Increasing attention has been drawn to the misuse of statistical methods over recent years, with particular concern about the prevalence of practices such as poor experimental design, cherry picking and inadequate reporting. These failures are largely unintentional and no more common in ecology than in other scientific disciplines, with many of them easily remedied given the right guidance. Originating from a discussion at the 2020 International Statistical Ecology Conference, we show how ecologists can build their research following four guiding principles for impactful statistical research practices: (1) define a focussed research question, then plan sampling and analysis to answer it; (2) develop a model that accounts for the distribution and dependence of your data; (3) emphasise effect sizes to replace statistical significance with ecological relevance; and (4) report your methods and findings in sufficient detail so that your research is valid and reproducible. These principles provide a framework for experimental design and reporting that guards against unsound practices. Starting with a well‐defined research question allows researchers to create an efficient study to answer it, and guards against poor research practices that lead to poor estimation of the direction, magnitude, and uncertainty of ecological relationships, and to poor replicability. Correct and appropriate statistical models give sound conclusions. Good reporting practices and a focus on ecological relevance make results impactful and replicable. Illustrated with two examples—an experiment to study the impact of disturbance on upland wetlands, and an observational study on blue tit colouring—this paper explains the rationale for the selection and use of effective statistical practices and provides practical guidance for ecologists seeking to improve their use of statistical methods.

As species recover from exploitation, continued assessments of connectivity and population structure are warranted to provide information for conservation and management. This is particularly true in species with high dispersal capacity, such as migratory whales, where patterns of connectivity could change rapidly. Here we build on a previous long-term, large-scale collaboration on southern right whales (Eubalaena australis) to combine new (n_new) and published (n_pub) mitochondrial (mtDNA) and microsatellite genetic data from all major wintering grounds and, uniquely, the South Georgia (Islas Georgias del Sur: SG) feeding grounds. Specifically, we include data from Argentina (n_pub mtDNA/microsatellite = 208/46), Brazil (n_new mtDNA/microsatellite = 50/50), South Africa (n_new mtDNA/microsatellite = 66/77, n_pub mtDNA/microsatellite = 350/47), Chile–Peru (n_new mtDNA/microsatellite = 1/1), the Indo-Pacific (n_pub mtDNA/microsatellite = 769/126), and SG (n_pub mtDNA/microsatellite = 8/0, n_new mtDNA/microsatellite = 3/11) to investigate the position of previously unstudied habitats in the migratory network: Brazil, SG, and Chile–Peru. These new genetic data show connectivity between Brazil and Argentina, exemplified by weak genetic differentiation and the movement of 1 genetically identified individual between the South American grounds. The single sample from Chile–Peru had an mtDNA haplotype previously only observed in the Indo-Pacific and had a nuclear genotype that appeared admixed between the Indo-Pacific and South Atlantic, based on genetic clustering and assignment algorithms. The SG samples were clearly South Atlantic and were more similar to the South American than the South African wintering grounds. This study highlights how international collaborations are critical to provide context for emerging or recovering regions, like the SG feeding ground, as well as those that remain critically endangered, such as Chile–Peru.

Tertiary institutions internationally aim to increase student diversity, however are struggling to achieve equitable academic outcomes for indigenous and ethnic minority students and detailed exploration of factors that impact on success is required. This study explored the predictive effect of admission variables on academic outcomes for health professional students by ethnic grouping. Kaupapa Māori and Pacific research methodologies were used to conduct a quantitative analysis using data for 2686 health professional students [150 Māori, 257 Pacific, 2279, non-Māori non-Pacific (nMnP)]. The predictive effect of admission variables: school decile; attending school in Auckland; type of admission; bridging programme; and first-year bachelor results on academic outcomes: year 2–4 grade point average (GPA); graduating; graduating in the minimum time; and optimal completion for the three ethnic groupings and the full cohort was explored using multiple regression analyses. After adjusting for admission variables, for every point increase in first year bachelor GPA: year 2–4 GPA increased by an average of 0.46 points for Māori (p = 0.0002, 95% CI 0.22, 0.69), 0.70 points for Pacific (p < 0.0001, CI 0.52, 0.87), and 0.55 points for nMnP (p < 0.0001, CI 0.51, 0.58) students. For the total cohort, ethnic grouping was consistently the most significant predictor of academic outcomes. This study demonstrated clear differences in academic outcomes between both Māori and Pacific students when compared to nMnP students. Some (but not all) of the disparities between ethnic groupings could be explained by controlling for admission variables.

Objective To determine associations between admission markers of socioeconomic status, transitioning, bridging programme attendance and prior academic preparation on academic outcomes for indigenous Māori, Pacific and rural students admitted into medicine under access pathways designed to widen participation. Findings were compared with students admitted via the general (usual) admission pathway. Design Retrospective observational study using secondary data. Setting 6-year medical programme (MBChB), University of Auckland, Aotearoa New Zealand. Students are selected and admitted into Year 2 following a first year (undergraduate) or prior degree (graduate). Participants 1676 domestic students admitted into Year 2 between 2002 and 2012 via three pathways: GENERAL admission (1167), Māori and Pacific Admission Scheme—MAPAS (317) or Rural Origin Medical Preferential Entry—ROMPE (192). Of these, 1082 students completed the programme in the study period. Main outcome measures Graduated from medical programme (yes/no), academic scores in Years 2–3 (Grade Point Average (GPA), scored 0–9). Results 735/778 (95%) of GENERAL, 111/121 (92%) of ROMPE and 146/183 (80%) of MAPAS students graduated from intended programme. The graduation rate was significantly lower in the MAPAS students (p<0.0001). The average Year 2–3 GPA was 6.35 (SD 1.52) for GENERAL, which was higher than 5.82 (SD 1.65, p=0.0013) for ROMPE and 4.33 (SD 1.56, p<0.0001) for MAPAS. Multiple regression analyses identified three key predictors of better academic outcomes: bridging programme attendance, admission as an undergraduate and admission GPA/Grade Point Equivalent (GPE). Attending local urban schools and higher school deciles were also associated with a greater likelihood of graduation. All regression models have controlled for predefined baseline confounders (gender, age and year of admission). Conclusions There were varied associations between admission variables and academic outcomes across the three admission pathways. Equity-targeted admission programmes inclusive of variations in academic threshold for entry may support a widening participation agenda, however, additional academic and pastoral supports are recommended.