which indicator performances at a regional scale are quantified and visualized allowing for the selection of complementary indicator suites. We demonstrate its application by comparing the performance of pelagic food web indicators for three basins of the Baltic Sea and by assessing the food web status based on selected indicator suites. Our analysis sheds light on spatial differences in indicator performances with respect to direct and indirect pressures, the role of non-linearity and non-additivity in pressure responses, as well as relationships between indicators caused by species interactions. Moreover, our results suggest that the present food web states in the Bornholm and Gotland basins of the Baltic Sea deviate distinctly from an earlier reference period. We advocate the use of our quantitative framework as decision-support tool for selecting suites of complementary indicators under given management schemes such as the EU Marine Strategy Framework Directive.

[1]  R. Gowen,et al.  Use of a Phytoplankton Community Index to assess the health of coastal waters , 2008 .

[2]  Anik Brind'Amour,et al.  New trophic indicators and target values for an ecosystem-based management of fisheries , 2016 .

[3]  C. Möllmann,et al.  Reorganization of a large marine ecosystem due to atmospheric and anthropogenic pressure: a discontinuous regime shift in the Central Baltic Sea , 2009 .

[4]  J. Link.  Translating ecosystem indicators into decision criteria , 2005 .

[5]  Paul J. Somerfield,et al.  An Objective Framework to Test the Quality of Candidate Indicators of Good Environmental Status , 2016, Front. Mar. Sci..

[6]  Kung-Sik Chan,et al.  NONADDITIVE EFFECTS OF THE ENVIRONMENT ON THE SURVIVAL OF A LARGE MARINE FISH POPULATION , 2004 .

[7]  Y. Shin,et al.  Using indicators for evaluating, comparing and communicating the ecological status of exploited marine ecosystems. 1. The IndiSeas project , 2010 .

[8]  David G. Reid,et al.  Interpreting the large fish indicator for the Celtic Sea , 2011 .

[9]  A. Rindorf,et al.  Towards ecosystem-based management: identifying operational food-web indicators for marine ecosystems , 2017 .

[10]  C. Möllmann,et al.  Marine Ecosystem Regime Shifts Induced by Climate and Overfishing: A Review for the Northern Hemisphere , 2012 .

[11]  A. Andersson,et al.  Efficiency of a phytoplankton‐based and a bacterial‐based food web in a pelagic marine system , 2007 .

[12]  Y. Shin,et al.  Using indicators for evaluating, comparing, and communicating the ecological status of exploited marine ecosystems. 2. Setting the scene. , 2010 .

[13]  Copepod grazing in a summer cyanobacteria bloom in the Gulf of Finland , 1994 .

[14]  Jérôme Guitton,et al.  Fishing impact and environmental status in European seas: A diagnosis from stock assessments and ecosystem indicators , 2016 .

[15]  C. Möllmann,et al.  Population dynamics of calanoid copepods and the implications of their predation by clupeid fish in the Central Baltic Sea , 2002 .

[16]  S. Mackinson,et al.  Effort reduction and the large fish indicator: spatial trends reveal positive impacts of recent European fleet reduction schemes , 2015, Environmental Conservation.

[17]  Axel G. Rossberg,et al.  Assessing the sensitivity and specificity of fish community indicators to management action , 2012 .

[18]  P. Schulte,et al.  Thermal performance curves, phenotypic plasticity, and the time scales of temperature exposure. , 2011, Integrative and comparative biology.

[19]  Carrie V. Kappel,et al.  A Global Map of Human Impact on Marine Ecosystems , 2008, Science.

[20]  Carolyn Strange.  Facing the Brink without Crossing It , 2007 .

[21]  Ludwig von Bertalanffy,et al.  The History and State of General Systems Theory , 1972 .

[22]  Gerjan J. Piet,et al.  Development of the EcoQO for the North Sea fish community , 2011 .

[23]  Emilio Hernández-García,et al.  Ecological thresholds and regime shifts: approaches to identification. , 2009, Trends in ecology & evolution.

[24]  N. Hintzen,et al.  Assessing the state of pelagic fish communities within an ecosystem approach and the European Marine Strategy Framework Directive , 2014 .

[25]  S. Carpenter,et al.  Catastrophic regime shifts in ecosystems: linking theory to observation , 2003 .

[26]  B. MacKenzie,et al.  Quantifying environmental heterogeneity : habitat size necessary for successful development of cod Gadus morhua eggs in the Baltic Sea , 2000 .

