Global energy-related carbon dioxide emissions grew by 1.4% in 2017, reaching a historic high of 32.5 billion metric tons, according to a recent report by the International Energy Agency. The increase occurred because of a 2.1% increase in the global amount of energy consumed. Figure 1 shows the trend on energy-related carbon dioxide emissions.
(Click on figure for larger view.)
More than 40% of the increase in energy consumption was driven by China and India. (See Figure 2) The result was an almost 150 million metric ton increase in China’s carbon dioxide emissions from energy. India’s emissions are not broken out, but carbon dioxide emissions from the rest of developing Asia (ex-China) were approximately 125 million metric tons higher than in 2016 (amounts are not precise because they are read from a graph).
Some countries had lower carbon dioxide emissions. The biggest decline came from the USA, where emissions declined 25 million metric tons, or 0.5%. In Mexico, emissions dropped 4%, and in the United Kingdom they dropped 3.8%. Way to go Mexico and United Kingdom! Because those countries consume far less energy than does the USA, the raw number of metric tons reduced was less than in the USA, despite the percentage being higher.
Last December I published a post reporting that worldwide carbon dioxide emissions from energy had held constant for the three years ending in 2016. What happened?
Figure 3 shows the drivers of the change in carbon dioxide emissions. Energy intensity (in yellow) has decreased every year since 2011, meaning that it required less energy to produce a unit of economic output. The rate at which energy intensity improved seemed to grow until 2015, but the rate of improvement seems to have slowed since then. Carbon dioxide intensity also seems to have improved in many of the years (meaning that less carbon dioxide is released per unit of energy produced, most likely from cleaner fuel). On the other hand, economic growth has occurred in every year. It accelerated in 2017, and its effect overwhelmed the effects of the other two drivers.
Figure 4 shows the annual growth in energy consumption by fuel. The chart shows that from 2006-2015, there was an average increase in consumption of all types of energy except nuclear. In 2016, however, there was a significant reduction in demand for energy from burning coal. Readers of this blog know that represents an important achievement, as coal emits more carbon dioxide per unit of energy than do the other fuels. However, in 2017, that achievement reversed itself, and demand for energy from burning coal rose again.
In 2017, the largest increase in energy demand was met by burning natural gas. The second largest increase in energy demand was met by renewable energy.
Overall, the report is not good news. As readers of this blog know, to prevent the worst effects of climate change, greenhouse gas emissions need to peak, and then be significantly reduced. There is no sign that is occurring. To quote the report:
The IEA’s Sustainable Development Scenario charts a path towards meeting long-term climate goals. Under this scenario, global emissions need to peak soon and decline steeply to 2020; this decline will now need to be even greater given the increase in emissions in 2017. The share of low-carbon energy sources must increase by 1.1 percentage points every year, more than five-times the growth registered in 2017. In the power sector, specifically, generation from renewable sources must increase by an average 700 TWh annually in that scenario, an 80% increase compared to the 380 TWh increase registered in 2017. (International Energy Agency, 2018, p. 4)
International Energy Agency. 2018. Global Energy & CO2 Status Report, 2017. Downloaded 4/18/2018 from https://www.iea.org/geco.
Developed land is on the increase, while cropland, pastureland, and rangeland are on the decrease, according to the 2012 Natural Resources Inventory. The U.S. Department of Agriculture has conducted the inventory every 5 years since 1982, but it takes several years to put the report together, so the inventory for 2017 is not yet available.
Figure 1 graphs the surface area of the contiguous 48 states by land cover/land use in 2012. The top 3 uses were forest land, rangeland, and federal land, each of which accounted for 21% of the total. When the USA was first settled, forest land and rangeland were much more extensive, but they have been converted into cropland and developed land. In addition, we think of our country as having huge freshwater lakes, but only about 3% of the surface area is water. Freshwater is very precious and special.
Of course, federal land could also be categorized into forest land, rangeland, cropland, and the other categories, but the Natural Resources Inventory does not do so.
Figure 2 shows the change in land cover/land use since 1982. Over that time, cropland decreased and developed land increased by more acres than did any other category. “CRP Land” is land placed in the Conservation Resource Program.
The Natural Resources Inventory grew out of the National Erosion Reconnaissance Survey, conducted in 1934 because of severe dust storms and erosion during the Dust Bowl. Thus, since its inception, the report has been concerned with erosion. Figure 3 shows the estimated erosion rate on cropland in 1982, and Figure 4 shows the same data for 2012. You can see that in 1982, erosion was most severe in a region centered on Iowa’s borders with Illinois, Missouri, and Nebraska, but also extending along the Mississippi River into western Tennessee. In 2012, that region remained the one with the most severe erosion, but the rate had been significantly reduced. Across northern Missouri in 1982, more than 10 tons of soil eroded from each acre of cropland each year! In 2012 that had been reduced by 50% or so.
Figure 5 shows land use in Missouri from 1982 – 2012 in a few broad categories. The green areas of the columns represent federal land, which is not broken-out according to use. The red areas represent water. The two blue areas represent non-federal land, and they are broken into two categories: developed (light blue) and rural (dark blue). You can see that rural land represents by far the largest use of land in Missouri. In 2012, it represented 86.8% of Missouri’s surface area, while federal land, water areas, and developed land represented 4.5%, 2.0%, and 6.7%, respectively. Over the 30-year period, federal land increased slightly, water areas increased slightly, and developed areas increased by a whopping 38%, all being converted from rural land.
