nasa-gesdisc/es-publications-researchareas huggingface dataset:
The devil is in the dispersers: predictions of landscape connectivity change with demography (2014)

Summary Concern about the effects of habitat fragmentation has led to increasing interest in dispersal and connectivity modelling. Most modern techniques for connectivity modelling have resistance surfaces as their foundation. However, resistance surfaces for animal movement are frequently estimated without considering dispersal, despite being the principal natural mechanism by which organisms move between populations. We collected Global Positioning System data over 10 years from 50 African lions Panthera leo (11 male natal dispersers, 20 adult males and 19 adult females) and used a path level analysis to parameterize demographic‑specific resistance surfaces for the Kavango Zambezi Transfrontier Conservation Area (KAZA) in Southern Africa. Lion path selection varied according to demographic grouping: adult females were most averse to risky landscapes such as agro‑pastoral lands, towns, areas of high human density and highways. Male natal dispersers were the least‑risk averse suggesting they are potentially the most prone demographic to human–lion conflict. Adults of both sexes selected bushed grassland and shrubland habitats and avoided woodland. Male natal dispersers displayed the opposite trend suggesting con‑specific avoidance and/or suboptimal habitat use. We used the resistance surfaces to calculate factorial least‑cost path networks for each demographic‑specific resistance surface and present results that show substantial differences between predicted patterns of connectivity for male natal dispersers, adult females and adult males. Synthesis and applications. Resistance surfaces are widely used to create connectivity models, which are promoted for use by conservation managers. Our results suggest that the demographic category used to parameterize resistance surfaces may lead to radically different conclusions about connectivity. Failure to include dispersing individuals when parameterizing resistance surfaces intended for connectivity modelling may lead to erroneous conclusions about connectivity and potentially unsound management strategies. Resistance surfaces are widely used to create connectivity models, which are promoted for use by conservation managers. Our results suggest that the demographic category used to parameterize resistance surfaces may lead to radically different conclusions about connectivity. Failure to include dispersing individuals when parameterizing resistance surfaces intended for connectivity modelling may lead to erroneous conclusions about connectivity and potentially unsound management strategies.

Research areas: Ecosystems
Direct measurements reveal instabilities and turbulence within large amplitude internal solitary waves beneath the ocean (2021)

Internal solitary waves are ubiquitous in coastal regions and marginal seas of the worlds oceans. As the waves shoal shoreward, they lose the energy obtained from ocean tides through globally significant turbulent mixing and dissipation and consequently pump nutrient-rich water to nourish coastal ecosystem. Here we present fine-scale, direct measurements of shoaling internal solitary waves in the South China Sea, which allow for an examination of the physical processes triggering the intensive turbulent mixing in their interior. These are convective breaking in the wave core and the collapse of KelvinHelmholtz billows in the wave rear and lower periphery of the core, often occurring simultaneously. The former takes place when the particle velocity exceeds the waves propagating velocity. The latter is caused by the instability induced by the strong velocity shear overcoming the stratification. The instabilities generate turbulence levels four orders of magnitude larger than that in the open ocean.

Research areas: Atmospheric/Ocean Indicators
Microplastics in Arctic polar waters: the first reported values of particles in surface and sub-surface samples (2015)

Plastic, as a form of marine litter, is found in varying quantities and sizes around the globe from surface waters to deep-sea sediments. Identifying patterns of microplastic distribution will benefit an understanding of the scale of their potential effect on the environment and organisms. As sea ice extent is reducing in the Arctic, heightened shipping and fishing activity may increase marine pollution in the area. Microplastics may enter the region following ocean transport and local input, although baseline contamination measurements are still required. Here we present the first study of microplastics in Arctic waters, south and southwest of Svalbard, Norway. Microplastics were found in surface (top 16 cm) and sub-surface (6 m depth) samples using two independent techniques. Origins and pathways bringing microplastic to the Arctic remain unclear. Particle composition (95% fibres) suggests they may either result from the breakdown of larger items (transported over large distances by prevailing currents, or derived from local vessel activity), or input in sewage and wastewater from coastal areas. Concurrent observations of high zooplankton abundance suggest a high probability for marine biota to encounter microplastics and a potential for trophic interactions. Further research is required to understand the effects of microplastic-biota interaction within this productive environment.

