Breeding Success at the Range Margin of a Desert Species: Implications for a Climate-Induced Elevational Shift

Species are limited to specific geographic area by historical contingency and an interaction between extrinsic abiotic and biotic factors and intrinsic dispersal abilities and adaptive traits. Species-occupied areas immediately adjacent to species-absent territories are defined as range margins, which often are associated with poor quality habitat and declining species fitness (reproductive success) and therefore a lower population density. However, if limiting environmental conditions change at a range margin, the distributions of species may expand or retract in response to that change. Hargrove and Rotenberry 2011 investigated whether the breeding success and the abundance of the desert species Amphispiza bilineata, the black-throated sparrow, was reduced at its range margins and if these reductions were linked to a potential climate-induced elevational shift. The authors compared the abundance and breeding success (at the nest level, territory level, and population level) of A. bilineata at two spatially separate sites over a period of three years. The first site was a mesic environment (characterized by chapparal vegetation) within the sparrow’s upper elevation margin. It was located near site two, a desert habitat (characterized by desert scrub vegetation) at lower elevations that was more commonly occupied by the sparrow. The results show that although sparrow abundance was greater at the drier site, the species’ reproductive success at the mesic site significantly outperformed the reproductive success of the sparrows inhabiting the drier site during the two driest years of the study. However, the reproductive success of the birds inhabiting the desert scrub environment improved during a year with higher precipitation levels. Despite these observations, there was little indication of an upward elevational shift in the sparrows’ distribution over a 26-year period although a warming trend and drier conditions were observed, suggesting the presence of an “ecological trap” within the system. Ultimately, this “ecological trap” could prevent or delay sparrow climate-induced range shifts.—Megan Smith

Hargrove, L., and John T. Rotenberry, 2011. Breeding Success at the Range Margin of a Desert Species: Implications for a Cliamate-Induced Elevational Shift. Oikos 120: 1568–1576.

The black-throated sparrow (Amphispiza bilineata) breeds territorially throughout the desert of the southwest United States and northern Mexico. It is non-territorial in winter. The study area was located at the species’ western range margin in San Diego County, California. There, the Peninsular Mountains create a rain barrier to the eastern Colorado Desert. There is a strong ecological gradient that varies with elevation along the eastern slopes of these mountains. This ecological gradient is also correlated with temperature and precipitation. Within this area, the sparrows are abundant in desert habitat east of the Peninsular Mountains but are rare or absent at higher elevations and coastal areas. The species’ distributional margin occurs along a plant community transition at mid-elevation between desert scrub and chaparral.
Large-scale sparrow distributions and abundance were calculated using point counts at 90 locations along the full elevational gradient (150–1850 m in elevation over a distance of 30 km) from desert scrub to chaparral vegetation. Point counts lasting 15 minutes were conducted between the 2005–2008 breeding seasons. They were repeated 2–3 times a year using distance sampling with a single observer. The relationship between mean birds per point count and elevation was compared using statistical analysis. Local-scale bird abundance and breeding activity was recorded by establishing 10 study sites along the margin of the sparrows’ distribution limits at 1150–1450 m and 6 study sites in lower-elevation desert scrub at 150–650 m. The higher elevation sites were characterized by chaparral vegetation while the lower elevation sites were characterized by desert scrub. Mean distance between the desert scrub and chaparral sites was 13 km, while mean within-habitat distance of sites was 6.7 km. The study sites were approximately 24 ha in area (1200 X 200 m). Local-scale bird abundance was estimated based on territory density estimates at each of the 16 sites using weekly territory mapping during the breeding seasons. The locations of birds and their behaviors were plotted weekly and territories were identifiable based on male singing and aggressive interactions exhibited with neighbors and pairs that foraged closely together. Territory density was calculated for each study site as the maximum number of territories at any point in time. A territory was defined by the presence of a single male during three consecutive weeks. Differences between desert scrub and chaparral sites were tested using a statistical analysis.
