Higher temporal variability of forest breeding bird communities in fragmented landscapes

Understanding the relationship between animal community dynamics and landscape structure has become a priority for biodiversity conservation. In particular, predicting the effects of habitat destruction that confine species to networks of small patches is an important prerequisite to conservation plan development. Theoretical models that predict the occurrence of species in fragmented landscapes, and relationships between stability and diversity do exist. However, reliable empirical investigations of the dynamics of biodiversity have been prevented by differences in species detection probabilities among landscapes. Using long-term data sampled at a large spatial scale in conjunction with a capture-recapture approach, we developed estimates of parameters of community changes over a 22-year period for forest breeding birds in selected areas of the eastern United States. We show that forest fragmentation was associated not only with a reduced number of forest bird species, but also with increased temporal variability in the number of species. This higher temporal variability was associated with higher local extinction and turnover rates. These results have major conservation implications. Moreover, the approach used provides a practical tool for the study of the dynamics of biodiversity.

Point mutations and sequence variability in proteins: Redistributions of preexisting populations

Here we study the effect of point mutations in proteins on the redistributions of the conformational substates. We show that regardless of the location of a mutation in the protein structure and of its type, the observed movements of the backbone recur largely at the same positions in the structures. Despite the different interactions that are disrupted and formed by the residue substitution, not only are the conformations very similar, but the regions that move are also the same, regardless of their sequential or spatial distance from the mutation. This observation leads us to conclude that, apart from some extreme cases, the details of the interactions are not critically important in determining the protein conformation or in specifying which parts of the protein would be more prone to take on different local conformations in response to changes in the sequence. This finding further illustrates why proteins manifest a robustness toward many mutational events. This nonuniform distribution of the conformer population is consistently observed in a variety of protein structural types. Topology is critically important in determining folding pathways, kinetics, building block cutting, and anatomy trees. Here we show that topology is also very important in determining which regions of the protein structure will respond to sequence changes, regardless of the sequential or spatial location of the mutation.

Spatial Distribution of Marine Epibenthic Communities in the Hola Trough (Vesterålen, Northern Norway)

The Lofoten-Vesterålen marine shelf is one of the most geologically diverse coast and offshore margin areas in Norway. This leads to huge heterogeneity in marine environments, and often high biodiversity. However, little is known yet about the benthic communities in this region. Within the ARCTOS LoVe MarineEco project the epibenthic communities of the Hola trough (Vesterålen) are analysed to give a first description of their spatial distribution. In this trough both a complex hydrodynamic system and varied topographic submarine elements occur. Trawling samples were collected for two different approaches: one in a meso-scale and another in a small-scale. For the broad scale a transect consisting in three stations was developed, while for the fine scale a small area on a sand wave field, consisting in five stations called HolaBox, was sampled. All organisms were intended to be identified to species level and colonial fauna was discarded for the analysis. Different diversity indexes were assessed (Shannon index (H’) and Pielou’s eveness (J’)). Clustering and nMDS analyses identified four statistically significant groups in terms of abundance (ind./100m2). A total amount of 211 different taxa were found within all stations. The more outer part of the transect (close to the shelf edge) presented a huge abundance of organisms and was dominated by the hemi sessile tube-builder polychaetes Nothria conchylega and Eunice dubitata and the sea urchin Gacilechinus acutus, while the more inner parts presented less abundance of individuals. Probably some upwelling produced by the Norwegian Atlantic Current (NWAC) is influencing the shelf edge increasing the primary production and, therefore, enriching the seafloor in this region. The sand wave field presented two different groups with few amount of individuals. Small-scale variability could be produced by the high heterogeneity within the different types of sand waves, while the scarce abundance of animals can be produced by the permanent changing environment that movable sand waves produce. Here more active and mobile fauna was found such as brittle stars and hermit crabs (among others). Finally, a fourth group was found in the most inner station of the transect, laying on a ridge in the central part of the trough. This station, with coarse substrate, was mainly dominated again by brittle stars and sea urchins. We can conclude that this is a really heterogeneous trough in environments and therefore in communities (even in a local scale). More detailed studies that focus in the local environmental drivers have to be carried out to get an integrated understanding of the structure of benthic communities in this system.

Exploring the spatial variation of tides for seafloor mapping data corrections

Senior thesis written for Oceanography 445

Spatial and temporal variation in algal-assemblage structure in isolated dryland river waterholes, Cooper Creek and Warrego River, Australia

The scale at which algal biodiversity is partitioned across the landscape, and the biophysical processes and biotic interactions which shape these communities in dryland river refugia was studied on two occasions from 30 sites in two Australian dryland rivers. Despite the waterholes studied having characteristically high levels of abiogenic turbidity, a total of 186 planktonic microalgae, 253 benthic diatom and 62 macroalgal species were recorded. The phytoplankton communities were dominated by flagellated cryptophytes, euglenophytes and chlorophytes, the diatom communities by cosmopolitan taxa known to tolerate wide environmental conditions, and the macroalgal communities by filamentous cyanobacteria. All algal communities showed significant differences between catchments and sampling times, with a suite of between 5 and 12 taxa responsible for similar to 50% of the observed change. In general, algal assemblage patterns were poorly correlated with the measured environmental variables. Phytoplankton and diatom assemblage patterns were weakly correlated with several waterhole geomorphic measures, whereas macroalgal assemblage patterns showed some association with variability in ionic concentration.