Figure 6 looks at Missouri’s non-federal rural land more closely. In 2012, more land was used for crops than for any other purpose (36% of rural land), followed by forest land (32%) and pastureland (27%). Over the 30-year period, the amount used for cropland decreased slightly, pastureland has decreased 17%, and rangeland, which was already such a small portion of the land that you can barely see it on the chart, declined 62%. Forest land and other rural land have increased. The Conservation Reserve Program (CRP Land) began after 1982, peaking in 1997, and declining since then.
This report is compiled and published by the U.S. Department of Agriculture, and from an environmental perspective it may be a bit misleading. Figure 5 shows that developed land represents only 6.7% of all Missouri land. However, Figure 6 shows that almost 1/3 of rural land is cropland, and another 27% of it is pastureland. It is not as if these lands are undeveloped. While they may not be covered in asphalt or highly populated, they are intensively used. They may be subject to high levels of erosion, as shown in Figure 3, or they may be disturbed by tilling and the application of agricultural chemicals. Pig farms and feed lots, for instance, are located in rural areas, but they are highly developed operations, in many cases resembling factories.
Thus, the Natural Resources Inventory probably provides the most comprehensive look at land cover/land use in the USA. It does not, however, provide an in depth review of the ecological status of the land.
Missouri Department of Natural Resources. 2018. Soil and Water Conservation Program. Viewed online 4/18/2018 at https://dnr.mo.gov/env/swcp.
U.S. Department of Agriculture. 2015. Summary Report: 2012 National Resources Inventory, Natural Resources Conservation Service, Washington, DC, and Center for Survey Statistics and Methodology, Iowa State University, Ames, Iowa. http://www.nrcs.usda.gov/technical/nri/12summary.
Arctic sea ice apparently reached its annual maximum extent on March 17, 2018, and it was the second lowest in the record, according to a report from the National Snow and Ice Data Center.
Each summer the arctic warms, and as it does, the sea ice covering the Arctic Ocean melts, reaching an annual low-point in late summer. Then, each winter the arctic cools, the surface of the ocean freezes, and the area covered by sea ice expands. The sea ice reaches its maximum extent in late winter, this year on March 17.
The National Snow and Ice Data Center tracks the extent of the sea ice using satellite images, as shown in Figure 1. The map is a polar view, with the North Pole in the center, the sea ice in white, and the ocean in blue. The land forms are in gray, with North America at lower left, and Eurasia running from Spain at lower right to the Russian Far East at the top. The magenta line shows the 1981-2010 average extent of the ice for the month of March. It doesn’t look like much on the map, but the anomaly in 2018 amounts to 436,300 square miles less than average.
(Click on figure for larger view.)
Figure 2 shows the trend in Arctic sea ice from 1979-2018. The declining trend is easy to see. (The y-axis does not extend to zero to better show the change.) The National Snow and Ice Data Center applied a linear regression trend line to the data (blue line), and the trend shows an average loss of 16,400 square miles per year.
What about the annual minimum? That has been shrinking, too. Figure 3 shows the Arctic sea ice minimum in 1980, and Figure 4 shows it in 2012. The prevailing winds tend to blow the ice up against Greenland and the far northern islands of Canada, but you can see that in 1980 most of the sea, from the Canadian islands, to Greenland, to the Svalbard Islands, to Severnaya Zemla (anybody remember the Bond movie “GoldenEye?”), to the north of Far Eastern Russia, was covered by ice. In 2012, however, more than half of the Arctic Sea was ice-free, from north of the Svalbard Islands right around to the Canadian Islands. Even the famed Northwest Passage, a channel through the Canadian Islands, was open.
Figure 5 charts the trend in the annual minimum. At its low in 2012, it was less than half of what it was in 1980.
The volume of the polar ice cap also depends on how thick the ice is. Satellites can photograph the entire ice cap, but data on thickness come to us from on-site measurements at a limited number of points. I don’t have a chart to share with you, but the data seem to indicate that compared to the years 1958-1976, in 2003-2007 the thickness had declined about 50% to 64%, depending on where the measurement was taken. (This change is approximate, being read off of a graph by Kwok and Rothrock, 2009.)
Thus, the decline in the arctic ice cap is actually much larger than suggested by the change in its extent.
Why does arctic sea ice matter? First, Arctic sea ice does not form primarily from snowfall, as does the snowcap in the western United States. Arctic sea ice forms because the temperature is low enough to cause the surface of the water to freeze, just as the your local pond or lake freezes if it gets cold enough. Thus, declining Arctic sea ice is a sign that the Arctic is warming. The Arctic seems to be the part of the planet that is warming the most from climate change, and this is a clear and graphic sign of that change.
Oddly, the warming arctic is one reason for the bizarre weather we have had in Missouri this winter. As noted in a post on 1/22/2015, the warming arctic weakens the polar vortex, which allows arctic cold to escape and travel south, impacting us in Missouri. Figure 6 shows the anomaly in Arctic temperatures from December, 2017 through February, 2018, in C. While it was warm over the entire Arctic, as much as 7°C above average (12.6°F), it was 2-3°C cooler than average over North America (3.6-5.4°F).
Second, it matters because ice is white, but the ocean is blue. That means that sunlight hitting ice reflects back towards space, and is not absorbed. Being blue, however, the ocean absorbs the light, and converts the energy to heat. This reflective capacity is called “albedo,” and the albedo of ocean is less than that of ice. Thus, the ice is melting because of global warming, but then, the melting contributes to even more global warming through the change in albedo. People are fond of saying that the earth has buffering mechanisms that tend to inhibit large climate changes, and such mechanisms do exist, but not everywhere in all things. This is one example where the earth shows positive feedback that destabilizes the climate even further.
Melting Arctic ice is not a major factor in the rising sea level. The reason is that the ice is already in the water. When the ice in your glass of iced tea melts, it doesn’t make the glass overflow. In the same way, as this ice melts, it has only a small effect on sea level. On the other hand, the Greenland Ice Cap and the Antarctic Ice Cap are not already in the water, and as they melt, they do affect sea level.
