nasa-gesdisc/es-publications-researchareas huggingface dataset:
Effectively and accurately mapping global biodiversity patterns for (2021)

AimThe aim was to understand the representativeness and accuracy of expert range maps and to explore alternative methods for mapping species distributions accurately.LocationGlobal.Time periodContemporary.Major taxa studiedTerrestrial vertebrates and Odonata.MethodsWe analysed the biases in 50,768 animal International Union for Conservation of Nature, Global Assessment of Reptile Distributions and BirdLife species maps and assessed the links between these maps and existing political boundaries and various non‑ecological boundaries to assess their accuracy for certain types of analyses. We cross‑referenced each species map with data from the Global Biodiversity Information Facility to assess whether maps captured the whole range of a species and what percentage of occurrence points fell within the assessed range of the species. In addition, we used a number of different methods to map diversity patterns and compared these with high‑resolution models of distribution patterns.ResultsOn average, 20–30% of the non‑coastal range boundaries of species overlapped with administrative national boundaries. In total, 60% of areas with the highest spatial turnover in species (high densities of species range boundaries marking high levels of shift in the community of species present) occurred at political boundaries, which was especially common in Southeast Asia. Different biases existed for different taxa, with gridded analysis in reptiles, river basins in Odonata (except the Americas) and county boundaries for amphibians in the USA. On average, up to half (25–46%) of the recorded range points of species fell outside their mapped distributions. Filtered minimum convex polygons performed better than expert range maps in reproducing modelled diversity patterns.Main conclusionsExpert range maps showed high bias at administrative borders in all taxa, but this was highest at the transition from tropical to subtropical regions. The methods used were inconsistent across space, time and taxa, and the ranges mapped did not match species distribution data. Alternative approaches can reconstruct patterns of distribution better than expert maps, and data‑driven approaches are needed to provide reliable alternatives to gain a better understanding of species distributions.

Research areas: Ecosystems
Energy determines broad pattern of plant distribution in Western Himalaya (2017)

Several factors describe the broad pattern of diversity in plant species distribution. We explore these determinants of species richness in Western Himalayas using high‑resolution species data available for the area to energy, water, physiography and anthropogenic disturbance. The floral data involves 1279 species from 1178 spatial locations and 738 sample plots of a national database. We evaluated their correlation with 8‑environmental variables, selected on the basis of correlation coefficients and principal component loadings, using both linear (structural equation model) and nonlinear (generalised additive model) techniques. There were 645 genera and 176 families including 815 herbs, 213 shrubs, 190 trees, and 61 lianas. The nonlinear model explained the maximum deviance of 67.4% and showed the dominant contribution of climate on species richness with a 59% share. Energy variables (potential evapotranspiration and temperature seasonality) explained the deviance better than did water variables (aridity index and precipitation of the driest quarter). Temperature seasonality had the maximum impact on the species richness. The structural equation model confirmed the results of the nonlinear model but less efficiently. The mutual influences of the climatic variables were found to affect the predictions of the model significantly. To our knowledge, the 67.4% deviance found in the species richness pattern is one of the highest values reported in mountain studies. Broadly, climate described by water–energy dynamics provides the best explanation for the species richness pattern. Both modeling approaches supported the same conclusion that energy is the best predictor of species richness. The dry and cold conditions of the region account for the dominant contribution of energy on species richness.

Research areas: Ecosystems
Increasing functional diversity in a global land surface model illustrates uncertainties related to parameter simplification (2022)

Simulations of the land surface carbon cycle typically compress functional diversity into a small set of plant functional types (PFT), with parameters defined by the average value of measurements of functional traits. In most earth system models, all wild plant life is represented by between five and 14 PFTs and a typical grid cell (≈100 × 100 km) may contain a single PFT. Model logic applied to this coarse representation of ecological functional diversity provides a reasonable proxy for the carbon cycle, but does not capture the non-linear influence of functional traits on productivity. Here we show through simulations using the Energy Exascale Land Surface Model in 15 diverse terrestrial landscapes, that better accounting for functional diversity markedly alters predicted total carbon uptake. The shift in carbon uptake is as great as 30% and 10% in boreal and tropical regions, respectively, when compared to a single PFT parameterized with the trait means. The traits that best predict gross primary production vary based on vegetation phenology, which broadly determines where traits fall within the global distribution. Carbon uptake is more closely associated with specific leaf area for evergreen PFTs and the leaf carbon to nitrogen ratio in deciduous PFTs.

