Natural Cycles of Polar Sea Ice: The Arctic Iris Effect

The Arctic Iris Effect, Dansgaard-Oeschger Events, 

and Climate Model Shortcomings. 

Lesson from Climate Past - part 1.

Dansgaard Oeschger Events and the Arctic Iris Effect

During the last Ice Age, Greenland’s average temperatures dramatically rose on average every 1500 years by 10°C +/- 5°C in a just matter of one or two decades, and then more gradually cooled as illustrated in Figure 1 below (8 of the 25 D-O events are numbered in red on upper graph; from Ahn 2008). These extreme temperature fluctuations between cold “stadials” that lasted about a thousand years and warm “interstadials” lasting decades are dubbed Dansgaard-Oeschger events (D-O events). These rapid temperature fluctuations not only rivaled the 100,000‑year fluctuations between maximum glacial cold and warm interglacial temperatures but D‑O warm events coincided with expanding Eurasian forests (Sánchez Goñi 2008, Jimenez-Moreno 2009), northward shifts of subtropical currents along the California coast (Hendy 2000), and shifts in belts of precipitation in northern South America (Peterson 2001).

Dansgaard Oeschger Events

Just 25 years ago most climate researchers were hesitant to accept initial Greenland ice core evidence suggesting such abrupt D‑O warming events (Dansgaard 1985). But as other Greenland ice cores verified their reality, it was clear that the only mechanism realistically capable of producing such abrupt warming was the sudden removal of insulating sea ice that allowed ventilation of heat previously stored in the Arctic as Dansgaard (1985) had first proposed. Still that begged the question ‘what caused the sudden loss of insulating sea ice’?

Changes in CO2 concentration are unlikely to have had much impact on D‑O events (3^rd graph from the top in Figure 1). CO2 concentrations did fluctuate by about 20 ppm during a third of the D-O events (red numbers), but could contribute directly to no more than 0.4°C to only 30% of the largest warming events.  In contrast during 68% of the other D-O events (not numbered), abrupt warming occurred while CO2 was declining.  Thus rapid warming and cooling seems independent of any CO2 forcing.

Abrupt D‑O warming and cooling suggested to researchers (Broecker 1985) that the Atlantic Meridonal Overturning Circulation (AMOC) turned “on” and “off”. Based on the misleading belief in the existence of a simplistic “ocean conveyor belt” (Wunsch 2007), researchers incorrectly interpreted a lack of deep-water formation as evidence of a lack of warm water flowing into the Arctic. However based on increasing proxy evidence (Rasmussen 2004, Ezat 2014), it is now understood that the inflow of warm Atlantic Waters never “shut off” but continued to enter the Arctic and warmed the subsurface layers. As seen in Figure 2  (from Itkin 2015) the upper layer of fresh water and the halocline insulate the warm Atlantic water from the overlying ice.  Together the thick sea ice and polar mixed layer simply “turn off“ any heat flux from the ocean to the air, thus maintaining cold stadial air temperatures. Furthermore if the salty Atlantic Water cannot be cooled by the cold Arctic air, then North Atlantic Deep Water is shut off as well.

Basic Vertical Structure of Arctic Ocean

Although climate models have failed to simulate D‑O events, models were manipulated to shut off poleward heat transport by prescribing ad hoc floods of freshwater. As long as freshwater “hosing” was applied, the models prevented the cooling and sinking of North Atlantic waters, which shutoff the deep water formation and thus “ocean conveyor belt” resulting in contrived cooling.  That interpretation became the reigning paradigm and researchers began searching for evidence of a flood of freshwater, while nearly every model engaged in “hosing” experiments to explain abrupt climate change. But evidence of the required freshwater flooding has yet to be found and a growing wealth of proxy evidence suggested there was as much freshwater during stadials as there was during interstadials. Even the notion of freshwater floods from an armada of melting icebergs was not consistent with the timing of D‑O events (Barker 2015). Freshwater shutdown of the Atlantic Meridonal Overturning Circulation is most likely just a figment of the models’ configuration.

