Teaching Statistics to Biology students at Abertay:would an integrative teaching approach help or hinder their learning?

Statistical skills are becoming more important for graduates in the STEM sector. However, in many courses in these fields, statistics is not integrated in the rest of the curriculum, even though such an approach can be very beneficial for acquiring such skills. Integrating statistics in the rest of the curriculum can facilitate so called deep learning to enhance a relational and abstract understanding of statistics with the rest of their learning. This paper discusses some of the few available studies that tested the effect of integrating statistics in biology undergraduate classes. It consequently discusses how such an approach would align with the Abertay Graduate attributes and the Abertay Employability Strategy

Teaching Statistics to Biology students at Abertay:would an integrative teaching approach help or hinder their learning?

Statistical skills are becoming more important for graduates in the STEM sector. However, in many courses in these fields, statistics is not integrated in the rest of the curriculum, even though such an approach can be very beneficial for acquiring such skills. Integrating statistics in the rest of the curriculum can facilitate so called deep learning to enhance a relational and abstract understanding of statistics with the rest of their learning. This paper discusses some of the few available studies that tested the effect of integrating statistics in biology undergraduate classes. It consequently discusses how such an approach would align with the Abertay Graduate attributes and the Abertay Employability Strategy

Shrub encroachment in Arctic tundra : Betula nana effects on above- and belowground litter decomposition

Author Posting. © Ecological Society of America, 2017. This article is posted here by permission of Ecological Society of America for personal use, not for redistribution. The definitive version was published in Ecology 98 (2017): 1361–1376, doi:10.1002/ecy.1790.Rapid arctic vegetation change as a result of global warming includes an increase in the cover and biomass of deciduous shrubs. Increases in shrub abundance will result in a proportional increase of shrub litter in the litter community, potentially affecting carbon turnover rates in arctic ecosystems. We investigated the effects of leaf and root litter of a deciduous shrub, Betula nana, on decomposition, by examining species-specific decomposition patterns, as well as effects of Betula litter on the decomposition of other species. We conducted a 2-yr decomposition experiment in moist acidic tundra in northern Alaska, where we decomposed three tundra species (Vaccinium vitis-idaea, Rhododendron palustre, and Eriophorum vaginatum) alone and in combination with Betula litter. Decomposition patterns for leaf and root litter were determined using three different measures of decomposition (mass loss, respiration, extracellular enzyme activity). We report faster decomposition of Betula leaf litter compared to other species, with support for species differences coming from all three measures of decomposition. Mixing effects were less consistent among the measures, with negative mixing effects shown only for mass loss. In contrast, there were few species differences or mixing effects for root decomposition. Overall, we attribute longer-term litter mass loss patterns to patterns created by early decomposition processes in the first winter. We note numerous differences for species patterns between leaf and root decomposition, indicating that conclusions from leaf litter experiments should not be extrapolated to below-ground decomposition. The high decomposition rates of Betula leaf litter aboveground, and relatively similar decomposition rates of multiple species below, suggest a potential for increases in turnover in the fast-decomposing carbon pool of leaves and fine roots as the dominance of deciduous shrubs in the Arctic increases, but this outcome may be tempered by negative litter mixing effects during the early stages of encroachment.National Science Foundation Grant Numbers: OPP-0909507, OPP-0807639, ARC-0806451; Arctic LTER Project. Grant Number: DEB-102684

Contrasting effects of long term versus short-term nitrogen addition on photosynthesis and respiration in the Arctic

