Carbon fluxes from tropical deforestation and regrowth are highly uncertain components of the contemporary carbon budget, due in part to the lack of spatially explicit and consistent information on changes in forest area. We estimate fluxes for the 1980s and 1990s using subpixel estimates of percent tree cover derived from coarse (National Oceanic and Atmospheric Administration's Advanced Very High Resolution Radiometer) satellite data in combination with a terrestrial carbon model. The satellite-derived estimates of change in forest area are lower than national reports and remote-sensing surveys from the United Nations Food and Agriculture Organization Forest Resource Assessment (FRA) in all tropical regions, especially for the 1980s. However, our results indicate that the net rate of tropical forest clearing increased approximate to10% from the 1980s to 1990s, most notably in southeast Asia, in contrast to an 11% reduction reported by the FRA. We estimate net mean annual carbon fluxes from tropical deforestation and regrowth to average 0.6 (0.3-0.8) and 0.9 (0.5-1.4) petagrams (Pg)(.)yr(-1) for the 1980s and 1990s, respectively. Compared with previous estimates of 1.9 (0.6-2.5) Pg(.)yr(-1) based on FRA national statistics of changes in forest area, this alternative estimate suggests less "missing" carbon from the global carbon budget but increasing emissions from tropical land-use change.

The net flux of carbon from land use and land-cover change (LULCC) accounted for 12.5% of anthropogenic carbon emissions from 1990 to 2010. This net flux is the most uncertain term in the global carbon budget, not only because of uncertainties in rates of deforestation and forestation, but also because of uncertainties in the carbon density of the lands actually undergoing change. Furthermore, there are differences in approaches used to determine the flux that introduce variability into estimates in ways that are difficult to evaluate, and not all analyses consider the same types of management activities. Thirteen recent estimates of net carbon emissions from LULCC are summarized here. In addition to deforestation, all analyses considered changes in the area of agricultural lands (croplands and pastures). Some considered, also, forest management (wood harvest, shifting cultivation). None included emissions from the degradation of tropical peatlands. Means and standard deviations across the thirteen model estimates of annual emissions for the 1980s and 1990s, respectively, are 1.14 +/- 0.23 and 1.12 +/- 0.25 PgC yr(-1) (1 Pg = 1015 g carbon). Four studies also considered the period 2000-2009, and the mean and standard deviations across these four for the three decades are 1.14 +/- 0.39, 1.17 +/- 0.32, and 1.10 +/- 0.11 PgC yr(-1). For the period 1990-2009 the mean global emissions from LULCC are 1.14 +/- 0.18 PgC yr(-1). The standard deviations across model means shown here are smaller than previous estimates of uncertainty as they do not account for the errors that result from data uncertainty and from an incomplete understanding of all the processes affecting the net flux of carbon from LULCC. Although these errors have not been systematically evaluated, based on partial analyses available in the literature and expert opinion, they are estimated to be on the order of +/- 0.5 PgC yr(-1).

The recent 70% decline in deforestation in the Brazilian Amazon suggests that it is possible to manage the advance of a vast agricultural frontier. Enforcement of laws, interventions in soy and beef supply chains, restrictions on access to credit, and expansion of protected areas appear to have contributed to this decline, as did a decline in the demand for new deforestation. The supply chain interventions that fed into this deceleration are precariously dependent on corporate risk management, and public policies have relied excessively on punitive measures. Systems for delivering positive incentives for farmers to forgo deforestation have been designed but not fully implemented. Territorial approaches to deforestation have been effective and could consolidate progress in slowing deforestation while providing a framework for addressing other important dimensions of sustainable development.

Although satellite-based variables have for long been expected to be key components to a unified and global biodiversity monitoring strategy, a definitive and agreed list of these variables still remains elusive. The growth of interest in biodiversity variables observable from space has been partly underpinned by the development of the essential biodiversity variable (EBV) framework by the Group on Earth Observations - Biodiversity Observation Network, which itself was guided by the process of identifying essential climate variables. This contribution aims to advance the development of a global biodiversity monitoring strategy by updating the previously published definition of EBV, providing a definition of satellite remote sensing (SRS) EBVs and introducing a set of principles that are believed to be necessary if ecologists and space agencies are to agree on a list of EBVs that can be routinely monitored from space. Progress toward the identification of SRS-EBVs will require a clear understanding of what makes a biodiversity variable essential, as well as agreement on who the users of the SRS-EBVs are. Technological and algorithmic developments are rapidly expanding the set of opportunities for SRS in monitoring biodiversity, and so the list of SRS-EBVs is likely to evolve over time. This means that a clear and common platform for data providers, ecologists, environmental managers, policy makers and remote sensing experts to interact and share ideas needs to be identified to support long-term coordinated actions.