[27]  Kristin N. Marshall,et al.  Ecological indicators to capture the effects of fishing on biodiversity and conservation status of marine ecosystems , 2016 .

[28]  A. Richardson.  In hot water: zooplankton and climate change , 2008 .

[29]  Jameal F. Samhouri,et al.  Selecting Indicator Portfolios for Marine Species and Food Webs: A Puget Sound Case Study , 2011, PloS one.

[30]  Carrie V. Kappel,et al.  Characterizing driver-response relationships in marine pelagic ecosystems for improved ocean management. , 2016, Ecological applications : a publication of the Ecological Society of America.

[31]  C. Möllmann,et al.  Marine regime shifts around the globe: theory, drivers and impacts , 2015, Philosophical Transactions of the Royal Society B: Biological Sciences.

[32]  B. MacKenzie,et al.  Multi-decadal responses of a cod (Gadus morhua) population to human-induced trophic changes, fishing, and climate. , 2011, Ecological applications : a publication of the Ecological Society of America.

[33]  Mark de Berg,et al.  Computational geometry: algorithms and applications , 1997 .

[34]  B. Qin,et al.  Large-scale field evidence on the enhancement of small-sized cladocerans by microcystis blooms in Lake Taihu, China , 2012 .

[35]  P. A. Clark,et al.  Extraction of a weak climatic signal by an ecosystem , 2002, Nature.

[36]  Julia L. Blanchard,et al.  Trend analysis of indicators: a comparison of recent changes in the status of marine ecosystems around the world , 2010 .

[37]  Edward L. Mills,et al.  Use of Zooplankton Size to Assess the Community Structure of Fish Populations in Freshwater Lakes , 1987 .

[38]  Friedrich W. Köster,et al.  FISH PRODUCTION AND CLIMATE: SPRAT IN THE BALTIC SEA , 2004 .

[39]  L. Uusitalo,et al.  Indicator Properties of Baltic Zooplankton for Classification of Environmental Status within Marine Strategy Framework Directive , 2016, PloS one.

[40]  V. Dakos,et al.  A holistic view of marine regime shifts , 2015, Philosophical Transactions of the Royal Society B: Biological Sciences.

[41]  J. Link,et al.  Defining trends and thresholds in responses of ecological indicators to fishing and environmental pressures , 2013 .

[42]  J. Mauchline.  The biology of calanoid copepods , 1998 .

[43]  C. Möllmann,et al.  The marine copepod, Pseudocalanus elongatus, as a mediator between climate variability and fisheries in the Central Baltic Sea , 2003 .

[44]  M. Llope,et al.  Predator transitory spillover induces trophic cascades in ecological sinks , 2012, Proceedings of the National Academy of Sciences.

[45]  M. Cardinale,et al.  Multi-level trophic cascades in a heavily exploited open marine ecosystem , 2008, Proceedings of the Royal Society B: Biological Sciences.

[46]  J. Link,et al.  Evaluation of quantitative indicators for marine fish communities , 2006 .

[47]  Johanna J. Heymans,et al.  Trophic level-based indicators to track fishing impacts across marine ecosystems , 2014 .

[48]  O. Heikinheimo.  Average salinity as an index for environmental forcing on cod recruitment in the Baltic Sea , 2008 .

[49]  M. Cardinale,et al.  Trophic cascades promote threshold-like shifts in pelagic marine ecosystems , 2009, Proceedings of the National Academy of Sciences.

[50]  D. Bates,et al.  Mixed-Effects Models in S and S-PLUS , 2001 .

[51]  S. Wood.  Generalized Additive Models: An Introduction with R , 2006 .

[52]  N. Stenseth,et al.  Climatic forcing of zooplankton dynamics is stronger during low densities of planktivorous fish , 2009 .

[53]  R. Cowen,et al.  Larval dispersal and marine population connectivity. , 2009, Annual review of marine science.

[54]  Hadley Wickham,et al.  ggplot2 - Elegant Graphics for Data Analysis (2nd Edition) , 2017 .

[55]  Y. Shin,et al.  Comparing data-based indicators across upwelling and comparable systems for communicating ecosystem states and trends , 2010 .

[56]  Johanna J. Heymans,et al.  Can simple be useful and reliable? Using ecological indicators to represent and compare the states of marine ecosystems , 2010 .