Other researchers suggested drivers of past and present rapid temperature change were likely to be very similar (Bond 2001, 2005), and recent findings are now supporting that notion. More recent explanatory hypotheses for D‑O events are gaining widespread critical acceptance and do not require any massive floods of freshwater nor a shutdown of the AMOC (Rasmussen 2004, Li 2010, Peterson 2013, Dokken 2013, Hewitt 2015). When sea ice prevents heat ventilation, the inflow of warm and dense Atlantic Waters continues to store heat in the subsurface layers. As heat accumulated, the warm Atlantic Waters became more buoyant, upwelled and melted the insulating ice cover. The loss of an insulating ice cover “turns on” the heat flux causing a dramatic rise in surface temperatures to begin the D‑O interstadial.  Although details of hypothesized D‑O mechanisms vary slightly, they all agree on the ability of growing and shrinking sea ice to affect the heating and cooling of the northern hemisphere. I refer to this sea ice control of heat ventilation the Arctic Iris Effect.

The signature of an Arctic Iris Effect is the opposing temperature trends in the ocean versus atmosphere: when ice is removed, warmer air temperatures coincide with cooler ocean temperatures. When ice returns cooler air temperatures coincide with a warmer ocean. The thicker the sea ice, as during the last Ice Age, the longer the period between ventilations such as the D‑O events. Thick sea ice is less sensitive to small changes in insolation and/or natural variations of inflowing Atlantic Waters. As discussed in Hewitt 2015 decreases in the freshwater layer that separates sea ice from the warm Atlantic Waters are also likely critical contributors to D‑O events. For example as the Laurentide Ice Sheet grew, sea levels fell shutting of the inflow of fresher Pacific water through the Bering Strait, coinciding with an increased frequency between D‑O events from 8 thousand to 1.5 thousand years.

Peterson 2013 suggested that in addition to thick multiyear sea ice, ice shelves were critical for maintaining the longer cold stadials by better resisting small oscillations of increased inflow of Atlantic Water. Likewise with the current reduction of Arctic ice shelves and reduced multiyear sea ice during our present interglacial, much smaller changes in insolation and/or Atlantic inflow could more easily initiate ventilation events. With smaller time spans between each ventilation event, less heat accumulates and warm spikes are more muted (1°C to 2°C) compared to 10°C +/- 5°C during the D‑O interstadials. Over the past 6000 years, decades of rapid ice loss resulted in 2°C to 6°C air temperatures warmer than today quickly followed by centuries of colder temperatures and more sea ice (Mudie 2005).

The 20^th century ventilation events produced only a 1°C to 2°C increase yet the signature of the Arctic Iris Effect is still observed.  In 2001, Dr. Vinje of the Norwegian Polar Institute reported on the opposing temperature effects as ice retreated in the Nordic Seas. Between 1850 and 1900 there was a rapid warming of 0.5°C ocean temperatures between 1850 and 1900 with very little change in atmospheric temperature. Then they reported, “The warming event during the first decades of this century is characterized by a significant decrease in the Nordic Seas’ April ice extent, an increase of ~3°C in the Arctic surface winter temperature, averaged over the circumpolar zone between 72.5° and 87.5°N, and an increase in the Spitsbergen mean winter temperature of as much ~9°C. During this warming event the temperature in the ocean was lower than normal.

An increasing preponderance of positive ice extent anomalies, with an optimum in the 1960s, is observed during the period 1949–66, concurrent with a cooling in the circumpolar zone of ~1°C, a fall in the Spitsbergen mean winter temperature of ~3°C, and an increase in the mean winter air pressure in the western Barents Sea of ~6 hPa. During this cooling event the temperature in the ocean was higher than normal.” [Emphasis Added]

Similarly the most recent Arctic warming again reveals the fingerprint of the Arctic Iris Effect. There was no atmospheric warming in Arctic when there was an insulating cover of multiyear sea ice. Measurements between 1950 and 1990 reported a cooling Arctic atmosphere prompting researchers to publish, “Absence Of Evidence For Greenhouse Warming Over The Arctic Ocean In The Past 40 Years”.  They concluded, “This discrepancy suggests that present climate models do not adequately incorporate the physical processes that affect the Polar Regions.”

