Abstract
In the Mediterranean Sea, structured and standardized monitoring programs of marine resources were set only in the last decades, so the need to analyze changes in marine communities over longer time scale has to rely on different sources. In this work, we used seven decades (1945-2014) of disaggregated landing statistics for the Northern Adriatic Sea (Mediterranean) to infer changes in the ecosystem. Analysis of landings composition was enriched with the application of a suite of ecological indicators (e.g., trophodynamic indicators, such as the primary production required to sustain the catches - PPR; size-based indicators, such as the large species indicator - LSI; other indicators, such as the elasmobranchs-bony fish ratio – E/B ratio). Indicators were further compared with main ecosystem drivers, i.e., fishing capacity, nutrient loads and climate change. Species most vulnerable to fishing (i.e., elasmobranchs and large-sized species) dramatically declined at the beginning of the industrialization of fishery that occurred right afterwards World War II, as can be inferred by the negative drop of LSI and E/B ratio in the mid-1950s. However, until the mid-1980s landings and PPR increased due to improvements in fishing activities (e.g., the introduction of more efficient fishing gears) increasing fishing capacity, high productivity of the ecosystem. Overall, long-term effects of fishing were buffered by an increase in productivity in the period of high nutrient discharge (up to mid-1980s), but still drove significant changes in fish community structure. From the mid-1980s, a reduction in nutrient load caused a decline in productivity but the food-web structure was already modified and unable to support, or recover from, such unbalanced situation, resulting in the collapse of landings. This collapse is coherent with alternative stable states hypothesis, typical of complex real systems, that implies drastic interventions that go beyond fisheries management and include regulation of nutrient release for recovery. The work highlights that, despite poor capabilities to track species dynamics, landings and applied indicators might help to shed light on the long-term dynamics of marine communities, thus contributing to place current situation in an historical framework with potential for supporting management.
Highlights
Long-term analyses of the interactions between human society and the oceans are necessary for understanding the processes that brought the marine ecosystems as we see today, avoiding the so-called “shifting the baseline syndrome” and understanding the magnitude and causes of change (Pauly, 1995; Jackson et al, 2001)
Landings were dominated by small pelagics in all periods, with a percentage contribution ranging between 37% (SD: 8%; 1945–1954) and 68% (SD: 3%; 2009–2014)
In the first two periods, the third group in terms of biomass was medium pelagics that represented more than 10% of the landings [13% (SD: 4%) and 10% (SD: 6%), respectively], but medium pelagics declined in the following periods down to 1.1% (SD: 0.4%) in recent years (2009–2014)
Summary
Long-term analyses of the interactions between human society and the oceans are necessary for understanding the processes that brought the marine ecosystems as we see today, avoiding the so-called “shifting the baseline syndrome” and understanding the magnitude and causes of change (Pauly, 1995; Jackson et al, 2001). The need to bridge the gap between request of knowledge on past status of ecosystems and the available monitoring data, triggered the uses of different approaches to extract information from data coming from other sources, including paleontological, archeological, and historical sources, as well as the use of landings (e.g., Rosenberg et al, 2005; SàenzArroyo et al, 2005; Lotze et al, 2006; Fortibuoni et al, 2010, 2016; Van Beveren et al, 2016) In this context, detailed and disaggregated fishery statistics represent an important source of information that can be used as proxies to evaluate long-term changes in marine fisheries and communities. Catch statistics are recognized to be linked to fishing and environmental pressures and respond selectively to management action (Coll et al, 2016)
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