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Biodiversity monitoring from space – towards large-scale mapping of functional diversity with imaging spectroscopy and lidar
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Imaging Spectroscopy for Biodiversity Science: Plant Spectra, Traits, Diversity and Function Across Spatial Scales
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Perfect storms shape biodiversity in time and space
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The Comparative Approach to Bio-Inspired Design: Integrating Biodiversity and Biologists into the Design Process
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A marine heatwave changes the stabilizing effects of biodiversity in kelp forests
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Loss of Biodiversity Dimensions through Shifting Climates and Ancient Mass Extinctions
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The emergent interactions that govern biodiversity change
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Probabilistic models of species discovery and biodiversity comparisons
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OceanSpace Research Performance Progress Report-FINAL Advancing optical imaging and classification to enhance biodiversity monitoring.
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Study of the Microbial Diversity of a Newly Discovered East Antarctic Freshwater Lake, L27C, and of a Perennially Ice-Covered Lake Untersee
The microbial communities that reside within freshwater lakes of Schirmacher and Untersee Oases in East Antarctica must cope with extreme conditions that may include cold temperature, annual freeze-thaw cycles, exposure to UV radiation, especially during the austral summer months, low light beneath thick ice-cover, followed by seasonal darkness. The objective of this study was to assess the microbial biodiversity and distribution from samples taken from two freshwater lakes (L27C and Lake Untersee) that were collected during the Tawani 2008 International Antarctic Expedition that conducted research in this region of Antarctica. L27C is a small, previously unreported lake residing 2 km WNW of Maitri Station at Schirmacher Oasis. Biodiversity and distribution of microorganisms within the lake were studied using both culture-independent and culture-dependent methodologies based upon the analysis of eubacterial 16S rRNA gene sequences. Lake Untersee, a perennially ice-covered, ultra-oligotrophic, lake in the Otto-von-Gruber-Gebirge (Gruber Mountains) of central Dronning Maud Land was also sampled and the microbial diversity was analyzed by eubacterial 16S rRNA gene sequences derived from pure cultures. Direct culturing of water samples from each lake on separate R2A growth medium exhibited a variety of microorganisms including: Janthinobacterium, Hymenobacter, Sphingamonas, Subtercola, Deinococcus, Arthrobacter, Flavobacterium, Polaromonas, Rhodoferax and Duganella. The evaluation of samples from L27C through culture-independent methodology identified a rich microbial diversity consisting of six different phyla of bacteria. The culture-independent analysis also displayed the majority of bacteria (56%) belonged to the Class gamma-proteobacteria within the phylum Proteobacteria. Within the Class gamma-proteobacteria, Acinetobacter dominated (48%) the total microbial load. Overall, L27C exhibited 7 different phyla of bacteria and 20 different genera. Statistical analysis (Shannon-Weaver Diversity Index and Simpson Diversity Index) of the biodiversity of L27C displayed a moderately rich and diverse community. Investigations of the biodiversity and distribution of microorganisms in these lakes will help further our understanding of how the physical environment impact the structure and function within these microbially dominated ecosystems.
