Patterns of Temporal and Spatial Variability of Sponge Assemblages

<p>The primary goals of this thesis were to understand the spatial and temporal pattern of sponge assemblage variation over a variety of scales and investigate suitable monitoring methods for sponge assemblages. Sponges are an ecologically significant group in benthic marine communities, which are often ignored in current monitoring schemes. In chapter two the sponge biodiversity of New Zealand waters to 200m was examined using Taxonomic Distinctness measures initially to test if genera data could be used as a proxy for species level data in New Zealand waters. It was found that over 50% of the variation in genera biodiversity could be explained by location and depth around New Zealand. The study helped pinpoint where there were gaps in the New Zealand dataset, in particular for the West Coast of the South Island and also areas such as the Wellington South Coast, which had higher than expected values for Average and Variation Taxonomic distinctness measures, which as important areas where sponges should be monitored to make sure the high levels of biodiversity are protected. Taxonomic distinctness measures are useful for initially assessing how the biodiversity is distributed, especially when using a data set with uneven sampling effort, as it is robust to spatial and temporal bias in the majority of cases. However, there was an outlier to the genera data correlating well with the variation in species data in the case of a site dominated by Haliclona sp (Lyttelton Harbour). In chapters three and four the spatial and temporal variability of sponge assemblages of the Wellington South Coast were explored creating both a species list for the area and an understanding of how the sponge assemblage varies over time and space. There were significant differences in the sponges assemblages in similar habitat types over a scale of a few hundred metres. In addition, although all the sponge assemblages changed seasonally, the changes at each sampling site responded in a slightly different way most likely due to spatiotemporal variation in environmental conditions. A similar seasonal pattern was also observed in chapter five for sponge assemblages at Skomer Marine Reserve and this pattern was also clear when using morphological monitoring methods. This means that once a site has been mapped for biodiversity it is possible for some habitats to use morphological monitoring to identify if the sponge assemblage is changing significantly saving time and money. The results from Indonesia (chapter six) showed that although the sponge assemblages were changing significantly in the actual species present and their abundances, the proportion of diversity within each spatial level (quadrat, site and region) remained consistent when sampled at the same time each year throughout the five year study. In species rich assemblages there are a variety of life strategies that can respond differently to shifts in environmental conditions and contribute to ecological functioning in various ways. Various monitoring methods have been tested using sponge assemblages over various spatial and temporal scales in this thesis. Spatial, temporal and the interaction of spatial and temporal factors were all important for identifying significant assemblage differences at all of the sites. Further studies integrating the interaction of spatial and temporal factors into understanding monitoring data sets are vital to understand the patterns of assemblage variability and therefore incorporate into habitat management plans.</p>

Patterns of Temporal and Spatial Variability of Sponge Assemblages

<p>The primary goals of this thesis were to understand the spatial and temporal pattern of sponge assemblage variation over a variety of scales and investigate suitable monitoring methods for sponge assemblages. Sponges are an ecologically significant group in benthic marine communities, which are often ignored in current monitoring schemes. In chapter two the sponge biodiversity of New Zealand waters to 200m was examined using Taxonomic Distinctness measures initially to test if genera data could be used as a proxy for species level data in New Zealand waters. It was found that over 50% of the variation in genera biodiversity could be explained by location and depth around New Zealand. The study helped pinpoint where there were gaps in the New Zealand dataset, in particular for the West Coast of the South Island and also areas such as the Wellington South Coast, which had higher than expected values for Average and Variation Taxonomic distinctness measures, which as important areas where sponges should be monitored to make sure the high levels of biodiversity are protected. Taxonomic distinctness measures are useful for initially assessing how the biodiversity is distributed, especially when using a data set with uneven sampling effort, as it is robust to spatial and temporal bias in the majority of cases. However, there was an outlier to the genera data correlating well with the variation in species data in the case of a site dominated by Haliclona sp (Lyttelton Harbour). In chapters three and four the spatial and temporal variability of sponge assemblages of the Wellington South Coast were explored creating both a species list for the area and an understanding of how the sponge assemblage varies over time and space. There were significant differences in the sponges assemblages in similar habitat types over a scale of a few hundred metres. In addition, although all the sponge assemblages changed seasonally, the changes at each sampling site responded in a slightly different way most likely due to spatiotemporal variation in environmental conditions. A similar seasonal pattern was also observed in chapter five for sponge assemblages at Skomer Marine Reserve and this pattern was also clear when using morphological monitoring methods. This means that once a site has been mapped for biodiversity it is possible for some habitats to use morphological monitoring to identify if the sponge assemblage is changing significantly saving time and money. The results from Indonesia (chapter six) showed that although the sponge assemblages were changing significantly in the actual species present and their abundances, the proportion of diversity within each spatial level (quadrat, site and region) remained consistent when sampled at the same time each year throughout the five year study. In species rich assemblages there are a variety of life strategies that can respond differently to shifts in environmental conditions and contribute to ecological functioning in various ways. Various monitoring methods have been tested using sponge assemblages over various spatial and temporal scales in this thesis. Spatial, temporal and the interaction of spatial and temporal factors were all important for identifying significant assemblage differences at all of the sites. Further studies integrating the interaction of spatial and temporal factors into understanding monitoring data sets are vital to understand the patterns of assemblage variability and therefore incorporate into habitat management plans.</p>

Exploring an Efficient POI Recommendation Model Based on User Characteristics and Spatial-Temporal Factors

The advent of mobile scenario-based consumption popularizes and gradually maturates the application of point of interest (POI) recommendation services based on geographical location. However, the insufficient fusion of heterogeneous data in the current POI recommendation services leads to poor recommendation quality. In this paper, we propose a novel hybrid POI recommendation model (NHRM) based on user characteristics and spatial-temporal factors to enhance the recommendation effect. The proposed model contains three sub-models. The first model considers user preferences, forgetting characteristics, user influence, and trajectories. The second model studies the impact of the correlation between the locations of POIs and calculates the check-in probability of POI with the two-dimensional kernel density estimation method. The third model analyzes the influence of category of POI. Consequently, the above results were combined and top-K POIs were recommended to target users. The experimental results on Yelp and Meituan data sets showed that the recommendation performance of our method is superior to some other methods, and the problems of cold-start and data sparsity are alleviated to a certain extent.

