356 research outputs found

    Local Victory: Assessing Interspecific Competition in Seagrass From a Trait-Based Perspective

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    Tropical seagrass meadows are formed by an array of seagrass species that share the same space. Species sharing the same plot are competing for resources, namely light and inorganic nutrients, which results in the capacity of some species to preempt space from others. However, the drivers behind seagrass species competition are not completely understood. In this work, we studied the competitive interactions among tropical seagrass species of Unguja Island (Zanzibar, Tanzania) using a trait-based approach. We quantified the abundance of eight seagrass species under different trophic states, and selected nine traits related to light and inorganic nutrient preemption to characterize the functional strategy of the species (leaf maximum length and width, leaves per shoot, leaf mass area, vertical rhizome length, shoots per meter of ramet, rhizome diameter, roots per meter of ramet, and root maximum length). From the seagrass abundance we calculated the probability of space preemption between pairs of seagrass species and for each individual seagrass species under the different trophic states. Species had different probabilities of space preemption, with the climax species Thalassodendron ciliatum, Enhalus acoroides, Thalassia hemprichii, and the opportunistic Cymodocea serrulata having the highest probability of preemption, while the pioneer and opportunistic species Halophila ovalis, Syringodium isoetifolium, Halodule uninervis, and Cymodocea rotundata had the lowest. Traits determining the functional strategy showed that there was a size gradient across species. For two co-occurring seagrass species, probability of preemption was the highest for the larger species, it increased as the size difference between species increased and was unaffected by the trophic state. Competitive interactions among seagrass species were asymmetrical, i.e., negative effects were not reciprocal, and the driver behind space preemption was determined by plant size. Seagrass space preemption is a consequence of resource competition, and the probability of a species to exert preemption can be calculated using a trait-based approach

    Limited carbon and biodiversity co-benefits for tropical forest mammals and birds

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    The conservation of tropical forest carbon stocks offers the opportunity to curb climate change by reducing greenhouse gas emissions from deforestation and simultaneously conserve biodiversity. However, there has been considerable debate about the extent to which carbon stock conservation will provide benefits to biodiversity in part because whether forests that contain high carbon density in their aboveground biomass also contain high animal diversity is unknown. Here, we empirically examined medium to large bodied ground-dwelling mammal and bird (hereafter "wildlife") diversity and carbon stock levels within the tropics using camera trap and vegetation data from a pantropical network of sites. Specifically, we tested whether tropical forests that stored more carbon contained higher wildlife species richness, taxonomic diversity, and trait diversity. We found that carbon stocks were not a significant predictor for any of these three measures of diversity, which suggests that benefits for wildlife diversity will not be maximized unless wildlife diversity is explicitly taken into account; prioritizing carbon stocks alone will not necessarily meet biodiversity conservation goals. We recommend conservation planning that considers both objectives because there is the potential for more wildlife diversity and carbon stock conservation to be achieved for the same total budget if both objectives are pursued in tandem rather than independently. Tropical forests with low elevation variability and low tree density supported significantly higher wildlife diversity. These tropical forest characteristics may provide more affordable proxies of wildlife diversity for future multi-objective conservation planning when fine scale data on wildlife are lacking
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