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- Species distribution models often fail to predict observed patterns of species diversity, and this is because some species within a regional pool that are tolerant of conditions at a given location may nevertheless be absent from the local community. These missing species have been termed “dark diversity”. In the present study, we investigated which factors explain dark diversity among fish assemblages in Amazonian streams.
- We sampled 71 streams in areas with different types of land use within two river basins and estimated dark diversity from patterns of species co-occurrence, using Beals’ index, along environmental gradients. From this procedure, taxa are designated as dark diversity components when they are absent from a given stream, but often co-occur with the local species at other streams, indicating similar ecological requirements. We used generalised linear models both to determine whether environmental or landscape variables, connectivity, instream environmental heterogeneity or some combination of these factors explained dark diversity of fishes, and to evaluate whether ecomorphology is associated with the extent to which a species contributes to dark diversity and which specific traits contribute the most to explaining variation in dark diversity.
- Mean local diversity exceeded observed dark diversity. The magnitude of dark diversity was directly associated with the proportion of secondary forest in the immediate catchment and with the index of proximity to anthropogenic impact. Species that have high affinity for environments with higher current velocity, low swimming ability and that capture food mainly on the surface contributed more to dark diversity, which suggests that swimming ability, habitat preference and aspects related to diet are key predictors of the probability that a given species will be present at locations with suitable habitat.
- Our findings reinforce the idea that dark diversity results from interactions between species traits and environmental factors, including anthropogenic impacts. Understanding the interplay among environmental factors and species traits that contribute to dark diversity provides targets for improved ecosystem restoration and sustainability of native species assemblages.
Parkinson’s disease (PD) signs and symptoms regularly include tremor. Interestingly, the nucleoside guanosine (GUO) has already proven to be effective in reducing reserpine-induced tremulous jaw movements (TJMs) in rodent models, thus becoming a promising antiparkinsonian drug. Here, we aimed at revealing the mechanism behind GUO antiparkinsonian efficacy by assessing the role of adenosine A1 and A2A receptors (A1R and A2AR) on GUO-mediated anti-tremor effects in the reserpinized mouse model of PD. Reserpinized mice showed elevated reactive oxygen species (ROS) production and cellular membrane damage in striatal slices assessed ex vivo and GUO treatment reversed ROS production. Interestingly, while the simultaneous administration of sub-effective doses of GUO (5 mg/kg) and SCH58261 (0.01 mg/kg), an A2AR antagonist, precluded reserpine-induced TJMs, these were ineffective on reverting ROS production in ex vivo experiments. Importantly, GUO was able to reduce TJM and ROS production in reserpinized mouse lacking the A2AR, thus suggesting an A2AR-independent mechanism of GUO-mediated effects. Conversely, the administration of DPCPX (0.75 mg/kg), an A1R antagonist, completely abolished both GUO-mediated anti-tremor effects and blockade of ROS production. Overall, these results indicated that GUO anti-tremor and antioxidant effects in reserpinized mice were A1R dependent but A2AR independent, thus suggesting a differential participation of adenosine receptors in GUO-mediated effects.
相似文献The potential impact of the soil seed bank of a given species and subsequent population persistence will depend on the robustness of the seeds against depletion. Invasiveness is frequently linked to this behavior and successful control of invasive species depends on reducing the size of their seed banks. We propose a hybrid model that simulates the seed bank dynamics in association with their physical dormancy (PD) based on experimental data on seed bank depletion of a Leucaena leucocephala population during the dispersal phase. The hybrid model uses cellular automata (CA) and Monte Carlo techniques. The sensitivity analysis revealed that the model delivers reproducible and reliable results. Then, we discuss the ability of the hybrid model to predict the effect of seasonal climate change. A 2.0 °C increase in temperature was enough to cause a considerable impact in the seed depletion curve, and after 1 year, ~?75% of the seeds had already disappeared from the seed bank. The proposed hybrid CA model can be used to study soil-stored seed banks with physical dormancy, and could be applied to other Fabaceae species with similar seed traits. We believe that this computational model contributes to a better understanding of seed bank dynamics and will aid in the control of invasive species and for testing different scenarios to reduce or eliminate seed banks that have already been formed.
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