Over half of western United States' most abundant tree species in decline.

Changing forest disturbance regimes and climate are driving accelerated tree mortality across temperate forests. However, it remains unknown if elevated mortality has induced decline of tree populations and the ecological, economic, and social benefits they provide. Here, we develop a standardized forest demographic index and use it to quantify trends in tree population dynamics over the last two decades in the western United States. The rate and pattern of change we observe across species and tree size-distributions is alarming and often undesirable. We observe significant population decline in a majority of species examined, show decline was particularly severe, albeit size-dependent, among subalpine tree species, and provide evidence of widespread shifts in the size-structure of montane forests. Our findings offer a stark warning of changing forest composition and structure across the western US, and suggest that sustained anthropogenic and natural stress will likely result in broad-scale transformation of temperate forests globally.

Deep learning and computer vision will transform entomology.

Most animal species on Earth are insects, and recent reports suggest that their abundance is in drastic decline. Although these reports come from a wide range of insect taxa and regions, the evidence to assess the extent of the phenomenon is sparse. Insect populations are challenging to study, and most monitoring methods are labor intensive and inefficient. Advances in computer vision and deep learning provide potential new solutions to this global challenge. Cameras and other sensors can effectively, continuously, and noninvasively perform entomological observations throughout diurnal and seasonal cycles. The physical appearance of specimens can also be captured by automated imaging in the laboratory. When trained on these data, deep learning models can provide estimates of insect abundance, biomass, and diversity. Further, deep learning models can quantify variation in phenotypic traits, behavior, and interactions. Here, we connect recent developments in deep learning and computer vision to the urgent demand for more cost-efficient monitoring of insects and other invertebrates. We present examples of sensor-based monitoring of insects. We show how deep learning tools can be applied to exceptionally large datasets to derive ecological information and discuss the challenges that lie ahead for the implementation of such solutions in entomology. We identify four focal areas, which will facilitate this transformation: 1) validation of image-based taxonomic identification; 2) generation of sufficient training data; 3) development of public, curated reference databases; and 4) solutions to integrate deep learning and molecular tools.

Long-term loss in extent and current protection of terrestrial ecosystem diversity in the temperate and tropical Americas.

Documenting changes in ecosystem extent and protection is essential to understanding status of biodiversity and related ecosystem services and have direct applications to measuring Essential Biodiversity Variables, Targets under the Convention on Biological Diversity (CBD), and IUCN Red List of Ecosystems. We developed both potential and current distribution maps of terrestrial ecosystem types for the temperate and tropical Americas; with "potential" estimating where a type would likely occur today had there not been prior land conversion for modern land uses. We utilized a hierarchical classification to describe and map natural ecosystem types at six levels of thematic detail, with lower thematic levels defining more units each with narrower floristic range than upper levels. Current land use/land cover was derived using available global data on human land use intensity and combined with the potential distribution maps to estimate long-term change in extent for each ecosystem type. We also assessed representation of ecosystem types within protected areas as defined by IUCN I-VI land status categories. Of the 749 ecosystem types assessed, represented at 5th (n = 315) vs. 6th (n = 433) levels of the classification hierarchy, 5 types (1.6%) and 31 types (7.1%), respectively, have lost >90% of their potential extent. Some 66 types (20.9%) and 141 types (32.5%), respectively, have lost >50% of their potential extent; thus, crossing thresholds of Vulnerable status under IUCN Red List criterion A3. For ecosystem type representation within IUCN protected area classes, with reference to potential extent of each type, 111 (45.3%) and 125 (28.8%) of types, respectively, have higher representation (>17%) than CBD 2020 targets. Twelve types (3.8%) and 23 (5.3%) of types, respectively, are represented with <1% within protected areas. We illustrate an option for visualizing and reporting on CBD targets (2020 and proposed post-2020) for ecosystem representativeness using both potential extent as a baseline.

Deficiency syndromes in top predators associated with large-scale changes in the Baltic Sea ecosystem.

