Climate, Water Navigability, and Economic Development

Geographic information systems (GIS) data was used on a global scale to examine the relationship between climate (ecozones), water navigability, and economic development in terms of GDP per capita. GDP per capita and the spatial density of economic activity measured as GDP per km2 are high in temperate ecozones and in regions proximate to the sea (within 100 km of the ocean or a sea-navigable waterway). Temperate ecozones proximate to the sea account for 8 percent of the world’s inhabited land area, 23 percent of the world’s population, and 53 percent of the world’s GDP. The GDP densities in temperate ecozones proximate to the sea are on average eighteen times higher than in non-proximate non-temperate areas.

Geography and Economic Development

This paper addresses the complex relationship between geography and macroeconomic growth. We investigate the ways in which geography may matter directly for growth, controlling for economic policies and institutions, as well as the effects of geography on policy choices and institutions. We find that location and climate have large effects on income levels and income growth, through their effects on transport costs, disease burdens, and agricultural productivity, among other channels. Furthermore, geography seems to be a factor in the choice of economic policy itself. When we identify geographical regions that are not conducive to modern economic growth, we find that many of these regions have high population density and rapid population increase. This is especially true of populations that are located far from the coast, and thus that face large transport costs for international trade, as well as populations in tropical regions of high disease burden. Furthermore, much of the population increase in the next thirty years is likely to take place in these geographically disadvantaged regions.geography, empirical growth models, transportation costs, tropical disease, tropical agriculture, urbanization, population

Climate, Water Navigability, and Economic Development

Geographic information systems (GIS) data was used on a global scale to examine the relationship between climate (ecozones), water navigability, and economic development in terms of GDP per capita. GDP per capita and the spatial density of economic activity measured as GDP per km2 are high in temperate ecozones and in regions proximate to the sea (within 100 km of the ocean or a sea-navigable waterway). Temperate ecozones proximate to the sea account for 8 percent of the world's inhabited land area, 23 percent of the world's population, and 53 percent of the world's GDP. The GDP densities in temperate ecozones proximate to the sea are on average eighteen times higher than in non-proximate non-temperate areas

Geography, Economic Policy, and Regional Development in China

Many studies of regional disparity in China have focused on the preferential policies received by the coastal provinces. We decomposed the location dummies in provincial growth regressions to obtain estimates of the effects of geography and policy on provincial growth rates in 1996-99. Their respective contributions in percentage points were 2.5 and 3.5 for the province-level metropolises, 0.6 and 2.3 for the northeastern provinces, 2.8 and 2.8 for the coastal provinces, 2.0 and 1.6 for the central provinces, 0 and 1.6 for the northwestern provinces, and 0.1 and 1.8 for the southwestern provinces. Because the so-called preferential policies are largely deregulation policies that have allowed coastal Chinese provinces to integrate into the international economy, it is far superior to reduce regional disparity by extending these deregulation policies to the interior provinces than by re-regulating the coastal provinces. Two additional inhibitions to income convergence are the household registration system, which makes the movement of the rural poor to prosperous areas illegal, and the monopoly state bank system that, because of its bureaucratic nature, disburses most of its funds to its large traditional customers, few of whom are located in the western provinces. Improving infrastructure to overcome geographic barriers is fundamental to increasing western growth, but increasing human capital formation (education and medical care) is also crucial because only it can come up with new better ideas to solve centuries-old problems like unbalanced growth

Geography and Economic Development

This paper addresses the complex relationship between geography and macroeconomic growth. We investigate the ways in which geography may matter directly for growth, controlling for economic policies and institutions, as well as the effects of geography on policy choices and institutions. We find that location and climate have large effects on income levels and income growth, through their effects on transport costs, disease burdens, and agricultural productivity, among other channels. Furthermore, geography seems to be a factor in the choice of economic policy itself. When we identify geographical regions that are not conducive to modern economic growth, we find that many of these regions have high population density and rapid population increase. This is especially true of populations that are located far from the coast, and thus that face large transport costs for international trade, as well as populations in tropical regions of high disease burden. Furthermore, much of the population increase in the next thirty years is likely to take place in these geographically disadvantaged regions.

Exploring movement patterns and changing distributions of baleen whales in the western North Atlantic using a decade of passive acoustic data

