Investigating the Direct and Indirect Effects of Forest Fragmentation on Plant Functional Diversity

Ongoing habitat loss and fragmentation alter the functional diversity of forests. Generalising the magnitude of change in functional diversity of fragmented landscapes and its drivers is challenging because of the multiple scales at which landscape fragmentation takes place. Here we propose a multi-scale approach to determine whether fragmentation processes at the local and landscape scales are reducing functional diversity of trees in the East Usambara Mountains, Tanzania. We employ a structural equation modelling approach using five key plant traits (seed length, dispersal mode, shade tolerance, maximum tree height, and wood density) to better understand the functional responses of trees to fragmentation at multiple scales. Our results suggest both direct and indirect effects of forest fragmentation on tree functional richness, evenness and divergence. A reduction in fragment area appears to exacerbate the negative effects resulting from an increased amount of edge habitat and loss of shape complexity, further reducing richness and evenness of traits related to resource acquisition and favouring tree species with fast growth. As anthropogenic disturbances affect forests around the world, we advocate to include the direct and indirect effects of forest fragmentation processes to gain a better understanding of shifts in functional diversity that can inform future management efforts

Employing Plant Functional Groups to Advance Seed Dispersal Ecology and Conservation

Seed dispersal enables plants to reach hospitable germination sites and escape natural enemies. Understanding when and how much seed dispersal matters to plant fitness is critical for understanding plant population and community dynamics. At the same time, the complexity of factors that determine if a seed will be successfully dispersed and subsequently develop into a reproductive plant is daunting. Quantifying all factors that may influence seed dispersal effectiveness for any potential seed-vector relationship would require an unrealistically large amount of time, materials and financial resources. On the other hand, being able to make dispersal predictions is critical for predicting whether single species and entire ecosystems will be resilient to global change. Building on current frameworks, we here posit that seed dispersal ecology should adopt plant functional groups as analytical units to reduce this complexity to manageable levels. Functional groups can be used to distinguish, for their constituent species, whether it matters (i) if seeds are dispersed, (ii) into what context they are dispersed and (iii) what vectors disperse them. To avoid overgeneralization, we propose that the utility of these functional groups may be assessed by generating predictions based on the groups and then testing those predictions against species-specific data. We suggest that data collection and analysis can then be guided by robust functional group definitions. Generalizing across similar species in this way could help us to better understand the population and community dynamics of plants and tackle the complexity of seed dispersal as well as its disruption

The scale dependency of trait-based tree neighborhood models

Questions: We asked: (a) whether the strength of conspecific and heterospecific neighborhood crowding effects on focal tree survival and growth vary with neighborhood radii; and (b) if the relative strength of the effect of neighborhood interactions on tree growth and survival varies with neighborhood scale. Location: Luquillo Forest Dynamics Plot, Puerto Rico. Methods: We used tree survival and growth data and included information on species‐mean trait values related to several leaf traits, maximum height, seed mass and wood density. We incorporated a tree neighborhood modeling approach that uses an area around a focal tree with a specified radius, to describe the interactions between a focal tree and its neighbors. We constructed survival and growth models for each functional trait using a Bayesian approach, and varied the size of the radius from 5 m to 30 m, at 5‐m intervals. Results: The results suggested that the estimated effects of conspecific and heterospecific neighbors on tree performance do not vary based on the size of the neighborhood (5–30 m), suggesting that the effects of conspecific and heterospecific neighbors on the performance of a focal tree likely do not vary substantially beyond a neighborhood radius of 5 m in the Luquillo forest. In contrast, the estimated strength of the functional neighborhood (effect of neighbors based on their functional trait values) on tree performance was dependent on the neighborhood range. Our results also suggested that the effects of trait distances and trait hierarchies on tree survival and growth are acting simultaneously and at the same spatial scales. Conclusion: Findings from this study highlight the importance of spatial scale in community assembly processes, and specifically, call for increased attention when selecting the radius that defines the neighborhood around a focal tree as the selected neighborhood radius influences the community patterns discovered, and affects the conclusions about the drivers that control community assembly

BRCA2 polymorphic stop codon K3326X and the risk of breast, prostate, and ovarian cancers