One final word: the data above are not computer models of future events. They are the best data available of what has already been happening, and what is happening now. To deny the reality of climate change is like denying that a river will flood, even as its water already swirls around your knees.
Kwok, R., and D./A. Rothrock. 2009. “Decline in Arctic Sea Ice Thickness from Submarine and ICESat Records: 1958-2008. Beophysical Research Letters 36:L15501. Cited in National Snow & Ice Data Center. State of the Cryosphere. Viewed online 4/12/2018 at http://nsidc.org/cryosphere/sotc/sea_ice.html.
NASA Global Climate Change. Arctic Sea Ice Minimum. Downloaded 4/12/18 from https://climate.nasa.gov/vital-signs/arctic-sea-ice.
NASA Scientific Visualization Studio. Annual Arsctic Sea Ice Minimum 1979-2015 with Area Graph. Downloaded 4/12/18 from https://svs.gsfc.nasa.gov/4435.
NASA Scientific Visualization Studio. Annual Arsctic Sea Ice Minimum 1979-2015 with Area Graph. Downloaded 4/12/18 from https://svs.gsfc.nasa.gov/4435.
National Snow & Ice Data Center. “2018 Winter Arctic Sea Ice: Bering Down. Arctic Sea Ice News & Analysis. 4/4/2018. Downloaded 4/12/2018 from http://nsidc.org/arcticseaicenews.
The National Center for Health Statistics keeps data for each year going back to 1909 on the number of live births in the United States and on the fertility rate. Fertility rate is defined as the number of births per 1,000 women. These data are an important environmental concern because they greatly influence future population. The more people there are in the world, and the higher their standard of living, the more environmental stress is created. The United States has a high standard of living, so an increasing population here increases environmental strain.
Figure 1 shows the trend in births and fertility rate from 1909 to 2016. Live births are shown in blue, and should be read against the left vertical axis. The fertility rate is shown in red and should be read against the right vertical axis. In 1909 there were 2,718,000 live births, rising to a peak of 4,316,233 in 2007, and easing since then to 3,945,875 in 2016. In 1909 the birth rate was 126.8. It fell sharply to 75.8 in 1936 (the depths of the Great Depression), then increased sharply to 122.9 in 1957 (the baby boom). It then decreased sharply until the 1970s, and has trended slowly down since then. In 2016, the fertility rate was 62.0.
(Click on chart for larger view.)
Birth and fertility rates are also important from several other policy perspectives The NCHS report shows that the fertility rate is declining among all age groups under 30 years old, and the rate of teen births has been cut by more than half since 2007. This is a very important change for public health and welfare. The fertility rate for women over 30 has increased over time. In fact, the fertility rate for women in their 30s was 102.7 in 2016, compared to 73.8 for women aged 20-24, and 102.1 for women aged 25-29. Thus, more older women are giving birth.
In Missouri, data on the number of births goes back to 1990, when there were 79,135. Births then decreased to a low in 1995 of 72,804, after which they increased to 81,833 in 2007. Since 2007, they have declined to 74,664 in 2016. The fertility rate statistic is only available from 1996, when it was 61.4. It increased to 68.8 in 2007, and has declined since then, to 63.7 in 2016. The data is shown in Figure 2. The blue line is for the number of births, and should be read against the left vertical axis. The red line is for the fertility rate, and should be read against the right vertical axis.
Figure 3 shows the 2016 fertility rate for the 50 states plus the District of Columbia. South Dakota had the highest fertility rate, at 77.7, and Vermont had the lowest, at 50.3. Missouri was 19th highest. I don’t think that anybody believes that state boundaries control fertility rate, but these data give a small snapshot of what is happening in our state compared to others.
National Center for Health Statistics Data Visualization Gallery (data portal). Data downloaded 3/28/2018 from https://www.cdc.gov/nchs/data-visualization/natality-trends.
Martin JA, Hamilton BE, Osterman MJK, Driscoll AK, Drake P. Births: Final data for 2016. National Vital Statistics Reports; vol 67 no 1. Hyattsville, MD: National Center for Health Statistics. 2018. https://www.cdc.gov/nchs/data/nvsr/nvsr67/nvsr67_01.pdf.
Missouri Department of Health and Senior Services. Missouri Information for Community Assessment Data Portal. Data downloaded 3/28/2018 from https://webapp01.dhss.mo.gov/MOPHIMS/MICAHome.
The western snowpack was seriously below average this year, and it was way below average in the Lower Colorado Region.
It is early April, and that means it is time to check-in with snowpack data in California and the American West. On average, the snowpack reaches its maximum by April 1, after which it begins to shrink as it melts away. California and much of the West have a monsoonal precipitation pattern: the bulk of the yearly precipitation falls during the winter. Because the summer and fall are so dry, many regions depend on melting snow, which they collect into reservoirs. The snowpack serves as a kind of natural reservoir, collecting precipitation during the winter, and releasing it gradually as the snow melts.
Snowpack is measured in inches of water equivalent. To equal an inch of melted water requires between 7 and 20 inches of snow, depending on how slushy or powdery the snow is. To quantify the snowpack, scientists calculate how many inches of snow are on the ground, and how much water it would represent if it were instantaneously melted. The result is called the snow water equivalent. Thus, 1 inch of snow water equivalent means that, no matter how deep the snow is lying on the ground, if you melted it, it would equal 1 inch of water.