Using airborne and DESIS imaging spectroscopy to map plant diversity across the largest contiguous tract of tallgrass prairie on earth
Grassland ecosystems are under threat globally, primarily due to land-use and land-cover changes that have adversely affected their biodiversity. Given the negative ecological impacts of biodiversity loss in grasslands, there is an urgent need for developing an operational biodiversity monitoring system that functions in these ecosystems. In this paper, we assessed the capability of airborne and spaceborne imaging spectroscopy (also known as hyperspectral imaging) to capture plant α-diversity in a large naturally-assembled grassland while considering the impact of common management practices, specifically prescribed fire. We collected a robust in-situ plant diversity data set, including species composition and percent cover from 2500 sampling points with different burn ages, from recently-burned to transitional and pre-prescribed fire at the Joseph H. Williams Tallgrass Prairie Preserve in Oklahoma, USA. We expressed in-situ plant α-diversity using the first three Hill numbers, including species richness (number of observed species in a plant community), exponential Shannon entropy index (hereafter Shannon diversity; effective number of common species, where species are weighed proportional to their percent cover), and inverse Simpson concentration index (hereafter Simpson diversity; effective number of dominant species, where more weight is given to dominant species) at four different plot sizes, including 60 m × 60 m, 120 m × 120 m, 180 m × 180 m, and 240 m × 240 m. We collected full-range airborne hyperspectral data with fine spatial resolution (1 m) and visible and near-infrared spaceborne hyperspectral data from DESIS sensor with coarse spatial resolution (30 m), and used the spectral diversity hypothesis—i.e., that the variability in spectral data is largely driven by plant diversity—to estimate α-diversity remotely. In recently-burned plots and those at the transitional stage, both airborne and spaceborne data were capable of capturing Simpson diversity—a metric that calculates the effective number of dominant species by emphasizing abundant species and discounting rare species—but not species richness or Shannon diversity. Further, neither airborne nor spaceborne hyperspectral data sets were capable of capturing plant α-diversity of 60 m × 60 m or 120 m × 120 m plots. Based on these results, three main findings emerged: (1) management practices influence grassland biodiversity patterns that can be remotely detected, (2) both fine- and coarse-resolution remotely-sensed data can detect the effective number of dominant species (e.g., Simpson diversity), and (3) attention should be given to site-specific plant diversity field data collection to appropriately interpret remote sensing results. Findings of this study indicate the feasibility of estimating Simpson diversity in naturally-assembled grasslands using forthcoming spaceborne imagers such as National Aeronautics and Space Administration's Surface Biology and Geology mission.
Exploring the Integration of Earth Observations to Support Community Management of a Protected Area in Guatemala
Central America faces increasing challenges of deforestation and habitat fragmentation with complex drivers. Protected areas are one response to these challenges, forming a continuous forest stand subject to national conservation systems and laws. As part of a novel shared-management model, both the community of Santa María Tzejá and the Protected Areas Council of Guatemala (CONAP in Spanish) co-manage Cerro Cantil, a protected area in the Ixcán department of northwestern Guatemala covering approximately 314 ha. The SERVIR program, a joint initiative between NASA and USAID, in partnership with leaders from Santa María Tzejá, began a pilot project to explore how the integration of satellite remote sensing can support forest and biodiversity monitoring and contribute to the community’s reporting requirements. To assess Cerro Cantil’s potential role to protect endemic species between three larger protected areas, we model least cost corridors between Cerro Cantil and Laguna Lachuá, Visi Cabá, and Montes Azules for Alouatta pigra (Black Howler Monkey). Additionally, we evaluate the potential contribution of a forestry-conservation incentives program (PROBOSQUE) to stem fragmentation and support biodiversity by assessing the forest area overlapping both the modeled corridors and plots belonging to families enrolled in PROBOSQUE. Results contribute to community understanding of the value of Cerro Cantil to protect local biodiversity as well as the interaction of a forestry incentive program and protected area designation.
Rooting for function: community‐level fine‐root traits relate to many ecosystem functions
Humans are driving biodiversity change, which also alters community functional traits. However, how changes in the functional traits of the community alter ecosystem functions—especially belowground—remains an important gap in our understanding of the consequences of biodiversity change. We test hypotheses for how the root traits of the root economics space (composed of the collaboration and conservation gradients) are associated with proxies for ecosystem functioning across grassland and forest ecosystems in both observational and experimental datasets from 810 plant communities. First, we assessed whether community-weighted means of the root economics space traits adhered to the same trade-offs as species-level root traits. Then, we examined the relationships between community-weighted mean root traits and aboveground biomass production, root standing biomass, soil fauna biomass, soil microbial biomass, decomposition of standard and plot-specific material, ammonification, nitrification, phosphatase activity, and drought resistance. We found evidence for a community collaboration gradient but not for a community conservation gradient. Yet, links between community root traits and ecosystem functions were more common than we expected, especially for aboveground biomass, microbial biomass, and decomposition. These findings suggest that changes in species composition, which alter root trait means, will in turn affect critical ecosystem functions.