Breeding success was calculated by conducting weekly censuses and nest monitoring at each of the 16 study sites during the breeding seasons of 2005–2008. Breeding activity was monitored for each territory from vantage points that were unlikely to cause disturbance. The locations and numbers of all adults and fledglings were mapped weekly at each study site, and all nesting activity was monitored. Survival probability was estimated daily through nest checks. Nests were avoided if they were being constructed or if sparrows were laying eggs. Clutch size and final nest outcome were estimated if possible. Additionally, the authors calculated an index of relative productivity using the fledgling ratio (proportion of total fledglings relative to adults across the season) based on weekly observations of adult and fledgling numbers. Fledglings were identified through begging calls and by visually observing their limited movement. Tail length and mobility were used to approximate fledgling age.  Differences in fledgling ratios between desert scrub and chaparral sites were tested using statistical analyses.
A site-specific breeding index was generated by scoring each territory based on the highest stage of progression observed during the breeding season: 1) territorial male alone, 2) adult pair, 3) nest construction, 4) nest with eggs, 5) nest with nestlings, 6) fledglings, and 7) fledglings plus a second nest attempted. Differences in territory breeding index scores were tested using a statistical analysis. Mean clutch size was estimated using nests for which the final clutch size was determined with certainty. Daily nest survival probability was estimated using nests for which the final outcome was known. A maximum-likelihood estimate of daily nest survival probability for each habitat type and year assuming constant daily survival rate was generated using Program MARK, version 5.1. Differences between the two vegetation sites for clutch size and daily nest survival probability were tested using statistical analyses.
The authors used weather data from PRISM Group, Oregon State University to create an approximation of environmental conditions during the study period. This data was compared to 40-year means. The cumulative precipitation during the July to June rain-year, and the mean monthly minimum and maximum temperatures during spring months (March to June, when nesting occurred) were calculated for each site.
Hargrove and Rotenberry found that between 2006 and 2008, the mean monthly maximum temperature during the spring season was 16.2°C greater at the lower-elevation desert scrub sites compared to the higher-elevation chaparral sites, and that the mean minimum temperature was 8.5°C greater at the desert scrubs sites. Over a period of 40 years, the mean monthly maximum temperature in spring increased 2.4°C at the low-elevation desert scrub sties and 2.7°C at the higher-elevation chaparral sites while the mean monthly minimum temperature in spring increased 0.4°C at the low elevation desert scrub sites and 2.1°C at the higher elevation sites. Precipitation levels were lower at the low-elevation desert scrub sites in comparison to the higher-elevation scrub sites. Across the three years of the study, the desert scrub sites experienced 79% less precipitation than the chaparral sites. All the sites and years between 2006 and 2008 were below the 40-year precipitation means. In 2007, the area experienced record drought conditions while 2008 came close to the 40-year mean precipitation levels. A figure displaying the cumulative precipitation during July to June rain-year at desert scrub sites and chaparral sites between 2006 and 2008 was constructed.
The authors also found that mean black-throated sparrow abundance declined toward the upper elevation margin across all three years of the study. Overall abundance was 157% greater in the 150–650 m elevation range (desert scrub sites) than in the 1150–1450 m elevation range (chaparral sites). Sparrows were absent from the 1450–1850 m elevation range. Similarly, territory density between 2006 and 2008 was 81% greater at desert scrub sites than at chaparral sites. A figure displaying the mean black-throated sparrow abundance along the elevation gradient was constructed.
The results show that productivity (ratio of fledglings) was greater at the chaparral study sites across all three years. The most productive year was 2008 followed by 2006, with 2007 being the least productive year. No fledglings were observed at the desert scrub sites in 2006 or 2007, demonstrating a 100% reproductive failure at these sites during the two driest years of the study despite the greater density of birds found at these sites. However, in 2008 (the wetter year), the fledgling ratio was equivalent to the fledgling ratio found at the chaparral sites in 2008. Breeding success measured at the territory level was significantly lower at desert scrub sites than at chaparral sites between 2006 and 2008. The breeding index three-year average at chaparral sites was 4.0 while the breeding index in 2006 and 2007 for the desert scrub sites were 2.4 and 2.0, but was 5.1 in 2008. There were a small number of nests at the desert scrub sites in 2006 and 2007. Although clutch size and daily survival probability could not be estimated in 2007 for desert scrub sites, the authors proposed that the overall pattern was similar to other breeding success measures, suggesting a reduction in both clutch size and nest survival probability at desert scrub sites in the two driest years (2006 and 2007). A reversal of that pattern was seen in 2008. Clutch size was greater at chaparral sites than at desert scrub sites in 2006, but there was no difference between sites in 2008. Lay dates were earlier at desert scrub sites than at chaparral sites. A figure displaying the territory-level breeding success of black-throated sparrows at deserts scrub and chaparral sites between 2006 and 2008 was constructed.