Figure 1 shows the snowpack in California for the three major snow regions: North, Central, and South, with the snow water equivalent given along the vertical axis on the left. The dark blue line represents the 2017-2018 winter, and the line ends on March 29. The blue number at the end of each blue line represents the snow water equivalent of this year’s snowpack as a percentage of the historical average for that date. At lower right the three regions are combined into a single number, representing the snow water content of the entire state’s snowpack for 3/29/18. At the bottom left the chart shows the statewide percentage compared to what’s average for April 1.
Through the end of February, this winter was the second driest on record, and the snowpack was something like 20% of average. March was a wet month, however, tripling the snowpack. Even so, that only brought it up to a statewide average of 57%.
California also depends on water from outside of the state, especially water from the Colorado River. Figure 2 shows readings for the entire region upon which California draws. It encompasses much of the southwestern United States. The data for this map come from a different data set than the ones in the previous chart, and thus the data for California are slightly different. (Most of the difference probably arises from using somewhat different reference periods to represent “average.”)
As you can see, the entire region has had a smaller than average snowpack. However, the snowpack in the Lower Colorado Region is particularly worrisome, as it is only 21% of average.
The Mammoth Mountain Ski Resort publishes a detailed history of the snowfall at the resort, and I use it as an example of the snowfall in a given California location. Figure 3 shows the data. The total amount of snow at Mammoth Mountain through March 31 was 248 inches this year, compared to an average of 308 over the period from 1969-2018. The length of the colored bars for 2018 illustrates that more than half of the snow for the whole season fell during March. The chart also shows just how wet a winter it was last year, the second wettest in the record. Bear in mind that Mammoth Mountain is measuring snowfall, not snowpack.
So, measurements of the snowpack indicate that it is seriously below average. What, then, is the status of California’s water supply? The quick answer is that for this year they should be fine.
California’s water supply is impacted this year by an extraordinary circumstance: in February, 2017, the Oroville Dam suffered a failure of the main and emergency spillways, leading to the evacuation of 188,000 people lest the dam fail entirely (see here). It didn’t fail, but since then the reservoir has been partially emptied to facilitate repairs and improvements.
Figure 4 shows the data for the largest California reservoirs. On the chart, the blue bars represent the level of each reservoir on March 30, while the yellow bars represent the maximum capacity. The red line represents the historical average level of each reservoir on March 30. The blue number below the bars represents the amount of water in each reservoir compared to its capacity, while the red number represents the amount of water compared to the historical average for March 30.
As you can see, most of the reservoirs are at or above their average for March 30, and only Lake Oroville is considerably below average. The region around Santa Barbara, however, remains in a serious drought. The two largest reservoirs in Santa Barbara County, the Cachuma and Twitchell Reservoirs, are at 40% and 2% of capacity, respectively (not shown on the chart).
In addition to the California reservoir system, southern California relies heavily on water from the Colorado River. Lake Mead, the largest reservoir on the Colorado River, has been overused for years, and was even forecast to have a strong chance of going dry (see here). Figure 5 plots the water level at Lake Mead over the past year. Each year it fills with the spring snowmelt, and then is drawn down throughout the rest of the year. Beginning just after 2000 Lake Mead has suffered a steady and rather alarming drop. Last year, for the first time in many years, Lake Mead showed a year-to-year increase in its water storage. This year, as of April 1, the water level of Lake Mead is basically unchanged from last year.
Lake Powell, a large reservoir upstream from Lake Mead, is up 16 feet from last year on this date. That is a significant increase, and it comes entirely from the large snowpack last year.
So, what does all this mean? The snowpack this year was seriously below average, and it was way below average in the Lower Colorado drainage region. California’s reservoirs, however, appear to be in good shape except in the region around Santa Barbara. Lake Mead has not lost additional water, and the fact that Lake Powell has gained water means that officials may be able to move water from there to Lake Mead if needed. Thus, the water supply, for this year may be sufficient for California and for those regions that draw on the Colorado River below Lake Mead.
It is worrisome, however, that after having experienced a severe multi-year drought, and then only 1 year of high precipitation, California and the Southwest have returned to below average snowpacks. I have reported previously that climate predictions include a permanent reduction of the snowpack throughout the West (see here) and in California (see here). We will have to keep watching over many years to see how this plays out.
California Department of Water Resources, California Data Exchange Center. Reservoir Conditions, 4/1/2018. Downloaded 4/2/2018 from http://cdec.water.ca.gov/cgi-progs/products/rescond.pdf.
California Department of Water Resources, California Data Exchange Center. California Statewide Water Conditions, Current Year Regional Snow Sensor Water Content Chart (PDF). Downloaded 4/1/2018 from https://cdec.water.ca.gov/water_cond.html.
Mammoth Mountain Ski Resort. Snow Conditions and Weather. Viewed online 4/1/2018 at https://www.mammothmountain.com/winter/mountain-information/mountain-information/snow-conditions-and-weather.
National Resources Conservation Service. Open the Interactive Map. Select “Basins Only.” On the map, select “Percent oNCRS 1981-2010 Average,” “Region,” “Watershed Labels,” and “Parameter.” Downloaded 4/2/2018 from https://www.wcc.nrcs.usda.gov/snow/snow_map.html.
Santa Barbara County Flood Control District. Rainfall and Reservoir Summary, 4/1/2018. Viewed online 4/2/2018 at https://www.countyofsb.org/uploadedFiles/pwd/Content/Water/Documents/rainfallreport.pdf.
How are the birds doing? Ever since Rachael Carson revealed in the 1960s that pesticides were decimating bird populations, how the birds are doing has been an important question. DDT was the worst-offending pesticide, and it was soon banned, but other chemicals and other factors affect the ability of birds to survive. These days, the most important may be habitat destruction, competition from invasive species, and the effects of other chemicals, such as lead.