Belowground cross-trophic networks impact CH4 and CO2 emissions in degraded alpine peatlands
Belowground organisms forming complex cross-trophic ecological networks are essential for maintaining peatland carbon stability and energy flow. However, how peatland degradation affects the biodiversity and cross-trophic ecological networks of soil communities remains poorly understood. Here, we examined the degradation effects on soil prokaryotes (i.e., bacteria, archaea), fungi and nematodes in alpine peatlands on the eastern Tibetan Plateau, characterized by varying water table depths (indicating degradation levels). We found that peatland degradation, accompanied by significant shifts in soil moisture and pH (P < 0.05), reduced the taxonomic richness and phylogenetic diversity of prokaryotes, fungi, and nematodes, particularly in deeper soil layers (20–50 cm). Crucially, peatland degradation weakened potential cross-trophic interactions within bipartite networks of prokaryotes-nematodes and fungi-nematodes, resulting in less than 6.5 %–28.8 % of unchanged modules. Degradation-induced changes in soil moisture and pH were identified as primary drivers of biodiversity loss and network restructuring. Furthermore, such changes of belowground cross-trophic networks (particularly prokaryote-nematode) were significantly correlated with greenhouse gas emissions, such as decreased CO2 emissions, maintained CH4 emissions (leading to a higher CH4/CO2 ratio in deep layers), and reduced temperature sensitivity (Q10) of soil respiration. These findings underscore the critical need to protect soil biodiversity and cross-trophic networks in peatlands, particularly under the threat of climate change, to preserve peatland carbon stocks and maintain ecosystem stability. Our findings highlight that belowground cross-trophic networks are pivotal to decipher soil carbon dynamics of degraded peatlands and project the fate of peatland carbon stocks under future climate change scenarios.
Calibrating the Ordovician Radiation of marine life: implications for Phanerozoic diversity trends
It has long been suspected that trends in global marine biodiversity calibrated for the Phanerozoic may be affected by sampling problems. However, this possibility has not been evaluated definitively, and raw diversity trends are generally accepted at face value in macroevolutionary investigations. Here, we analyze a global-scale sample of fossil occurrences that allows us to determine directly the effects of sample size on the calibration of what is generally thought to be among the most significant global biodiversity increases in the history of life: the Ordovician Radiation. Utilizing a composite database that includes trilobites, brachiopods, and three classes of molluscs, we conduct rarefaction analyses to demonstrate that the diversification trajectory for the Radiation was considerably different than suggested by raw diversity time-series. Our analyses suggest that a substantial portion of the increase recognized in raw diversity depictions for the last three Ordovician epochs (the Llandeilian, Caradocian, and Ashgillian) is a consequence of increased sample size of the preserved and catalogued fossil record. We also use biometric data for a global sample of Ordovician trilobites, along with methods of measuring morphological diversity that are not biased by sample size, to show that morphological diversification in this major clade had leveled off by the Llanvirnian. The discordance between raw diversity depictions and more robust taxonomic and morphological diversity metrics suggests that sampling effects may strongly influence our perception of biodiversity trends throughout the Phanerozoic.
Improved assessment of mangrove forests in Sundarbans East Wildlife Sanctuary using WorldView 2 and TanDEM-X high resolution imagery
Recent developments of remote sensing techniques which can capture both the structure and function of the ecosystem provide a more representative view of the landscape. These unique Earth observations were used to help improve traditional forestry surveys by providing species-specific land cover classes for mangrove forests in the Sundarbans East Wildlife Sanctuary. By combining optical data from WorldView2 (WV2; 2 m pixel) and a canopy height model derived using radar data from TanDEM-X (TDX; 12 m pixel), we identified nine mangrove and five non-mangrove classes by following an Iterative Self-Organizing Data Analysis Algorithm. Three dominant mangrove species accounted for nearly 50% of the sanctuary. Heritieria fomes disproportionately covered the largest area at 43%, overturning previous field-based estimates of Excoecaria agallocha dominance. E. agallocha and Sonneratia apetala, covered 3% and 1.47% of the sanctuary, respectively. Four mixed species classes were also identified with clear vegetation zonation patterns that trended toward species homogeneity with increasing distance from shore. The overall land cover accuracy (WV2: 89.33%; WV2-TDX: 89.89%), the Kappa Coefficient (WV2:0.88; WV2-TDX: 0.89) and change statistics between WV2 and WV2-TDX landcover classifications indicate that the WV2 imagery can separate mangrove community types without structural data. The combination of the land cover classifications and the canopy height model indicated that H. fomes were not only the most dominant forest but also, on average, the tallest (12.3 m) among the other eight mangrove types. Our large-scale mapping with high resolution optical and radar platforms can capture subtle changes in mangrove vegetation and canopy structural gradients more accurately and be used to monitor biodiversity changes and Aichi Biodiversity Targets and Indicators, which would contribute to biodiversity policy updating.