Tag Archives: Remote Sensing

Examining the Spatial Relationships between Seascapes and Forage Fishes

Description of Research Question

My objective is to study the spatial relationships between sea-surface conditions and assemblages of forage fish in the California Current System from 1998 to 2015. Forage fish are a class of fishes that are of importance to humans and resource managers, as they serve as the main diet for economically and recreationally valuable large-game fishes. Using a combination of remotely sensed and in-situ data, sea-surface conditions can be classified into distinct classes, known as “seascapes,” that change gradually over time. These seascapes, which are based on a conglomeration of measurable oceanographic conditions, can be used to infer conditions within the water column. My goal is to determine if any relationship exists between forage fish assemblages and certain seascape classes by examining the changes in the spatial patterns related to each over time. Forage fish assemblage may be related to seascapes as certain seascape classes may correspond to physical (temperature) or biological (chlorophyll concentration) conditions, either on the surface or in the water column, which happen to be favorable for a specific species or group of species.

My question can be formatted as: “How is the spatial pattern of forage fish assemblage in the California Current System related to the spatial pattern of seascapes based on the sea-surface conditions used to classify the seascapes (temperature, salinity, and chlorophyll)?

Description of Data

Midwater trawls have been conducted annually by the National Oceanic and Atmospheric Administration’s (NOAA) Southwest Fisheries Science Center (SWFSC) in an attempt to monitor the recruitment of pelagic rockfish (Sebastes spp.) and other epipelagic micronekton at SWFSC stations off California. The trawls have informed a dataset that represents overall abundance of all midwater pelagic species that commonly reside along the majority of the nearshore coast of California from 1998 to 2015. Each trawl contains both fish abundance, recorded in absolute abundance, and location data, recorded in the form of latitude and longitude. The dataset also includes a breakdown of species by taxa, which will be used to determine if a fish is a “forage fish.”

Seascapes have been classified using a combination of in-situ data (from the trawls) and remotely sensed data from NASA’s MODIS program. Seascapes were classified using the methods described in Kavanaugh et al., 2014 and represent the seascape class in the immediate area that each trawl occurred. Seascapes are classified at 1 km and 4 km spatial resolution and at 8-day and monthly temporal resolution. Each seascape has been assigned an ID number which is used to identify similar conditions throughout the dataset.

The map below shows the locations of every trawl over the course of the study.

Figure 1: Map showing all trawl sites contained in the dataset. Trawls occurred at a consistent depth using consistent methods between and including the years of 1998 and 2015


I hypothesize that any measurable spatial changes in the spatial extend of certain seascape classes will also be identifiable in the spatial variability of forage fish assemblage over time. Preliminary multivariate community structure analysis has shown some statistically significant relationships between certain species and certain seascape classes using this data. If spatial patterns do exist, I expect there to be some relationship between the surface conditions and the fish found at depth of the midwater trawls.

Hypothesis: I expect the spatial distribution of forage fish species to be related to spatial distribution of seascape conditions based on the variables used to classify the seascapes (temperature, salinity, chlorophyll).

Potential Approaches

I hope to utilize the tools within both R and the ArcGIS Suite of products to identify and measure spatial patterns in both seascape classes and forage fish assemblages over the designated time period. I also aim to run analyses to determine if any relationship exists between the variability in spatial extent of each variable. These analyses will be used to supplement the previously completed multivariate community structure analyses done on these data.

For Exercise 1, I will identify and test for the spatial patterns of the forage fish family Gobiidae (Goby) and Seascape Class 10, as initial indicator species analyses indicated that there may be a relationship between the two. In Ex. 2, cross-correlation and/or GWR will examine relationships between these patterns.

Expected Outcome/Ideal Outcome

Ideally, I would like to determine and define the relationship between seascape classes and forage fishes in the California Current System over the designated period of time. Any sort of definitive answer, positive, negative, or none, provides valuable insight into the relationships between this remotely sensed data and these fishes. If that claim could be bolstered by a visual which outlines the relationship between my variables (or lack thereof), that would be icing on the theoretical cake.

Significance of Research

Measuring the predictability of forage fish assemblage has wide-ranging impacts and could be found useful by policymakers, fishermen, conservationists, and even members of the general public. Additionally, this research can be used to underscore the importance of seascape-based management or seascape approaches to ecology or management. This research could also be used as inspiration for future studies about different species, taxa, or geographic locations.

Level of Preparation

I completed a minor in GIS during my undergraduate studies, but have not had to utilize those skills for about 15 months. After some time, I believe that I will be extremely comfortable using the software. I have basic exposure to R software (mostly in the context of statistical analysis) and have used CodeAcademy to further my understanding of Python. I did some image processing during my undergraduate studies as well, but am not particularly comfortable with that set of skills. I have used leaflet to embed my maps and create time series before, so that could be an option for this work.


Kavanaugh M. T., Hales B., Saraceno M., Spitz Y.H., White A. E., Letelier R. M. 2014. Hierarchical and dynamic seascapes: A quantitative framework for scaling pelagic biogeochemistry and ecology, Progress in Oceanography, Volume 120, Pages 291-304, ISSN 0079-6611, https://doi.org/10.1016/j.pocean.2013.10.013.

Sakuma, K., Lindley, S. 2017. Rockfish Recruitment and Ecosystem Assessment Cruise Report.  United States Department of Commerce: National Oceanic and Atmospheric Administration, National Marine Fisheries Service.

-Willem Klajbor, 2019