© The Author(s), 2020. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Davis, G. E., Baumgartner, M. F., Corkeron, P. J., Bell, J., Berchok, C., Bonnell, J. M., Thornton, J. B., Brault, S., Buchanan, G. A., Cholewiak, D. M., Clark, C. W., Delarue, J., Hatch, L. T., Klinck, H., Kraus, S. D., Martin, B., Mellinger, D. K., Moors-Murphy, H., Nieukirk, S., Nowacek, D. P., Parks, S. E., Parry, D., Pegg, N., Read, A. J., Rice, A. N., Risch, D., Scott, A., Soldevilla, M. S., Stafford, K. M., Stanistreet, J. E., Summers, E., Todd, S., & Van Parijs, S. M. Exploring movement patterns and changing distributions of baleen whales in the western North Atlantic using a decade of passive acoustic data. Global Change Biology, (2020): 1-30, doi:10.1111/gcb.15191.Six baleen whale species are found in the temperate western North Atlantic Ocean, with limited information existing on the distribution and movement patterns for most. There is mounting evidence of distributional shifts in many species, including marine mammals, likely because of climate‐driven changes in ocean temperature and circulation. Previous acoustic studies examined the occurrence of minke (Balaenoptera acutorostrata ) and North Atlantic right whales (NARW; Eubalaena glacialis ). This study assesses the acoustic presence of humpback (Megaptera novaeangliae ), sei (B. borealis ), fin (B. physalus ), and blue whales (B. musculus ) over a decade, based on daily detections of their vocalizations. Data collected from 2004 to 2014 on 281 bottom‐mounted recorders, totaling 35,033 days, were processed using automated detection software and screened for each species' presence. A published study on NARW acoustics revealed significant changes in occurrence patterns between the periods of 2004–2010 and 2011–2014; therefore, these same time periods were examined here. All four species were present from the Southeast United States to Greenland; humpback whales were also present in the Caribbean. All species occurred throughout all regions in the winter, suggesting that baleen whales are widely distributed during these months. Each of the species showed significant changes in acoustic occurrence after 2010. Similar to NARWs, sei whales had higher acoustic occurrence in mid‐Atlantic regions after 2010. Fin, blue, and sei whales were more frequently detected in the northern latitudes of the study area after 2010. Despite this general northward shift, all four species were detected less on the Scotian Shelf area after 2010, matching documented shifts in prey availability in this region. A decade of acoustic observations have shown important distributional changes over the range of baleen whales, mirroring known climatic shifts and identifying new habitats that will require further protection from anthropogenic threats like fixed fishing gear, shipping, and noise pollution.We thank Chris Pelkie, David Wiley, Michael Thompson, Chris Tessaglia‐Hymes, Eric Matzen, Chris Tremblay, Lance Garrison, Anurag Kumar, John Hildebrand, Lynne Hodge, Russell Charif, Kathleen Dudzinski, and Ann Warde for help with project planning, field work support, and data management. For all the support and advice, thanks to the NEFSC Protected Species Branch, especially the passive acoustics group, Josh Hatch, and Leah Crowe. We thank the field and crew teams on all the ships that helped in the numerous deployments and recoveries. This research was funded and supported by many organizations, specified by projects as follows: data recordings from region 1 were provided by K. Stafford (funding: National Science Foundation #NSF‐ARC 0532611). Region 2 data: D. K. Mellinger and S. Nieukirk, National Oceanic and Atmospheric Administration (NOAA) PMEL contribution #5055 (funding: NOAA and the Office of Naval Research #N00014–03–1–0099, NOAA #NA06OAR4600100, US Navy #N00244‐08‐1‐0029, N00244‐09‐1‐0079, and N00244‐10‐1‐0047). Region 3A data: D. Risch (funding: NOAA and Navy N45 programs). Region 3 data: H. Moors‐Murphy and Fisheries and Oceans Canada (2005–2014 data), and the Whitehead Lab of Dalhousie University (eastern Scotian Shelf data; logistical support by A. Cogswell, J. Bartholette, A. Hartling, and vessel CCGS Hudson crew). Emerald Basin and Roseway Basin Guardbuoy data, deployment, and funding: Akoostix Inc. Region 3 Emerald Bank and Roseway Basin 2004 data: D. K. Mellinger and S. Nieukirk, NOAA PMEL contribution #5055 (funding: NOAA). Region 4 data: S. Parks (funding: NOAA and Cornell University) and E. Summers, S. Todd, J. Bort Thornton, A. N. Rice, and C. W. Clark (funding: Maine Department of Marine Resources, NOAA #NA09NMF4520418, and #NA10NMF4520291). Region 5 data: S. M. Van Parijs, D. Cholewiak, L. Hatch, C. W. Clark, D. Risch, and D. Wiley (funding: National Oceanic Partnership Program (NOPP), NOAA, and Navy N45). Region 6 data: S. M. Van Parijs and D. Cholewiak (funding: Navy N45 and Bureau of Ocean and Energy Management (BOEM) Atlantic Marine Assessment Program for Protected Species [AMAPPS] program). Region 7 data: A. N. Rice, H. Klinck, A. Warde, B. Martin, J. Delarue, and S. Kraus (funding: New York State Department of Environmental Conservation, Massachusetts Clean Energy Center, and BOEM). Region 8 data: G. Buchanan, and K. Dudzinski (funding: New Jersey Department of Environmental Protection and the New Jersey Clean Energy Fund) and A. N. Rice, C. W. Clark, and H. Klinck (funding: Center for Conservation Bioacoustics at Cornell University and BOEM). Region 9 data: J. E. Stanistreet, J. Bell, D. P. Nowacek, A. J. Read, and S. M. Van Parijs (funding: NOAA and US Fleet Forces Command). Region 10 data: L. Garrison, M. Soldevilla, C. W. Clark, R. A. Chariff, A. N. Rice, H. Klinck, J. Bell, D. P. Nowacek, A. J. Read, J. Hildebrand, A. Kumar, L. Hodge, and J. E. Stanistreet (funding: US Fleet Forces Command, BOEM, NOAA, and NOPP). Region 11 data: C. Berchok as part of a collaborative project led by the Fundacion Dominicana de Estudios Marinos, Inc. (Dr. Idelisa Bonnelly de Calventi; funding: The Nature Conservancy [Elianny Dominguez]) and D. Risch (funding: World Wildlife Fund, NOAA, and Dutch Ministry of Economic Affairs)