Transition areas between biomes are particularly sensitive to environmental changes. Our understanding of the impacts of ongoing climate change on terrestrial ecosystems has significantly increased during the last years. However, it is largely unknown how climatic change will affect transitions among major vegetation types. We modelled the distribution of three alternative states (forest, savanna and treeless areas) in the tropical and subtropical Americas by means of climate-niche modelling. We studied how such distribution will change by the year 2070 by using 17 downscaled and calibrated global climate models from the Coupled Model Intercomparison Project Phase 5 and the latest scenarios provided by the 5th Assessment Report of the IPCC.

Our results support the savannization of the tropical and subtropical Americas because of climate change, with an increase in savannas mainly at the expense of forests. Our models predict an important geographical shift in the current distribution of transition areas between forest and savannas, which is much less pronounced in the case of those between savannas and treeless areas. Largest shifts, up to 600 km northward, are predicted in the forest–savanna transitions located in the eastern Amazon. Our findings indicate that climate change will promote a shift towards more unstable states: the extent of the transition areas will notably increase, and largely stable forest areas are predicted to shrink dramatically.

Our work explores dimensions of the impact of climate change on biomes that have received little attention so far. Our results indicate that climate change will not only affect the extent of savanna, forest and treeless areas in the tropical and subtropical Americas, but also will: (i) promote a significant geographical shift and an increase of the extent of transition areas between biomes and (ii) decrease the stability of the equilibrium between forest, savanna and treeless areas, yielding a more unpredictable system.

We study the physics potential of the detection of the Cosmic Neutrino Back- ground via neutrino capture on tritium, taking the proposed PTOLEMY experiment as a case study. With the projected energy resolution of ∆ ∼ 0.15eV, the experiment will be sensitive to neutrino masses with degenerate spectrum, m₁ ≃ m₂ ≃ m₃ = m_ν 0.1eV. These neutrinos are non-relativistic today; detecting them would be a unique opportunity to probe this unexplored kinematical regime. The signature of neutrino capture is a peak in the electron spectrum that is displaced by 2m_ν above the beta decay endpoint. The signal would exceed the background from beta decay if the energy resolution is ∆ 0.7 mν. Interestingly, the total capture rate depends on the origin of the neutrino mass, being Γ^D ≃ 4 and Γ^M ≃ 8 events per year (for a 100 g tritium target) for unclustered Dirac and Majorana neutrinos, respectively. An enhancement of the rate of up to O(1) is expected due to gravitational clustering, with the unique potential to probe the local overdensity of neutrinos. Turning to more exotic neutrino physics, PTOLEMY could be sensitive to a lepton asymmetry, and reveal the eV-scale sterile neutrino that is favored by short baseline oscillation searches. The experiment would also be sensitive to a neutrino lifetime on the order of the age of the uni- verse and break the degeneracy between neutrino mass and lifetime which affects existing bounds.

Detecting edges in images from a finite sampling of Fourier data is important in a variety of applications. For example, internal edge information can be used to identify tissue boundaries of the brain in a magnetic resonance imaging (MRI) scan, which is an essential part of clinical diagnosis. Likewise, it can also be used to identify targets from synthetic aperture radar data. Edge information is also critical in determining regions of smoothness so that high resolution reconstruction algorithms, i.e. those that do not “smear over” the internal boundaries of an image, can be applied. In some applications, such as MRI, the sampling patterns may be designed to oversample the low frequency while more sparsely sampling the high frequency modes. This type of non-uniform sampling creates additional difficulties in processing the image. In particular, there is no fast reconstruction algorithm, since the FFT is not applicable. However, interpolating such highly non-uniform Fourier data to the uniform coefficients (so that the FFT can be employed) may introduce large errors in the high frequency modes, which is especially problematic for edge detection. Convolutional gridding, also referred to as the non-uniform FFT, is a forward method that uses a convolution process to obtain uniform Fourier data so that the FFT can be directly applied to recover the underlying image. Carefully chosen parameters ensure that the algorithm retains accuracy in the high frequency coefficients. Similarly, the convolutional gridding edge detection algorithm developed in this paper provides an efficient and robust way to calculate edges. We demonstrate our technique in one and two dimensional examples.

What explains the success and failure of radical right parties over time and across countries? This article presents a new theory of the radical right that emphasizes its reactive nature and views it as backlash against the political successes of minorities and concessions extracted on their behalf. Unlike approaches that focus on competition between the extreme and mainstream parties, the theory stresses the dynamics between radical right and non-proximate parties that promote minority rights. Most notably, it derives the salience of identity issues in party politics from the polarization of the party system. The theory is tested with a new party-election-level dataset covering all post-communist democracies over the past 20 years. The results provide strong support for the theory and show that the rise and fall of radical right parties is shaped by the politics of minority accommodation.

Transactional theories support that parent-child processes are best studied in conjunction with one another, addressing their reciprocal influence and change across time. This study tested a longitudinal, autoregressive model exploring bidirectional relations among maternal symptomatology, child internalizing/externalizing symptoms, and maternal sensitivity during the preschool period (child ages 3 to 5 years), comparing relations among families of typically developing children and children with developmental risk. This study included 250 families, 110 of which had a child with early developmental delay. Analyses utilized data from maternal report, father report, and observational methods. The results indicated significant stability in maternal symptomatology, child internalizing/externalizing symptoms, and maternal sensitivity over time. Support for bidirectional effects between maternal symptomatology and child internalizing symptoms was found specifically for mothers of children with developmental risk. Maternal symptomatology was found to mediate the influence of child internalizing and externalizing symptoms on maternal sensitivity. The findings underscore critical transactional processes within families of children with early developmental risk that connect increased maternal symptomatology to emerging child internalizing symptoms during the preschool period.