[57]  J. Rice,et al.  Do explicit criteria help in selecting indicators for ecosystem-based fisheries management? , 2005 .

[58]  M. Edwards,et al.  Synchronous response of marine plankton ecosystems to climate in the Northeast Atlantic and the North Sea , 2014 .

[59]  Anne Chenuil,et al.  Quantitative criteria for choosing targets and indicators for sustainable use of ecosystems , 2017, Ecological indicators.

[60]  Jae S. Choi,et al.  Trophic Cascades in a Formerly Cod-Dominated Ecosystem , 2005, Science.

[61]  G. Daskalov,et al.  Trophic cascades triggered by overfishing reveal possible mechanisms of ecosystem regime shifts , 2007, Proceedings of the National Academy of Sciences.

[62]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .

[63]  K. Sasaoka,et al.  Temperature and zooplankton size structure: climate control and basin-scale comparison in the North Pacific , 2015, Ecology and evolution.

[64]  Vanessa Stelzenmüller,et al.  A benchmarking and assessment framework to operationalise ecological indicators based on time series analysis , 2015 .

[65]  C. Hsieh,et al.  Eutrophication and warming effects on long-term variation of zooplankton in Lake Biwa , 2011 .

[66]  Matthew K. Lau,et al.  How do ecologists select and use indicator species to monitor ecological change? Insights from 14 years of publication in Ecological Indicators , 2016 .

[67]  L. Bergström,et al.  Temporal development and spatial scale of coastal fish indicators in reference ecosystems: hydroclimate and anthropogenic drivers , 2017 .

[68]  B T Grenfell,et al.  Noisy Clockwork: Time Series Analysis of Population Fluctuations in Animals , 2001, Science.

[69]  S. T. Buckland,et al.  ANALYSIS OF POPULATION TRENDS FOR FARMLAND BIRDS USING GENERALIZED ADDITIVE MODELS , 2000 .

[70]  A. Mysterud,et al.  Modelling non–additive and nonlinear signals from climatic noise in ecological time series: Soay sheep as an example , 2004, Proceedings of the Royal Society of London. Series B: Biological Sciences.

[71]  Massimo Stafoggia,et al.  Spie charts, target plots, and radar plots for displaying comparative outcomes of health care. , 2011, Journal of clinical epidemiology.

[72]  V. Trenkel,et al.  Intersection–union tests for characterising recent changes in smoothed indicator time series , 2009 .

[73]  B. Menge,et al.  The Role of Indirect Effects in Food Webs , 1996 .

[74]  G. Beaugrand,et al.  Comparisons of zooplankton time series , 2010 .

[75]  C. Möllmann,et al.  Feeding ecology of central Baltic Sea herring and sprat , 2004 .

[76]  N. Swenson.  Functional and Phylogenetic Ecology in R , 2014 .

[77]  P. Levin,et al.  Integrated Ecosystem Assessments: Developing the Scientific Basis for Ecosystem-Based Management of the Ocean , 2009, PLoS biology.

[78]  S. Rogers,et al.  Indicators of the health of the North Sea fish community: identifying reference levels for an ecosystem approach to management , 2006 .

[79]  R. Tibshirani,et al.  Generalized additive models for medical research , 1986, Statistical methods in medical research.

[80]  M. Pace.  An empirical analysis of zooplankton community size structure across lake trophic gradients1 , 1986 .

[81]  M. Llope,et al.  Interactions among density, climate, and food web effects determine long-term life cycle dynamics of a key copepod , 2014 .

[82]  M. Casini,et al.  Food-web indicators accounting for species interactions respond to multiple pressures , 2017 .

[83]  Gerjan J. Piet,et al.  Surveillance indicators and their use in implementation of the Marine Strategy Framework Directive , 2015, ICES 2015.

[84]  Y. Shin,et al.  Relationships among fisheries exploitation, environmental conditions, and ecological indicators across a series of marine ecosystems , 2015 .

[85]  J. Rice,et al.  A framework for selecting a suite of indicators for fisheries management , 2005 .

[86]  Rodney M. Forster,et al.  Framework for understanding marine ecosystem health , 2013 .

[87]  Steven R. Hare,et al.  Empirical evidence for North Pacific regime shifts in 1977 and 1989 , 2000 .

[88]  Karen L. McLeod,et al.  Sea sick? Setting targets to assess ocean health and ecosystem services , 2012 .