Research areas: Ecosystems
Genomic history and ecology of the geographic spread of rice (2020)

Rice (Oryza sativa) is one of the worlds most important food crops, and is comprised largely of japonica and indica subspecies. Here, we reconstruct the history of rice dispersal in Asia using whole-genome sequences of more than 1,400 landraces, coupled with geographic, environmental, archaeobotanical and paleoclimate data. Originating around 9,000 yr ago in the Yangtze Valley, rice diversified into temperate and tropical japonica rice during a global cooling event about 4,200 yr ago. Soon after, tropical japonica rice reached Southeast Asia, where it rapidly diversified, starting about 2,500 yr bp. The history of indica rice dispersal appears more complicated, moving into China around 2,000 yr bp. We also identify extrinsic factors that influence genome diversity, with temperature being a leading abiotic factor. Reconstructing the dispersal history of rice and its climatic correlates may help identify genetic adaptations associated with the spread of a key domesticated species.

Research areas: Agriculture
Linking marine phytoplankton emissions, meteorological processes, and downwind particle properties with FLEXPART (2021)

Abstract. Marine biogenic particle contributions to atmospheric aerosol concentrations are not well understood though they are important for determining cloud optical and cloud-nucleating properties. Here we examine the relationship between marine aerosol measurements (with satellites and model fields of ocean biology) and meteorological variables during the North Atlantic Aerosols and Marine Ecosystems Study (NAAMES). NAAMES consisted of four field campaigns between November 2015 and April 2018 that aligned with the four major phases of the annual phytoplankton bloom cycle. The FLEXible PARTicle (FLEXPART) Lagrangian particle dispersion model is used to spatiotemporally connect these variables to ship-based aerosol and dimethyl sulfide (DMS) observations. We find that correlations between some aerosol measurements with satellite-measured and modeled variables increase with increasing trajectory length, indicating that biological and meteorological processes over the air mass history are influential for measured particle properties and that using only spatially coincident data would miss correlative connections that are lagged in time. In particular, the marine non-refractory organic aerosol mass correlates with modeled marine net primary production when weighted by 5 d air mass trajectory residence time (r=0.62). This result indicates that non-refractory organic aerosol mass is influenced by biogenic volatile organic compound (VOC) emissions that are typically produced through bacterial degradation of dissolved organic matter, zooplankton grazing on marine phytoplankton, and as a by-product of photosynthesis by phytoplankton stocks during advection into the region. This is further supported by the correlation of non-refractory organic mass with 2 d residence-time-weighted chlorophyll a (r=0.39), a proxy for phytoplankton abundance, and 5 d residence-time-weighted downward shortwave forcing (r=0.58), a requirement for photosynthesis. In contrast, DMS (formed through biological processes in the seawater) and primary marine aerosol (PMA) concentrations showed better correlations with explanatory biological and meteorological variables weighted with shorter air mass residence times, which reflects their localized origin as primary emissions. Aerosol submicron number and mass negatively correlate with sea surface wind speed. The negative correlation is attributed to enhanced PMA concentrations under higher wind speed conditions. We hypothesized that the elevated total particle surface area associated with high PMA concentrations leads to enhanced rates of condensation of VOC oxidation products onto PMA. Given the high deposition velocity of PMA relative to submicron aerosol, PMA can limit the accumulation of secondary aerosol mass. This study provides observational evidence for connections between marine aerosols and underlying ocean biology through complex secondary formation processes, emphasizing the need to consider air mass history in future analyses.

Research areas: Ecosystems
Persistency and Surface Convergence Evidenced by Two Maker Buoys in the Great Pacific Garbage Patch (2023)

The accumulation of plastic debris on land and coastlines and in waterways and garbage patches is one of the greatest ecological concerns of the 21st century. In that context, the sources and pathways of plastic marine debris (PMD) have been increasingly studied in the past ten years. The purpose of this communication was to analyze, thanks to the tracks of two drifting buoys released in MayJune 2019 in the North-East Pacific, two features encountered within the Great Pacific Garbage Patch (GPGP): a surface convergence, which could lead to the formation of plastic hotspots, and the persistency of the floating material in this area of the ocean. The evolution of the distance between the buoys was compared with the local circulation field divergence, a Lagrangian plastic dispersal model and sea-level anomalies (SLAs). These analyses highlighted the link between the converging behavior of the drifters and a persistent negative velocity divergence as well as a higher than average-encountered modelled plastic surface density (MPSD). The persistence of the material within the GPGP was observed thanks to the trajectory of the longest persisting drifter in comparison with the trajectory of the GPGP center and extent.