Research areas: Water Quality
The physiological response of marine diatoms to ocean acidification: (2019)

Although increasing the pCO2 for diatoms will presumably down‑regulate the CO2‑concentrating mechanism (CCM) to save energy for growth, different species have been reported to respond differently to ocean acidification (OA). To better understand their growth responses to OA, we acclimated the diatoms Thalassiosira pseudonana, Phaeodactylum tricornutum, and Chaetoceros muelleri to ambient (pCO2 400 μatm, pH 8.1), carbonated (pCO2 800 μatm, pH 8.1), acidified (pCO2 400 μatm, pH 7.8), and OA (pCO2 800 μatm, pH 7.8) conditions and investigated how seawater pCO2 and pH affect their CCMs, photosynthesis, and respiration both individually and jointly. In all three diatoms, carbonation down‑regulated the CCMs, while acidification increased both the photosynthetic carbon fixation rate and the fraction of CO2 as the inorganic carbon source. The positive OA effect on photosynthetic carbon fixation was more pronounced in C. muelleri, which had a relatively lower photosynthetic affinity for CO2, than in either T. pseudonana or P. tricornutum. In response to OA, T. pseudonana increased respiration for active disposal of H+ to maintain its intracellular pH, whereas P. tricornutum and C. muelleri retained their respiration rate but lowered the intracellular pH to maintain the cross‑membrane electrochemical gradient for H+ efflux. As the net result of changes in photosynthesis and respiration, growth enhancement to OA of the three diatoms followed the order of C. muelleri &gt; P. tricornutum &gt; T. pseudonana. This study demonstrates that elucidating the separate and joint impacts of increased pCO2 and decreased pH aids the mechanistic understanding of OA effects on diatoms in the future, acidified oceans.

Research areas: Ecosystems
The rise and fall of an alien: why the successful colonizer Littorina saxatilis failed to invade the Mediterranean Sea (2022)

Understanding what determines range expansion or extinction is crucial to predict the success of biological invaders. We tackled this long-standing question from an unparalleled perspective using the failed expansions in Littorina saxatilis and investigated its present and past habitat suitability in Europe through Ecological Niche Modelling. This intertidal snail is a typically successful Atlantic colonizer and the earliest confirmed alien species in the Mediterranean Sea, where, however, it failed to thrive despite its high dispersal ability and adaptability. We explored the environmental constraints affecting its biogeography, identified potential glacial refugia in Europe that fuelled its post-glacial colonisations and tested whether the current gaps in its distribution are linked to local ecological features. Our results suggested that L. saxatilis is unlikely to be a glacial relict in the Mediterranean basin. Multiple Atlantic glacial refugia occurred in the Last Glacial Maximum, and abiotic environmental features such as salinity and water temperature have influenced the past and current distributions of this snail and limited its invasion of the Mediterranean Sea. The snail showed a significant overlap in geographic space and ecological niche with Carcinus maenas, the Atlantic predator, but distinct from Pachygrapsus marmoratus, the Mediterranean predator, further pointing to Atlantic-like habitat requirements for this species. Abiotic constrains during introduction rather than dispersal abilities have shaped the past and current range of L. saxatilis and help explaining why some invasions have not been successful. Our findings contribute to clarifying the processes constraining or facilitating shifts in species distributions and biological invasions.

Research areas: Ecosystems
Variations in export production, lithogenic sediment transport and iron fertilization in the Pacific sector of the Drake Passage over the past 400 kyr (2022)

Abstract. Changes in Southern Ocean export production have broad biogeochemical and climatic implications. Specifically, iron fertilization likely increased subantarctic nutrient utilization and enhanced the efficiency of the biological pump during glacials. However, past export production in the subantarctic southeastern Pacific is poorly documented, and its connection to Fe fertilization, potentially related to Patagonian Ice Sheet dynamics, is unknown. We report biological productivity changes over the past 400 kyr, based on a combination of 230Thxs-normalized and stratigraphy-based mass accumulation rates of biogenic barium, organic carbon, biogenic opal and calcium carbonate as indicators of paleo-export production in a sediment core upstream of the Drake Passage (57.5 S, 70.3 W). In addition, we use fluxes of iron and lithogenic material as proxies for terrigenous input, and thus potential micronutrient supply. Stratigraphy-based mass accumulation rates are strongly influenced by bottom-current dynamics, which result in variable sediment focussing or winnowing at our site. Carbonate is virtually absent in the core, except during peak interglacial intervals of the Holocene, and Marine Isotope Stages (MIS) 5 and 11, likely caused by transient decreases in carbonate dissolution. All other proxies suggest that export production increased during most glacial periods, coinciding with high iron fluxes. Such augmented glacial iron fluxes at the core site were most likely derived from glaciogenic input from the Patagonian Ice Sheet promoting the growth of phytoplankton. Additionally, glacial export production peaks are also consistent with northward shifts of the Subantarctic and Polar Fronts, which positioned our site south of the Subantarctic Front and closer to silicic acid-rich waters of the Polar Frontal Zone. However, glacial export production near the Drake Passage was lower than in the Atlantic and Indian sectors of the Southern Ocean, which may relate to complete consumption of silicic acid in the study area. Our results underline the importance of micro-nutrient fertilization through lateral terrigenous input from South America rather than eolian transport and exemplify the role of frontal shifts and nutrient limitation for past productivity changes in the Pacific entrance to the Drake Passage.

