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This study examines the impact of government spending, income, and tourism consumption on CO2 emissions in the 50 US states through a novel theoretical model derived from the Armey Curve model and the Environmental Kuznets Curve hypothesis. The findings of this research are essential for policymakers to develop effective strategies for mitigating environmental pollution. Utilizing panel cointegration analysis, the study provides valuable insights into whether continued increases in government spending contribute to higher pollution levels. By identifying the threshold point of spending as a percentage of GDP, policymakers can make informed decisions to avoid the trade-off between increased spending and environmental degradation. For instance, the analysis reveals that Hawaii's tipping point is 16.40%. The empirical results underscore the importance of adopting sustainable policies that foster economic growth while minimizing environmental harm. These findings will aid policymakers in formulating targeted and efficient approaches to tackle climate change and promote long-term environmental sustainability in the United States. Moreover, the impact of tourism development on CO2 emissions varies across states, with some US states experiencing a decrease while others see an increase. [ABSTRACT FROM AUTHOR]

The Hawaiian Islands have been identified as a global biodiversity hotspot. We examine the Normalized Difference Vegetation Index (NDVI) using Climate Data Records products (0.05 × 0.05°) to identify significant differences in NDVI between neutral El Niño-Southern Oscillation years (1984, 2019) and significant long-term changes over the entire time series (1982–2019) for the Hawaiian Islands and six land cover classes. Overall, there has been a significant decline in NDVI (i.e., browning) across the Hawaiian Islands from 1982 to 2019 with the islands of Lāna'i and Hawai'i experiencing the greatest decreases in NDVI (≥44%). All land cover classes significantly decreased in NDVI for most months, especially during the wet season month of March. Native vegetation cover across all islands also experienced significant declines in NDVI, with the leeward, southwestern side of the island of Hawai'i experiencing the greatest declines. The long-term trends in the annual total precipitation and annual mean Palmer Drought Severity Index (PDSI) for 1982–2019 on the Hawaiian Islands show significant concurrent declines. Primarily positive correlations between the native ecosystem NDVI and precipitation imply that significant decreases in precipitation may exacerbate the decrease in NDVI of native ecosystems. NDVI-PDSI correlations were primarily negative on the windward side of the islands and positive on the leeward sides, suggesting a higher sensitivity to drought for leeward native ecosystems. Multi-decadal time series and spatially explicit data for native landscapes provide natural resource managers with long-term trends and monthly changes associated with vegetation health and stability. [ABSTRACT FROM AUTHOR]

Complex socio-ecological issues, such as climate change have historically been addressed through technical problem solving methods. Yet today, climate science approaches are increasingly accounting for the roles of diverse social perceptions, experiences, cultural norms, and worldviews. In support of this shift, we developed a research program on Hawaiʻi Island that utilizes knowledge coproduction to integrate the diverse worldviews of natural and cultural resource managers, policy professionals, and researchers within actionable science products. Through their work, local field managers regularly experience discrete land and waterscapes. Additionally, in highly interconnected rural communities, such as Hawaiʻi Island, managers often participate in the social norms and values of communities that utilize these ecosystems. Such local manager networks offer powerful frameworks within which to co-develop and implement actionable science. We interviewed a diverse set of local managers with the aim of incorporating their perspectives into the development of a collaborative climate change research agenda that builds upon existing professional networks utilized by managers and scientists while developing new research products. We report our manager needs assessment, the development process of our climate change program, our interactive forums, and our ongoing research products. Our needs assessment showed that the managers’ primary source of information were other professional colleagues, and our in-person forums informed us that local managers are very interested in interacting with a wider range of networks to build upon their management capacities. Our initial programmatic progress suggests that co-created research products and in-person forums strengthen the capacities of local managers to adapt to change. [ABSTRACT FROM AUTHOR]

Over the last century, significant declines in rainfall across the state of Hawai‘i have been observed, and it is unknown whether these declines are due to natural variations in climate, or manifestations of human-induced climate change. Here, a statistical analysis of the observed rainfall variability was applied as first step towards better understanding causes for these long-term trends. Gridded seasonal rainfall from 1920 to 2012 is used to perform an empirical orthogonal function (EOF) analysis. The leading EOF components are correlated with three indices of natural climate variations (El Niño-Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), and Pacific North American (PNA)), and multiple linear regression (MLR) is used to model the leading components with climate indices. PNA is the dominant mode of wet season (November-April) variability, while ENSO is most significant in the dry season (May-October). To assess whether there is an anthropogenic influence on rainfall, two methods are used: a linear trend term is included in the MLR, and pattern correlation coefficients (PCC) are calculated between recent rainfall trends and future changes in rainfall projected by downscaling methods. PCC results indicate that recent observed rainfall trends in the wet season are positively correlated with future expected changes in rainfall, while dry season PCC results do not show a clear pattern. The MLR results, however, show that the trend term adds significantly to model skill only in the dry season. Overall, MLR and PCC results give weak and inconclusive evidence for detection of anthropogenic signals in the observed rainfall trends. [ABSTRACT FROM AUTHOR]

