Losses and gains in species diversity affect ecological stability 1-7 and the sustainability of ecosystem functions and services 8-13. Experiments and models reveal positive, negative, and no effects of diversity on individual components of stability such as temporal variability, resistance, and resilience 2,3,6,11,12,14. How these stability components covary is poorly appreciated 15 , as are diversity effects on overall ecosystem stability 16 , conceptually akin to ecosystem multifunctionality 17,18. We observed how temporal variability, resistance, and overall ecosystem stability responded to diversity (i.e. species richness) in a large experiment involving 690 micro-ecosystems sampled 19 times over 40 days, resulting in 12939 samplings. Species richness increased temporal stability but decreased resistance to warming. Thus, two stability components negatively covaried along the diversity gradient. Previous biodiversity manipulation studies rarely reported such negative covariation despite general predictions of negative effects of diversity on individual stability components 3. Integrating our findings with the ecosystem multifunctionality concept revealed hump-and U-shaped effects of diversity on overall ecosystem stability. That is, biodiversity can increase overall ecosystem stability when biodiversity is low, and decrease it when biodiversity is high, or the opposite with a Ushaped relationship. Effects of diversity on ecosystem multifunctionality would also be hump-or U-shaped if diversity has positive effects on some functions and negative effects on others. Linking the ecosystem multifunctionality concept and ecosystem stability can transform perceived effects of diversity on ecological stability and may assist translation of this science into policy-relevant information. Ecological stability consists of numerous components including temporal variability, resistance to environmental change, and rate of recovery from disturbance 1,2,16. Effects of species losses and gains on these components are of considerable interest, not least due to potential effects on ecosystem functioning and hence the sustainable delivery of ecosystem services 1-13. A growing number of experimental studies reveal stabilising effects of diversity on individual stability components. In particular, higher diversity often, but not always, reduces temporal variability of biomass production 13. Positive effects of diversity on resistance are common, though neutral and negative effects on resistance and resilience also occur 9,13,19,20. While assessment of individual stability components is essential, a more integrative approach to ecological stability could lead to clearer conceptual understanding 15 and might improve policy guidance concerning ecological stability 16. Analogous to ecosystem multifunctionality 17,18 , a more integrative approach considers variation in multiple stability components, and the often-ignored covariation among stability components. The nature of this covariation is of paramount importance, as it defines whe...

The recent description of potentially generic early warning signals is a promising development that may help conservationists to anticipate a population's collapse prior to its occurrence. So far, the majority of such warning signals documented have been in highly controlled laboratory systems or theoretical models. Data from wild populations, however, are typically restricted both temporally and spatially due to limited monitoring resources and intrinsic ecological heterogeneity -limitations that may affect the detectability of generic early warning signals, as they add additional stochasticity to population abundance estimates. Consequently, spatial and temporal subsampling may serve either to muffle or magnify early warning signals. Using a combination of theoretical models and analysis of experimental data, we evaluate the extent to which statistical warning signs are robust to data corruption. Online enhancements: appendixes, zip file.abstract: The recent description of potentially generic early warning signals is a promising development that may help conservationists to anticipate a population's collapse prior to its occurrence. So far, the majority of such warning signals documented have been in highly controlled laboratory systems or in theoretical models. Data from wild populations, however, are typically restricted both temporally and spatially due to limited monitoring resources and intrinsic ecological heterogeneity-limitations that may affect the detectability of generic early warning signals, as they add additional stochasticity to population abundance estimates. Consequently, spatial and temporal subsampling may serve to either muffle or magnify early warning signals. Using a combination of theoretical models and analysis of experimental data, we evaluate the extent to which statistical warning signs are robust to data corruption.

The extent to which immune cell phenotypes in the peripheral blood reflect within-tumor immune activity prior to and early in cancer therapy is unclear. To address this question, we studied the population dynamics of tumor and immune cells, and immune phenotypic changes, using clinical tumor and immune cell measurements and single-cell genomic analyses. These samples were serially obtained from a cohort of advanced gastrointestinal cancer patients enrolled in a trial with chemotherapy and immunotherapy. Using an ecological population model, fitted to clinical tumor burden and immune cell abundance data from each patient, we find evidence of a strong tumor-circulating immune cell interaction in responder patients but not in those patients that progress on treatment. Upon initiation of therapy, immune cell abundance increased rapidly in responsive patients, and once the peak level is reached tumor burden decreases, similar to models of predator–prey interactions; these dynamic patterns were absent in nonresponder patients. To interrogate phenotype dynamics of circulating immune cells, we performed single-cell RNA sequencing at serial time points during treatment. These data show that peripheral immune cell phenotypes were linked to the increased strength of patients’ tumor–immune cell interaction, including increased cytotoxic differentiation and strong activation of interferon signaling in peripheral T cells in responder patients. Joint modeling of clinical and genomic data highlights the interactions between tumor and immune cell populations and reveals how variation in patient responsiveness can be explained by differences in peripheral immune cell signaling and differentiation soon after the initiation of immunotherapy.

Combining cyclin-dependent kinase (CDK) inhibitors with endocrine therapy improves outcomes for metastatic estrogen receptor positive (ER+) breast cancer patients but its value in earlier stage patients is unclear. We examined evolutionary trajectories of early-stage breast cancer tumors, using single cell RNA sequencing (scRNAseq) of serial biopsies from the FELINE clinical trial ( #NCT02712723 ) of endocrine therapy (letrozole) alone or combined with the CDK inhibitor ribociclib. Despite differences in subclonal diversity evolution across patients and treatments, common resistance phenotypes emerged. Resistant tumors treated with combination therapy showed accelerated loss of estrogen signaling with convergent up-regulation of JNK signaling through growth factor receptors. In contrast, cancer cells maintaining estrogen signaling during mono- or combination therapy showed potentiation of CDK4/6 activation and ERK upregulation through ERBB4 signaling. These results indicate that combination therapy in early-stage ER+ breast cancer leads to emergence of resistance through a shift from estrogen to alternative growth signal-mediated proliferation.