Abruptly rapid Arctic warming began in the 1990s with an initial loss and thinning of Arctic sea ice when the Arctic Oscillation’s shifted wind directions and below‑freezing winds from Siberia pushed multiyear ice out of the Arctic. Rigor 2002 correctly pointed out, “One could ask, did the warming of SAT [Surface Air Temperatures] act to thin and decrease the area of sea ice, or did the thinner and less expansive area of sea ice allow more heat to flux from the ocean to warm the atmosphere?” They concluded, “Intuitively, one might have expected the warming trends in SAT to cause the thinning of sea ice, but the results presented in this study imply the inverse causality; that is, that the thinning ice has warmed SAT by increasing the heat flux from the ocean.” [Emphasis Added] That conclusion has been further supported by recent analyses of ocean heat content by Wunsch and Heimbach 2014, two of the world’s premiere ocean scientists from Harvard and MIT. They reported the deep oceans are cooling suggesting the oceans and atmosphere are still not in equilibrium and oceans are still ventilating heat from below 2000 meters that was stored long ago.  Also in their map illustrating changes in the upper 700 meters of the world’s oceans (their Figure shown below), we see the entire Arctic Ocean has cooled between 1993 and 2011, as would be expected from the Arctic Iris Effect. Keep in mind that the warm layer of Atlantic water on average occupies the depths between 100 and 900 meters.

Change in upper 700  meters Ocean Heat Content 1993 t0 2011

The Earth’s Energy Budget

The Earth’s energy budget depends on a balance between absorbed solar radiation and outgoing infrared radiation. While some atmospheric scientists have focused on a possible energy imbalance created by 2 watts/m² generated by rising CO2, widespread regions of the ocean absorb and ventilate over 200 watts/m² of heat each year. As illustrated in Figure 3 (from Liang 2015), the oceans absorb heat (blue shades, in watts/m2) along the equator and over the upwelling zones along the continents’ west coast. Intense tropical insolation and evaporation creates warm dense salty waters that sink below the surface storing heat at depth. Changes in insolation, tropical cloud cover, and ocean oscillations like El Nino affect how much heat the oceans absorb or ventilate. Excess heat absorbed in the tropics is transported poleward. To gain a proper perspective on the importance of heat transport from the tropics to the poles, currently Polar Regions average 30°C colder than the equator. If there was no heat transport, the poles would be 110°C colder than the tropics (Gill 1982, Lozier 2012).

On average, the greatest ventilation of ocean heat happens where heat transportation is most concentrated: along the east coast of Asia over the Kuroshio Current and along east coast of North America along the Gulf Stream. Additionally large amounts of heat are also ventilated over Arctic’s Nordic Seas region, a focal point of the Arctic Iris Effect. A comparison of the temperature changes at varying ice core locations from southeast to northwest Greenland, points to this North Atlantic region as the main source of heat ventilated during each D‑O event (Buizert 2014). Likewise modeling work (Li 2010) shows that reduced ice extent in this region exerts the greatest impact on Greenland temperatures and snow accumulation rates. And it is in this same region that Vinje 2001 reports the greatest reduction in ice cover coinciding with the rapid changes in Greenland’s instrumental data. While CO2 warming would predict the greatest rate of Greenland warming in the most recent decades, the Arctic Iris effect would predict a greater rate of warming in the 1920s because thick sea ice from the Little Ice Age would have caused a greater accumulation of heat. Indeed Chylek 2005 reported, “the rate of warming in 1920–1930 was about 50% higher than that in 1995–2005.”