Many, many bird species migrate. Those that do require habitats along the way where they can rest and refuel. Break the chain of habitats in even one place, and you seriously harm the ability of the birds to survive.
The largest and most important survey of bird populations is the Breeding Bird Survey, which has been conducted every year since 1966. Here’s how they conduct the survey: during peak breeding season, starting 1/2-hour before sunrise, volunteers follow a route with 50 stops, each stop at least 1/2 mile apart. The route stays the same from year-to-year. The volunteer counts all birds of that species seen or heard within a quarter mile of the stop. Figure 1 shows a map of the routes. The routes look like blue dots because of the scale of the map. You can see that coverage of the USA is quite good.
From the multiple routes in each geographical area, for each species a yearly index is constructed. These indexes represent “the mean count of birds on a typical route in the region for a year.” (USGS, Patuxent Wildlife Research Center)
The results are mixed, differing from species-to-species and from region-to-region. As you might expect, even though the routes have 50 stops on them, and the method used is quite rigorous, it is not the same as physically being able to count every bird. Some of the birds may not be calling when the volunteer is there, or they may be hidden in brush, etc. The survey method does not permit a calculation of the absolute number of birds in a region, and the annual index is only reliable if a sufficient number of birds are observed. Thus, the Breeding Bird Survey provides crucial data, but it may be only part of the picture.
Trend data on how the annual indices for each species have changed is available for every species and for every state and region. I shall focus only on observations in Missouri. Table 1 shows the data. The trends are reported from 1966-2015 and from 2005-2015. The trends represent the annual rate of change over the period of interest.
(Click on table for larger view.)
The table is a bit complex, so let’s unpack it. It shows all species observed in Missouri. They are listed in order of the change between 1966 and 2005, with species that declined on the left side, and species that increased on the right. Each side of the chart begins with 4 columns intended to comment on the quality of the data for a given species. They are coded “G”, for green, or good, “Y” for yellow, or caution, and “R” for red, or extreme caution. The first column comments on the credibility of the measurement. The second column comments on the size of the data sample. The third column comments on how precise the measurements are. The fourth column comments on the relative abundance of the species.
The trend statistics follow the names of the species, and they are color-coded with green and red bars, representing the size of the change. Readers of this blog know that time series are vulnerable to year-to-year variation, but the fact that these are trends computed over the entire period of measurement should minimize that effect.
Between 1966 and 2015, annual indices for 58 bird species decreased, while 79 increased. If one counts only species for which the Regional Credibility Measure was “G,” then the situation is reversed: 40 species decreased and 31 increased.
Those with declines of more than 5% were the blue-winged teal, the loggerhead shrike, the house sparrow, and the American bittern. The blue-winged teal declined at a rate of 18.1% per year, however the Regional Credibility Measure for that species is red, indicating that use and interpretation of the data for that species warrants extreme caution. The same is true for the American bittern. The Regional Credibility Measures for the loggerhead shrike and house sparrow, however, are good.
Because 1966-2015 is a 49 year period, even small annual changes can accumulate to rather significant changes across the entire period. Any decline of 1.4% per year over 49 years would result in a 50% decline over the whole period. The loggerhead shrike, for which the Regional Credibility Measure is “G,” declined at an annual rate of 6.68% per year. Over 49 years, that computes to a decline of 97%!
Among the success stories are some birds that are everybody’s favorites: bald eagle observations increased almost 40% per year, great egret observations increased almost 11%, and cedar waxwing observations increased almost 9%. With the bald eagle and great egret, however the Regional Credibility Measures are red, again indicating extreme caution in using and interpreting the data, and for the cedar waxwing it is yellow.
These findings reinforce what was stated above: the Breeding Bird Survey provides crucial data, but it may not be a complete picture.
Missouri is home to 9 federal wildlife refuges and hundreds of state conservation areas. All are devoted to providing animals and plants the habitat they need to survive. If you visit them on the wrong day, they often look empty, and you can come away wondering what the big deal is. If you visit them on the right day, however, they can be teeming. Figure 2, for instance, shows the afternoon lift-off of a flock of snow geese at Loess Bluffs NWR in northwestern Missouri. The snow geese are only there to rest and refuel for a few days each spring and fall.
Keyserill, Robert. 2017. “Afternoon Lift Off.” Source: U.S. Fish and Wildlife Service. “Loess Bluffs National Wildlife Refuge.” Downloaded 3/18/2018 from https://www.fws.gov/refuge/Loess_Bluffs.
Sauer, J. R., D. K. Niven, J. E. Hines, D. J. Ziolkowski, Jr, K. L. Pardieck, J. E. Fallon, and W. A. Link. 2017. The North American Breeding Bird Survey, Results and Analysis 1966 – 2015. Version 2.07.2017 USGS Patuxent Wildlife Research Center, Laurel, MD. Downloaded 3/14/2018 from https://www.mbr-pwrc.usgs.gov/bbs.
Siolkowski, Dave, Jr., Keith Pardieck, and John Sauer. 2010. “On the Road Again for a Bird Survey that Counts.” Birding, 42, (4), pp. 32-40. Downloaded 3/18/2018 from https://www.pwrc.usgs.gov/bbs/bbsnews/Pubs/Birding-Article.pdf.
United States Geological Survey, Patuxent Wildlife Research Center. Trend and Annual Index Information. Downloaded 3/19/2018 from https://www.mbr-pwrc.usgs.gov/bbs/trend_info15.html.
We know that emitting carbon dioxide into the atmosphere causes climate change. We also know that climate change is causing damage, and that it will cause even greater damage in the future. But how much damage? Can anybody put a dollar sign on the cost?