Rare earth element and yttrium variability in South East Queensland waterways

We present data for the rare earth elements and yttrium (REY) in the National Research Council of Canada natural river water reference material SLRS-4 and 19 natural river waters from small catchments in South-East Queensland, Australia, by a direct ICP-MS method. The 0.22 mu m filtered river water samples show a large degree of variability in both the REY concentration, e.g., La varies from 13 to 1157 ppt, and shape of the alluvial-sediment-normalised REY patterns with different samples displaying light, middle or heavy rare earth enrichment. In addition, a spatial study was undertaken along the freshwater section of Beerburrum Creek, which demonstrates that similar to 75% of the total REYs in this waterway are removed prior to estuarine mixing without evidence of fractionation.

The use of ERS-1 crossovers and TOPEX/Poseidon repeat pass data for global sea surface variability studies

In previous sea-surface variability studies, researchers have failed to utilise the full ERS-1 mission due to the varying orbital characteristics in each mission phase, and most have simply ignored the Ice and Geodetic phases. This project aims to introduce a technique which will allow the straightforward use of all orbital phases, regardless of orbit type. This technique is based upon single satellite crossovers. Unfortunately the ERS-1 orbital height is still poorly resolved (due to higher air drag and stronger gravitational effects) when compared with that of TOPEX/Poseidon (T/P), so to make best use of the ERS-1 crossover data corrections to the ERS-1 orbital heights are calculated by fitting a cubic-spline to dual-crossover residuals with T/P. This correction is validated by comparison of dual satellite crossovers with tide gauge data. The crossover processing technique is validated by comparing the extracted sea-surface variability information with that from T/P repeat pass data. The two data sets are then combined into a single consistent data set for analysis of sea-surface variability patterns. These patterns are simplified by the use of an empirical orthogonal function decomposition which breaks the signals into spatial modes which are then discussed separately. Further studies carried out on these data include an analysis of the characteristics of the annual signal, discussion of evidence for Rossby wave propagation on a global basis, and finally analysis of the evidence for global mean sea level rise.

Rainfall variability in the upper Napo River Basin, Ecuadorian Amazon

The purpose of this research was to investigate the influence of elevation and other terrain characteristics over the spatial and temporal distribution of rainfall. A comparative analysis was conducted between several methods of spatial interpolations using mean monthly precipitation values in order to select the best. Following those previous results it was possible to fit an Artificial Neural Network model for interpolation of monthly precipitation values for a period of 20 years, with input values such as longitude, latitude, elevation, four geomorphologic characteristics and anchored by seven weather stations, it reached a high correlation coefficient (r=0.85). This research demonstrated a strong influence of elevation and other geomorphologic variables over the spatial distribution of precipitation and the agreement that there are nonlinear relationships. This model will be used to fill gaps in time-series of monthly precipitation, and to generate maps of spatial distribution of monthly precipitation at a resolution of 1km2.

Evidence of climate variability and tropical cyclone activity from diatom assemblage dynamics in coastal southwest Florida

Estuaries are dynamic on many spatial and temporal scales. Distinguishing effects of unpredictable events from cyclical patterns can be challenging but important to predict the influence of press and pulse drivers in the face of climate change. Diatom assemblages respond rapidly to changing environmental conditions and characterize change on multiple time scales. The goals of this research were to 1) characterize diatom assemblages in the Charlotte Harbor watershed, their relationships with water quality parameters, and how they change in response to climate; and 2) use assemblages in sediment cores to interpret past climate changes and tropical cyclone activity. ^ Diatom assemblages had strong relationships with salinity and nutrient concentrations, and a quantitative tool was developed to reconstruct past values of these parameters. Assemblages were stable between the wet and dry seasons, and were more similar to each other than to assemblages found following a tropical cyclone. Diatom assemblages following the storm showed a decrease in dispersion among sites, a pattern that was consistent on different spatial scales but may depend on hydrological management regimes. ^ Analysis of sediment cores from two southwest Florida estuaries showed that locally-developed diatom inference models can be applied with caution on regional scales. Large-scale climate changes were suggested by environmental reconstructions in both estuaries, but with slightly different temporal pacing. Estimates of salinity and nutrient concentrations suggested that major hydrological patterns changed at approximately 5.5 and 3 kyrs BP. A highly temporally-resolved sediment core from Charlotte Harbor provided evidence for past changes that correspond with known climate records. Diatom assemblages had significant relationships with the three-year average index values of the Atlantic Multidecadal Oscillation and the El Niño Southern Oscillation. Assemblages that predicted low salinity and high total phosphorus also had the lowest dispersion and corresponded with some major storms in the known record, which together may provide a proxy for evidence of severe storms in the paleoecological record. ^