THE EFFECT OF SPATIAL AND TEMPORAL FACTORS ON OCCUPANTS’ BLIND USE BEHAVIORS IN MULTIFAMILY RESIDENTIAL BUILDINGS

ABSTRACT Existing studies show that occupants’ behavior contribute to fluctuations in energy consumption of residential units within the same building configuration. Window blinds are one of the interior design elements that the occupants use to control indoor environmental conditions. The way that occupants adjust their blinds could affect the energy performance of buildings. Thus, the purpose of this research was to identify spatial and temporal explanatory variables that correlate with occupants’ use of the blinds and determine whether those variables relate to building design and surrounding sites. Data were collected by observing how occupants in apartment buildings located in a multifamily residential complex adjust their blinds. Descriptive statistics were used to define the effect of floor level, window orientation, day of observation, the hour of observation, and weather conditions on the blind status. In addition, a generalized linear mixed model was used to predict the effect of floor level and window orientation on the occupants’ adjustment of blinds. The results revealed that occupants’ use of the blinds correlated significantly with spatial factors, such as the apartment buildings’ floor level and windows’ orientation. Interesting blind use patterns were related to temporal factors, such as the day and hour of observation.

Annual, seasonal, cultural and vacation patterns in sleep, sedentary behaviour and physical activity: a systematic review and meta-analysis

Background Time spent in daily activities (sleep, sedentary behaviour and physical activity) has important consequences for health and wellbeing. The amount of time spent varies from day to day, yet little is known about the temporal nature of daily activity patterns in adults. The aim of this review is to identify the annual rhythms of daily activity behaviours in healthy adults and explore what temporal factors appear to influence these rhythms. Methods Six online databases were searched for cohort studies exploring within-year temporal patterns (e.g. season effects, vacation, cultural festivals) in sleep, sedentary behaviour or physical activity in healthy 18 to 65-year-old adults. Screening, data extraction, and risk of bias scoring were performed in duplicate. Extracted data was presented as mean daily minutes of each activity type, with transformations performed as needed. Where possible, meta-analyses were performed using random effect models to calculate standardised mean differences (SMD). Results Of the 7009 articles identified, 17 studies were included. Studies were published between 2003 and 2019, representing 14 countries and 1951 participants, addressing variation in daily activities across season (n = 11), Ramadan (n = 4), vacation (n = 1) and daylight savings time transitions (n = 1). Meta-analyses suggested evidence of seasonal variation in activity patterns, with sleep highest in autumn (+ 12 min); sedentary behaviour highest in winter (+ 19 min); light physical activity highest in summer (+ 19 min); and moderate-to-vigorous physical activity highest in summer (+ 2 min) when compared to the yearly mean. These trends were significant for light physical activity in winter (SMD = − 0.03, 95% CI − 0.58 to − 0.01, P = 0.04). Sleep appeared 64 min less during, compared to outside Ramadan (non-significant). Narrative analyses for the impact of vacation and daylight savings suggested that light physical activity is higher during vacation and that sleep increases after the spring daylight savings transition, and decreases after the autumn transition. Conclusions Research into temporal patterns in activity behaviours is scarce. Existing evidence suggests that seasonal changes and periodic changes to usual routine, such as observing religious events, may influence activity behaviours across the year. Further research measuring 24-h time use and exploring a wider variety of temporal factors is needed.

Temporal Factors Modulate Haloperidol-Induced Conditioned Catalepsy

Repeated pairings of a neutral context and the effects of haloperidol give rise to conditioned catalepsy when the context is subsequently presented in a drug-free test. In order to confirm whether this response is based on Pavlovian processes, we conducted two experiments involving two manipulations that affect conditioning intensity in classical conditioning procedures: time of joint exposure to the conditioned and the unconditioned stimulus, and the length of the inter-stimulus interval (ISI). The results revealed that both an increase in the length of context-drug pairings during conditioning and a reduced ISI between drug administration and context exposure increased conditioned catalepsy. These results are discussed in terms of the temporal peculiarities of those procedures that involve drugs as the unconditioned stimulus along with the role of Pavlovian conditioning in context-dependent catalepsy.

NanoDam identifies novel temporal transcription factors conserved between the Drosophila central brain and visual system

Temporal patterning of neural progenitors is an evolutionarily conserved strategy for generating neuronal diversity. Type II neural stem cells in the Drosophila central brain produce transit-amplifying intermediate neural progenitors (INPs) that exhibit temporal patterning. However, the known temporal factors cannot account for the neuronal diversity in the adult brain. To search for new temporal factors, we developed NanoDam, which enables rapid genome-wide profiling of endogenously-tagged proteins in vivo with a single genetic cross. Mapping the targets of known temporal transcription factors with NanoDam identified Homeobrain and Scarecrow (ARX and NKX2.1 orthologues) as novel temporal factors. We show that Homeobrain and Scarecrow define middle-aged and late INP temporal windows and play a role in cellular longevity. Strikingly, Homeobrain and Scarecrow have conserved functions as temporal factors in the developing visual system. NanoDam enables rapid cell type-specific genome-wide profiling with temporal resolution and can be easily adapted for use in higher organisms.