Within southern California, the desert regions are predicted to become warmer and drier within the next 100 years while events such as floods and droughts are expected to increase. Therefore, if the sparrows breeding success improves at the distribution margin, breeding distributions are expected to expand unless there are other fitness-related factors interacting within the system. However, although sparrow-breeding success was greater at the upper elevational margin (since drought was the probable cause of reduced reproduction at the desert scrub sites), the birds showed little sign of any upward shift in their elevation distribution. Higher sparrow abundance persisted at the desert scrub sites even during the direst years of the study and the upper elevational limit did not experience a shift either. The authors additionally did not find evidence for an upward elevational shift for the sparrows at another site despite strong warming trends and drier conditions.
Hargrove and Rotenberry proposed that the sparrows’ observed stasis could be attributed to tradeoffs—such as increased survival rates at lower elevations—that increase overall species fitness within the desert scrub habitat. Additionally, the life-history strategy of the sparrow may explain its range stasis. For example, the sparrow species could take advantage of wet years for reproduction while reproductively stagnating during dry years. Finally, desert scrub habitat may have a greater suitability historically for the black-throated sparrows, indicating that the species has evolved a preference for desert scrub vegetation over that of chaparral. Therefore, the greater density of sparrows at sites with reduced reproductive success that are close to sites with lower density and greater reproductive success signals the presence of an ecological trap for this species. Ecological traps can drive a population to extinction and occur when low-quality habitat is preferred over high quality available habitat. So, even if marginal areas have greater climatic suitability, sparrows may still retain an inherited preference for less-suitable central habitat, leading to their extinction. Ultimately, the local biotic interactions of these sparrows outweigh the effects of climate change, thereby inhibiting range shifts. 

Gray-Brown Mouse Lemurs (Microcebus griseorufus) as an Example of Distributional Constraints through Increasing Desertification

Anthropogenic climate change may threaten endemic species commonly found in biodiversity hotspots around the world. One endemic species of particular concern is the Gray-Brown Mouse Lemur (Microcebus griseorufus), a primate species found in Madagascar—a biodiversity hotspot. Currently, climate change is increasing rates of aridity and desertification within the lemurs’ habitats. These climatic changes may affect the species’ end-of-the-wet-season food supply, an important resource that primarily contributes to their survival during the harsh, dry season. Therefore, to assess the impacts of aridity on lemurs and to identify factors that could inhibit the species’ distribution and range expansion under dry conditions, Bohr et al. (2011) compared two populations of lemurs in adjacent habitats that differed in humidity levels. They measured differences in lemur abundance, body mass, body condition, and food type abundance between the two sites, and also determined lemur distributions and feeding patterns. The authors found that the more humid site produced more high-quality food and maintained a higher population density of Microcebus griseorufus, with individuals in better condition compared to the drier site. The results showed that at the end of the wet season, the lemurs adjusted their home range size to local food plant density, indicating that lemurs modify their food intake at the end of the wet season to prepare for the dry season.  A negative, exponential relationship between food plant density and home range size also demonstrated that lemurs had an upper limit for the size of their home ranges. Therefore, primates from the drier habitat were unable to compensate for their reduced food availability by expanding their home range beyond this upper limit. Unfortunately, although lemurs would have the ability to migrate to mesic habitats under drier climate scenarios in search of food, habitat fragmentation in Madagascar could significantly reduce the lemurs’ ability to do so.—Megan Smith
Bohr, Y.E.M.B., Giertz, P., Ratovonamana, Y.R., Ganzhorn, J.U., 2011. Gray-Brown Mouse Lemurs (Microcebus griseorufus) as an Example of Distributional Constraints through Increasing Desertification. International Journal of Primatology 32:4, 901–913.