Whole genome sequences, which can be provided even for non-model organisms owing to high-throughput sequencers, are valuable in enhancing the understanding of adaptive evolution. Metrosideros polymorpha, a tree species endemic to the Hawaiian Islands, occupies a wide range of ecological habitats and shows remarkable polymorphism in phenotypes among/within populations. The biological functions of genetic variations observed within this species could provide significant insights into the adaptive radiation found in a single species. Here de novo assembled genome sequences of M. polymorpha are presented to reveal basic genomic parameters about this species and to develop our knowledge of ecological divergences. The assembly yielded 304-Mbp genome sequences, half of which were covered by 19 scaffolds with >5 Mbp, and contained 30 K protein-coding genes. Demographic history inferred from the genome-wide heterozygosity indicated that this species experienced a dramatic rise and fall in the effective population size, possibly owing to past geographic or climatic changes in the Hawaiian Islands. This M. polymorpha genome assembly represents a high-quality genome resource useful for future functional analyses of both intra- and interspecies genetic variations or comparative genomics. [ABSTRACT FROM AUTHOR]

Background: Spatially explicit forest carbon (C) monitoring aids conservation and climate change mitigation efforts, yet few approaches have been developed specifically for the highly heterogeneous landscapes of oceanic island chains that continue to undergo rapid and extensive forest C change. We developed an approach for rapid mapping of aboveground C density (ACD; units = Mg or metric tons C ha-1) on islands at a spatial resolution of 30 m (0.09 ha) using a combination of cost-effective airborne LiDAR data and full-coverage satellite data. We used the approach to map forest ACD across the main Hawaiian Islands, comparing C stocks within and among islands, in protected and unprotected areas, and among forests dominated by native and invasive species. Results: Total forest aboveground C stock of the Hawaiian Islands was 36 Tg, and ACD distributions were extremely heterogeneous both within and across islands. Remotely sensed ACD was validated against U.S. Forest Service FIA plot inventory data (R2 = 0.67; RMSE = 30.4 Mg C ha-1). Geospatial analyses indicated the critical importance of forest type and canopy cover as predictors of mapped ACD patterns. Protection status was a strong determinant of forest C stock and density, but we found complex environmentally mediated responses of forest ACD to alien plant invasion. Conclusions: A combination of one-time airborne LiDAR data acquisition and satellite monitoring provides effective forest C mapping in the highly heterogeneous landscapes of the Hawaiian Islands. Our statistical approach yielded key insights into the drivers of ACD variation, and also makes possible future assessments of C storage change, derived on a repeat basis from free satellite data, without the need for additional LiDAR data. Changes in C stocks and densities of oceanic islands can thus be continually assessed in the face of rapid environmental changes such as biological invasions, drought, fire and land use. Such forest monitoring information can be used to promote sustainable forest use and conservation on islands in the future. [ABSTRACT FROM AUTHOR]

With climate warming, malaria in humans and birds at upper elevations is an emerging infectious disease because development of the parasite in the mosquito vector and vector life history are both temperature dependent. An enhanced-mosquito-movement model from climate warming predicts increased transmission of malaria at upper elevation sites that are too cool for parasite development in the mosquito vector. We evaluate this model with avian malaria ( Plasmodium relictum) at 1,900-m elevation on the Island of Hawaii, with air temperatures too low for sporogony in the vector ( Culex quinquefasciatus). On a well-defined site over a 14-year period, 10 of 14 species of native and introduced birds became infected, several epizootics occurred, and the increase in prevalence was driven more by resident species than by mobile species that could have acquired their infections at lower elevations. Greater movement of infectious mosquitoes from lower elevations now permits avian malaria to spread at 1,900 m in Hawaii, in advance of climate warming at that elevation. The increase in malaria at upper elevations due to dispersal of infectious mosquitoes is a real alternative to temperature for the increased incidence of human malaria in tropical highlands. [ABSTRACT FROM AUTHOR]