Research areas: Ecosystems
Treating coral bleaching as weather: a framework to validate and (2020)

Few coral reefs remain unscathed by mass bleaching over the past several decades, and much of the coral reef science conducted today relates in some way to the causes, consequences, or recovery pathways of bleaching events. Most studies portray a simple cause and effect relationship between anomalously high summer temperatures and bleaching, which is understandable given that bleaching rarely occurs outside these unusually warm times. However, the statistical skill with which temperature captures bleaching is hampered by many false alarms, times when temperatures reached nominal bleaching levels, but bleaching did not occur. While these false alarms are often not included in global bleaching assessments, they offer valuable opportunities to improve predictive skill, and therefore understanding, of coral bleaching events. Here, I show how a statistical framework adopted from weather forecasting can optimize bleaching predictions and validate which environmental factors play a role in bleaching susceptibility. Removing the 1 C above the maximum monthly mean cutoff in the typical degree heating weeks (DHW) definition, adjusting the DHW window from 12 to 9 weeks, using regional-specific DHW thresholds, and including an El Nino threshold already improves the model skill by 45%. Most importantly, this framework enables hypothesis testing of other factors or metrics that may improve our ability to forecast coral bleaching events.

Research areas: Ecosystems
Formulating and parameterizing the allocation of net primary productivity for modeling overmature stands in boreal forest ecosystems (2006)

In process-based models of forest ecosystems, carbon allocation is a key process that partitions the net primary productivity (NPP) among different biomass components and thus affects forest growth patterns at different stages of the forest's growth. Common allocation models usually express the carbon allocation as linear or monotonic functions of time. These models are acceptable for a limited growth period, but inadequate for simulating long-term development of a forest. To improve the usefulness of these models and simplify the model structure, we developed an analytical solution to partition NPP that considers the effects of litterfall and growth rate. We derived NPP allocation functions based on functions for the net growth rate (dry mass) and based on empirical growth curves estimated from normal yield tables for northern Ontario, Canada. The improved allocation reflects growth restrictions that arise in overmature stands according to different site classes across landscape. The details of the derivation and parameterization are presented and discussed. We validated the new NPP allocation functions for black spruce ( Picea mariana) in the boreal forest of northern Ontario. The improved NPP allocation simulated the NPP dynamics of forest ecosystems more accurately over the course of stand development, and the results were biologically realistic.

Research areas: Ecosystems
Assessing the impact of climate change on threatened endemic vascular plants of Argentina (2022)

Biodiversity loss due to climate change is one of the most critical current environmental problems. Global warming is causing substantial species-range shifts and local extirpations, especially for species with restricted distribution ranges. Studies of impact of the climate change on species ranges and environmental suitability have become a fundamental tool for evaluating conservation strategies. However, one important limitation of these approaches is that only species with an adequate number of spatially distinct occurrence records can be modelled, generally excluding threatened rare species from the analyses, a situation referred to as the rare species modelling paradox. To overcome this limitation, we analysed the effect of climate change on the richness of threatened endemic plants of Argentina employing a macroecological modelling approach, using three different modelling techniques (generalized linear mixed models  GLMM, generalized additive models  GAM, and boosted regression trees  BRT), four general circulation models, two representative CO2 concentration pathways (RCPs), and two time periods (2050 and 2070). We identified grid cells with the greatest decline in numbers of threatened endemics, determined species composition in these cells and characterized their vulnerability using three indices. A loss of species richness is observed in ca 83% of the cells, and both protected areas and hotspots of threatened species show significant decrease in future species richness. We identified 32 most affected cells under future climatic projections, including a total of 370 threatened endemic species and exhibiting high beta diversity values (high dissimilarity) among most of the cells. Cells with the highest vulnerability were located along the Central Andes of northwestern Argentina, along the Southern Andean Yungas, High Monte and Central Andean Puna ecoregions, and including a total of 118 threatened endemics (15% of those registered for Argentina) with greater representation of Asteraceae, Apocynaceae, Cactaceae and Iridaceae. However, coverage of protected area network is less than 5% for each of these cells. Our results highlight the urgent need for both in situ and ex situ conservation policies and strategies for the vascular flora of Argentina.