 

Global Ocean Heat Flux (blue: heat enters ocean, red heat exits ocean) Liang 2015

Climate Model Shortcomings

In 2008 leading climate scientists at the University of East Anglia’s Climatic Research Unit published Attribution Of Polar Warming To Human Influence.  As seen in their graph below, their models completely failed to account for the 2°C Arctic warming event observed from 1920 to the 1940s, (illustrated by the black line labeled “Obs” for observed).  This was a warming event that climate scientists called “the most spectacular event of the century” (Bengtsson 2004). Their modeled results of natural climate change grossly underestimated the 40s peak warming by ~0.8° C, and simulated a flat temperature trend throughout the 20^th century as illustrated by the blue line labeled “NAT” for natural. More striking when the models added CO2 and sulfates, the modeled results (red line labeled all) cooled the observed warming event further. Despite their failure to model natural events they concluded, “We find that the observed changes in Arctic and Antarctic temperatures are not consistent with internal climate variability or natural climate drivers alone, and are directly attributable to human influence.”

However their results only demonstrated that their models failed to account for natural climate change, the Arctic Iris Effect and ventilation of ocean heat during the 1930s and 40s. By all accounts the recent warming of the 1990s and 2000 was likewise a ventilation event that also cooled the upper layers of the Arctic Ocean. The failure to model ventilated heat events led to incorrectly attributing that warming to increasing concentrations of CO2.  That failed modeling further led to explanations that reduced albedo effect allowed greater absorption of summer insolation, warming the Arctic Ocean and amplifying temperatures. But observations show the ocean has cooled.  Like the 40s peak, it is likely 1990s/2000s ventilation similarly contributed a minimum of ~0.8° C to the recent rise in Arctic temperatures, and probably much more as the greater reduction in sea ice extent has allowed for much more ventilation.

Failed Climate Model and Warm Arctic Events

If climates models are correctly configured, they should be able to reproduce both D‑O events and the 1940s ventilation events. We don’t expect model perfection, but turning a massive warming event into a below average cool period is unacceptable.  When the modeling community simulates the Arctic Iris Effect more accurately, only then will their attribution of polar warming to human vs. natural factors be trustworthy! Until then all the natural factors - lower insolation with reduced Atlantic inflow, cooler oceans, negative North Atlantic Oscillation, and increasing multiyear ice – all suggest the current ventilation event will soon come to a close. But the return to cooler surface temperatures and more sea ice has always been much slower than the abrupt warming. When sea ice is reduced, the winds are suddenly able to mix the ocean’s fresher upper layer with the saltier lower Atlantic Waters disrupting the halocline. But once the halocline and upper layers of freshwater are restored, the cooling is rapid.  

In contrast, those who attribute Arctic warming to rising CO2 predict a continued sea ice death spiral. And those who also suggest global warming is slowing down the poleward flow of Atlantic Water, also argue CO2 warming will offset any cooling effects of that slowdown (Rhamstorf and Mann 2015). Within the next 2 decades, nature should demonstrate how well these competing models and competing interpretations extrapolate into the future. Good scientists always embrace 2 or more working hypotheses. But with the politicization of science, I sincerely doubt President Obama is travelling to the Arctic to advise the world to be good scientists!

Plight of the Bumble Bees: How shabby climate analyses and lax peer review promote a dreadful remedy

Bumblebee

 In July 2015 the journal Science published Kerr et al’s Climate Change Impacts On Bumblebees Converge Across Continents. It was a woeful analysis hyped by the media. It did very little to further our understanding of the causes of bumblebee declines and more likely obscured the real problems. But it did illustrate why the public is becoming increasingly suspicious of “scientific claims” regards catastrophic climate change as well as demonstrating the inadequacy of the peer review process.

There were 4 major problems.

1) By employing a skewed statistical methodology and using inappropriate metrics, Kerr 2015 contradicted the biologists’ consensus (Goulson 2015) to argue bumblebees declines are independent of land use changes, pesticides and introduced pathogens.

2) Kerr 2015 results demonstrated that bees are not tracking their climate niche and are not responding to climate changes as predicted. Their data strongly suggests range shifts have been independent of climate change. Either the bees are insensitive to decades of climate change or climate change has had little impact on the bees’ critical microclimates. Nonetheless based on bad statistical modeling, they claimed range shifts were “independent of changing land uses or pesticides”, and then spun a climate catastrophe scenario by simply asserting the default cause must be climate change.

