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Experiences early in life can have lasting effects on the health and survival of humans and other creatures. Whether early hardships can also influence the wellbeing of the next generation is less clear. One previous study with captive hamsters suggested that adversity early in the life of a mother may indeed shorten how long her offspring will live. But hamsters only live for a few years and much less is known about the possibility for intergenerational effects in animals with longer lifespans. This is partly because such studies are time-consuming and thus more difficult to complete. Over the past 45 years, scientists have collected data on generations of baboons living in and around the Amboseli National Park in southern Kenya. Baboons live in social groups with a strict hierarchy, and individuals can live for up to 30 years in the wild. Previous research has shown that early life adversity – such as being orphaned or simply having a low-ranking mother – can shorten the lifespan of female baboons even if they make it to adulthood. It was unclear, however, whether these ill effects could be passed on to the next generation. Now, Zipple et al. have used the wealth of data about the Amboseli baboons to find the answer. After taking into account any adversity that each baboon experienced directly, Zipple et al. showed that juvenile baboons whose mothers were orphaned before reaching adulthood were 44% more likely to die young than juveniles whose grandmothers survived during their mother’s early years. Baboons whose mothers had a close-in-age younger sibling were also 42% more likely to die early as compared to those whose mothers did not, perhaps because the younger sibling competed with the mother for access to maternal care. The analysis suggests that early life adversity in female baboons can have intergenerational effects. More studies are needed to determine if this is also true of humans. If it is, such a result may help explain the persistence of poor health outcomes across generations and shed light on how best to intervene to interrupt this transmission. 

Primate offspring often depend on their mothers well beyond the age of weaning, and offspring that experience maternal death in early life can suffer substantial reductions in fitness across the life span. Here, we leverage data from eight wild primate populations (seven species) to examine two underappreciated pathways linking early maternal death and offspring fitness that are distinct from direct effects of orphaning on offspring survival. First, we show that, for five of the seven species, offspring face reduced survival during the years immediately preceding maternal death, while the mother is still alive. Second, we identify an intergenerational effect of early maternal loss in three species (muriquis, baboons, and blue monkeys), such that early maternal death experienced in one generation leads to reduced offspring survival in the next. Our results have important implications for the evolution of slow life histories in primates, as they suggest that maternal condition and survival are more important for offspring fitness than previously realized. 

Abstract Accurately quantifying species’ area requirements is a prerequisite for effective area‐based conservation. This typically involves collecting tracking data on species of interest and then conducting home‐range analyses. Problematically, autocorrelation in tracking data can result in space needs being severely underestimated. Based on the previous work, we hypothesized the magnitude of underestimation varies with body mass, a relationship that could have serious conservation implications. To evaluate this hypothesis for terrestrial mammals, we estimated home‐range areas with global positioning system (GPS) locations from 757 individuals across 61 globally distributed mammalian species with body masses ranging from 0.4 to 4000 kg. We then applied block cross‐validation to quantify bias in empirical home‐range estimates. Area requirements of mammals <10 kg were underestimated by a mean approximately15%, and species weighing approximately100 kg were underestimated by approximately50% on average. Thus, we found area estimation was subject to autocorrelation‐induced bias that was worse for large species. Combined with the fact that extinction risk increases as body mass increases, the allometric scaling of bias we observed suggests the most threatened species are also likely to be those with the least accurate home‐range estimates. As a correction, we tested whether data thinning or autocorrelation‐informed home‐range estimation minimized the scaling effect of autocorrelation on area estimates. Data thinning required an approximately93% data loss to achieve statistical independence with 95% confidence and was, therefore, not a viable solution. In contrast, autocorrelation‐informed home‐range estimation resulted in consistently accurate estimates irrespective of mass. When relating body mass to home range size, we detected that correcting for autocorrelation resulted in a scaling exponent significantly >1, meaning the scaling of the relationship changed substantially at the upper end of the mass spectrum.