EcoService Models Library (ESML)
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Which comparison is best for me?EM Variables by Variable Role
One quick way to compare ecological models (EMs) is by comparing their variables. Predictor variables show what kinds of influences a model is able to account for, and what kinds of data it requires. Response variables show what information a model is capable of estimating.
This first comparison shows the names (and units) of each EM’s variables, side-by-side, sorted by variable role. Variable roles in ESML are as follows:
- Predictor Variables
- Time- or Space-Varying Variables
- Constants and Parameters
- Intermediate (Computed) Variables
- Response Variables
- Computed Response Variables
- Measured Response Variables
EM Variables by Category
A second way to use variables to compare EMs is by focusing on the kind of information each variable represents. The top-level categories in the ESML Variable Classification Hierarchy are as follows:
- Policy Regarding Use or Management of Ecosystem Resources
- Land Surface (or Water Body Bed) Cover, Use or Substrate
- Human Demographic Data
- Human-Produced Stressor or Enhancer of Ecosystem Goods and Services Production
- Ecosystem Attributes and Potential Supply of Ecosystem Goods and Services
- Non-monetary Indicators of Human Demand, Use or Benefit of Ecosystem Goods and Services
- Monetary Values
Besides understanding model similarities, sorting the variables for each EM by these 7 categories makes it easier to see if the compared models can be linked using similar variables. For example, if one model estimates an ecosystem attribute (in Category 5), such as water clarity, as a response variable, and a second model uses a similar attribute (also in Category 5) as a predictor of recreational use, the two models can potentially be used in tandem. This comparison makes it easier to spot potential model linkages.
All EM Descriptors
This selection allows a more detailed comparison of EMs by model characteristics other than their variables. The 50-or-so EM descriptors for each model are presented, side-by-side, in the following categories:
- EM Identity and Description
- EM Modeling Approach
- EM Locations, Environments, Ecology
- EM Ecosystem Goods and Services (EGS) potentially modeled, by classification system
EM Descriptors by Modeling Concepts
This feature guides the user through the use of the following seven concepts for comparing and selecting EMs:
- Conceptual Model
- Modeling Objective
- Modeling Context
- Potential for Model Linkage
- Feasibility of Model Use
- Model Certainty
- Model Structural Information
Though presented separately, these concepts are interdependent, and information presented under one concept may have relevance to other concepts as well.
Compare Criteria:
Show Criteria
Hide CriteriaEM Identity and Description
EM Identification
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EM ID
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EM-184 |
EM-541 
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EM-661
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EM-836 | EM-904 |
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EM Short Name
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ROS (Recreation Opportunity Spectrum), Europe | InVEST fisheries, lobster, South Africa | Alwife phosphorus flux in lakes, Connecticut, USA | Bird abundance on restored landfills, UK | Drag coefficient Laminaria hyperborea |
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EM Full Name
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ROS (Recreation Opportunity Spectrum), Europe | Integrated Valuation of Ecosystem Services and Trade-offs Fisheries, rock lobster, South Africa | Net phosphorus flux in freshwater lakes from alewives, Connecticut, USA | Bird abundance on restored landfills compared to paired reference sites, East Midlands, UK | Drag coefficient Laminaria hyperborea |
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EM Source or Collection
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EU Biodiversity Action 5 | InVEST | None | None | None |
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EM Source Document ID
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293 |
349 ?Comment:Supplemented with the InVEST Users Guide fisheries. |
383 | 406 | 424 |
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Document Author
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Paracchini, M.L., Zulian, G., Kopperoinen, L., Maes, J., Schägner, J.P., Termansen, M., Zandersen, M., Perez-Soba, M., Scholefield, P.A., and Bidoglio, G. | Ward, Michelle, Hugh Possingham, Johathan R. Rhodes, Peter Mumby | West, D. C., A. W. Walters, S. Gephard, and D. M. Post | Rahman, M. L., S. Tarrant, D. McCollin, and J. Ollerton | Mendez, F. J. and I. J. Losada |
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Document Year
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2014 | 2018 | 2010 | 2011 | 2004 |
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Document Title
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Mapping cultural ecosystem services: A framework to assess the potential for outdoor recreation across the EU | Food, money and lobsters: Valuing ecosystem services to align environmental management with Sustainable Development Goals | Nutrient loading by anadromous alewife (Alosa pseudoharengus): contemporary patterns and predictions for restoration efforts | The conservation value of restored landfill sites in the East Midlands, UK for supporting bird communities in the East Midlands, UK for supporting bird communities | An empirical model to estimate the propagation of random breaking and nonbreaking waves over vegetation fields |
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Document Status
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Peer reviewed and published | Peer reviewed and published | Peer reviewed and published | Peer reviewed and published | Peer reviewed and published |
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Comments on Status
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Published journal manuscript | Published journal manuscript | Published journal manuscript | Published journal manuscript | Published journal manuscript |