3) Kerr 2015 totally ignored the leading hypothesis that points to introduced pathogens as the cause of sudden declines and shifts in a select group of related North American Bees (Cameron 2014, The Xerces Society 2008). Kerr’s climate interpretation suggests transporting bumblebees to new northerly habitat, knowing it poses greater risks by spreading pathogens and further endangering susceptible species.

4) Kerr 2015 demonstrate that the journal Science strayed from objectivity into climate change advocacy. Science not only failed to properly edit this paper, they added an additional “news” commentary Bumblebees Aren’t Keeping Up With A Warming Planet and quote Kerr’s catastrophic view, “Climate change is crushing species in a vise”. The other global warming advocacy journal Nature ran a simultaneous apocalyptic story “Climate Change Crushes Bee Populations” encouraging wide spread media fear mongering.

1. Kerr 2015’s Inappropriate Statistical Methodology

The first statistical violation was Kerr’s categorization of time periods that prevented their models from accurately detecting the effects of land use change. They analyzed changes in bees’ latitudinal and thermal limits using records for 31 North American and 36 European species. To create a “pre-climate change” baseline for each species, they averaged 5, 10 or 20 extreme observations (depending on availability) for the time period 1901-1974. For example to determine a species’ most southerly latitude, they averaged the 5 most southerly records across the continent. However those averages would be dominated by the earliest decades and could hide any northward retractions that happened in the baseline’s later decades. To determine the bees’ warmest thermal limits, they likewise averaged 5 modeled temperatures from the warmest occupied sites. They similarly averaged observations restricted to 3 later 11-year periods of purported human caused climate change spanning 1975-1986, 1987-1998, and 1999-2010, and then compared those averaged results with the baseline averages.

However their asymmetrical categorization of a 74‑year baseline period vs. three 11‑year “climate change” periods is highly problematic. If their intent was to determine the timing of any significant shifts, their analysis should have compared equal decade-long periods.  Instead because their technique averaged the most extreme southern latitudes, the baseline would easily be dominated by the earliest 20^th century observations. Any range retractions that happened later during the baseline period would not be “statistically detected” until the 1975-1986 “climate change” period. Any editor or peer reviewer should have required a correction, knowing their asymmetrical categorization could cause such misleading results.

Many researchers from both North America and Europe (Fitzpatrick 2007) have documented that the period between 1940-1960 encompassed the greatest shift in agricultural expansion and intensity that has gravely affected bee populations. For example, studies in Illinois (Grixti 2009) determined that the greatest loss of bumblebee abundance, species richness and shifting ranges occurred between 1940-1960 due to agricultural intensification. After 1960, only minimal shifts occurred for the following 2 decades as agricultural expansion waned. But Kerr’s baseline categorization would not detect those range shifts until the 1975-86 period. The resulting statistical illusion of their model then created the incorrect perception that major range shifts were independent of those agricultural changes. 

Kerr’s main paper only provided graphs for the final 1999-2010 period, so in my Figure 1 below, I have also added the 1975-1986 graphs from their supplemental data to also compare the recent decadal shifts. Oddly their results contradict their assertion that landscape restrictions were preventing bees from migrating, and therefore climate change was “crushing bees in a vise”. Their data clearly show half of the European species (green dots) were moving northward while most of the North American species (red dots) were shifting southward. In a NY Times’ interview, bumblebee expert Dr. Sydney Cameron also noted this lack of correspondence between assertions and evidence, diplomatically stating Kerr’s suggestion of thwarted northward migration was “a surprising conclusion given the data.” Clearly the bees are not caught in any such vise. The average shift in latitudinal positions was simply contradicting global warming theory.

Second if the 1940-1960s land use changes were the major driving factor, instead of climate change, we would expect dramatic range shifts in the 1975-1986 period, but only minor range shifts between 1975 and 2010. In contrast if climate change was the driver, we would expect increasing range shifts between 1975 and 2010 as purported climate change intensified. The data does not support a climate change interpretation.