Research areas: Ecosystems
Predicting global terrestrial biomes with the LeNet convolutional neural network (2022)

Abstract. A biome is a major regional ecological community characterized by distinctive life forms and principal plants. Many empirical schemes such as the Holdridge life zone (HLZ) system have been proposed and implemented to predict the global distribution of terrestrial biomes. Knowledge of physiological climatic limits has been employed to predict biomes, resulting in more precise simulation; however, this requires different sets of physiological limits for different vegetation classification schemes. Here, we demonstrate an accurate and practical method to construct empirical models for biome mapping: a convolutional neural network (CNN) was trained by an observation-based biome map, as well as images depicting air temperature and precipitation. Unlike previous approaches, which require assumption(s) of environmental constrain for each biome, this method automatically extracts non-linear seasonal patterns of climatic variables that are relevant in biome classification. The trained model accurately simulated a global map of current terrestrial biome distribution. Then, the trained model was applied to climate scenarios toward the end of the 21st century, predicting a significant shift in global biome distribution with rapid warming trends. Our results demonstrate that the proposed CNN approach can provide an efficient and objective method to generate preliminary estimations of the impact of climate change on biome distribution. Moreover, we anticipate that our approach could provide a basis for more general implementations to build empirical models of other climate-driven categorical phenomena.

Research areas: Ecosystems
Connectivity conservation at the crossroads: protected areas versus payments for ecosystem services in conserving connectivity for Colombian carnivores (2022)

Protected areas (PAs) constitute one of the main tools for global landscape conservation. Recently, payments for environmental services (PES) have attracted interest from national and regional governments and are becoming one of the leading conservation policy instruments in tropical countries. However, the degree to which areas designated for PES overlap with areas that are critical for maintaining species' landscape connectivity is rarely evaluated. We estimated habitat distributions and connectivity for 16 of the 22 mammalian carnivores occurring in the Caribbean region of Colombia, and identified the overlap between existing PAs and areas identified as being important for connectivity for these species. We also evaluated the potential impact of creation of new PAs versus new PES areas on conserving connectivity for carnivores. Our results show that PAs cover only a minor percentage of the total area that is important for maintaining connectivity (x=26.8%20.2 s.d.). On the other hand, PES, if implemented extensively, could contribute substantially to mammalian carnivores connectivity (x=45.4%12.8 s.d.). However, in a more realistic scenario with limited conservation investment in which fewer areas are set aside, a strategy based on implementing new PAs seems superior to PES. We argue that prioritizing designation of new PAs will be the most efficient means through which to maintain connectivity.

Research areas: Ecosystems
A new synergistic approach for Sentinel-1 and PALSAR-2 in a machine learning framework to predict aboveground biomass of a dense mangrove forest (2022)

Mangroves are well-recognized for their very high carbon sequestration potential. However, studies on their role in global carbon cycling and climate change are hindered due to lack of operational methodologies to model and map their biophysical properties. This study establishes a robust methodological protocol for aboveground biomass (AGB) estimation using i) field measurements, ii) a generic (in the absence of species-specific) allometric equation, iii) multi-sensor/polarization SAR data and derived variables thereof, and iv) machine learning models; that demonstrated high prediction accuracy (R2 = 0.93) and low uncertainty (mean  3% and median  1.5%) for a mangrove forest. Following stratified random sampling and on-field accessibility criteria, we laid out 314 elementary sampling points of 0.04 ha each at Bhitarkanika wildlife sanctuary (BWS), India and measured circumference at breast height (CBH) and canopy tree height for 18 species. The estimated AGB range of a generic allometric equation was 9474 Mg/ha for BWS, with a major representation of 9347 Mg/ha. We utilized Sentinel-1 and ALOS-2/PALSAR-2 and derived their variables for AGB prediction. Compared to single sensor-based model, we observed higher prediction accuracy for combined sensor data (R2 = 0.63, 0.87, 0.93; RMSE = 66.75, 39.95, 28.35 Mg/ha; MAE = 52.63, 24.21, 19.55 Mg/ha; and Bias = 3.42, 0.22, 2.15 Mg/ha for C, L and C & L bands respectively using a Generalized Additive Model (GAM) over Random Forest (RF), Gradient Boosting Machines (GBM) and Support Vector Regression (SVR). The higher uncertainty pixels represented seasonal grassland and scrubs in the swampy areas and along the fringes of the creeks that experience diurnal tidal fluctuations. This robust methodology can be replicated for AGB estimates in other mangrove ecosystems to meet the operational carbon accounting requirements of various entities.

Research areas: Ecosystems