Assessment of the Spatial and Temporal Distribution of Functional Connectivity in Resting-State BOLD fMRI

Recent research into resting-state functional magnetic resonance imaging (fMRI) has shown that the brain is very active during rest. This thesis work utilizes blood oxygenation level dependent (BOLD) signals to investigate the spatial and temporal functional network information found within resting-state data, and aims to investigate the feasibility of extracting functional connectivity networks using different methods as well as the dynamic variability within some of the methods. Furthermore, this work looks into producing valid networks using a sparsely-sampled sub-set of the original data.

In this work we utilize four main methods: independent component analysis (ICA), principal component analysis (PCA), correlation, and a point-processing technique. Each method comes with unique assumptions, as well as strengths and limitations into exploring how the resting state components interact in space and time.

Correlation is perhaps the simplest technique. Using this technique, resting-state patterns can be identified based on how similar the time profile is to a seed region’s time profile. However, this method requires a seed region and can only identify one resting state network at a time. This simple correlation technique is able to reproduce the resting state network using subject data from one subject’s scan session as well as with 16 subjects.

Independent component analysis, the second technique, has established software programs that can be used to implement this technique. ICA can extract multiple components from a data set in a single analysis. The disadvantage is that the resting state networks it produces are all independent of each other, making the assumption that the spatial pattern of functional connectivity is the same across all the time points. ICA is successfully able to reproduce resting state connectivity patterns for both one subject and a 16 subject concatenated data set.

Using principal component analysis, the dimensionality of the data is compressed to find the directions in which the variance of the data is most significant. This method utilizes the same basic matrix math as ICA with a few important differences that will be outlined later in this text. Using this method, sometimes different functional connectivity patterns are identifiable but with a large amount of noise and variability.

To begin to investigate the dynamics of the functional connectivity, the correlation technique is used to compare the first and second halves of a scan session. Minor differences are discernable between the correlation results of the scan session halves. Further, a sliding window technique is implemented to study the correlation coefficients through different sizes of correlation windows throughout time. From this technique it is apparent that the correlation level with the seed region is not static throughout the scan length.

The last method introduced, a point processing method, is one of the more novel techniques because it does not require analysis of the continuous time points. Here, network information is extracted based on brief occurrences of high or low amplitude signals within a seed region. Because point processing utilizes less time points from the data, the statistical power of the results is lower. There are also larger variations in DMN patterns between subjects. In addition to boosted computational efficiency, the benefit of using a point-process method is that the patterns produced for different seed regions do not have to be independent of one another.

This work compares four unique methods of identifying functional connectivity patterns. ICA is a technique that is currently used by many scientists studying functional connectivity patterns. The PCA technique is not optimal for the level of noise and the distribution of the data sets. The correlation technique is simple and obtains good results, however a seed region is needed and the method assumes that the DMN regions is correlated throughout the entire scan. Looking at the more dynamic aspects of correlation changing patterns of correlation were evident. The last point-processing method produces a promising results of identifying functional connectivity networks using only low and high amplitude BOLD signals.

GIS technologies and spatial organization patterns among hunter-gatherers: an archaeological case study from Southern Patagonia (southern South America)

This paper discusses some aspects of hunter-gatherer spatial organization in southern South Patagonia, in later times to 10,000 cal yr BP. Various methods of spatial analysis, elaborated with a Geographic Information System (GIS) were applied to the distributional pattern of archaeological sites with radiocarbon dates. The shift in the distributional pattern of chronological information was assessed in conjunction with other lines of evidence within a biogeographic framework. Accordingly, the varying degrees of occupation and integration of coastal and interior spaces in human spatial organization are explained in association with the adaptive strategies hunter-gatherers have used over time. Both are part of the same human response to changes in risk and uncertainty variability in the region in terms of resource availability and environmental dynamics.