The 2 graphs on Figure 1’s left (A’s) illustrate shifts in each species’ average extreme northern latitude, while the 2 graphs on the right (C’s), illustrate the change in their southern extremes. The X-axis represents the species latitudinal extremes in terms of distance (kilometers) from the equator during the base-line period. (Figure 2 helps the reader visualize the geographic location for those distances.) The Y-axis represents the species latitudinal deviation from the baseline period. A positive number means the species’ extreme latitude shifted northward and a negative number means it shifted southward. The dashed line at “0” represents the 1901-1974 base line latitude. Species that have not shifted their latitudinal margins will be located on that dashed lines.

For example, I added blue arrows to highlight that one European species’ northern-most latitude, originally located about 6400 km north of the equator (X-axis), had already shifted northwards by 1000 km (Y-axis) by the 1975‑period. Assuming the second arrow points to the same species, there was no further shift through the 1999-2010 period, suggesting no effect from recent climate change. Readers should also note that a majority of the species on both continents had retracted their northern limit southwards by the 1975-1986 period, again the opposite of what global warming predicts. By 1999-2010, half the species still exhibited ranges that had retracted southwards, although there was a slight increase in species that expanded northward.

 

Bumblebee northern and southern extreme range changes

The graphs on Figure 1’s right side represent shifts in the species most southerly margins. Again the bees are shifting differently on each continent, suggesting regional drivers, not global climate change. Because Kerr’s graphs have a different scale, I added a blue line to highlight any northerly retraction exceeding 400 km.  By the 1975-period (top right), nearly all the North American species (red dots) had already retracted their southern range northward to some degree. By the 1999-2010 period, the greatest North American retraction remained at 1000 km, while 3 species expanded their range southward, again contradicting a global warming interpretation. The remaining North American latitudinal shifts are not noticeably different between 1975 and 2010. Furthermore, it should be noted that any retractions in the southeast USA are probably not linked to global warming because most of that area has been deemed a “warming hole” with a 20^th century cooling trend for maximum temperatures (see Fig 13 Menne 2009).

In Europe (green dots), half the species had expanded southward by the 1975-1986 period again contradicting global warming theory. By the 1999-2010 period more species began retracting northwards while the 2 most northerly species move southward retracing their earlier retractions. Because some declining species have shifted northwards while others shifted southward, most European researchers had rejected the hypothesis that climate change has been driving declining bee populations. (Willliams 2007)

Unfortunately from Kerr’s results, we cannot determine which dot represents which species, and thus we are prevented from using additional research that might elucidate why an individual species shifted its range when another species did not. Meta-analyses such as this only create average trends from a lumped set of species but typically obscure the variety of confounding factors that may be driving these diverse and complex range shifts. Yet such meta-analyses are often the preferred method for researchers advocating climate change disruption because they assume the variety of confounding factors cancel out, leaving only a climate change footprint (Dr. Singer, personal communication) A problematic IPCC meta-analysis is discussed here.

In addition to skewed temporal categories, Kerr 2015 used an inappropriate metric to dismiss land use changes. Kerr compared recent satellite data with past characterizations of the landscapes to determine changes in cropland and pasture extent. But extent, or acreage, is not the only land use factor that could impact bees. The major factor is the loss of flowers.

Due to cheaper synthetic fertilizers, many croplands no longer plant crops of bee-nourishing alfalfa to rotate with crops of wind-pollinated corn or wheat. Planting alfalfa had partially offset the loss of flowers when native grasslands were cultivated. Additionally pastures and grasslands are managed to reduce insect pollinated flowers and promote more wind‑pollinated grasses.

Furthermore methods for producing silage have increasingly replaced traditional hay‑making. Traditional hay‑making requires a good stretch of dry weather that lowers the hay’s water content, so mowing typically occurs in late summer. In contrast silage fermentation requires greater water content than hay, so fields are mowed earlier and sometimes more often. Earlier mowing removes nourishing flowers so bee species that emerge later in the season from “hibernation” are critically impacted (Fitzpatrick 2007). Additionally wind-pollinated corn has increasingly become a major source of silage replacing alfalfa and soybean.