Research areas: Water Quality
Cascading effects of a disease outbreak in a remote protected area (2022)

Disease outbreaks induced by humans increasingly threaten wildlife communities worldwide. Like predators, pathogens can be key top‑down forces in ecosystems, initiating trophic cascades that may alter food webs. An outbreak of mange in a remote Andean protected area caused a dramatic population decline in a mammalian herbivore (the vicuña), creating conditions to test the cascading effects of disease on the ecological community. By comparing a suite of ecological measurements to pre‑disease baseline records, we demonstrate that mange restructured tightly linked trophic interactions previously driven by a mammalian predator (the puma). Following the mange outbreak, scavenger (Andean condor) occurrence in the ecosystem declined sharply and plant biomass and cover increased dramatically in predation refuges where herbivory was historically concentrated. The evidence shows that a disease‑induced trophic cascade, mediated by vicuña density, could supplant the predator‑induced trophic cascade, mediated by vicuña behaviour, thereby transforming the Andean ecosystem.

Research areas: Ecosystems
Satellite observations document trends consistent with a boreal forest (2022)

AbstractThe boreal forest biome is a major component of Earth's biosphere and climate system that is projected to shift northward due to continued climate change over the coming century. Indicators of a biome shift will likely first be evident along the climatic margins of the boreal forest and include changes in vegetation productivity, mortality, and recruitment, as well as overall vegetation greenness. However, the extent to which a biome shift is already underway remains unclear because of the local nature of most field studies, sparsity of systematic groundbased ecological monitoring, and reliance on coarse resolution satellite observations. Here, we evaluated early indicators of a boreal forest biome shift using four decades of moderate resolution (30 m) satellite observations and biogeoclimatic spatial datasets. Specifically, we quantified interannual trends in annual maximum vegetation greenness using an ensemble of vegetation indices derived from Landsat observations at 100,000 sample sites in areas without signs of recent disturbance. We found vegetation greenness increased (greened) at 38 [29, 42] % and 22 [15, 26] % of sample sites from 1985 to 2019 and 2000 to 2019, whereas vegetation greenness decreased (browned) at 13 [9, 15] % and 15 [13, 19] % of sample sites during these respective periods [95% Monte Carlo confidence intervals]. Greening was thus 3.0 [2.6, 3.5] and 1.5 [0.8, 2.0] times more common than browning and primarily occurred in cold sparsely treed areas with high soil nitrogen and moderate summer warming. Conversely, browning primarily occurred in the climatically warmest margins of both the boreal forest biome and major forest types (e.g., evergreen conifer forests), especially in densely treed areas where summers became warmer and drier. These macroecological trends reflect underlying shifts in vegetation productivity, mortality, and recruitment that are consistent with early stages of a boreal biome shift.

Research areas: Ecosystems
CO2-driven ocean acidification repressed the growth of adult sea urchin Strongylocentrotus intermedius by impairing intestine function (2020)

Strongylocentrotus intermedius cultured in the northern Yellow Sea in China was utilized to evaluate the effects of chronic CO2-driven ocean acidification (OA) on adult sea urchins. Based on the projection of the Intergovernmental Panel on Climate Change (IPCC), present natural seawater conditions (pHNBS = 8.10  0.03) and three laboratory-controlled OA conditions (OA1, pHNBS =  0.3 units; OA2, pHNBS =  0.4 units; OA3, pHNBS =  0.5 units) were employed. After 60-day incubation, our results showed that (1) OA significantly repressed the growth of adult S. intermedius; (2) food consumption tended to be decreased with pH decline; (3) intestinal morphology was changed, and activities of intestinal cellulase and lipase were decreased under acidified conditions; (4) expression levels of two immune-related genes (SiTNF14 and SiTGF-) were altered; (5) rate-limiting enzyme activities of the glycolytic pathway and tricarboxylic acid cycle (TAC) were changed in all OA treatments compared to those of controls.

Research areas: Ecosystems
Rapid Loss of CO
            2
            From the South Pacific Ocean During the Last Glacial Termination (2019)