Microcebus griseorufus occured in southwestern Madagascar and occupied all vegetation formations from spiny bush to evergreen humid forest. They were the only mouse lemurs that inhabited the driest of these habitats (the spiny bush), and therefore represented the arid end of the genus’ ecological niche. In the more mesic parts of its range, it lived with Microcebus murinus, and these two species often hybridized. There were distinct dry and wet seasons within the species’ habitat, and Microcebus griseorufus tended to reduce their day range and activity (and therefore reduce their metabolic rate) during the dry season in response to food shortage. Therefore, lemur energy reserves accumulated during the wet season were crucial for their survival during the dry season.
The study site was located in the Parc National de Tsimanampetsotsa, which experienced highly seasonal rainfall. Recently, this region experienced a shift in maximum rainfall from December and February to March and April. This zone had the highest levels of plant endemism on the island (48% of the genera and 95% of the species were endemic). The majority of the vegetation was xerophytic and was classified among Madagascar’s spiny forest formations. There were two different vegetation formations within the study site that varied according to the underlying soil and the soil’s water holding capacity. The first location was a dry forest on unconsolidated sands (DFS) and the second location was a spiny bush formation on calcareous soil (XBC). The DFS site was more humid than the XBC site. The study period lasted from April until July 2008. April and May were defined as the late wet season and June and July were defined as the early dry season. A map of the study site showing the different vegetation types and the location of both study plots was displayed.
Within each vegetation structure, the authors established one study plot of 6 ha (150 X 400 m) and placed 96 Sherman Livetraps at 25 m intervals in each plot. Traps were placed 0.5–2.0 m high in the vegetation and were baited with bananas. One trapping session was conducted in each habitat in each season and lasted for 4 consecutive nights. This resulted in a total of 384 trap nights per habitat per season. Captured lemurs were anesthetized and marked with a microchip. They were weighed and their tail circumference was measured at the tail base. In addition to body mass, tail circumference represented body condition since gray-brown mouse lemurs store fat in their tail before the dry season.
Twenty-two individuals (DFS: 6 females, 5 males; XBC: 5 females, 6 males) were supplied with radio collars to assess feeding and ranging patterns. The authors studied feeding behavior through focal observations of 2 radio-collared individuals (1 female, 1 male) per habitat per season. The type of food ingested and the lemur’s position each time it moved was recorded. Frequency of feeding on certain food categories was documented rather than time spent feeding on items since the animals time processing and handling food items (fruits, gum, and arthrpods) varied depending on the type of food consumed.  All 22 mouse lemurs were sequentially tracked over a total of 8 half-nights by triangulation to assess their spatial and temporal distribution. Home range sizes were estimated using Animal Movement and the minimum-convex-polygon method. The authors compared the sizes of home ranges to test for seasonal variation in home range size between the wet and dry season. Home range data was also analyzed to test for habitat effects. Two graphs displaying the correlations between the numbers of food plants per ha and home range size (ha) for the wet and dry seasons were constructed.
All known food plants within the study plots were mapped using ArcView 3.2a. The plant data were overlaid over home range polygons to assess food availability within the individual home ranges. Food plants that had a height >1 m or a diameter at breast height >10 cm were included in the study. The researchers checked the plants for flowers and fruits twice a month. A graph displaying the phenology of fruit plants in the studied habitats between March and July 2008 was constructed. All the data were assessed using statistical analyses. Three tables displaying the results of the statistical analyses were constructed.
Bohr et al. found that the population density in the mesic dry forest was 3 times higher than in the drier spiny bush and that at the end of the wet season, mouse lemurs had higher body masses and larger tail circumferences (fat storage) than at the beginning of the dry season. Lemurs from the dry forest were in better condition than those from the spiny bush. Home ranges were also larger at the end of the wet season than during the dry season. Home range sizes did not differ between the two sites, and home range size was positively correlated with tail circumference.