Vitamin B1 (thiamin) deficiency is an issue periodically affecting a wide range of taxa worldwide. In aquatic pelagic systems, thiamin is mainly produced by bacteria and phytoplankton and is transferred to fish and birds via zooplankton, but there is no general consensus on when or why this transfer is disrupted. We focus on the occurrence in salmon (Salmo salar) of a thiamin deficiency syndrome (M74), the incidence of which is highly correlated among populations derived from different spawning rivers. Here, we show that M74 in salmon is associated with certain large-scale abiotic changes in the main common feeding area of salmon in the southern Baltic Sea. Years with high M74 incidence were characterized by stagnant periods with relatively low salinity and phosphate and silicate concentrations but high total nitrogen. Consequently, there were major changes in phytoplankton and zooplankton, with, e.g., increased abundances of Cryptophyceae, Dinophyceae, Diatomophyceae and Euglenophyceae and Acartia spp. during high M74 incidence years. The prey fish communities also had increased stocks of both herring and sprat in these years. Overall, this suggests important changes in the entire food web structure and nutritional pathways in the common feeding period during high M74 incidence years. Previous research has emphasized the importance of the abundance of planktivorous fish for the occurrence of M74. By using this 27-year time series, we expand this analysis to the entire ecosystem and discuss potential mechanisms inducing thiamin deficiency in salmon.

Composition and structure of the marine benthic community in Terra Nova Bay, Antarctica: Responses of the benthic assemblage to disturbances.

The community structure and assemblages of marine benthic organisms were investigated in coastal areas near the Jang Bogo Antarctic Research Station in Terra Nova Bay during the 2012-2018 summer seasons. We also examined the recovery pattern of marine benthic organisms following disturbance due to the construction of the Jang Bogo Station. A total of 26 taxa were identified in the study area during the experimental period. Species number and diversity indices (richness, evenness, and diversity) were relatively low compared to data previously reported from Terra Nova Bay. Sphaerotylus antarcticus, Clavularia frankliniana, Hydractinia sp., Iridaea cordata, Fragilariopsis spp., Alcyonium antarcticum, and Metalaeospira pixelli were the dominant species in this area. Of these, the diatom Fragilariopsis spp. were the most abundant species, indicating their key role in maintaining the marine benthic community and controlling biogeochemical cycling. During the construction of the Jang Bogo Station, sediment coverage increased and diatoms declined due to the release of sediment into the coastal area. In February 2014, one month after the disturbance due to cyclone, the diatom coverage increased dramatically and thereby species number, richness index, and diversity index steadily rose from 2015 to 2018. However, non-metric multidimensional scaling ordination analysis of species similarities among sampling times showed that community structure had not completely recovered by 2018. Thus, long-term monitoring is required to elucidate the post-disturbance settlement mechanisms of marine benthic organisms at the study area in Terra Nova Bay.

Population density of the spur-thighed tortoise Testudo graeca declines after fire in north-western Africa.

Fire is a key ecological process in several biomes worldwide. Over recent decades, human activities (e.g. rural abandonment, monoculture plantations) and global warming are magnifying the risk of fire, with changes in fire intensity and frequency. Here, we offer the first study that examines the impact of fire on the spur-thighed tortoise Testudo graeca living in a native cork oak forest and pine plantation in north-western Africa. A total of 44 transects (22 burnt and 22 unburnt) were sampled at 8 sites affected by fires of natural cork oak forest and pine plantation with 8 surveys per site in 2015-2017 (264 hours of sampling effort). Tortoise densities were estimated with line-transect distance sampling. The detection probability of tortoises was higher in burnt (0.915) than unburnt (0.474) transects. The density of tortoises was negatively associated with elevation and declined with fire by c. 50% in both forest types. The negative response of T. graeca to fire should be considered in conservation planning of this species in north-western Africa in a future scenario of changes in fire regime.

Carbon choices determine US cities committed to futures below sea level.