Software and Access
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EM ID
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EM-184 |
EM-541
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EM-661
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EM-836 | EM-904 |
| Not applicable | https://www.naturalcapitalproject.org/invest/ | Not applicable | Not applicable | Not applicable | |
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Contact Name
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Maria Luisa Paracchini | Michelle Ward | Derek C. West | Lutfor Rahman | F. J. Mendez |
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Contact Address
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Joint Research Centre, Institute for Environment and Sustainability, Via E.Fermi, 2749, I-21027 Ispra (VA), Italy | ARC Centre of Excellence for Environmental Decisions, The University of Queensland, Brisbane, QLD 4072, Australia | Dept. of Ecology and Evolutionary Biology, Yale University, 165 Prospect Street, New Haven, CT 06511, USA | Landscape and Biodiversity Research Group, School of Science and Technology, The University of Northampton, Avenue Campus, Northampton NN2 6JD, UK | Not reported |
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Contact Email
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luisa.paracchini@jrc.ec.europa.eu | m.ward@uq.edu.au | derek.west@yale.edu | lutfor.rahman@northampton.ac.uk | mendezf@unican.es |
EM Description
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EM ID
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EM-184 |
EM-541
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EM-661
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EM-836 | EM-904 |
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Summary Description
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ABSTRACT: "Research on ecosystem services mapping and valuing has increased significantly in recent years. However, compared to provisioning and regulating services, cultural ecosystem services have not yet beenfully integrated into operational frameworks. One reason for this is that transdisciplinarity is required toaddress the issue, since by definition cultural services (encompassing physical, intellectual, spiritual inter-actions with biota) need to be analysed from multiple perspectives (i.e. ecological, social, behavioural).A second reason is the lack of data for large-scale assessments, as detailed surveys are a main sourceof information. Among cultural ecosystem services, assessment of outdoor recreation can be based ona large pool of literature developed mostly in social and medical science, and landscape and ecologystudies. This paper presents a methodology to include recreation in the conceptual framework for EUwide ecosystem assessments (Maes et al., 2013), which couples existing approaches for recreation man-agement at country level with behavioural data derived from surveys and population distribution data.The proposed framework is based on three components: the ecosystem function (recreation potential),the adaptation of the Recreation Opportunity Spectrum framework to characterise the ecosystem serviceand the distribution of potential demand in the EU." | AUTHOR'S DESCRIPTION: "Here we develop a method for assessing future scenarios of environmental management change that improve coastal ecosystem services and thereby, support the success of the SDGs. We illustrate application of the method using a case study of South Africa’s West Coast Rock Lobster fishery within the Table Mountain National Park (TMNP) Marine Protected Area...We calculated the retrospective and current value of the West Coast Rock Lobster fishery using published and unpublished data from various sources and combined the market worth of landed lobster from recreational fishers, small-scale fisheries (SSF), large-scale fisheries (LSF) and poachers. Then using the InVEST tool, we combined data to build scenarios that describe possible futures for the West Coast Rock Lobster fishery (see Table 1). The first scenario, entitled ‘Business as Usual’ (BAU), takes the current situation and most up-to-date data to model the future if harvest continues at the existing rate. The second scenario is entitled ‘Redirect the Poachers’ (RP), which attempts to model implementation of strict management, whereby poaching is minimised from the Marine Protected Area and other economic and nutritional sources are made available through government initiatives. The third scenario, entitled ‘Large Scale Cutbacks’ (LSC), excludes large-scale fisheries from harvesting West Coast Rock Lobster within the TMNP Marine Protected Area." | ABSTRACT: "Anadromous alewives (Alosa pseudoharengus) have the potential to alter the nutrient budgets of coastal lakes as they migrate into freshwater as adults and to sea as juveniles. Alewife runs are generally a source of nutrients to the freshwater lakes in which they spawn, but juveniles may export more nutrients than adults import in newly restored populations. A healthy run of alewives in Connecticut imports substantial quantities of phosphorus; mortality of alewives contributes 0.68 g P_fish–1, while surviving fish add 0.18 g P, 67% of which is excretion. Currently, alewives contribute 23% of the annual phosphorus load to Bride Lake, but this input was much greater historically, with larger runs of bigger fish contributing 2.5 times more phosphorus in the 1960s..." AUTHOR'S DESCRIPTION: "Here, we evaluate the patterns of net nutrient loading by alewives over a range of population sizes. We concentrate on phosphorus, as it is generally the nutrient that limits production in the lake ecosystems in which alewives spawn (Schindler 1978). First, we estimate net alewife nutrient loading and parameterize an alewife nutrient loading model using data from an existing run of anadromous alewives in Bride Lake. We then compare the current alewife nutrient load to that in the 1960s when alewives were more numerous and larger. Next, since little is known about the actual patterns of nutrient loading during restoration, we