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Moving in the Anthropocene
(2018)
Animal movement is fundamental for ecosystem functioning and species survival, yet the effects of the anthropogenic footprint on animal movements have not been estimated across species. Using a unique GPS-tracking database of 803 individuals across 57 species, we found that movements of mammals in areas with a comparatively high human footprint were on average one-half to one-third the extent of their movements in areas with a low human footprint. We attribute this reduction to behavioral changes of individual animals and to the exclusion of species with long-range movements from areas with higher human impact. Global loss of vagility alters a key ecological trait of animals that affects not only population persistence but also ecosystem processes such as predator-prey interactions, nutrient cycling, and disease transmission.
While zwitterionic interfaces are known for their excellent low-fouling properties, the underlying molecular principles are still under debate. In particular, the role of the zwitterion orientation at the interface has been discussed recently. For elucidation of the effect of this parameter, self-assembled monolayers (SAMs) on gold were prepared from stoichiometric mixtures of oppositely charged alkyl thiols bearing either a quaternary ammonium or a carboxylate moiety. The alkyl chain length of the cationic component (11-mercaptoundecyl)-N,N,N-trimethylammonium, which controls the distance of the positively charged end group from the substrate's surface, was kept constant. In contrast, the anionic component and, correspondingly, the distance of the negatively charged carboxylate groups from the surface was varied by changing the alkyl chain length in the thiol molecules from 7 (8-mercaptooctanoic acid) to 11 (12-mercaptododecanoic acid) to 15 (16-mercaptohexadecanoic acid). In this way, the charge neutrality of the coating was maintained, but the charged groups exposed at the interface to water were varied, and thus, the orientation of the dipoles in the SAMs was altered. In model biofouling studies, protein adsorption, diatom accumulation, and the settlement of zoospores were all affected by the altered charge distribution. This demonstrates the importance of the dipole orientation in mixed-charged SAMs for their inertness to nonspecific protein adsorption and the accumulation of marine organisms. Overall, biofouling was lowest when both the anionic and the cationic groups were placed at the same distance from the substrate's surface.
Home range estimation is routine practice in ecological research. While advances in animal tracking technology have increased our capacity to collect data to support home range analysis, these same advances have also resulted in increasingly autocorrelated data. Consequently, the question of which home range estimator to use on modern, highly autocorrelated tracking data remains open. This question is particularly relevant given that most estimators assume independently sampled data. Here, we provide a comprehensive evaluation of the effects of autocorrelation on home range estimation. We base our study on an extensive data set of GPS locations from 369 individuals representing 27 species distributed across five continents. We first assemble a broad array of home range estimators, including Kernel Density Estimation (KDE) with four bandwidth optimizers (Gaussian reference function, autocorrelated‐Gaussian reference function [AKDE], Silverman's rule of thumb, and least squares cross‐validation), Minimum Convex Polygon, and Local Convex Hull methods. Notably, all of these estimators except AKDE assume independent and identically distributed (IID) data. We then employ half‐sample cross‐validation to objectively quantify estimator performance, and the recently introduced effective sample size for home range area estimation ( N̂ area
) to quantify the information content of each data set. We found that AKDE 95% area estimates were larger than conventional IID‐based estimates by a mean factor of 2. The median number of cross‐validated locations included in the hold‐out sets by AKDE 95% (or 50%) estimates was 95.3% (or 50.1%), confirming the larger AKDE ranges were appropriately selective at the specified quantile. Conversely, conventional estimates exhibited negative bias that increased with decreasing N̂ area. To contextualize our empirical results, we performed a detailed simulation study to tease apart how sampling frequency, sampling duration, and the focal animal's movement conspire to affect range estimates. Paralleling our empirical results, the simulation study demonstrated that AKDE was generally more accurate than conventional methods, particularly for small N̂ area. While 72% of the 369 empirical data sets had >1,000 total observations, only 4% had an N̂ area >1,000, where 30% had an N̂ area <30. In this frequently encountered scenario of small N̂ area, AKDE was the only estimator capable of producing an accurate home range estimate on autocorrelated data.