These agricultural practices have increased production over the past few decades without cultivating more land, so those land use changes would not be detected as changes in cropland or pasture “extent”. But those changes most certainly impact bees.  Again any editor or peer-reviewer familiar with the plight of the bumblebees should have been aware that “extent” was likely a meaningless metric. Yet by using the “extent” metric, Kerr’s models incorrectly asserted that landscape changes had no impact, contradicting a wealth of research demonstrating a heavy toll by landscape changes.

 

Latitude in terms of kilometers north of equator

Still Kerr schizophrenically embraced landscape changes to help explain why so many bee species had contradicted climate change theory by shifting to lower elevations (Figure 3 below). Bees that moved to higher elevations were touted as confirmation of climate change induced shifts. But to dismiss the contradictory evidence, Kerr 2015 nebulously suggested global warming could increase forest growth at higher elevations and that resulting landscape change could eliminate bee habitat thus forcing bees to lower levations. But that begs the question of why half the bees still migrated to higher elevations. Reforestation may eliminate some warm sunny bee habitat, but in Europe the dominant cause of reforestation has been the abandonment of marginal farmlands (Gehrig-Fasel 2007). Furthermore the downward shift in elevation seen in Europe’s high latitude bee species is consistent with Scandinavian tree ring data that suggests temperatures have been cooler since the 1950s (Esper 2012). In agreement with “cooling” tree rings, many butterflies in Finland that had expanded northward during peak warming of during the 1930s to 50s, have also retreated southward. (Poyry 2009).

 

Bumblebee Elevational Changes

In North America, many bee species have also moved to lower elevations in the most recent decades (Figure 3) and this is consistent with shifts to lower elevations by several other species. In the United States vegetation in the Sierra Nevada has been moving down‑slope (Crimmins 2011). Montane butterfly populations that Parmesan claimed had gone extinct due to global warming have now returned and there is no longer a statistical shift to higher elevations (discussed here). A high percentage of newly discovered pika populations have been observed at much lower elevations than had been observed during the 1920s (discussed here). And mirroring bumblebees’ shifts, 20% of California’s bird species have moved upslope, while 20% moved down‑slope while most have not shifted at all during the 20^th century (Tingsley 2012).

2. Bumble Bees Move Independently of Climate Change

Assuming that species are in equilibrium with their environment, ecologists infer a species’ temperature tolerances based on the most extreme temperatures throughout their range and then construct a bioclimatic envelope. However the usefulness of bioclimatic envelopes has been increasingly debated (Hampe 2004) and Kerr’s data demonstrates why. Theory predicts that if a habitat warms or cools, species must shift in order to remain within their temperature envelope’s boundaries. In Kerr’s graph below (Figure 4), the dashed line, at zero on the Y-axis, represents each species’ baseline limit for cold temperature tolerance (Fig. 4’s graphs on left, B’s), and for warmth tolerance (graphs on right, D’s).

Bumblebee Changes in Extreme Temperature LImits

If a species’ range tracked its thermal limits, its representative dot would sit on the dashed line. Any dot above that line means they have retreated to warmer habitat. Any dot below the dashed line means the species retreated to cooler habitat. The X-axis represents the species thermal limit determined by the base line period. For example, for species’ extreme cold limits, several species persisted in regions experiencing winter extremes of  -10°C during the base line period (X-axis).  But during all the later periods, the coldest temperatures experienced by most species were 2 to 6 degrees warmer, (-8 to -4°C). So the bees are said to be lagging climate change because they are remaining in warmer regions.

Regards the bees’ extreme warm limits, the opposite is happening for most species. Nearly all of North America’s species (red) retracted their range by 1975 and inhabit much cooler regions than required by their bioclimatic envelope. Those bees now inhabit regions where maximum temperatures are 1 to 12 degrees cooler than their baseline period. In contrast, many European species expanded into warmer regions although the majority also retracted to cooler areas. With few species sitting on the dashed line, the data clearly shows most bee species are not tracking climate change and have shifted their ranges independently of calculated thermal limits. An alternative interpretation would argue the baseline observations never accurately defined the bioclimatic envelope. Whatever the case, clearly factors other than climate were forcing bees to alter their thermal ranges.