predict the net nutrient loading for a newly restored population across a range of adult escapement… Anadromous fish move nutrients both into and out of freshwater ecosystems, although inputs are typically more obvious and much better studied (Moore and Schindler 2004). Net loading into freshwater ecosystems is fully described as inputs due to adult mortality, gametes, and direct excretion of nutrients minus the removal of nutrients from freshwater ecosystems by juvenile fish when they emigrate… Our research was conducted at Bride Lake and Linsley Pond in Connecticut. Bride Lake contains an anadromous alewife population that we used to both evaluate contemporary and historic net nutrient loading by an alewife population and parameterize our general alewife nutrient loading model." | ABSTRACT: "There has been a rapid decline of grassland bird species in the UK over the last four decades. In order to stem declines in biodiversity such as this, mitigation in the form of newly created habitat and restoration of degraded habitats is advocated in the UK biodiversity action plan. One potential restored habitat that could support a number of bird species is re-created grassland on restored landfill sites. However, this potential largely remains unexplored. In this study, birds were counted using point sampling on nine restored landfill sites in the East Midlands region of the UK during 2007 and 2008. The effects of restoration were investigated by examining bird species composition, richness, and abundance in relation to habitat and landscape structure on the landfill sites in comparison to paired reference sites of existing wildlife value. Twelve bird species were found in total and species richness and abundance on restored landfill sites was found to be higher than that of reference sites. Restored landfill sites support both common grassland bird species and also UK Red List bird species such as skylark Alauda arvensis, grey partridge Perdix perdix, lapwing Vanellus vanellus, tree sparrow, Passer montanus, and starling Sturnus vulgaris. Size of the site, percentage of bare soil and amount of adjacent hedgerow were found to be the most influential habitat quality factors for the distribution of most bird species. Presence of open habitat and crop land in the surrounding landscape were also found to have an effect on bird species composition. Management of restored landfill sites should be targeted towards UK Red List bird species since such sites could potentially play a significant role in biodiversity action planning." AUTHOR'S DESCRIPTION: "Mean number of birds from multiple visits were used for data analysis. To analyse the data generalized linear models (GLMs) were constructed to compare local habitat and landscape parameters affecting different species, and to establish which habitat and landscape characteristics explained significant changes in the frequency of occurrence for each species. To ensure analyses focused on resident species, habitat associations were modelled for those seven bird species which were recorded at least three times in the surveys. The analysis was carried out with the software R (R Development Core Team 2003). Nonsignificant predictors (independent variables) were removed in a stepwise manner (least significant factor first). For distribution pattern of bird species, data were initially analysed using detrended correspondence analysis. Redundancy analysis (RDA) was performed on the same data using CANOCO for Windows version 4.0 (ter Braak and Smilauer 2002)." | ABSTRACT: "In this work, a model for wave transformation on vegetation fields is presented. The formulation includes wave damping and wave breaking over vegetation fields at variable depths. Based on a nonlinear formulation of the drag force, either the transformation of monochromatic waves or irregular waves can be modelled considering geometric and physical characteristics of the vegetation field. The model depends on a single parameter similar to the drag coefficient, which is parameterized as a function of the local Keulegan–Carpenter number for a specific type of plant. Given this parameterization, determined with laboratory experiments for each plant type, the model is able to reproduce the root-mean-square wave height transformation observed in experimental data with reasonable accuracy." AUTHOR'S DESCRIPTION: "Therefore, a relation between C˜D and some nondimensional flow parameters is desirable to characterize hydrodynamically the L. hyperborea model plants for predictable purposes." |
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Specific Policy or Decision Context Cited
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None identified | Future rock lobster fisheries management | Restoration and management of diadromous fish runs in coastal New England | None identified | None identified |
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Biophysical Context
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No additional description provided | No additional description provided | Bride Lake is 28.7 ha and linked to Long Island Sound by the 3.3 km Bride Brook. | The study area covered mainly Northamptonshire and parts of Bedfordshire, Buckinghamshire and Warwickshire, ranging from 51o58’44.74” N to 52o26’42.18” N and 0o27’49.94” W to 1o19’57.67” W. This region has countryside of low, undulating hills separated by valleys and lies entirely within the great belt of scarplands formed by rocks of Jurassic age which stretch across England from Yorkshire to Dorset (Beaver 1943; Sutherland 1995; Wilson 1995). | No additional description provided |
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EM Scenario Drivers
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No scenarios presented | Fisheries exploitation; fishing vulnerability (of age classes) | current and historical run size | No scenarios presented | No scenarios presented |
EM Relationship to Other EMs or Applications
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EM ID
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EM-184 |
EM-541
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EM-661
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EM-836 | EM-904 |
