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Findings

Understanding the Resource System

MultiTip conducted an analysis of the Lake Victoria resource system with the goal of contributing to knowledge on tipping points and on socio-ecological systems (SES).

Lv Sunset
Sunset at Lake Victoria.

To understand the resource system, our researchers developed a mathematical tipping point concept for Lake Victoria, combined data with mathematical models for fisheries management and modeled the spatiality of the resource system. 

A Tipping Point Concept for Lake Victoria

Data Model Integration in Fisheries Research

Spatiality of the Resource System

 

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A Tipping Point Concept for Lake Victoria

Tipping points are an important property of many complex SESs like the Lake Victoria Nile perch fishery. Understanding the occurrence of tipping points in both experimental and empirical settings is important for the sustainable management of an SES.

To this end, we developed a mathematically rigorous, general, analytical and operationalized tipping point concept for the Lake Victoria resource system. We call this concept the subcritical bifurcation of system dynamics . It is applied to the single-species Nile perch context, which constitutes a first capstone of the project.Behind this deliverable stands an important shift that MultiTip has set into motion in modeling the Lake Victoria resource system: moving from computational box models with merely computed trajectories to more analytical approaches that emphasize system characteristics like stable equilibria, regime shifts and tipping points.The subcritical bifurcation of system dynamics can be used to identify tipping points in corresponding mathematical models. It also enables an understanding of which non-linear components of the model cause the phenomenon and which types of feedback should be examined. Thus, it is used to improve the understanding of the SES and of the corresponding decision-making processes.

Researchers: Prof. Dr. Anna Marciniak-Czochra , Johannes Kammerer (Ph.D. Candidate)

Publication: Marciniak-Czochra, A. (2021). Mathematical models for tipping points. In: Boutrus, M., Nussel, F. (eds.): Forum Marsilius Kolleg 19, 139-143. doi:10.11588/fmk.2021.0.78677

 

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Data Model Integration in Fisheries Research

A common approach of studying lake management in agent-based models is to treat social processors and decision-making about resource use as external factors (Martin & Schülter, 2015). However, to improve management, it is crucial to recognize the dynamics in a coupled SES. This requires methods to account for how humans are shaping and shaped by the ecosystem they interact with (Folke, 2006).

MultiTip has succeeded in this critical task by integrating socio-ecological survey data with new analytical models of the resource system. This was done using the spectrum slope of the fish size distribution as a management-relevant integration point. We were able to adjudicate between conflicting survey evidence by using the model to structure the four sets of survey data (Catch Assessment Survey, Frame Survey, Hydro-acoustic Survey, Bottom-Trawl Survey). Moreover, this data was used to calibrate the analytical model for the Nile perch with optimization and Bayesian inference (Edwards et al., 2017; Miles, 2019).

Resource system Fig1
(Click to enlarge)
Empirical size distribution of the Nile perch population in Uganda, Tanzania and Kenya from the Hydro-acoustic Survey, 2020

This constitutes a breakthrough in the analysis and interpretation of size-based fish population data at Lake Victoria and its rigorous integration into a state-of-the-art numerical stock model. We also identified the spectrum slope as a key management indicator of population health and reproductive potential (Blanchard et al., 2014; Diekert et al., 2010) which is critical for system stability. From the spectrum slope, we then simulated how fishing selectively translates to catches.

Resource system Fig2
(Click to enlarge)
Simulation of the fishery with the empirical fleet selectivity and the effect of the fishing pressure on the size distribution of the fish stock (top) and on the size distribution of the catch (bottom). Gray shaded rectangles indicate the range of legal fishing size (50-85cm). With higher fishing pressure (increasing from black to gray) the spectrum slope becomes more negative (top) and the catch distribution shifts towards smaller fish (bottom).