3. Failure to Address Pathogen Spillover Hypothesis

In North America a few closely related species in the same subgenus began a rapid decline in the late 90s. Abundance declined by up to 96% and geographic ranges contracted by 23‑87%, mostly within the last 20 years (Cameron 2011). Species once designated as abundant or common, declined to being rare or absent in just 7 to 10 years. In addition to the rapid decline, only certain species were affected while others remained abundant. So many researchers rejected climate change as a causative factor and suggested the importation of a novel pathogen was the likely cause (Thorp 2008). Commercially grown bumblebees were being transported around the world, and in the late 90s North American native bees, were reared for commercial purposes in European facilities and then re-introduced to America. Those species are believed to have been infected by a novel pathogen that they introduced to North America. One species, Bombus occidentalis that widely inhabited western North America, began a sudden sharp decline at the same time commercially raised B. occidentalis populations in greenhouses were also exhibiting declines due to the parasite Nosema bombi. Shortly thereafter two other closely related bee species began to rapidly decline. By 2010, over 60 top bee biologists petitioned the USDA’s Animal and Plant Health Inspection Service to regulate the commercial bumblebee industry to ensure transported bees were disease free.

Although the specific strain of pathogen driving these observed declines has not been determined with full certainty, there has been growing support for the pathogen hypothesis as declining species are observed to harbor heavier pathogen loads than stable bee populations (Cameron 2011, Szabo 2012, Colla 2006, Malfi 2014).

Understanding and preventing the spread of deadly disease should be a major societal focus because it severely affects all species. Introduced pathogens wreaked havoc in the Americas ever since Europeans brought smallpox to the western hemisphere and decimated Native American populations. More recently, an introduced chytrid fungus has inflicted a wave of global amphibian extinctions. An introduced European fungus is now  decimating eastern USA bats. In the 80s, scientists were transporting the African Clawed Frog around the world to use in pregnancy testing and embryological studies. The African Clawed Frog harbors the deadly chytrid but is unaffected by it and so served as a carrier. As the fungus was inadvertently spread to new environments, susceptible species like Costa Rica’s Golden Toad and other closely related species rapidly went extinct. While ecologists embarked on efforts to minimize the spread of the disease and save the most vulnerable amphibian species, one of the IPCC’s specially selected biologists, Alan Pounds, denigrated those efforts because he falsely believed the extinctions were a result of catastrophic climate change (discussed here). He oddly argued that by blaming the pathogen, scientists were redirecting the public’s attention from addressing a speculative CO2 climate catastrophe. But Pounds’ remedy, reducing our carbon footprint, would never have stopped the spreading disease, nor saved a single frog and CO2 advocates were hindering the development of real solutions. Likewise controlling our carbon footprint will do precious little to remedy the plight of the bumblebees.

Not only does Kerr 2015 completely ignore the devastating impacts of introduced pathogens, their climate change remedy argues for transporting species northward into habitats where global warming models suggest species should have shifted. In contrast, in a NY Times interview, bumblebee expert Dr. Sydney Cameron took issue with Kerr’s suggestion that we should intervene with “assisted migration”, because that remedy risks spreading pathogens.

Dr. James Strange added. “I did not come away convinced that climate change is causing these movements.” Strange also worries that Kerr 2015 might cause people to blame climate change entirely for bee population destruction and ignore potential factors such as parasites, pesticides and habitat destruction. “There’s a bit of me that’s nervous someone will pick this up and say ‘They figured it out: It’s climate change,’ ” Dr. Strange said. “But really, we haven’t figured it out yet.”

Indeed Dr. Strange should be concerned. If there is anything we have learned from the Golden Toad extinctions, Edith’s Checkerspot extirpations, or the Emperor Penguins, advocacy for CO2 caused catastrophic climate change has blinded people from all walks of life to the more urgent conservation issues.