Protected areas are intended to promote biodiversity representation and persistence; yet, whether they are effective in degraded landscapes where much of the original vegetation structure remains ...intact has received relatively little attention. We test whether avian assemblages in communal rangelands in savannas differ from savannas supporting a full complement of native herbivores and predators. Birds were surveyed in 36 transect counts conducted over 18 days. We also compare the vegetation structure between the two land-use types to assess whether differences in bird assemblages could be attributed to changes in vegetation structure. Bird assemblages were richer, had greater abundances and different compositions inside protected areas than rangelands. The median body mass of birds was larger inside than outside protected areas, and rangelands supported fewer grassland specialists, but more closed-canopy specialists. However, no differences in feeding guild composition were found between protected areas and communal rangelands. Additionally, vegetation structure, but not richness, differed between protected areas and communal rangelands: communal rangelands had higher densities of woody vegetation and shorter grass height than the protected areas. Our findings suggest that the altered vegetation structure in communal grazing camps has led to changes in the species richness and composition of bird communities and has been selected by closed-canopy specialists at the cost of open grassy specialists. Hunting in communal rangelands is likely to have resulted in the loss of large birds and in reductions in bird abundance in the rangelands. Therefore, land-use management that does not lead to irreversible landscape transformation can nevertheless result in changes in the diversity, composition and functioning of native assemblages.Conservation implications: Savanna landscapes that are degraded, but not transformed, support fewer bird species, fewer open habitat specialists and smaller birds because of vegetation homogenisation.
Intelligence is related to both height and body mass index (BMI) at various stages of life. Several studies have demonstrated longitudinal relationships between these measures, but none has ...established whether height and intelligence, or BMI and intelligence are linked from childhood through to older age.
We assessed the relations between these measures over an interval of up to 67 years using data from the 36-Day Sample, an initially-representative sample of Scottish people born in 1936, assessed at age 11 years (N = 6,291) and again at 77-78 years (N = 722). This paper focuses on the 423 participants (6.7 % of the original sample) who provided relevant data in late adulthood.
Height and intelligence were significantly positively associated in childhood (β = .23) and late adulthood (β = .21-.29). Longitudinal correlations also showed that childhood intelligence predicted late-adulthood height (β = .20), and childhood height predicted late-adulthood cognitive ability (β = .12-.14). We observed no significant relationship between BMI and intelligence either in childhood or in late adulthood, nor any longitudinal association between the two in this sample.
Our results on height and intelligence are the first to demonstrate that their relationship spans almost seven decades, from childhood through to late adulthood, and they call for further investigation into the mechanisms underlying this lifelong association.
Fluctuating body asymmetry is theorized to indicate developmental instability, and to have small positive associations with low socioeconomic status (SES). Previous studies have reported small ...negative associations between fluctuating body asymmetry and cognitive functioning, but relationships between fluctuating brain asymmetry and cognitive functioning remain unclear. The present study investigated the association between general intelligence (a latent factor derived from a factor analysis on 13 cognitive tests) and the fluctuating asymmetry of four structural measures of brain hemispheric asymmetry: cortical surface area, cortical volume, cortical thickness, and white matter fractional anisotropy. The sample comprised members of the Lothian Birth Cohort 1936 (LBC1936, N = 636, mean age = 72.9 years). Two methods were used to calculate structural hemispheric asymmetry: in the first method, regions contributed equally to the overall asymmetry score; in the second method, regions contributed proportionally to their size. When regions contributed equally, cortical thickness asymmetry was negatively associated with general intelligence (β = −0.18,p < .001). There was no association between cortical thickness asymmetry and childhood SES, suggesting that other mechanisms are involved in the thickness asymmetry-intelligence association. Across all cortical metrics, asymmetry of regions identified by the parieto-frontal integration theory (P-FIT) was not more strongly associated with general intelligence than non-P-FIT asymmetry. When regions contributed proportionally, there were no associations between general intelligence and any of the asymmetry measures. The implications of these findings, and of different methods of calculating structural hemispheric asymmetry, are discussed.
•Previous work has shown links between cortical asymmetry and intelligence.•In the current study, two methods of calculating global cortical hemispheric asymmetry were compared.•Equal region contribution: the association between cortical thickness asymmetry and general intelligence was β = −0.18.•Proportional region contribution: no associations between three measures of cortical asymmetry and general intelligence.