The intestine is responsible for efficient absorption and packaging of dietary lipids before they enter the circulatory system. This review provides a comprehensive overview of how intestinal enterocytes from diverse model organisms absorb dietary lipid and subsequently secrete the largest class of lipoproteins (chylomicrons) to meet the unique needs of each animal. We discuss the putative relationship between diet and metabolic disease progression, specifically Type 2 Diabetes Mellitus. Understanding the molecular response of intestinal cells to dietary lipid has the potential to undercover novel therapies to combat metabolic syndrome.

The concepts that we generally associate with the field of data science are strikingly descriptive of the way that life, in general, processes information about its environment. The 'information life cycle', which enumerates the stages of information treatment in data science endeavours, also captures the steps of data collection and handling in biological systems. Similarly, the 'data-information-knowledge ecosystem', developed to illuminate the role of informatics in translating raw data into knowledge, can be a framework for understanding how information is constantly being transferred between life and the environment. By placing the principles of data science in a broader biological context, we see the activities of data scientists as the latest development in life's ongoing journey to better understand and predict its environment. Finally, we propose that informatics frameworks can be used to understand the similarities and differences between abiotic complex evolving systems and life.

Stomata, cellular valves found on the surfaces of aerial plant tissues, present a paradigm for studying cell fate and patterning in plants. A highly conserved core set of related basic helix-loop-helix (bHLH) transcription factors regulates stomatal development across diverse species. We characterized BdFAMA in the temperate grass Brachypodium distachyon and found this late-acting transcription factor was necessary and sufficient for specifying stomatal guard cell fate, and unexpectedly, could also induce the recruitment of subsidiary cells in the absence of its paralogue, BdMUTE. The overlap in function is paralleled by an overlap in expression pattern and by unique regulatory relationships between BdMUTE and BdFAMA. To better appreciate the relationships among the Brachypodium stomatal bHLHs, we used in vivo proteomics in developing leaves and found evidence for multiple shared interaction partners. We reexamined the roles of these genes in Arabidopsis thaliana by testing genetic sufficiency within and across species, and found that while BdFAMA and AtFAMA can rescue stomatal production in Arabidopsis fama and mute mutants, only AtFAMA can specify Brassica-specific myrosin idioblasts. Taken together, our findings refine the current models of stomatal bHLH function and regulatory feedback among paralogues within grasses as well as across the monocot/dicot divide.

The recent discovery of SPINDLY (SPY)-catalyzed protein O-fucosylation revealed a novel mechanism for regulating nucleocytoplasmic protein functions in plants. Genetic evidence indicates important roles of SPY in diverse developmental and physiological processes. However, the upstream signal controlling SPY activity and the downstream substrate proteins O-fucosylated by SPY remain largely unknown. Here, we demonstrated that SPY mediates sugar-dependent growth in Arabidopsis (Arabidopsis thaliana). We further identified hundreds of O-fucosylated proteins using lectin affinity chromatography followed by mass spectrometry. All the O-fucosylation events quantified in our proteomic analyses were undetectable or dramatically decreased in the spy mutants, and thus likely catalyzed by SPY. The O-fucosylome includes mostly nuclear and cytosolic proteins. Many O-fucosylated proteins function in essential cellular processes, phytohormone signaling, and developmental programs, consistent with the genetic functions of SPY. The O-fucosylome also includes many proteins modified by O-linked-N-acetylglucosamine (O-GlcNAc) and by phosphorylation downstream of the target of rapamycin (TOR) kinase, revealing the convergence of these nutrient signaling pathways on key regulatory functions such as post-transcriptional/translational regulation and phytohormone responses. Our study identified numerous targets of SPY/O-fucosylation and potential nodes of crosstalk among sugar/nutrient signaling pathways, enabling future dissection of the signaling network that mediates sugar regulation of plant growth and development.

Pathway enrichment analysis is indispensable for interpreting omics datasets and generating hypotheses. However, the foundations of enrichment analysis remain elusive to many biologists. Here, we discuss best practices in interpreting different types of omics data using pathway enrichment analysis and highlight the importance of considering intrinsic features of various types of omics data. We further explain major components that influence the outcomes of a pathway enrichment analysis, including defining background sets and choosing reference annotation databases. To improve reproducibility, we describe how to standardize reporting methodological details in publications. This article aims to serve as a primer for biologists to leverage the wealth of omics resources and motivate bioinformatics tool developers to enhance the power of pathway enrichment analysis.