DOI: 10.5061/dryad.sf7m0cgmz
title: Data generated from: The role of fisheries management in enhancing the resistance of marine ecosystems to biological invasion

description: Biological invasion is one of the major threats to biodiversity, ecosystem
 health, and services worldwide. In marine ecosystems, invasions are
 difficult to monitor and control; thus, management strategies that can
 enhance biotic resistance are the key to tackle invasion risks. However,
 the biotic resistance of marine ecosystems is poorly understood with
 respect to the influencing factors and regulating mechanisms. We used an
 individual-based modelling approach to predict the potential risks of a
 biological invasion event from an ecosystem perspective, and tested how
 fishing as a driving factor of ecosystem structure can alter biotic
 resistance. We considered a species of high invasive risk globally,
 European green crab (Carcinus maenas) as an example, and evaluated its
 invasion risk in a heavily exploited ecosystem, Haizhou Bay, China.
 Further, we illustrated the role of fishery management to improve biotic
 resistance in order to inform the development of resistance-enhancing
 strategies. We found that the Haizhou Bay ecosystem would be vulnerable to
 the invasion of green crab, while reducing fishing intensity by half could
 effectively enhance its biotic resistance by decreasing the invasion
 success rate by up to 52 %. Alternatively, the reduced predation pressure
 experienced by juvenile C. maenas would largely contribute to successful
 invasions. Fishing activities could regulate the predation pressure by
 changing predator biomass and trophic links within the ecosystem, and
 thereby alter the biotic resistance to invasion. We further designed a
 range of simplified management strategies that controlled the fishing
 efforts on selected predators, and illustrated their effectiveness to
 enhance biotic resistance. These strategies could mediate the trade-offs
 between fisheries production and ecosystem management to a certain degree.
 We validated the predation-based hypothesis of biotic resistance in marine
 ecosystems, and illustrated that fishery management can enhance biotic
 resistance by changing ecosystem structure. Based on this mechanism,
 fishery management strategies could simultaneously enhance biotic
 resistance and reduce management conflicts. We proposed an IBM-based
 framework as a comprehensive assessment tool that holding significant
 potential for developing precautionary management strategies.
description: # Data generated from: The role of fisheries management in enhancing the
 resistance of marine ecosystems to biological invasion Dataset DOI:
 [10.5061/dryad.sf7m0cgmz](https://doi.org/10.5061/dryad.sf7m0cgmz) ##
 Description of the data and file structure This dataset contains the data
 used to generate the figures in the manuscript, which were produced during
 our simulation procedures. ### Files and variables #### File:
 1.res_invasion_rate.csv **Description:** Invasion success rates under
 different fishing intensity scenarios ##### Variables * Scenario: Five
 fishing intensity scenarios * Invasion_intensity: Three introduced
 biomass scenarios * n: Number of successful invasions * Rate: Invasion
 success rate * changeF: Relative changes in fishing mortality #### File:
 3.res_predation_pressure_bySce.csv **Description:** Predation pressure
 under different fishing intensity scenarios ##### Variables *
 Scenario: Five fishing intensity scenarios * Predator: Predators of *C.
 maenas* * Mean: Biomass of *C. maenas* consumed by the predators (mean
 value across 100 simulations) * SD: Biomass of *C. maenas* consumed by the
 predators (SD value across 100 simulations) #### File:
 4.res_management.csv **Description:** The performance of alternative
 management strategies ##### Variables * F: Five fishing intensity
 scenarios * Invasion_intensity: Three introduced biomass scenarios * n:
 Number of successful invasions * Rate: Invasion success rate * changeF:
 Relative changes in fishing mortality * Predator: Management strategies
 (managing All species, Main predators, 2 predators, 1predator) #### File:
 2.res_mortality_bySce.csv **Description:** Mortality rates under
 different fishing intensity scenarios ##### Variables * Scenario: Five
 fishing intensity scenarios * Mean: Mortality (Mean value across 100
 simulations) * SD: Mortality (SD value across 100 simulations) * Year:
 Simulation time * Period: Life history stage of *C. maenas* * Type: Type
 of mortality (Predation mortality or Starvation mortality) * Invasion:
 Successful invasion or Failed invasion #### File: 5.res_SA.csv
 **Description:** Result of sensitivity analysis ##### Variables *
 Parameters: Studied parameters for sensitivity analysis * change: Relative
 changes in the parameters * rate: Invasion success rates * bio:
 Equilibrium biomass of *C. maenas* after invasion success (Mean value
 across 100 simulations) * sd_bio: Equilibrium biomass of *C. maenas* after
 invasion success (SD value across 100 simulations) ## Code/software
 Simulation and data process were performed using R (version 4.2.1).