Background: The K3326X variant in BRCA2 (BRCA2*c.9976A>T; p.Lys3326*; rs11571833) has been found to be associated with small increased risks of breast cancer. However, it is not clear to what extent linkage disequilibrium with fully pathogenic mutations might account for this association. There is scant information about the effect of K3326X in other hormone-related cancers. Methods: Using weighted logistic regression, we analyzed data from the large iCOGS study including 76 637 cancer case patients and 83 796 control patients to estimate odds ratios (ORw) and 95% confidence intervals (CIs) for K3326X variant carriers in relation to breast, ovarian, and prostate cancer risks, with weights defined as probability of not having a pathogenic BRCA2 variant. Using Cox proportional hazards modeling, we also examined the associations of K3326X with breast and ovarian cancer risks among 7183 BRCA1 variant carriers. All statistical tests were two-sided. Results: The K3326X variant was associated with breast (ORw = 1.28, 95% CI = 1.17 to 1.40, P = 5.9x10- 6) and invasive ovarian cancer (ORw = 1.26, 95% CI = 1.10 to 1.43, P = 3.8x10-3). These associations were stronger for serous ovarian cancer and for estrogen receptor–negative breast cancer (ORw = 1.46, 95% CI = 1.2 to 1.70, P = 3.4x10-5 and ORw = 1.50, 95% CI = 1.28 to 1.76, P = 4.1x10-5, respectively). For BRCA1 mutation carriers, there was a statistically significant inverse association of the K3326X variant with risk of ovarian cancer (HR = 0.43, 95% CI = 0.22 to 0.84, P = .013) but no association with breast cancer. No association with prostate cancer was observed. Conclusions: Our study provides evidence that the K3326X variant is associated with risk of developing breast and ovarian cancers independent of other pathogenic variants in BRCA2. Further studies are needed to determine the biological mechanism of action responsible for these associations

Advancing an interdisciplinary framework to study seed dispersal ecology

Although dispersal is generally viewed as a crucial determinant for the fitness of any organism, our understanding of its role in the persistence and spread of plant populations remains incomplete. Generalizing and predicting dispersal processes are challenging due to context dependence of seed dispersal, environmental heterogeneity and interdependent processes occurring over multiple spatial and temporal scales. Current population models often use simple phenomenological descriptions of dispersal processes, limiting their ability to examine the role of population persistence and spread, especially under global change. To move seed dispersal ecology forward, we need to evaluate the impact of any single seed dispersal event within the full spatial and temporal context of a plant’s life history and environmental variability that ultimately influences a population’s ability to persist and spread. In this perspective, we provide guidance on integrating empirical and theoretical approaches that account for the context dependency of seed dispersal to improve our ability to generalize and predict the consequences of dispersal, and its anthropogenic alteration, across systems. We synthesize suitable theoretical frameworks for this work and discuss concepts, approaches and available data from diverse subdisciplines to help operationalize concepts, highlight recent breakthroughs across research areas and discuss ongoing challenges and open questions. We address knowledge gaps in the movement ecology of seeds and the integration of dispersal and demography that could benefit from such a synthesis. With an interdisciplinary perspective, we will be able to better understand how global change will impact seed dispersal processes, and potential cascading effects on plant population persistence, spread and biodiversity

The total dispersal kernel: a review and future directions

The distribution and abundance of plants across the world depends in part on their ability to move, which is commonly characterized by a dispersal kernel. For seeds, the total dispersal kernel (TDK) describes the combined influence of all primary, secondary and higher-order dispersal vectors on the overall dispersal kernel for a plant individual, population, species or community. Understanding the role of each vector within the TDK, and their combined influence on the TDK, is critically important for being able to predict plant responses to a changing biotic or abiotic environment. In addition, fully characterizing the TDK by including all vectors may affect predictions of population spread. Here, we review existing research on the TDK and discuss advances in empirical, conceptual modelling and statistical approaches that will facilitate broader application. The concept is simple, but few examples of well-characterized TDKs exist. We find that significant empirical challenges exist, as many studies do not account for all dispersal vectors (e.g. gravity, higher-order dispersal vectors), inadequately measure or estimate long-distance dispersal resulting from multiple vectors and/or neglect spatial heterogeneity and context dependence. Existing mathematical and conceptual modelling approaches and statistical methods allow fitting individual dispersal kernels and combining them to form a TDK; these will perform best if robust prior information is available. We recommend a modelling cycle to parameterize TDKs, where empirical data inform models, which in turn inform additional data collection. Finally, we recommend that the TDK concept be extended to account for not only where seeds land, but also how that location affects the likelihood of establishing and producing a reproductive adult, i.e. the total effective dispersal kernel