The glucocorticoid hypothesis suggests that overexposure to stress may cause permanent upregulation of cortisol. Stress in youth may therefore influence cortisol levels even in older age. Using data ...from the 6-Day Sample, we investigated the effects of high stress in childhood, adolescence and early adulthood - as well as individual variables contributing to these measures; parental loss, social deprivation, school and home moves, illness, divorce and job instability - upon cortisol levels at age 77 years. Waking, waking +45 min (peak) and evening salivary cortisol samples were collected from 159 participants, and the 150 who were not using steroid medications were included in this study. After correcting for multiple comparisons, the only significant association was between early-adulthood job instability and later-life peak cortisol levels. After excluding participants with dementia or possible mild cognitive impairment, early-adulthood high stress showed significant associations with lower evening and mean cortisol levels, suggesting downregulation by stress, but these results did not survive correction for multiple comparisons. Overall, our results do not provide strong evidence of a relationship between stress in youth and later-life cortisol levels, but do suggest that some more long-term stressors, such as job instability, may indeed produce lasting upregulation of cortisol, persisting into the mid-to-late seventies.
Celotno besedilo
Dostopno za:
DOBA, IJS, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
Introduction
This study aims to first discover plasma proteomic biomarkers relating to neurodegeneration (N) and vascular (V) damage in cognitively normal individuals and second to discover proteins ...mediating sex‐related difference in N and V pathology.
Methods
Five thousand and thirty‐two plasma proteins were measured in 1061 cognitively normal individuals (628 females and 433 males), nearly 90% of whom had magnetic resonance imaging measures of hippocampal volume (as N) and white matter hyperintensities (as V).
Results
Differential protein expression analysis and co‐expression network analysis revealed different proteins and modules associated with N and V, respectively. Furthermore, causal mediation analysis revealed four proteins mediated sex‐related difference in N and one protein mediated such difference in V damage.
Discussion
Once validated, the identified proteins could help to select cognitively normal individuals with N and V pathology for Alzheimer's disease clinical trials and provide targets for further mechanistic studies on brain sex differences, leading to sex‐specific therapeutic strategies.
Background:
Within young individuals, mood disorder onset may be related to changes in trajectory of brain structure development. To date, however, longitudinal prospective studies remain scarce and ...show partly contradictory findings, with a lack of emphasis on changes at the level of global brain patterns. Cross-sectional adult studies have applied such methods and show that mood disorders are associated with accelerated brain aging. Currently, it remains unclear whether young individuals show differential brain structure aging trajectories associated with onset of mood disorder and/or presence of familial risk.
Methods:
Participants included young individuals (15-30 years, 53%F) from the prospective longitudinal Scottish Bipolar Family Study with and without close family history of mood disorder. All were well at time of recruitment. Implementing a structural MRI-based brain age prediction model, we globally assessed individual trajectories of age-related structural change using the difference between predicted brain age and chronological age (brain-predicted age difference (brain-PAD)) at baseline and at 2-year follow-up. Based on follow-up clinical assessment, individuals were categorised into three groups: (i) controls who remained well (C-well,
n
= 93), (ii) high familial risk who remained well (HR-well,
n
= 74) and (iii) high familial risk who developed a mood disorder (HR-MD,
n
= 35).
Results:
At baseline, brain-PAD was comparable between groups. Results showed statistically significant negative trajectories of brain-PAD between baseline and follow-up for HR-MD versus C-well (
β
= -0.60,
p
corrected
< 0.001) and HR-well (
β
= -0.36,
p
corrected
= 0.02), with a potential intermediate trajectory for HR-well (
β
= -0.24 years,
p
corrected
= 0.06).
Conclusions:
These preliminary findings suggest that within young individuals, onset of mood disorder and familial risk may be associated with a deceleration in brain structure aging trajectories. Extended longitudinal research will need to corroborate findings of emerging maturational lags in relation to mood disorder risk and onset.
Within young individuals, mood disorder onset may be related to changes in trajectory of brain structure development. To date, however, longitudinal prospective studies remain scarce and show partly ...contradictory findings, with a lack of emphasis on changes at the level of global brain patterns. Cross-sectional adult studies have applied such methods and show that mood disorders are associated with accelerated brain aging. Currently, it remains unclear whether young individuals show differential brain structure aging trajectories associated with onset of mood disorder and/or presence of familial risk.
Participants included young individuals (15-30 years, 53%F) from the prospective longitudinal Scottish Bipolar Family Study with and without close family history of mood disorder. All were well at time of recruitment. Implementing a structural MRI-based brain age prediction model, we globally assessed individual trajectories of age-related structural change using the difference between predicted brain age and chronological age (brain-predicted age difference (brain-PAD)) at baseline and at 2-year follow-up. Based on follow-up clinical assessment, individuals were categorised into three groups: (i) controls who remained well (C-well,
= 93), (ii) high familial risk who remained well (HR-well,
= 74) and (iii) high familial risk who developed a mood disorder (HR-MD,
= 35).
