Ecosystem indicatorsfor variability in species’trophic levels

Trophic level (TL)-based indicators are commonly used to track the ecosystem effects of fishing as the selective removal of organisms from the food web may result in changes to the trophic structure of marine ecosystems. The use of a fixed TL per species in the calculation of TL-based indicators has been questioned, given that species' TLs vary with ontogeny, as well as over time and space. We conducted a model-based assessment of the performance of fixed TL-based indicators vs. variable TL-based indicators for tracking the effects of fishing pressure. This assessment considered three TL-based indicators (the trophic level of the landed catch (TL c), the marine trophic index (MTI) and the tro-phic level of the surveyed community (TL sc)), three fishing scenarios that targeted specific model groups (the low TL scenario (LTL), the high TL scenario (HTL) and a scenario encompassing broad-scale exploitation (ALL)) and ten contrasting marine ecosystems with four types of ecosystem modelling approaches that differ in their structure and assumptions. Results showed that, overall, variable TL-based indicators have a greater capacity for detecting the effects of fishing pressure than fixed TL-based indicators. Across TL-based indicators, TL sc displayed

ICES Journal of Marine Science: Journal du Conseil, 2016

Trophic level (TL)-based indicators are commonly used to track the ecosystem effects of fishing as the selective removal of organisms from the food web may result in changes to the trophic structure of marine ecosystems. The use of a fixed TL per species in the calculation of TL-based indicators has been questioned, given that species’ TLs vary with ontogeny, as well as over time and space. We conducted a model-based assessment of the performance of fixed TL-based indicators vs. variable TL-based indicators for tracking the effects of fishing pressure. This assessment considered three TL-based indicators (the trophic level of the landed catch (TLc), the marine trophic index (MTI) and the trophic level of the surveyed community (TLsc)), three fishing scenarios that targeted specific model groups (the low TL scenario (LTL), the high TL scenario (HTL) and a scenario encompassing broad-scale exploitation (ALL)) and ten contrasting marine ecosystems with four types of ecosystem modelling...

M. 2005. The trophic spectrum: theory and application as an ecosystem indicator. e ICES Journal of Marine Science, 62: 443e452.

Ecology, 2008

www.gov.uk/government/uploads/system/uploads/attachment_data/file/290226/stre38-e-e.pdf

Oikos, 2016

Following environmental changes, communities disassemble and reassemble in seemingly unpredictable ways. Whether species respond to such changes individualistically or collectively (e.g. as functional groups) is still unclear. To address this question, we used an extensive new dataset for the lake communities in the Azores' archipelago to test whether: 1) individual species respond concordantly within trophic groups; 2) trophic groups respond concordantly to biogeographic and environmental gradients. Spatial concordance in individual species distributions within trophic groups was always greater than expected by chance. In contrast, trophic groups varied non-concordantly along biogeographic and environmental gradients revealing idiosyncratic responses to them. Whether communities respond individualistically to environmental gradients thus depends on the functional resolution of the data. Our study challenges the view that modelling environmental change effects on biodiversity always requires an individualist approach. Instead, it finds support for the longstanding idea that communities might be modelled as a cohort if the functional resolution is appropriate.

Bridging the Gap between Global Commitment and Local Action, 2013

Nature Ecology & Evolution , 2020

T he habitat heterogeneity hypothesis is one of the central pillars of ecological theory. It states that spatial heterogeneity in abiotic and biotic conditions increases niche dimensionality (that is, the number of available niches), allowing different species to co-exist such that biodiversity increases (Fig. 1) 1-3. The positive relationship between heterogeneity and species richness is often regarded as ubiquitous 2 since its first observation in the early 1960s when MacArthur and MacArthur 1 showed that local bird diversity strongly correlated with the vertical heterogeneity in forest stands across North America. However, if heterogeneity increases the number of species, the amount of suitable area available for individual species decreases per area unit. According to the area-hetero-geneity trade-off hypothesis 4 , this can result in a decrease in mean population sizes especially at high levels of habitat heterogeneity (Fig. 1). The result is an increased probability of stochastic extinctions and ultimately a decline in species richness. This mechanism, along with fragmentation effects that often accompany heterogene-ity, can lead to hump-shaped heterogeneity-diversity relationships (HDRs) 4,5 (Fig. 1). The area-heterogeneity trade-off hypothesis is a relatively recent concept and has received less scrutiny than the classical habitat het-erogeneity hypothesis. Addressing the area-heterogeneity trade-off hypothesis requires testing for nonlinear relationships between heterogeneity and biodiversity. However, such tests are poorly represented in the literature and subsequently, not included in a global meta-analysis which supported the prevalence of positive HDRs. Next to the growing evidence that HDRs can take nonlinear forms 4-10 , it has been shown that certain ecological properties, such as niche breadth, reproduction and dispersal rates 5,7-9 , moderate the responses of species to increasing niche dimensionality, reductions in effective area and the degree of fragmentation. Consequently, rather than investigating whether positive or hump-shaped HDRs prevail, recent theoretical approaches address the question of under which conditions HDR takes which shape 5,10,11. The habitat heterogeneity hypothesis predicts that biodiversity increases with increasing habitat heterogeneity due to greater niche dimensionality. However, recent studies have reported that richness can decrease with high heterogeneity due to sto-chastic extinctions, creating trade-offs between area and heterogeneity. This suggests that greater complexity in heterogene-ity-diversity relationships (HDRs) may exist, with potential for group-specific responses to different facets of heterogeneity that may only be partitioned out by a simultaneous test of HDRs of several species groups and several facets of heterogeneity. Here, we systematically decompose habitat heterogeneity into six major facets on ~500 temperate forest plots across Germany and quantify biodiversity of 12 different species groups, including bats, birds, arthropods, fungi, lichens and plants, representing 2,600 species. Heterogeneity in horizontal and vertical forest structure underpinned most HDRs, followed by plant diversity , deadwood and topographic heterogeneity, but the relative importance varied even within the same trophic level. Among substantial HDRs, 53% increased monotonically, consistent with the classical habitat heterogeneity hypothesis but 21% were hump-shaped, 25% had a monotonically decreasing slope and 1% showed no clear pattern. Overall, we found no evidence of a single generalizable mechanism determining HDR patterns. NATurE ECoLoGy & EvoLuTIoN | www.nature.com/natecolevol

Global Ecology and Biogeography, 2019

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Philip Roche and Ilse Geijzendorffer, 2013. EBONE: integrated figures of habitat and biodiversity indicators. Wageningen, Alterra, Alterra report 2392. 54 pp.; 21 fig.; 5 tab.; 15 ref.