That is just what a group called the Interagency Working Group on Social Cost of Carbon (IWGSCGG) tries to do. The task is especially difficult because the damage caused by carbon dioxide does not occur when it is first emitted. Carbon dioxide remains in the atmosphere for 80-100 years, and it continues to cause global warming the whole time it is there. The damages from carbon dioxide emitted today will continue to accrue over the entire 80-100 years. As the concentration of carbon dioxide in the atmosphere continues to rise, climate change will accelerate, and the damage it causes will increase. Thus, a metric ton of carbon dioxide emitted in 2050 is expected to cause more damage than a ton emitted in 2010.
First the numbers, then some background on what it means. The IWGSCGG uses several different methods to estimate the future costs of carbon emissions. Then they average the estimates and adjust them for inflation back to 2007 dollars. In calculations of this sort, the assumed inflation rate often has a large effect on the outcome.
In Table 1, the left column represents years in which a ton of CO2 might be emitted. The next three columns each assume a different inflation rate. The column on the far right represents similar information as the 3.0% Discount Average column, except instead of taking the average damage cost estimate, they took the 95th percentile. The idea is that, if inflation is 3.0%, the odds are 95% that the cost of the damage will be no higher than the values in this column.
The 3% discount rate is the one the author’s adopt as their most likely scenario. So, to say this data in plain English:
The most plausible estimate of the damage caused by each metric ton of carbon dioxide emitted into the atmosphere in 2010 is $31. The damage caused by each metric ton emitted in 2015 is $36, and for each metric ton emitted in 2020 it will be $42, and for each metric ton emitted 2050 it will be $69.
Compared to estimates made in 2013, the damages are estimated to be 1-2 dollars less per metric ton.
In 2010, the United States emitted an estimated 5,736.4 million metric tons of CO2. At $32 per metric ton, that equates to $183.6 billion. The GDP of the United States in 2010 was $14,958 billion, so the damage is roughly equal to 1.2% of our total economic output.
Why is this estimate important? Policy makers need to analyze the costs and benefits of the programs they mandate. Avoided future damage is a significant benefit, so they need to estimate how much future cost is avoided. The report suggests that the United States could spend up to $183.6 billion per year to reduce CO2 emissions, and be paid back by the damage prevented.
This report is an update of the second IWGSCGG report, issued in 2013. The cost estimates changed between reports because of increased knowledge about climate change and improvements in the computer models used to make the estimates. There is still considerable uncertainty here, but the IWGSCGG estimate may be the best estimate available.
Interagency Working Group on Social Cost of Greenhouse Gases. 2016. Technical Support Document: – Technical Update of the Social Cost of Carbon for Regulatory Impact Analysis – Under Executive Order 12866. Downloaded 3/20/2018 from https://19january2017snapshot.epa.gov/sites/production/files/2016-12/documents/sc_co2_tsd_august_2016.pdf.
For U.S. greenhouse gas emissions: EPA > Climate Change > Emissions > National Data, http://www.epa.gov/climatechange/ghgemissions/usinventoryreport.html.
For U.S. GDP: Bureau of Economic Analysis > National Economic Accounts > Current Dollar and “Real” GDP (Excel Spreadsheet). http://www.bea.gov/national/index.htm#gdp.
In the United States, 133 billion pounds of food were wasted in 2010.
In the USA, 133 billion pounds of the food supply available at the retail and consumer levels in 2010 went uneaten, according to a report from the U. S. Department of Agriculture. The total available food supply was 430 billion pounds, meaning that 31% of the food was lost. Retail losses represented 43 billion pounds, while consumer losses represented 90 billion pounds. The data is shown in Figure 1.
The total amount of food represents represents about 387 billion calories (Technically, kilocalories. In common speech, when we refer to “calories,” we are actually referring to “kilocalories.” In the rest of this post I’m going to follow common usage, and use “calories” to refer to “kilocalories.”) The report translates this to 1,249 calories per person per day, which is about half of a person’s daily caloric requirement.
These statistics have a humanitarian implication. There are many factors that would complicate attempts to deliver the wasted food to those who need it, but it would feed a lot of hungry people.
Food waste can also be thought of from an environmental perspective. Food waste constitutes about 14% of the total waste stream in America. After recycling products are separated out, it represents the largest category of waste going into our landfills: 21%. (See Figure 2) In addition, though the report doesn’t go into specifics, the growing and transport of food requires the use of energy, the spraying of pesticides and herbicides, the tapping of aquifers for irrigation, problems dealing with animal waste, and the erosion of topsoil, all of which are significant environmental problems. That almost 1/3 of the product produced with these practices is wasted should be a concern to almost everybody.
What are we throwing away so much of? In terms of total pounds of wastage, we throw away more dairy products than anything else (25.4 billion pounds), and vegetables are a close second (25.2 billion pounds). In terms of the percent of the available food supply that gets wasted, sugars and sweetners top the list (41%), followed by fish (39%).
Unfortunately, reducing waste is not so easy, and requires attention at all levels, including the level of the individual consumer. The EPA has published what they call a “food recovery hierarchy,” prioritizing different strategies. (Figure 3) Perhaps the basic first step involves the awareness that wasting food has a humanitarian and environmental cost.
U.S. Department of Agriculture. Estimated Calorie Needs per Day by Age, Gender, and Physical Activity Level. Viewed online 3/3/2018 at https://www.cnpp.usda.gov/sites/default/files/usda_food_patterns/EstimatedCalorieNeedsPerDayTable.pdf.
Buzby, Jean C., Hodan F. Wells, and Jeffrey Hyman. 2014. The Estimated Amount, Value, and Calories of Postharvest Food Losses at the Retail and Consumer Levels in the United States, EIB-121, U.S. Department of Agriculture, Economic Research Service, February 2014. Downloaded 1/3/2018 from https://www.ers.usda.gov/webdocs/publications/43833/43680_eib121.pdf.
