{"id":3147,"date":"2018-03-21T09:26:46","date_gmt":"2018-03-21T09:26:46","guid":{"rendered":"http:\/\/ar17.iiasa.ac.at\/?p=3147"},"modified":"2018-04-19T08:56:53","modified_gmt":"2018-04-19T07:56:53","slug":"threats-to-ecosystems","status":"publish","type":"post","link":"https:\/\/ar17.iiasa.ac.at\/threats-to-ecosystems\/","title":{"rendered":"Ecological network analysis reveals systemic impact of threats to ecosystems"},"content":{"rendered":"

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Ecological network analysis provides a systematic approach to assess the direct and indirect influences that one network node has on another. Researchers from the IIASA Advanced Systems Analysis Program engage in projects to develop these methodologies further and to explore new applications<\/strong>.<\/p>\n

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As part of the Southern African Young Scientists Summer Program<\/a> (SA-YSSP), IIASA researchers conducted systems analysis on a food web ecosystem in an estuary near Durban, South Africa [1]. The food web was analyzed using a novel methodology to identify keystone species (i.e., organisms that play a unique and crucial role in the way an ecosystem functions). The importance of a species was measured by the degree to which it influences other species or functional groups. While other keystone measures focus on the overall influence, this method differs because of a biomass-normalization that removes the bias of larger biomass compartments (i.e., the total quantity or weight of organisms in a given area) such as phytoplankton and detritus. This approach highlights the ecosystem interactions of smaller, typically top predator species. The results revealed that several predatory fish groups exhibited strong top-down control on the ecosystem. The research also utilized a unique time series dataset that allowed for investigation of changes in the food web during different seasons and different hydrological conditions. The study concluded that the ecosystem, in terms of the keystone species, remained resistant to these changes and other imposed disturbances.<\/p>\n

Another network project undertaken during the Young Scientists Summer Program<\/a>, and subsequently awarded the Peccei Award, employed a novel \u201cnetworks of networks\u201d approach that utilized both social and ecological network data [2]. A series of 19 reservoirs in Nebraska, USA, were studied to determine the spread of an invasive snail species. Food webs for each of the reservoirs were constructed based on collected field data. The invasive species were identified in five reservoirs. These reservoirs were considered contagious, as it was known that the snails could be spread to other reservoirs by anglers. Social network data showed how anglers moved from one reservoir to another based on their fishing preferences\u2013where they had last fished and where they intended to fish next. The snails attach themselves to boats and in this way have a chance of being transported to other reservoirs. Hence, researchers considered the uninfected reservoirs susceptible to invasion. Once the species were introduced to a new reservoir by anglers moving between the different bodies of water, the reservoir was \u201cinfected\u201d and the food web model in that reservoir would change as a result of the invaders\u2019 feeding patterns. At some point, the snail population in the newly infected reservoir would grow large enough to be contagious and the contamination process would be repeated. This network of networks approach identified which reservoirs are critical to avoid outward spread and inward infection, in order to slow the presence of the invasive species.<\/p>\n

In a third study, an ecological network approach was used as the foundation for understanding system sustainability [3]. All systems are open thermodynamic systems, in other words, they freely exchange energy and matter with their surroundings. This means that how they organize to use this energy is key to their sustainability. The IIASA researchers found that networks that maximize the total flow of energy or matter through the system and the time that energy\/material stays in a particular compartment of the system via cycling, are also the ones that can best slow down energy dissipation and thus achieve greater levels of energy extracted from available resources. According to this study, structural-, and functional organization that follows this pattern is observed in ecosystems and may prove to be a useful template for designing human, socioeconomic systems.<\/p>\n

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References<\/h3>\n

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[1] Banerjee A, Scharler UM,\u00a0Fath BD, & Ray S\u00a0(2017).\u00a0Temporal variation of keystone species and their impact on system performance in a South African estuarine ecosystem.<\/a>\u00a0Ecological Modelling<\/em>\u00a0363: 207-220.<\/p>\n

[2] Haak DM,\u00a0Fath B, Forbes VE, Martin DR, & Pope KL\u00a0(2017).\u00a0Coupling ecological and social network models to assess \u201ctransmission\u201d and \u201ccontagion\u201d of an aquatic invasive species.<\/a>\u00a0Journal of Environmental Management<\/em>\u00a0190 (1): 243-251.<\/p>\n

[3] Fath BD\u00a0(2017).\u00a0Systems ecology, energy networks, and a path to sustainability.<\/a>\u00a0International Journal of Design & Nature and Ecodynamics<\/em>\u00a012 (1): 1-15.<\/p>\n

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Further information<\/h3>\n

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