We examined the effects of short (<1–4 years) and long-term (22 years) nitrogen (N) and/or phosphorus (P) addition on the foliar CO2 exchange parameters of the Arctic species Betula nana and Eriophorum vaginatum in northern Alaska. Measured variables included: the carboxylation efficiency of Rubisco (Vcmax), electron transport capacity (Jmax), dark respiration (Rd), chlorophyll a and b content (Chl), and total foliar N (N). For both B. nana and E. vaginatum, foliar N increased by 20–50 % as a consequence of 1–22 years of fertilisation, respectively, and for B. nana foliar N increase was consistent throughout the whole canopy. However, despite this large increase in foliar N, no significant changes in Vcmax and Jmax were observed. In contrast, Rd was significantly higher (>25 %) in both species after 22 years of N addition, but not in the shorter-term treatments. Surprisingly, Chl only increased in both species the first year of fertilisation (i.e. the first season of nutrients applied), but not in the longer-term treatments. These results imply that: (1) under current (low) N availability, these Arctic species either already optimize their photosynthetic capacity per leaf area, or are limited by other nutrients; (2) observed increases in Arctic NEE and GPP with increased nutrient availability are caused by structural changes like increased leaf area index, rather than increased foliar photosynthetic capacity and (3) short-term effects (1–4 years) of nutrient addition cannot always be extrapolated to a larger time scale, which emphasizes the importance of long-term ecological experiments

Potential and limitations of inferring ecosystem photosynthetic capacity from leaf functional traits

The aim of this study was to systematically analyze the potential and limitations of using plant functional trait observations from global databases versus in situ data to improve our understanding of vegetation impacts on ecosystem functional properties (EFPs). Using ecosystem photosynthetic capacity as an example, we first provide an objective approach to derive robust EFP estimates from gross primary productivity (GPP) obtained from eddy covariance flux measurements. Second, we investigate the impact of synchronizing EFPs and plant functional traits in time and space to evaluate their relationships, and the extent to which we can benefit from global plant trait databases to explain the variability of ecosystem photosynthetic capacity. Finally, we identify a set of plant functional traits controlling ecosystem photosynthetic capacity at selected sites. Suitable estimates of the ecosystem photosynthetic capacity can be derived from light response curve of GPP responding to radiation (photosynthetically active radiation or absorbed photosynthetically active radiation). Although the effect of climate is minimized in these calculations, the estimates indicate substantial interannual variation of the photosynthetic capacity, even after removing site-years with confounding factors like disturbance such as fire events. The relationships between foliar nitrogen concentration and ecosystem photosynthetic capacity are tighter when both of the measurements are synchronized in space and time. When using multiple plant traits simultaneously as predictors for ecosystem photosynthetic capacity variation, the combination of leaf carbon to nitrogen ratio with leaf phosphorus content explains the variance of ecosystem photosynthetic capacity best (adjusted R-2 = 0.55). Overall, this study provides an objective approach to identify links between leaf level traits and canopy level processes and highlights the relevance of the dynamic nature of ecosystems. Synchronizing measurements of eddy covariance fluxes and plant traits in time and space is shown to be highly relevant to better understand the importance of intra-and interspecific trait variation on ecosystem functioning.Peer reviewe

TRY plant trait database – enhanced coverage and open access

Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants - determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits - almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Altitudinal variation in leaf mass per unit area, leaf tissue density and foliar nitrogen and phosphorus content along an Amazon-Andes gradient in Peru

Background: Leaf traits are important in determining the capacity for a plant to acquire carbon, but few data are available for montane cloud forests in the Andes. Aims: To investigate the changes in leaf traits along a large altitudinal transect (220-3600 m) from lowland to montane cloud forest in Peru. Methods: We determined leaf mass per area (LMA, g m-2), leaf tissue density (Ld, g cm-3), and foliar nitrogen (N) and phosphorus (P) content, both on a mass (Nm and Pm, %) and area (Na and Pa, g m-2) basis for the most abundant species locally. Results: LMA increased with altitude (62.8-169.4 g m-2), though overall, LMA was lower than in comparable tropical elevation gradients. Nm declined significantly with altitude (2.39-1.25%, P < 0.05), but Nm contents were higher than in comparable studies. The relatively high Nm and low LMA values are consistent with published global leaf trait datasets. No altitudinal trend for Pm was found; rather, our data highlighted the spatial variability in Pm (and Pa) within and among sites at different elevations. Foliar N:P ratios did not show a trend with altitude and did not indicate N limitation except at 3000 m altitude. Conclusions: Though leaf traits showed altitudinal trends similar to other studies, contrary to the general hypothesis, our data suggest that the tropical montane forests presented here are not N limited