ALBERT

Description: We report a decadally resolved record of atmospheric CO2 concentration for the last 1000 years, obtained from the West Antarctic Ice Sheet (WAIS) Divide shallow ice core. The most prominent feature of the pre-industrial period is a rapid ~7 ppm decrease of CO2 in a span of ~20-50 years at ~1600 A.D. This observation confirms the timing of an abrupt atmospheric CO2 decrease of ~10 ppm observed for that time period in the Law Dome ice core CO2 records, but the true magnitude of the decrease remains unclear. Atmospheric CO2 variations over the time period 1000-1800 A.D. are statistically correlated with northern hemispheric climate and tropical Indo-Pacific sea surface temperature. However, the exact relationship between CO2 and climate remains elusive due to regional climate variations and/or uneven geographical data density of paleoclimate records. We observe small differences of 0 ~2% (0 ~ 6 ppm) among the high-precision CO2 records from the Law Dome, EPICA Dronning Maud Land and WAIS Divide Antarctic ice cores. However, those records share common trends of CO2 change on centennial to multicentennial time scales, and clearly show that atmospheric CO2 has been increasing above preindustrial levels since ~1850 A.D.

Description: Transgenerational plasticity occurs when the conditions experienced by the parental generation influence the phenotype of their progeny. This may in turn affect progeny performance and physiological tolerance, providing a means by which organisms cope with rapid environmental change. We conditioned adult purple sea urchins, Strongylocentrotus purpuratus, to combined pCO2 and temperature conditions reflective of in situ conditions of their natural habitat, the benthos in kelp forests of nearshore California, and then assessed the performance of their progeny raised under different pCO2 levels. Adults were conditioned during gametogenesis to treatments that reflected static non-upwelling (~650 μatm pCO2, ~17 °C) and upwelling (~1300 μatm pCO2, ~13 °C) conditions. Following approximately 4 months of conditioning, the adults were spawned and embryos were raised under low pCO2 (~450 μatm pCO2) or high pCO2 (~1050 μatm pCO2) treatments to determine if differential maternal conditioning impacted the progeny response to a single abiotic stressor: pCO2. We examined the size, protein content, and lipid content of eggs from both sets of conditioned female urchins. Offspring were sampled at four stages of early development: hatched blastula, gastrula, prism, and echinopluteus. This resulted in four sets of offspring: (1) progeny from non-upwelling-conditioned mothers raised under low pCO2, (2) progeny from non-upwelling-conditioned mothers raised under high pCO2, (3) progeny from upwelling-conditioned mothers raised under low pCO2, and (4) progeny from upwelling-conditioned mothers raised under high pCO2. We then assessed the effects of maternal conditioning along with the effects of developmental pCO2 levels on body size of the progeny. Our results showed that differential maternal conditioning had no impact on average egg size, although non-upwelling females produced eggs that were more variable in size. Maternal conditioning did not affect protein content but did have a modest impact on egg lipid content. Developing embryos whose mothers were conditioned to simulated upwelling conditions (~1300 μatm pCO2, ~13 °C) were greater in body size, although this effect was no longer evident at the echinopluteus larval stage. Although maternal conditioning affected offspring body size, the pCO2 levels under which the embryos were raised did not. Overall, this laboratory study provides insight into how transgenerational effects may function in nature. The impacts of parental environmental history on progeny phenotype during early development have important implications regarding recruitment success and population-level effects.

Description: Acidification-induced changes in neurological function have been documented in several tropical marine fishes. Here, we investigate whether similar patterns of neurological impacts are observed in a temperate Pacific fish that naturally experiences regular and often large shifts in environmental pH/pCO2. In two laboratory experiments, we tested the effect of acidification, as well as pH/pCO2 variability, on gene expression in the brain tissue of a common temperate kelp forest/estuarine fish, Embiotoca jacksoni. Experiment 1 employed static pH treatments (target pH = 7.85/7.30), while Experiment 2 incorporated two variable treatments that oscillated around corresponding static treatments with the same mean (target pH = 7.85/7.70) in an eight-day cycle (amplitude ± 0.15). We found that patterns of global gene expression differed across pH level treatments. Additionally, we identified differential expression of specific genes and enrichment of specific gene sets (GSEA) in comparisons of static pH treatments and in comparisons of static and variable pH treatments of the same mean pH. Importantly, we found that pH/pCO2 variability decreased the number of differentially expressed genes detected between high and low pH treatments, and that inter-individual variability in gene expression was greater in variable treatments than static treatments. These results provide important confirmation of neurological impacts of acidification in a temperate fish species and, critically, that natural environmental variability may mediate the impacts of ocean acidification.