Many species have dwindled to the point that their continued survival is an issue of concern. So says the most recent edition of the Missouri Species and Communities of Conservation Concern Checklist. The checklist monitors the status (in Missouri) of:
- 18% of all vascular plants (plants with a specialized system to conduct nutrients throughout the plant, including almost all trees and flowering plants);
- 14% of all non-vascular plants (plants without a specialized circulatory system, including mosses and algae);
- 28% of all vertebrate animals (animals with a backbone, including fish, snakes, birds, rodents, cats, dogs, bear, and deer); and
an unknown percentage of native invertebrate species (animals lacking a backbone, including insects, worms, and shellfish).
Species have become threatened despite the fact that, legally at least, “All native animal species in the State of Missouri are protected as biological diversity elements unless a method of legal harvest, harm or take is described in the Code. All native plant species in the State of Missouri are protected as biological diversity elements only on land owned by the Missouri Department of Conservation.” (Missouri Department of Conservation 2018)
Threatened or endangered species in Missouri are defined as those listed as such by the Missouri Wildlife Code (3 CSR 10-4.111), or the U.S. Endangered Species Act. There are 75 listed in the checklist. They include such notable species as the Peregrine Falcon, the Greater Prairie-chicken, and the Snowy Egret.
There are many, many more species of concern that are not listed in those laws, however. The report lists 1,156 in total. Figure 1 shows the number of species by rank. (Some species carry more than one rank, thus, the total number of rankings is larger than the total number of species on the list.) Some of these species may exist in other parts of the country or the world, but some are (were) unique to Missouri.
Plants and animals tend to group together into communities where the species each fit into a niche that contributes to the health of the whole community. Weaken one and you weaken the whole community. Because Missouri’s landscape is fractured into relatively isolated ecosystems defined by soil type, sunlight, and the presence (or absence) of water, the state is home to many unique, but small communities of this kind. Many of Missouri’s threatened species live in such communities. Eighty-five such communities have been identified by the Missouri Department of Conservation. Of them, 24 are listed as imperiled (28% of the total), and 17 more are listed as critically imperiled (20% of the total). Together, that means 41 are either imperiled or critically imperiled (48% of the total). (Figure 2).
Consolidated State Rules of Missouri. 2017. 3 CSR 10-4.111, Wildlife Code, Endangered Species. Viewed online 2/15/2018 at https://www.sos.mo.gov/adrules/csr/current/3csr/3csr.asp.
Missouri Department of Conservation. 2018. Missouri Species and Communities of Conservation Concern. Publication # SC1077. Downloaded 2/15/2018 from https://nature.mdc.mo.gov/sites/default/files/downloads/2018_SOCC.pdf.
This post will focus on a few articles published recently that highlight effects that climate change is already having around the world. Though the phenomena studied in them occurred far away, they will have important consequences for us here in the USA, and even in Missouri.
Climate Change Causes Migration
Human migration into Europe has become a large political and humanitarian problem. European countries have been struggling to provide the basic services that the migrants need, and to find ways to integrate them into society. The problem of immigration has been one of the forces leading to Brexit, and to the upsurge in right-wing populism around the world (including here in America).
Missirian and Schlenker (2017) studied European asylum applications from 103 source countries, and found that the number of migrants from each country related to the weather in that country. In colder countries, when the temperature decreased, asylum applications increased. Conversely, in hot countries, when the temperature increased, asylum applications increased, and they did so in a non-linear fashion – small increases in temperature could lead to large increases in applications. Far more migrants have come to the EU from hot countries (Africa, the Middle East) than from cold countries, thus the temperature increase is the more important effect.
Holding everything else constant, Figure 1 shows the predicted increase in asylum applications by change in temperature. The red line shows the predicted increase, the shaded areas show the 90% and 99% confidence intervals. The blue line at the top should be read against the right vertical axis, and it represents the probability that asylum applications will increase. The more temperature increases, the more asylum applications are predicted to increase. Under the high emissions scenario, by the end of the century, applications are predicted to increase by 188%.
The study didn’t include migration into the USA from countries south of our border, but I suspect that the basic findings would apply here, as well. In fact, I already reported (here) that in 2014 the CNA Military Advisory Board concluded that climate change would become one of the most significant threats to national security faced by our nation. Climate change would lead to increased migration around the world, which would lead to political instability, which would cause conflicts to break out. Given the difficulty that Europe is having coping with the current problem, and that the problem could nearly triple in size by the end of the century, the Military Advisory Board’s conclusion doesn’t seem too far off. (May, 2014)
The Shrimp Are Gone From Maine
Northern Shrimp are a species of shrimp that require cold water in order to spawn. Maine has been the southern limit of their historical habitat, and they have represented a small but valuable fishery for New England states. Since 2012, the total biomass of shrimp estimated by the Gulf of Maine Summer Shrimp Survey have been the lowest on record. (Figure 2) Managers have closed the waters to shrimp fishing from 2014-2018 in an attempt to prevent shrimp from being completely eliminated from Maine waters. (Atlantic States Marine Fisheries Commission, 2017)
The primary cause of the decline is climate change. Ocean temperatures in the Gulf of Main have increased at a rate of about 0.5°F per year – that is incredibly fast, almost 8 times faster than the global rate. Figure 3 shows the data. The blue lines show the 15-day average water temperature anomaly in the Gulf of Maine from 1980 to 2015. The black dots show the average annual temperature anomaly, and the dashed line shows the trend over the whole time period. The red line shows the trend for the decade from 2005 to 2015.