Linking environmental variables with regional- scale variability in ecological structure and standing stock of carbon within UK kelp forests

Kelp forests represent some of the most productive and diverse habitats on Earth. Understanding drivers of ecological patterns at large spatial scales is critical for effective management and conservation of marine habitats. We surveyed kelp forests dominated by Laminaria hyperborea (Gunnerus) Foslie 1884 across 9° latitude and >1000 km of coastline and measured a number of physical parameters at multiple scales to link ecological structure and standing stock of carbon with environmental variables. Kelp density, biomass, morphology and age were generally greater in exposed sites within regions, highlighting the importance of wave exposure in structuring L. hyperborea populations. At the regional scale, wave-exposed kelp canopies in the cooler regions (the north and west of Scotland) were greater in biomass, height and age than in warmer regions (southwest Wales and England). The range and maximal values of estimated standing stock of carbon contained within kelp forests was greater than in historical studies, suggesting that this ecosystem property may have been previously undervalued. Kelp canopy density was positively correlated with large-scale wave fetch and fine-scale water motion, whereas kelp canopy biomass and the standing stock of carbon were positively correlated with large-scale wave fetch and light levels and negatively correlated with temperature. As light availability and summer temperature were important drivers of kelp forest biomass, effective management of human activities that may affect coastal water quality is necessary to maintain ecosystem functioning, while increased temperatures related to anthropogenic climate change may impact the structure of kelp forests and the ecosystem services they provide.

Linking environmental variables with regional- scale variability in ecological structure and standing stock of carbon within UK kelp forests

Kelp forests represent some of the most productive and diverse habitats on Earth. Understanding drivers of ecological patterns at large spatial scales is critical for effective management and conservation of marine habitats. We surveyed kelp forests dominated by Laminaria hyperborea (Gunnerus) Foslie 1884 across 9° latitude and >1000 km of coastline and measured a number of physical parameters at multiple scales to link ecological structure and standing stock of carbon with environmental variables. Kelp density, biomass, morphology and age were generally greater in exposed sites within regions, highlighting the importance of wave exposure in structuring L. hyperborea populations. At the regional scale, wave-exposed kelp canopies in the cooler regions (the north and west of Scotland) were greater in biomass, height and age than in warmer regions (southwest Wales and England). The range and maximal values of estimated standing stock of carbon contained within kelp forests was greater than in historical studies, suggesting that this ecosystem property may have been previously undervalued. Kelp canopy density was positively correlated with large-scale wave fetch and fine-scale water motion, whereas kelp canopy biomass and the standing stock of carbon were positively correlated with large-scale wave fetch and light levels and negatively correlated with temperature. As light availability and summer temperature were important drivers of kelp forest biomass, effective management of human activities that may affect coastal water quality is necessary to maintain ecosystem functioning, while increased temperatures related to anthropogenic climate change may impact the structure of kelp forests and the ecosystem services they provide.

Modeling long-term variability and change of soil moisture and groundwater level - from catchment to global scale

The water stored in and flowing through the subsurface is fundamental for sustaining human activities and needs, feeding water and its constituents to surface water bodies and supporting the functioning of their ecosystems. Quantifying the changes that affect the subsurface water is crucial for our understanding of its dynamics and changes driven by climate change and other changes in the landscape, such as in land-use and water-use. It is inherently difficult to directly measure soil moisture and groundwater levels over large spatial scales and long times. Models are therefore needed to capture the soil moisture and groundwater level dynamics over such large spatiotemporal scales. This thesis develops a modeling framework that allows for long-term catchment-scale screening of soil moisture and groundwater level changes. The novelty in this development resides in an explicit link drawn between catchment-scale hydroclimatic and soil hydraulics conditions, using observed runoff data as an approximation of soil water flux and accounting for the effects of snow storage-melting dynamics on that flux. Both past and future relative changes can be assessed by use of this modeling framework, with future change projections based on common climate model outputs. By direct model-observation comparison, the thesis shows that the developed modeling framework can reproduce the temporal variability of large-scale changes in soil water storage, as obtained from the GRACE satellite product, for most of 25 large study catchments around the world. Also compared with locally measured soil water content and groundwater level in 10 U.S. catchments, the modeling approach can reasonably well reproduce relative seasonal fluctuations around long-term average values. The developed modeling framework is further used to project soil moisture changes due to expected future climate change for 81 catchments around the world. The future soil moisture changes depend on the considered radiative forcing scenario (RCP) but are overall large for the occurrence frequency of dry and wet events and the inter-annual variability of seasonal soil moisture. These changes tend to be higher for the dry events and the dry season, respectively, than for the corresponding wet quantities, indicating increased drought risk for some parts of the world.

Causes of extreme variability of nest density among close and similar beaches of Boavista island (Cape Verde): From 1 to 2000 annual nests per km.

[EN] The 70 km of white sandy beaches of Boa Vista island in Cape Verde harbours one of the largest rookeries of the endangered loggerhead sea turtle, Caretta caretta. From middle June to early October, approximately 2000 to 4000 females lay up to 20000 nests annually. However, female beach selection, nesting success and nest density strongly varies among beaches and spatial patterns of nest abundance and distribution are relatively constant among seasons. The numbers of nesting activities and nests have been recorded along all beaches of the island during four nesting seasons (2007-2010)