During the last several decades, international and national agricultural research infrastructures have rapidly expanded, bringing the outputs of agricultural research to the world’s farmers. However, despite huge investments in agricultural research, there have been few systematic efforts to create digital platforms to meet the information requirements of farmers in a changing world. We describe an interactive information system in real time to provide agricultural information to farmers. The goals were to increase yields, reduce or optimize farm inputs, inform farmers about markets and government policies, and enable digital literacy among farmers, which (in the long run) would enhance rural incomes. Farmer clubs were created at the village level to increase engagement in the program and to access information. A call-in help center enabled farmers to get information in real time. In addition, a digital platform named eKisaan delivered relevant and contextual information in the local language, mostly in the video format via mobile and cloud technologies. The platform provided information about crop management and a variety of other parameters. The combined incremental savings and incremental earnings resulted in an estimated increase of 15% in income after 18 months, totaling INR₹26,250,000 (US$365,000), followed by an additional increase of 7% in the third year. The approximate cost of the information technology program and help center was INR₹15,000,000 (US$208,000). Over time, costs can decrease by spreading fixed costs over several years, with benefits reaching more farmers. Thus, the digital systems focused on information alone can be cost-effective, reduce inputs, increase productivity and income, and foster sustainability.

Competition among developing seeds and sibling rivalry within multiovulated ovaries can be deleterious for both the maternal parent and the siblings. Increased genetic relatedness of seeds within the ovary may foster kin selection and reduce the deleterious consequences of sibling competition. The pollen parent may also be selected for siring all progeny within a fruit. I propose a series of hypotheses to explain the evolution of a number of reproductive traits in angiosperms in the context of kin selection and sibling rivalry within the ovaries of angiosperms. I present evidence to show that a single-pollen parent, indeed, often sires seeds within multiovulated ovaries. Various types of pollen aggregations and transfer of such pollen masses to the stigmas of flowers by specialized pollinators make this increased genetic relatedness possible. An alternative mode to reduce sibling rivalry may be the reduction of ovule number to one, an evolutionary trend that has independently occurred many times in flowering plants. Finally, I build on previously established correlations to predict two sets of correlations among reproductive traits. In the first case, large showy flowers, transfer of pollenen masseby specialized pollinators, and multiovulated ovaries and multisided fruits seem to be correlated. In the second case, the previously established correlations among small and inconspicuous flowers, pollination by wind, water or generalist insects, flowers and fruits with few or single ovules and seeds, respectively, may also include monoecy or dioecy. Although correlations among many of these traits have been established in the past, I invoke kin selection and sibling competition to explain the evolution of correlated traits as two distinct evolutionary pathways in angiosperms.

Biodiversity is declining in many parts of the world. Biological diversity measurement and monitoring are fundamental to the assessment of the causes and consequences of environmental changes, identification of key areas for the protection of biodiversity or ecosystem services, determining the effectiveness of actions, and the creation of decision-support tools critical to maintaining a sustainable planet. Biodiversity measurement is rapidly changing due to advances in citizen science, image recognition, acoustic monitoring, environmental DNA, genomics, remote sensing, and AI. In this perspective, we outline the exciting opportunities these developments offer but also consider the challenges. Our key recommendations are to 1) Capitalize on the ability of novel technology to integrate data sources 2) agree to standard methods for data collection 3) ensure new technologies are calibrated with existing data; 4) fill data gaps by using emerging technologies and increasing capacity, especially in the tropics; 5) create living safeguarded databases of trusted information to reduce the risk of poisoning by AI hallucinated, or false, information; 6) ensure data generation is valued; 7) ensure respectful incorporation of Indigenous Knowledge; 8) ensure measurements enable the quantification of effectiveness of actions, and 9) increase the resilience of global datasets to technical and societal change. Radical new collaborations are needed between computer scientists, engineers, molecular biologists, data scientists, field ecologists, citizen scientists, Indigenous peoples, policymakers, and local communities to create the rigorous, resilient, accessible biodiversity information systems required to underpin policies and practices that ensure the maintenance and restoration of ecological systems.

A little over a year ago, the global community proposed\ud an ambitious new set of Sustainable Development Goals\ud (SDGs) to protect the environment and enhance human\ud well-being. Three months later, the United Nations Conference on Climate Change, CoP21 in Paris, announced\ud equally ambitious new targets for action on climate\ud change. Such bold commitments have been facilitated\ud by development trends in several emerging economies.\ud India, for one, has made truly astonishing gains: the World Bank reports that in over just seven years, from 2004 to 2011, the number of Indian citizens living in acute poverty fell from 426 million to 263 million, a reduction in the proportion of the population in poverty from 38% to <22%\u