David Carter, Scott Crosson, and Christopher Liese in PLOS ONE:
We introduce a regression approach that uses information on fishery-related internet search volume to provide more timely intraseasonal predictions of recreational harvest. There is a growing literature showing that the internet search volume on a particular topic (e.g., unemployment insurance) can be used to predict current levels of policy-relevant variables (e.g., unemployment rates) [4]. Importantly, these predictions are not forecasts of future conditions, but rather “nowcasts” of current conditions. In the words of Choi and Varian [5] the goal is to “predict the present.” Nowcasting has value because traditional methods of compiling statistics from surveys or official records takes time. Any lag between the time that decision makers need information and the time that the information is available increases uncertainty, which increases the risk of poor decision making. If nowcasting can reduce this uncertainty, the quality of decisions can be improved [5–9]. Nowcasting attempts to arrive at an estimate sooner, but in no way replaces traditional methods, which remain the standard against which nowcasts are judged and continuously re-calibrated.
We demonstrate the harvest nowcasting approach with the Gulf of Mexico recreational red snapper fishery. This fishery has been particularly difficult to manage with progressively shortening seasons in the presence of changes in effort and an increasing average fish size. The recreational sector has overharvested red snapper in every year from 2007 to 2013 with the exception of 2010, when the Deepwater Horizon (DWH) oil spill forced a mandatory closure of prime fishing grounds during the busy summer season.
NOAA fisheries forecasts recreational harvest of red snapper and other key species several months in advance in order to set fishing seasons [10]. Forecasts are based on trends in historical catch rates and fish weight by fishing sector (private, for-hire). The agency does not regularly monitor the harvest of red snapper within the season because the season is shorter than the data reporting period. However, there have been times when managers reopened the fishery later in the year. In these cases there was a need for information on the cumulative level of harvest before the harvest data were available. For example, in 2013 following a new stock assessment, the recreational quota increased after the summer season closed and there was an interest in re-opening the season in the fall. In this case, there was a need to determine whether the new quota had been exceeded during the original season. Our proposed approach is designed to warn fishery managers of pending quota overages within the year by nowcasting harvest using a regression model including data on internet searches during the summer months when fishing activity peaks.
This may be a big contribution to a huge problem, at least for popular species. Imagine a recreational fishing harvest quota. The NMFS estimates harvest from the MRIP creel survey in two month waves over the fishing season. Data collection, entry and analysis takes time (especially relative to commercial fishing statistics with centralized reporting at dockside). By the time the NMFS figures out that the recreational quota has been it plenty of time has gone by so that the quota might be significantly exceeded.
Here is an image of the impressive results:
Here is the reference:
Carter DW, Crosson S, Liese C (2015) Nowcasting Intraseasonal Recreational Fishing Harvest with Internet Search Volume. PLoS ONE 10(9): e0137752.