Anthropogenic carbon emissions lock in long-term sea-level rise that greatly exceeds projections for this century, posing profound challenges for coastal development and cultural legacies. Analysis based on previously published relationships linking emissions to warming and warming to rise indicates that unabated carbon emissions up to the year 2100 would commit an eventual global sea-level rise of 4.3-9.9 m. Based on detailed topographic and population data, local high tide lines, and regional long-term sea-level commitment for different carbon emissions and ice sheet stability scenarios, we compute the current population living on endangered land at municipal, state, and national levels within the United States. For unabated climate change, we find that land that is home to more than 20 million people is implicated and is widely distributed among different states and coasts. The total area includes 1,185-1,825 municipalities where land that is home to more than half of the current population would be affected, among them at least 21 cities exceeding 100,000 residents. Under aggressive carbon cuts, more than half of these municipalities would avoid this commitment if the West Antarctic Ice Sheet remains stable. Similarly, more than half of the US population-weighted area under threat could be spared. We provide lists of implicated cities and state populations for different emissions scenarios and with and without a certain collapse of the West Antarctic Ice Sheet. Although past anthropogenic emissions already have caused sea-level commitment that will force coastal cities to adapt, future emissions will determine which areas we can continue to occupy or may have to abandon.

The future of airborne sulfur-containing particles in the absence of fossil fuel sulfur dioxide emissions.

Sulfuric acid (H2SO4), formed from oxidation of sulfur dioxide (SO2) emitted during fossil fuel combustion, is a major precursor of new airborne particles, which have well-documented detrimental effects on health, air quality, and climate. Another precursor is methanesulfonic acid (MSA), produced simultaneously with SO2 during the atmospheric oxidation of organosulfur compounds (OSCs), such as dimethyl sulfide. In the present work, a multidisciplinary approach is used to examine how contributions of H2SO4 and MSA to particle formation will change in a large coastal urban area as anthropogenic fossil fuel emissions of SO2 decline. The 3-dimensional University of California Irvine-California Institute of Technology airshed model is used to compare atmospheric concentrations of gas phase MSA, H2SO4, and SO2 under current emissions of fossil fuel-associated SO2 and a best-case futuristic scenario with zero fossil fuel sulfur emissions. Model additions include results from (i) quantum chemical calculations that clarify the previously uncertain gas phase mechanism of formation of MSA and (ii) a combination of published and experimental estimates of OSC emissions, such as those from marine, agricultural, and urban processes, which include pet waste and human breath. Results show that in the zero anthropogenic SO2 emissions case, particle formation potential from H2SO4 will drop by about two orders of magnitude compared with the current situation. However, particles will continue to be generated from the oxidation of natural and anthropogenic sources of OSCs, with contributions from MSA and H2SO4 of a similar order of magnitude. This could be particularly important in agricultural areas where there are significant sources of OSCs.

Deciduous forest responses to temperature, precipitation, and drought imply complex climate change impacts.

Changes in spring and autumn phenology of temperate plants in recent decades have become iconic bio-indicators of rapid climate change. These changes have substantial ecological and economic impacts. However, autumn phenology remains surprisingly little studied. Although the effects of unfavorable environmental conditions (e.g., frost, heat, wetness, and drought) on autumn phenology have been observed for over 60 y, how these factors interact to influence autumn phenological events remain poorly understood. Using remotely sensed phenology data from 2001 to 2012, this study identified and quantified significant effects of a suite of environmental factors on the timing of fall dormancy of deciduous forest communities in New England, United States. Cold, frost, and wet conditions, and high heat-stress tended to induce earlier dormancy of deciduous forests, whereas moderate heat- and drought-stress delayed dormancy. Deciduous forests in two eco-regions showed contrasting, nonlinear responses to variation in these explanatory factors. Based on future climate projection over two periods (2041-2050 and 2090-2099), later dormancy dates were predicted in northern areas. However, in coastal areas earlier dormancy dates were predicted. Our models suggest that besides warming in climate change, changes in frost and moisture conditions as well as extreme weather events (e.g., drought- and heat-stress, and flooding), should also be considered in future predictions of autumn phenology in temperate deciduous forests. This study improves our understanding of how multiple environmental variables interact to affect autumn phenology in temperate deciduous forest ecosystems, and points the way to building more mechanistic and predictive models.