At baseline, brain-PAD was comparable between groups. Results showed statistically significant negative trajectories of brain-PAD between baseline and follow-up for HR-MD versus C-well (
= -0.60,
< 0.001) and HR-well (
= -0.36,
= 0.02), with a potential intermediate trajectory for HR-well (
= -0.24 years,
= 0.06).
These preliminary findings suggest that within young individuals, onset of mood disorder and familial risk may be associated with a deceleration in brain structure aging trajectories. Extended longitudinal research will need to corroborate findings of emerging maturational lags in relation to mood disorder risk and onset.
STratifying Resilience and Depression Longitudinally (STRADL) is a population-based study built on the Generation Scotland: Scottish Family Health Study (GS:SFHS) resource. The aim of STRADL is to ...subtype major depressive disorder (MDD) on the basis of its aetiology, using detailed clinical, cognitive, and brain imaging assessments. The GS:SFHS provides an important opportunity to study complex gene-environment interactions, incorporating linkage to existing datasets and inclusion of early-life variables for two longitudinal birth cohorts. Specifically, data collection in STRADL included: socio-economic and lifestyle variables; physical measures; questionnaire data that assesses resilience, early-life adversity, personality, psychological health, and lifetime history of mood disorder; laboratory samples; cognitive tests; and brain magnetic resonance imaging. Some of the questionnaire and cognitive data were first assessed at the GS:SFHS baseline assessment between 2006-2011, thus providing longitudinal measures relevant to the study of depression, psychological resilience, and cognition. In addition, routinely collected historic NHS data and early-life variables are linked to STRADL data, further providing opportunities for longitudinal analysis. Recruitment has been completed and we consented and tested 1,188 participants.
Emerging evidence suggests that obesity impacts brain physiology at multiple levels. Here we aimed to clarify the relationship between obesity and brain structure using structural MRI (n = 6420) and ...genetic data (n = 3907) from the ENIGMA Major Depressive Disorder (MDD) working group. Obesity (BMI > 30) was significantly associated with cortical and subcortical abnormalities in both mass-univariate and multivariate pattern recognition analyses independent of MDD diagnosis. The most pronounced effects were found for associations between obesity and lower temporo-frontal cortical thickness (maximum Cohen´s d (left fusiform gyrus) = -0.33). The observed regional distribution and effect size of cortical thickness reductions in obesity revealed considerable similarities with corresponding patterns of lower cortical thickness in previously published studies of neuropsychiatric disorders. A higher polygenic risk score for obesity significantly correlated with lower occipital surface area. In addition, a significant age-by-obesity interaction on cortical thickness emerged driven by lower thickness in older participants. Our findings suggest a neurobiological interaction between obesity and brain structure under physiological and pathological brain conditions.
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•We validate APSIM-Potato across several soil-climate-management combinations.•We evaluated the difference of yield and irrigation using input/output aggregation.•PAWC and source of ...water were the main drivers of differences due to aggregation.•Maximum differences were found for rainfed yield and irrigation requirement.•We highlight the need to quantify biases on model outputs due to data aggregation.
Crop models were originally developed for application at the field scale but are increasingly used to assess the impact of climate and/or agronomic practices on crop growth and yield and water dynamics at larger scales. This raises the question of how data aggregation approaches affect outputs when using crop models at large spatial scales. This study investigates how input and output data aggregation affected simulated rainfed and irrigated potato yield and irrigation water requirement (IWR) across potato production areas in Tasmania, Australia. First, the yield and IWR with aggregated model inputs at 15, 25 and 40 km resolutions (input aggregation) was simulated. Second, simulated model outputs generated with high-resolution input data were aggregated to 15, 25 and 40 km resolutions (output aggregation) and compared to the corresponding yield and IWR with simulations based on input data aggregation. Finally, the differences (D) (DY and DIWR for yield and IWR, respectively) between grids using input and output aggregation were evaluated. The results indicate that the effect of input and output data aggregation on yield depends on water-driven factors including plant available water capacity (PAWC), rainfall and irrigation. Maximum D values were found for rainfed yield (4.4 t ha−1) and IWR (137 mm). DY variations were correlated with the differences of PAWC caused by data aggregation in 82 % of potato production areas. Differences between aggregation methods were reduced when growing season rainfall increased. We conclude that PAWC and the source of water (rainfall or rainfall + irrigation) explained the larger errors associated with the input and output data aggregation on simulated potato yield and IWR. Future studies should consider the data aggregation method in their assessment to minimize errors and therefore produce higher quality advice or farming decisions.
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