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Method Only, Application of Method or Model Run
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Method + Application | Method + Application (multiple runs exist) View EM Runs | Method + Application (multiple runs exist) View EM Runs | Method Only | Method + Application |
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New or Pre-existing EM?
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Application of existing model | Application of existing model | New or revised model | New or revised model | New or revised model |
Related EMs (for example, other versions or derivations of this EM) described in ESML
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EM ID
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EM-184 |
EM-541
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EM-661
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EM-836 | EM-904 |
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Document ID for related EM
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Doc-290 | Doc-291 | Doc-289 | None | None | None | Doc-424 |
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EM ID for related EM
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None | None | EM-667 | EM-672 | EM-674 | EM-673 | EM-837 | EM-896 | EM-897 |
EM Modeling Approach
EM Relationship to Time
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EM ID
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EM-184 |
EM-541
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EM-661
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EM-836 | EM-904 |
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EM Temporal Extent
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Not reported | 1986-2115 | 1960"s and early 2000's | Not applicable | Not applicable |
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EM Time Dependence
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time-stationary | time-dependent | time-stationary | time-stationary | Not applicable |
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EM Time Reference (Future/Past)
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Not applicable | future time | Not applicable | Not applicable | Not applicable |
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EM Time Continuity
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Not applicable | discrete | Not applicable | Not applicable | Not applicable |
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EM Temporal Grain Size Value
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Not applicable | 1 | Not applicable | Not applicable | Not applicable |
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EM Temporal Grain Size Unit
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Not applicable | Year | Not applicable | Not applicable | Not applicable |
EM Spatial Extent
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EM ID
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EM-184 |
EM-541
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EM-661
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EM-836 | EM-904 |
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Bounding Type
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Geopolitical | Geopolitical | Watershed/Catchment/HUC | Multiple unrelated locations (e.g., meta-analysis) | Not applicable |
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Spatial Extent Name
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European Union countries | Table Mountain National Park Marine Protected Area | Bride Lake and Linsley Pond | East Midland | Not applicable |
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Spatial Extent Area (Magnitude)
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>1,000,000 km^2 | 100-1000 km^2 | 10-100 ha | 1000-10,000 km^2. | Not applicable |
Spatial Distribution of Computations
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EM ID
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EM-184 |
EM-541
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EM-661
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EM-836 | EM-904 |
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EM Spatial Distribution
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spatially distributed (in at least some cases) | spatially lumped (in all cases) | spatially lumped (in all cases) | spatially distributed (in at least some cases) | spatially lumped (in all cases) |
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Spatial Grain Type
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area, for pixel or radial feature | Not applicable | Not applicable | other (specify), for irregular (e.g., stream reach, lake basin) | Not applicable |
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Spatial Grain Size
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100 m x 100 m | Not applicable | Not applicable | multiple unrelated sites | Not applicable |
EM Structure and Computation Approach
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EM ID
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EM-184 |
EM-541
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EM-661
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EM-836 | EM-904 |
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EM Computational Approach
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Analytic | Numeric | Analytic | Analytic | Analytic |
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EM Determinism
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deterministic | deterministic | deterministic | deterministic | deterministic |
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Statistical Estimation of EM
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Model Checking Procedures Used
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EM ID
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EM-184 |
EM-541
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EM-661
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EM-836 | EM-904 |
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Model Calibration Reported?