During the termination of the last ice age, atmospheric CO2 rose ~80 ppm, but the origin of this carbon has not been fully resolved. Here we present novel constraints on the patterns and processes of deglacial CO2 release using three marine sediment cores from the southwest Pacific. Carbon isotopes (δ13C) and boron to calcium ratios (B/Ca) of benthic foraminiferal calcite provide records of the δ13C of total dissolved inorganic carbon (DIC) and carbonate ion concentrations ([CO32−]) in seawater, respectively. Together these properties indicate enhanced storage of respired CO2 between 1.2‑ and 2.5‑km water depth during the Last Glacial Maximum (19–23 thousand years ago, ka). The first major rise in atmospheric CO2 during the last deglaciation, at the time of Heinrich Stadial 1, was accompanied by increases in δ13C and [CO32−] at all core depths. The initial increases could be attributed to southward shifted westerly winds driving increased upwelling in the Southern Ocean, sending a signal of enhanced ventilation northward into the Pacific. Our results confirm that southern Pacific interior water masses served as an important reservoir for CO2 during the last glacial period, likely extracted from the atmosphere via the biologic pump. Some abrupt changes in Pacific carbon storage coincide with changes in Southern Ocean pH (Rae et al., 2018, https://doi.org/10.1038/s41586‑018‑0614‑0), upwelling indicators (Anderson et al., 2009, https://doi.org/10.1126/science.1167441), and pCO2 (Monnin et al., 2001, https://doi.org/10.1126/science.291.5501.112), indicating that portions of the deep Pacific carbon pool can be ventilated rapidly to the atmosphere via the Southern Ocean.Key Points The southwest Pacific Ocean stored more respired CO2 during the Last Glacial Maximum than during the Holocene Carbonate ion concentration of intermediate water initially increases in tandem with inferred early deglacial Southern Ocean upwelling Release of respired CO2 from the interior Pacific Ocean contributed to the deglacial rise in atmospheric CO2

Research areas: Atmospheric/Ocean Indicators, Greenhouse Gases
Divergent climate change effects on widespread dryland plant communities driven by climatic and ecohydrological gradients (2021)

AbstractPlant community response to climate change will be influenced by individual plant responses that emerge from competition for limiting resources that fluctuate through time and vary across space. Projecting these responses requires an approach that integrates environmental conditions and species interactions that result from future climatic variability. Dryland plant communities are being substantially affected by climate change because their structure and function are closely tied to precipitation and temperature, yet impacts vary substantially due to environmental heterogeneity, especially in topographically complex regions. Here, we quantified the effects of climate change on big sagebrush (Artemisia tridentataNutt.) plant communities that span 76 million ha in the western United States. We used an individualbased plant simulation model that represents intra and interspecific competition for water availability, which is represented by a processbased soil water balance model. For dominant plant functional types, we quantified changes in biomass and characterized agreement among 52 future climate scenarios. We then used a multivariate matching algorithm to generate finescale interpolated surfaces of functional type biomass for our study area. Results suggest geographically divergent responses of big sagebrush to climate change (changes in biomass of 20% to +27%), declines in perennial C3grass and perennial forb biomass in most sites, and widespread, consistent, and sometimes large increases in perennial C4grasses. The largest declines in big sagebrush, perennial C3grass and perennial forb biomass were simulated in warm, dry sites. In contrast, we simulated no change or increases in functional type biomass in cold, moist sites. There was high agreement among climate scenarios on climate change impacts to functional type biomass, except for big sagebrush. Collectively, these results suggest divergent responses to warming in moisturelimited versus temperaturelimited sites and potential shifts in the relative importance of some of the dominant functional types that result from competition for limiting resources.

Research areas: Land Surface/Agriculture Indicators, Ecosystems
Effects of 21st-century climate, land use, and disturbances on ecosystem carbon balance in California (2019)

AbstractTerrestrial ecosystems are an important sink for atmospheric carbon dioxide (CO2), sequestering ~30% of annual anthropogenic emissions and slowing the rise of atmospheric CO2. However, the future direction and magnitude of the land sink is highly uncertain. We examined how historical and projected changes in climate, land use, and ecosystem disturbances affect the carbon balance of terrestrial ecosystems in California over the period 20012100. We modeled 32 unique scenarios, spanning 4 land use and 2 radiative forcing scenarios as simulated by four global climate models. Between 2001 and 2015, carbon storage in California's terrestrial ecosystems declined by 188.4 Tg C, with a mean annual flux ranging from a source of 89.8 Tg C/year to a sink of 60.1 Tg C/year. The large variability in the magnitude of the state's carbon source/sink was primarily attributable to interannual variability in weather and climate, which affected the rate of carbon uptake in vegetation and the rate of ecosystem respiration. Under nearly all future scenarios, carbon storage in terrestrial ecosystems was projected to decline, with an average loss of 9.4% (432.3 Tg C) by the year 2100 from current stocks. However, uncertainty in the magnitude of carbon loss was high, with individual scenario projections ranging from 916.2 to 121.2 Tg C and was largely driven by differences in future climate conditions projected by climate models. Moving from a high to a low radiative forcing scenario reduced net ecosystem carbon loss by 21% and when combined with reductions in landuse change (i.e., moving from a high to a low landuse scenario), net carbon losses were reduced by 55% on average. However, reconciling large uncertainties associated with the effect of increasing atmospheric CO2 is needed to better constrain models used to establish baseline conditions from which ecosystembased climate mitigation strategies can be evaluated.

Research areas: Greenhouse Gases