Researchers: Prof. Timo Goeschl, Ph.D. , Prof Dr Anna Marciniak-Czochra , Johannes Kammerer (Ph.D. Candidate)

Partners: Dr. Robert Jeremiah Kayanda (LVFO) , Dr. Chrisphine Nyamweya (KMFRI)

 

 

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Spatiality of the Resource System

Over-exploitation of the Nile perch fishery, coupled with difficulties in fisheries management, should result in depletion of the fish stock and consequently, a fall in productivity. However, the fishery has maintained a consistent overall productivity over the last decade (Kolding et al., 2014). There is no consensus on the reasons for this relative stability. For a better understanding of the resource system, MultiTip examines the effect of the spatiality of the system on the ability of fishers to exploit the resource (Gómez-Cardona, 2022). We find that the Lake's spatial dimensions (both size and shape) have surprising socio-ecological consequences.

Our model shows that there is an imbalance between the fish stock distribution and the fishing fleet's ability to access and profit from it. Lake Victoria's sheer size, combined with its shallowness, creates fish habitats that are distant from the shore (some more than 70km). Furthermore, despite the localized competition for fish (Peter and van Zwieten, 2018), the spatial pattern of most of the fleet is close to the shore. This is because Lake Victoria is both large in size and nearly circular in shape which implies that most artisanal fishing that is done close to the lakes center is economically unprofitable given fishing technology, fuel cost and fish prices. Therefore, the spatial dimensions of the resource system plays an important role in maintaining its productivity.

Resource system Fig3
A spatial model showing fishing effort distribution in Lake Victoria. Real fish-stock distribution data is used.
Fishing effort is divided into three boat categories: yellow for paddle boats, blue for motor boats and green for motor boats that make multiple-day fishing trips. The figure shows that fishing is mostly concentrated near the shore. Large areas of the lake are not exploited.

Researchers: Dr. Santiago Gomez-Cardona

Publication: Gómez-Cardona, S., 2022, Spatial Structure effects on Fisheries Management for Lake Victoria's Nile Perch. AWI Discussion Paper 713, Heidelberg University. https://doi.org/10.11588/heidok.00031342  

 

 

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References:

Blanchard, JL, Andersen, KH, Scott, F, Hintzen, NT, Piet, G, and Jennings, S (2014). Evaluating targets and trade-offs among fisheries and conservation objectives using a multi-species size spectrum model. Journal of Applied Ecology, 51(3):612-622.

Diekert, FK, Hjermann, D. Ø., Nævdal, E., and Stenseth, NC (2010). Spare the young fish: optimal harvesting policies for north-east arctic cod. Environmental and Resource Economics, 47(4):455-475.

Edwards, AM, Robinson, JP, Plank, MJ, Baum, JK, and Blanchard, JL (2017). Testing and recommending methods for fitting size spectra to data. Methods in Ecology and Evolution, 8(1):57-67.

Folke, C. (2006). Resilience: The emergence of a perspective for social-ecological systems analyses. Global Environmental Change, 16(3), 253-267. https://doi.org/10.1016/j.gloenvcha.2006.04.002

Kolding, J., Medard, M., Mkumbo, O., and van Zwieten, P. (2014). Status, trends and management of the Lake Victoria Fisheries. Inland Fisheries Evolution and Management—Case Studies from Four Continents. FAO Fisheries and Aquaculture Technical Paper, 579.

Martin, R., & Schlueter, M. (2015). Combining system dynamics and agent-based modeling to analyze social-ecological interactions—an example from modeling restoration of a shallow lake. Frontiers in Environmental Science, 3(October), 1-15. https://doi.org/10.3389/fenvs.2015.00066

Miles, PR (2019). pymcmcstat: A python package for bayesian inference using delayed rejection adaptive metropolis. Journal of Open Source Software, 4(38):1417.

Peter, HK and van Zwieten, PA (2018). Operational, environmental, and resource productivity factors driving spatial distribution of gillnet and longline fishers targeting nile-perch (lates niloticus), lake victoria. Journal of Great Lakes Research, 44(6):1235-1251.

 

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Updated on: 23.08.2022
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