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No | No | Yes | Not applicable | Yes |
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Model Goodness of Fit Reported?
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No | No | No | Not applicable | Not applicable |
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Goodness of Fit (metric| value | unit)
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None | None | None | None | None |
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Model Operational Validation Reported?
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No |
Yes ?Comment:A validation analysis was carried out running the model using data from 1880 to 2001, and then comparing the output for the adult population with the 2001 published data. |
No | Not applicable | Unclear |
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Model Uncertainty Analysis Reported?
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No | No | No | Not applicable | No |
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Model Sensitivity Analysis Reported?
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No | No | Yes | Not applicable | No |
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Model Sensitivity Analysis Include Interactions?
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Not applicable | Not applicable | Unclear | Not applicable | Not applicable |
EM Locations, Environments, Ecology
Location of EM Application
Terrestrial location (Classification hierarchy: Continent > Country > U.S. State [United States only])
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| EM-184 |
EM-541
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EM-661
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EM-836 | EM-904 |
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None |
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None |
Marine location (Classification hierarchy: Realm > Region > Province > Ecoregion)
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| EM-184 |
EM-541
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EM-661
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EM-836 | EM-904 |
| None |
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None | None |
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Centroid Lat/Long (Decimal Degree)
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EM ID
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EM-184 |
EM-541
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EM-661
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EM-836 | EM-904 |
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Centroid Latitude
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48.2 | -34.18 | 41.33 | 52.22 | Not applicable |
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Centroid Longitude
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16.35 | 18.35 | -72.24 | -0.91 | Not applicable |
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Centroid Datum
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WGS84 | WGS84 | WGS84 | WGS84 | Not applicable |
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Centroid Coordinates Status
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Estimated | Provided | Estimated | Estimated | Not applicable |
Environments and Scales Modeled
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EM ID
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EM-184 |
EM-541
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EM-661
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EM-836 | EM-904 |
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EM Environmental Sub-Class
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Terrestrial Environment (sub-classes not fully specified) | Near Coastal Marine and Estuarine | Rivers and Streams | Lakes and Ponds | Created Greenspace | Grasslands | Near Coastal Marine and Estuarine |
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Specific Environment Type
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Not applicable | Rocky coast, mixed coast, sandy coast, rocky inshore, sandy inshore, rocky shelf and unconsolidated shelf | Coastal lakes and ponds and associated streams | restored landfills and conserved grasslands | Near Coastal Marine and Estuarine |
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EM Ecological Scale
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Ecological scale is finer than that of the Environmental Sub-class | Ecological scale corresponds to the Environmental Sub-class | Ecological scale corresponds to the Environmental Sub-class | Ecological scale corresponds to the Environmental Sub-class | Ecological scale corresponds to the Environmental Sub-class |
Scale and taxa of organisms modeled
Scale of differentiation of organisms modeled
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EM ID
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EM-184 |
EM-541
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EM-661
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EM-836 | EM-904 |
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EM Organismal Scale
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Not applicable | Individual or population, within a species | Individual or population, within a species | Individual or population, within a species | Species |
Taxonomic level and name of organisms or groups identified
taxonomyHelp
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| EM-184 |
EM-541
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EM-661
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EM-836 | EM-904 |
| None Available |
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EnviroAtlas URL
EM Ecosystem Goods and Services (EGS) potentially modeled, by classification system
CICES v 4.3 - Common International Classification of Ecosystem Services (Section > Division > Group > Class)
em.detail.cicesHelp
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| EM-184 |
EM-541
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EM-661
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EM-836 | EM-904 |
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<a target="_blank" rel="noopener noreferrer" href="https://www.epa.gov/eco-research/national-ecosystem-services-classification-system-nescs-plus">National Ecosystem Services Classification System (NESCS) Plus</a>
fegs1Help
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(Environmental Subclass > Ecological End-Product (EEP) > EEP Subclass > EEP Modifier)
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| EM-184 |
EM-541
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EM-661
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EM-836 | EM-904 |
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None | None | None |