Analysis of the CD1 Antigen Presenting System in Humanized SCID Mice

CD1 molecules are glycoproteins that present lipids and glycolipids for recognition by T cells. CD1-dependent immune activation has been implicated in a wide range of immune responses, however, our understanding of the role of this pathway in human disease remains limited because of species differences between humans and other mammals: whereas humans express five different CD1 gene products (CD1a, CD1b, CD1c, CD1d, and CD1e), muroid rodents express only one CD1 isoform (CD1d). Here we report that immune deficient mice engrafted with human fetal thymus, liver, and CD34+ hematopoietic stem cells develop a functional human CD1 compartment. CD1a, b, c, and d isoforms were highly expressed by human thymocytes, and CD1a+ cells with a dendritic morphology were present in the thymic medulla. CD1+ cells were also detected in spleen, liver, and lungs. APCs from spleen and liver were capable of presenting bacterial glycolipids to human CD1-restricted T cells. ELISpot analyses of splenocytes demonstrated the presence of CD1-reactive IFN-γ producing cells. CD1d tetramer staining directly identified human iNKT cells in spleen and liver samples from engrafted mice, and injection of the glycolipid antigen α-GalCer resulted in rapid elevation of human IFN-γ and IL-4 levels in the blood indicating that the human iNKT cells are biologically active in vivo. Together, these results demonstrate that the human CD1 system is present and functionally competent in this humanized mouse model. Thus, this system provides a new opportunity to study the role of CD1-related immune activation in infections to human-specific pathogens

Employing plant functional groups to advance seed dispersal ecology and conservation

Seed dispersal enables plants to reach hospitable germination sites and escape natural enemies. Understanding when and how much seed dispersal matters to plant fitness is critical for understanding plant population and community dynamics. At the same time, the complexity of factors that determine if a seed will be successfully dispersed and subsequently develop into a reproductive plant is daunting. Quantifying all factors that may influence seed dispersal effectiveness for any potential seed-vector relationship would require an unrealistically large amount of time, materials and financial resources. On the other hand, being able to make dispersal predictions is critical for predicting whether single species and entire ecosystems will be resilient to global change. Building on current frameworks, we here posit that seed dispersal ecology should adopt plant functional groups as analytical units to reduce this complexity to manageable levels. Functional groups can be used to distinguish, for their constituent species, whether it matters (i) if seeds are dispersed, (ii) into what context they are dispersed and (iii) what vectors disperse them. To avoid overgeneralization, we propose that the utility of these functional groups may be assessed by generating predictions based on the groups and then testing those predictions against species-specific data. We suggest that data collection and analysis can then be guided by robust functional group definitions. Generalizing across similar species in this way could help us to better understand the population and community dynamics of plants and tackle the complexity of seed dispersal as well as its disruption

Discordant identification of pediatric severe sepsis by research and clinical definitions in the SPROUT international point prevalence study

Introduction: Consensus criteria for pediatric severe sepsis have standardized enrollment for research studies. However, the extent to which critically ill children identified by consensus criteria reflect physician diagnosis of severe sepsis, which underlies external validity for pediatric sepsis research, is not known. We sought to determine the agreement between physician diagnosis and consensus criteria to identify pediatric patients with severe sepsis across a network of international pediatric intensive care units (PICUs). Methods: We conducted a point prevalence study involving 128 PICUs in 26 countries across 6 continents. Over the course of 5 study days, 6925 PICU patients <18 years of age were screened, and 706 with severe sepsis defined either by physician diagnosis or on the basis of 2005 International Pediatric Sepsis Consensus Conference consensus criteria were enrolled. The primary endpoint was agreement of pediatric severe sepsis between physician diagnosis and consensus criteria as measured using Cohen's ?. Secondary endpoints included characteristics and clinical outcomes for patients identified using physician diagnosis versus consensus criteria. Results: Of the 706 patients, 301 (42.6 %) met both definitions. The inter-rater agreement (? ± SE) between physician diagnosis and consensus criteria was 0.57 ± 0.02. Of the 438 patients with a physician's diagnosis of severe sepsis, only 69 % (301 of 438) would have been eligible to participate in a clinical trial of pediatric severe sepsis that enrolled patients based on consensus criteria. Patients with physician-diagnosed severe sepsis who did not meet consensus criteria were younger and had lower severity of illness and lower PICU mortality than those meeting consensus criteria or both definitions. After controlling for age, severity of illness, number of comorbid conditions, and treatment in developed versus resource-limited regions, patients identified with severe sepsis by physician diagnosis alone or by consensus criteria alone did not have PICU mortality significantly different from that of patients identified by both physician diagnosis and consensus criteria. Conclusions: Physician diagnosis of pediatric severe sepsis achieved only moderate agreement with consensus criteria, with physicians diagnosing severe sepsis more broadly. Consequently, the results of a research study based on consensus criteria may have limited generalizability to nearly one-third of PICU patients diagnosed with severe sepsis