Producing Distribution Maps for a Spatially-Explicit Ecosystem Model Using Large Monitoring and Environmental Databases and a Combination of Interpolation and Extrapolation

Abstract

To be able to simulate spatial patterns of predator-prey interactions, many spatially-explicit ecosystem modeling platforms, including Atlantis, need to be provided with distribution maps defining the annual or seasonal spatial distributions of functional groups and life stages. We developed a methodology combining extrapolation and interpolation of the predictions made by statistical habitat models to produce distribution maps for the fish and invertebrates represented in the Atlantis model of the Gulf of Mexico (GOM) Large Marine Ecosystem (LME) ("Atlantis-GOM"). This methodology consists of: (1) compiling a large monitoring database, gathering all the fisheries-independent and fisheries-dependent data collected in the northern (U.S.) GOM since 2000; (2) compiling a large environmental database, storing all the environmental parameters known to influence the spatial distribution patterns of fish and invertebrates of the GOM; (3) fitting binomial generalized additive models (GAMs) to the large monitoring and environmental databases, and geostatistical binomial generalized linear mixed models (GLMMs) to the large monitoring database; and (4) employing GAM predictions to infer spatial distributions in the southern GOM, and GLMM predictions to infer spatial distributions in the U.S. GOM. Thus, our methodology allows for reasonable extrapolation in the southern GOM based on a large amount of monitoring and environmental data, and for interpolation in the U.S. GOM accurately reflecting the probability of encountering fish and invertebrates in that region. We used an iterative cross-validation procedure to validate GAMs. When a GAM did not pass the validation test, we employed a GAM for a related functional group/life stage to generate distribution maps for the southern GOM. In addition, no geostatistical GLMMs were fit for the functional groups and life stages whose depth, longitudinal and latitudinal ranges within the U.S. GOM are not entirely covered by the data from the large monitoring database; for those, only GAM predictions were employed to obtain distribution maps for Atlantis-GOM. Pearson residuals were Grüss et al.Maps for an Ecosystem Model computed to validate geostatistical binomial GLMMs. Ultimately, 53 annual maps and 64 seasonal maps (for 32 different functional groups/life stages) were produced for Atlantis-GOM. Our methodology could serve other world's regions characterized by a large surface area, particularly LMEs bordered by several countries.

Shining a light on the composition and distribution patterns of mesophotic and subphotic fish communities in Hawai‘i

“…Additionally, when more data become available, seasonal distribution maps for relevant functional groups will also be very informative. Notwithstanding, the relative biomass maps generated in this study represent a valuable achievement, and will enhance the accuracy of simulated predator− prey dynamics, which form the basis of most ecosystem models (Grüss et al 2018b). If total biomass estimates (e.g.…”

“…From the survey data and literature, we determined the depth ranges of the functional groups. Then, from the 500 × 500 m spatial grid for the MHI, the environmental data used in this study and the estimated depth ranges of the functional groups, we created a prediction grid integrating environmental parameter values for each of the functional groups (Grüss et al 2018b).…”

Exploring spatio-temporal changes in the demersal and benthopelagic assemblages of the north-western Ionian Sea (central Mediterranean Sea)

“…Thus, these aggregations could be considered as units within which to identify functional groups useful in the framework of spatial modelling of marine food webs and ecosystems (e.g. Ecospace or Atlantis, Plaganyi 2007, Grüss et al 2018. Furthermore, the use of aggregation species for the assessment of the marine food web state, which is required by Descriptor 4 of the EU Marine Strategy Framework Directive (MSFD) (Tam et al 2017), and the indicator of species importance (such as IndVal) could be a sound method for the recognition of the most important species groups in a community to be used as indicators.…”

“…Regional diversity was then partitioned by species, sites, time and assemblages, allowing the identifica-tion of the main contributions relevant to characterize the biological community of the area. The analysis represents a basis for defining the aggregation criteria of species typical to the Mediterranean Sea to be considered, for example, for the definition of basic spatial aggregation units and functional groups in complex ecosystem models (Plaganyi 2007, Grüss et al 2018.…”

Prioritizing monitoring and conservation efforts for fish spawning aggregations in the U.S. Gulf of Mexico

“…In this study, we use the information on transient FSAs (hereafter usually called “FSAs”) compiled within the RESTORE project, and a large monitoring database compiled in previous studies 14 – 16 , to fit species distribution models (SDMs) and then map the distribution of potential FSA areas in the U.S. GOM. First, we employ the information on lengths at sexual maturity and spawning months compiled within the RESTORE project to extract relevant data from the large monitoring database.…”