It is easy to see that the ocean has been warming. The shrimp don’t spawn well in the warmer water, so they are dying out. (Evans-Brown, 2014)
The warmer temperatures have affected more than shrimp. As temperature has increased, cod have also declined, to the point that they are now commercially extinct in the New England fishery. With the cod, a failure to recognize the effect of global warming caused fishery regulators to keep the permitted catch at a high level that could not be sustained, and they were basically fished out out existence. The moratorium on shrimp fishing is an attempt to prevent a similar occurrence. (Pershing et al 2015)
Fishing, especially off New England, was the first colonial industry when Europeans came to America. Over the past century, several species have collapsed and no longer support viable commercial fishing: Atlantic halibut, ocean perch, haddock, and yellowtail flounder. These once fed millions of Americans. No more. Even the venerable Atlantic cod, once so numerous that it was said you could walk from America to England stepping on their backs, are commercially extinct. We are killing the oceans. More below. (NOAA Fisheries Service, 2017)
Global Warming Is Ravaging Coral Reefs
To live, coral requires a symbiotic relationship with certain species of algae. Coral bleaching occurs when stressful conditions cause the algae to be expelled from the coral, which then turns white. If algae don’t reenter the coral quickly enough, the coral will starve to death.
Before global warming, bleaching events were relatively rare, and reefs had enough time to recover between them. Scientists looked at 100 reefs globally and found that the average interval between bleaching events is now less than half of what it was previously. It is now only 6 years, which is not enough time for recovery. Figure 4 shows the findings. Chart A in the figure shows the number of locations experiencing bleaching events in a given year. You can see that the trend increases left to right, and that the worst years have all occurred in the most recent 2 decades. Chart B in the figure shows the cumulative number of locations that have remained free of bleaching over the time period in blue, and the total cumulative number of bleaching events in red. You can see that, over time, none of the locations have escaped bleaching, and that the number of bleaching events has topped 600. Chart C shows the frequency of bleaching events at individual locations. Almost 30 locations have experienced 3 severe bleaching events, and a similar number have experienced 8 or more bleaching events in total. Chart D counts intervals between bleaching events, and how many times each interval occurred. It used to be (1980-1999) that the most common interval was 10-12 years. Recently, however (2000-2016), an interval of 4-6 years was the most common. (Hughes et al 2018, Pols 2017) Thus, the data show that bleaching has spread to the point that none of the locations escaped it altogether, almost 1/3 of them have experienced 8 bleaching events of some kind, almost 1/3 have experienced 3 severe events, and the most common interval between events has shrunk to half of what it was previously.
The main culprit is global warming. Coral survives only in a relatively narrow temperature band, and if the water temperature rises too high, bleaching occurs. Temperatures have, indeed, risen. As noted above in the section on the Gulf of Maine, in some places they have increased incredibly quickly.
Coral reefs are like oases. In the desert, oases are separated by vast distances where life is scarce. Similarly, coral reefs are often separated by vast distances where life is scarce. Reefs, however, support thousands of species in great abundance. Though the reefs occupy less than 0.1% of the ocean’s surface, they support at least 25% of all marine species. (NOAA Fisheries Service 2018)
These phenomena, though occurring far away, are all signs that the basic systems that support life on this planet as we know it are in danger. If we think that they could not collapse, we are seriously kidding ourselves. They may be collapsing already. If we dream that we will somehow escape being affected, we need to wake up.
Atlantic States Marine Fisheries Commission. 2017. Northern Shrimp Species Profile. Viewed online 2/6/2018 at http://www.asmfc.org/species/northern-shrimp.
Evans-Brown, Sam. “Gulf of Maine Is Warming Faster Than Most of World’s Oceans.” New Hampshire Public Radio. Viewed online 2/6/2018 at http://nhpr.org/post/gulf-maine-warming-faster-most-worlds-oceans.
Hughes, Terry P., Kristen D. Anderson, Sean R. Connolly, Scott F. Heron, James T. Kerry, Janice M. Lough, Andrew H. Baird, Julia K. Baum, Michael L. Berumen, Tom C. Bridge, Danielle C. Claar, C. Mark Eakin, James P. Gilmour, Nicholas A. J. Graham Hugo Harrison, Jean-Paul A. Hobbs, Andrew S. Hoey, Mia Hoogenboom, Ryan J. Lowe, Malcolm T. McCulloch, John M. Pandolfi, Morgan Pratchett. Verena Schoepf, Gergely Torda, Shaun K. Wilson. 2018. “Spatial and Temporal Patterns of Mass Bleaching of Corals in the Anthropocene. Science 359 (6371), 80-83.
Missirian, Anouch, and Wolfram Schlenker. (2017). “Asylum Applications Respond to Temperature Fluctuations.” Science 358 (6370), 1610-1614.
Pershing, Andrew. Michael Alexander, Christina Hernandez, Lisa Kerr, Arnault Le Bris, Katherine Mills, Janet Nye, Nicholas Record, Hillary Scanell, James Scott, Graham Sherwood, and Andrew Thomas. 2015. “Slow Adaptation in the Face of Rapid Warming Leads to Coillapse of the Gulf of Maine Cod Fishery.” Science, 350 (6262), 809-812.
NOAA Fisheries Service. 2017. Brief History of the Groundfishing Industry of New England. Viewed online 2/6/2018 at https://www.nefsc.noaa.gov/history/stories/groundfish/grndfsh1.html.
Pols, Mary. 2018. “It’s Maine Shrimp Season, Without the Shrimp.” New York Times, 12/26/2017. Downloaded 2/6/2018 from https://www.nytimes.com/2017/12/26/dining/maine-shrimp-fishery-climate-change.html.