Description: To support local to international actions on climate change mitigation and biodiversity conservation, this spatial dataset prioritizes forestlands for preservation in the Western United States. The need for joint climate change mitigation and biodiversity conservation has led to efforts to protect 30% of land area by 2030 (30x30) and 50% by 2050 (50x50). A crucial aspects of these efforts is prioritizing lands for new protection so they best achieve climate and biodiversity goals. We developed and applied a quantitative forest preservation priority ranking (PPR) system that incorporated existing geospatial datasets related to forest carbon, biodiversity, and future vulnerabilities to climate change across the Western United States. Specifically, the forest PPR system incorporated estimates of (1) current forest carbon stocks, (2) near-term forest carbon accumulation, (3) terrestrial vertebrate species richness by taxa, (4) tree species richness, and (5) near-term forest vulnerability to increasing mortality rates from drought or fire. Input datasets were re-gridded to a common 1 x 1 km (1 km2) spatial resolution and reflect contemporary (2000-2020) and near-future (2020-2050) forest conditions, with near-future conditions derived using land surface simulations from the Community Land Model (CLM 4.5). We applied the forest PPR system such that each patch of forest (i.e., a 1 km2 grid cell) was ranked relative to others in its ecoregion based on metrics of carbon and/or biodiversity both with and without considering future vulnerabilities (i.e., six scenarios). We assessed the extent of forestlands that are currently protected (GAP 1 or 2; IUCN Ia-VI) and then identified the highest-ranked unprotected forestlands that could be preserved to meet the 30x30 and 50x50 targets using each prioritization scenario. This spatial dataset thus includes the locations of forestlands that could be strategically preserved to meet the 30x30 and 50x50 targets as prioritized using six scenarios. Each raster is provided at 1 km2 resolution in an Albers Equal Area Projection (EPSG 9822) and covers forestlands that occur across the 11 contiguous western states (i.e., Arizona, California, Colorado, Idaho, Montana, Nevada, New Mexico, Oregon, Utah, Washington, and Wyoming). Raster files are in GeoTiff format. These spatial data were produced as part of Law et al. (2021) and support cross-scale efforts to preserve forests for climate change mitigation and biodiversity conservation.

Description: To support local to regional climate change mitigation and adaptation actions, this spatial dataset prioritizes forestlands for preservation across Oregon, United States. The urgent need for climate change mitigation and adaptation actions has led to efforts to protect 30% of land area by 2030 (30x30) and 50% by 2050 (50x50). A key aspect of these efforts is strategically prioritizing lands for new protection, so they most effectively protect climate and biodiversity. Oregon has among the most carbon-rich forests on the planet, yet only about 10% of it's forests are currently protected, which is lower than any other state in the western United States. We therefore developed and applied a quantitative forest preservation priority ranking system that incorporated existing statewide spatial datasets related to forest carbon, biodiversity, and climate change resilience. Specifically, this approach utilized estimates of (1) tree aboveground carbon stocks, (2) tree, amphibian, bird, mammal, and reptile species richness, and (3) climate change resilience derived from metrics of topoclimatic diversity and landscape connectivity. Input datasets reflect contemporary (2000-2020) forest conditions and were re-gridded to a common 30 m x 30 m spatial resolution. Each forest patch (i.e., a 30 x 30 m grid cell) was ranked relative to others in its ecoregion based on carbon, biodiversity, and/or resilience metrics (i.e., four prioritization scenarios). The extent of currently protected (GAP 1 or 2; IUCN Ia-VI) forestlands was determined for each ecoregion and then the highest-ranked unprotected forestlands were identified that could be preserved to meet the 30x30 and 50x50 targets using each prioritization scenario. This spatial dataset therefore identifies the locations of forestlands that could be strategically preserved to meet the 30x30 and 50x50 targets as prioritized using each of the four scenarios. Each raster covers forestlands across Oregon at 30 m x 30 m spatial resolution and is provided in GeoTiff format using an Albers Equal Area projection. These spatial data were produced by Law et al. (2022) and support efforts to preserve Oregon's forests for climate change mitigation and adaptation.