Recent studies (e.g., Kuhn and Tatler, 2005) have suggested that magic tricks can provide a powerful and compelling domain for the study of attention and perception. In particular, many stage illusions involve attentional misdirection, guiding the observer's gaze to a salient object or event, while another critical action, such as sleight of hand, is taking place. Even if the critical action takes place in full view, people typically fail to see it due to inattentional blindness (IB). In an eye-tracking experiment, participants watched videos of a new magic trick, wherein a coin placed beneath a napkin disappears, reappearing under a different napkin. Appropriately deployed attention would allow participants to detect the “secret” event that underlies the illusion (a moving coin), as it happens in full view and is visible for approximately 550 ms. Nevertheless, we observed high rates of IB. Unlike prior research, eye-movements during the critical event showed different patterns for participants, depending upon whether they saw the moving coin. The results also showed that when participants watched several “practice” videos without any moving coin, they became far more likely to detect the coin in the critical trial. Taken together, the findings are consistent with perceptual load theory (Lavie and Tsal, 1994).

The site of Loperot in West Turkana, Kenya, is usually assigned to the Early Miocene. Recent discoveries at Loperot, including catarrhine primates, led to a revision of its mammalian fauna. Our revision of the fauna at Loperot shows an unusual taxonomic composition of the catarrhine community as well as several other unique mammalian taxa. Loperot shares two non-cercopithecoid catarrhine taxa with Early Miocene sites near Lake Victoria, e.g., Songhor and the Hiwegi Formation of Rusinga Island, but Loperot shares a cercopithecoid, Noropithecus, with Buluk (Surgei Plateau, near Lake Chew Bahir). We use Simpson’s Faunal Resemblance Index (Simpson’s FRI), a cluster analysis, and two partial Mantel tests, to compare Loperot to 10 other localities in East Africa representing several time divisions within the Early and Middle Miocene. Simpson’s FRI of mammalian communities indicates that Loperot is most similar in its taxonomic composition to the Hiwegi Formation of Rusinga Island, suggesting a similarity in age (≥18 Ma) that implies that Loperot is geographically distant from its contemporaries, i.e., Hiwegi Formation of Rusinga Island, Koru, Songhor, and Napak, while at the same time older than other sites in West Turkana (Kalodirr and Moruorot). The cluster analysis of the similarity indices of all the localities separates Loperot from other Early Miocene sites in the study. Two partial Mantel tests show that both temporal distance and geographic distance between sites significantly influence similarity of the mammalian community among sites. Thus, Loperot’s unique location in space and time may explain why it has an unusual catarrhine community and a number of unique taxa not seen elsewhere.

This study used growth mixture modeling to examine attendance trajectories among 292 Mexican–American primary female caregivers enrolled in a universal preventive intervention and the effects of health beliefs, participation intentions, cultural influences, and intervention group cohesion on trajectory group membership as well as trajectory group differences on a distal outcome, immediate posttest teacher report of child externalizing (T2). Results supported four trajectory groups—early terminators (ET), mid-program terminators (MPT), low-risk persistent attenders (LRPA), and high-risk persistent attenders (HRPA). Compared with LRPAs, caregivers classified as HRPAs had weaker familism values, less parenting efficacy, and higher externalizing children with lower GPAs. Caregivers in the two persistent attender groups reported strong group cohesion and providers rated these caregivers as having strong participation intentions. Children of caregivers in the LRPA group had the lowest T2 child externalizing. Children of caregivers in the MPT group had lower T2 externalizing than did those of the ET group, suggesting partial intervention dosage can benefit families. Despite high levels of attendance, children of caregivers in the HRPA had the highest T2 externalizing, suggesting this high-risk group needed either more intensive services or a longer period for parents to implement program skills to evidence change in child externalizing.

We present an age- and stage-structured population model to study some methods of control of one of the most important grapevine pests, the European grapevine moth. We consider control by insecticides that reduce either the proportion of surviving eggs, larvae or both, as well as chemicals that cause mating disruption, thereby reducing the number of eggs laid. We formulate optimal control problems with cost functionals related to real-life costs in the wine industry, and we prove that these problems admit a unique solution. We also provide some numerical examples from simulation.

In arid and semi-arid ecosystems, there are legacies of previous-year precipitation on current-year above-ground net primary production. We hypothesized that legacies of past precipitation occur through changes in tiller density, stolon density, tiller growth, axillary bud density and percentage of viable axillary buds. We examined the sensitivity to current- and previous-year precipitation of these grassland structural components in Bouteloua eriopoda, the dominant grass in the northern Chihuahuan Desert. We conducted a rainfall manipulation experiment consisting in −80% reduced precipitation, ambient, +80% increased precipitation treatments that were subjected to one of five precipitation levels in the previous two years (−80% and −50% reduced precipitation, ambient, +50% and +80% increased precipitation). The first two years preconditioned the experimental plots for year three, in which we created wet-to-dry and dry-to-wet transitions. Measurements were taken in year 3. We found that stolon density was the most sensitive to changes in precipitation and that percent-active buds were insensitive. We also found that past precipitation had a significant legacy on grassland structural components regardless of the precipitation received in the current year, and that the legacy occurs mostly through changes in stolon density. Here, we showed that there is a differential sensitivity of structural components to current and past precipitation and supported previous findings that vegetation structure is one of the controls of productivity during precipitation transitions.