It is time to acknowledge and overcome conservation's deep-seated systemic racism, which has historically marginalized Black, Indigenous and people of colour (BIPOC) communities and continues to do so. We describe how the mutually reinforcing ‘twin spheres’ of conservation science and conservation practice perpetuate this systemic racism. We trace how institutional structures in conservation science (e.g. degree programmes, support and advancement opportunities, course syllabuses) can systematically produce conservation graduates with partial and problematic conceptions of conservation's history and contemporary purposes. Many of these graduates go on to work in conservation practice, reproducing conservation's colonial history by contributing to programmes based on outmoded conservation models that disproportionately harm rural BIPOC communities and further restrict access and inclusion for BIPOC conservationists. We provide practical, actionable proposals for breaking vicious cycles of racism in the system of conservation we have with virtuous cycles of inclusion, equality, equity and participation in the system of conservation we want.

Early‐life environmental conditions can provide a source of individual variation in life‐history strategies and senescence patterns. Conditions experienced in early life can be quantified by measuring telomere length, which can act as a biomarker of survival probability in some species. Here, we investigate whether seasonal changes, weather conditions and group size are associated with early‐life and/or early‐adulthood telomere length in a wild population of European badgers (Meles meles). We found substantial intra‐annual changes in telomere length during the first 3 years of life, where within‐individual effects showed shorter telomere lengths in the winter following the first spring and a trend for longer telomere lengths in the second spring compared to the first winter. In terms of weather conditions, cubs born in warmer, wetter springs with low rainfall variability had longer early‐life (3–12 months old) telomeres. Additionally, cubs born in groups with more cubs had marginally longer early‐life telomeres, providing no evidence of resource constraint from cub competition. We also found that the positive association between early‐life telomere length and cub survival probability remained when social and weather variables were included. Finally, after sexual maturity, in early adulthood (i.e., 12–36 months) we found no significant association between same‐sex adult group size and telomere length (i.e., no effect of intrasexual competition). Overall, we show that controlling for seasonal effects, which are linked to food availability, is important in telomere length analyses, and that variation in telomere length in badgers reflects early‐life conditions and also predicts first year cub survival.

Ungulates in alpine ecosystems are constrained by winter harshness through resource limitation and direct mortality from weather extremes. However, little empirical evidence has definitively established how current climate change and other anthropogenic modifications of resource availability affect ungulate winter distribution, especially at their range limits. Here, we used a combination of historical (1997–2002) and contemporary (2012–2015) Eurasian roe deer (Capreolus capreolus) relocation datasets that span changes in snowpack characteristics and two levels of supplemental feeding to compare and forecast probability of space use at the species’ altitudinal range limit. Scarcer snow cover in the contemporary period interacted with the augmented feeding site distribution to increase the elevation of winter range limits, and we predict this trend will continue under climate change. Moreover, roe deer have shifted from historically using feeding sites primarily under deep snow conditions to contemporarily using them under a wider range of snow conditions as their availability has increased. Combined with scarcer snow cover during December, January, and April, this trend has reduced inter-annual variability in space use patterns in these months. These spatial responses to climate- and artificial resource-provisioning shifts evidence the importance of these changing factors in shaping large herbivore spatial distribution and, consequently, ecosystem dynamics.

Animals have played a vital role in every stage of space exploration, from early sub-orbital flights to contemporary missions. New physiological and psychological challenges arise with plans to venture deeper into the solar system. Advances in chimeric and knockout animal models, along with genetic modification techniques have enhanced our ability to study the effects of microgravity in greater detail. However, increased investment in the purposeful design of habitats and payloads, as well as in AI-enhanced behavioral monitoring in orbit can better support the ethical and effective use of animals in deep space research.

Quantifying abundance is often key to understanding ecological and evolutionary processes in wild populations. Despite shortcomings in producing accurate abundance estimates, minimum number alive (MNA) remains a widely used tool, due to its intuitive computation, reliable performance as an abundance indicator, and linkage to individual life-histories. Here, we propose a novel “efficiency-modified” MNA (eMNA) metric, which aims to preserve MNA’s favourable aspects while remedying its flaws, by incorporating (a) growth correlates to back-age individuals first captured as adults, and (b) estimates of undetected persistence beyond last capture based on time-varying capture efficiency. We evaluate eMNA through samplings of a simulated baseline population parameterised using data from a long-term demographic study of European badgers (Meles meles), under three different levels of capture efficiency (low; intermediate/“real” based on badger field data; high). We differentiate between eMNA’s performance as an abundanceestimator—how well it approximates true abundance (accuracy)—and as an abundanceindicator—how tightly it correlates with population abundance and changes thereof (precision). eMNA abundance estimates were negatively biased at all capture efficiencies. However, this bias was negligible at intermediate-to-high capture efficiency, particularly once low-information terminal sampling years (the first year and final three years of simulated studies) were removed. Excluding these years, eMNA under-estimated abundance by only 3.5 badgers (1.5% of population) at intermediate (real) capture efficiencies, and performed as a precise abundance indicator, with half the standard deviation of Cormack–Jolly–Seber probabilistic estimates and proving robust to inter-sampling variation in capture efficiency. Using undetected persistence probabilities to parameterise survival regression, we recreated baseline age-based survival relationships, albeit with some negative bias for under-represented ages. We offer considerations on the continued limitations of using eMNA for abundance estimates, minimum study duration for reliability, the metric’s benefits when individual identity is required, and potential for further improvement.