At the end of the rainy season, observed lemurs fed equally on fruits and gum. However, at the beginning of the dry season, the lemurs ingested more gum over fruits. In the dry forest, lemurs consumed gum and fruits equally, whereas lemurs in the spiny bush primarily consumed gum. Arthropods were also eaten more frequently in the spiny bush than in the dry forest. Tables displaying the diet of Microcebus griseorufus in the DFS and the XBC sites, as well as during the wet and dry seasons, were constructed.
Throughout the entire study, the number of fruit-bearing plants was lower and declined faster in the arid spiny bush versus the mesic dry forest. Overall food abundance was high in March, but steadily declined in June and July. A higher total number of fruit-producing versus gum-producing plant individuals were found in the home ranges of the dry forest, and home ranges in the spiny bush had a significantly lower density of fruit-producing plants. The density of gum-producing plants did not differ between sites. Home range size and food plant density correlated negatively at the end of the wet season, indicating that home range size would need to increase exponentially if food abundance was to further decrease. No such relationship was observed during the dry season.
These results demonstrate that there were substantial differences in habitat quality between the two sites, and that the dry forest was the more favorable habitat for Microcebus griseorufus since it contained a larger density of the lemurs’ favored food: fruit. Lemurs’ distribution was therefore linked to food abundance at the end of the wet season, but not during the dry season. The lemurs prepared for the less favorable dry season at the end of the wet season by expanding their home range size and increasing their food intake. They then reduced their metabolic rates and lowered their energy expenses instead of attempting to increase their energy intake. This suggests that the species was limited by bottom-up factors (food resources) rather than top-down factors (predation).
The observed higher population density in the dry forest, with its higher availability of fruit plants, also suggests that the lemur populations were regulated by bottom-up factors (food resources). The lemurs preferred fruit to gum, and arthropods were hunted opportunistically since they were more difficult to locate and defend. Although gum contained concentrations of protein or carbohydrates that exceeded those found in Madagascar fruit, the fruit may have been preferred over gum because the gum contained secondary compounds that inhibit digestion.
The lower density and poorer body condition of the lemurs within the spiny bush indicate that the spiny bush habitat was less favorable than the dry forest habitat. This suggests that the higher proportion of gum-producing plants in the spiny forest could not compensate for the reduced amount of fruit plants at this site. Animals with larger home ranges accumulated more fat in preparation for the dry season. However, if the lemurs were able to extend their home ranges beyond their present sizes, larger home ranges would have been observed in the spiny bush. Clearly, these lemurs were unable to extend their home ranges to include more food resources even when faced with a drier climate and unfavorable food. The animals could have reached a point where home range extension (as compensation for declining food abundance) became unprofitable. Since climate change induced-desiccation will shift food resources toward gum at the expense of fruits, lemurs will need to migrate to more mesic areas to obtain required food resources.
Since Microcebus griseorufus inhabits the dry limit of its ecological niche in the xerophytic spiny bush, it will have to migrate to more mesic areas as climate change-induced desiccation shifts its food resources towards unfavorable gum. However, connectivity between habitats in Madagascar has been extensively disrupted by anthropogenic habitat fragmentation. Therefore, conservation efforts must be made to establish connectivity between lemur habitats.

On the Generality of a Climate-Mediated Shift in the Distribution of the American Pika (Ochotona princeps)

Alpine species are extremely vulnerable to climate change-induced extinctions due to their physiological and geographic constraints. Scientists have already documented climate change-generated population extirpations and distributional shifts for numerous alpine plant and mammal species, such as the American Pika (Ochotona princeps). However, few studies have investigated the specific climatic drivers that cause these local species’ extinction at lower alpine levels. Using models and surveys of 69 American Pika population sites, Erb et al. (2011) analyzed pika distribution change throughout the Southern Rocky Mountains by assessing the effects of landscape, microhabitat, and climatic factors on pika persistence. Elevation, maximum summer temperature, annual precipitation, and habitat characteristics with potential climate-buffering effects (talus depth, porosity of rocks, soil moisture, and rock type) acted as the predictor variables. The authors found that only 4 of the 69 pika populations were extirpated in the Southern Rockies. However, these four sites revealed that climatic factors, rather than habitat features, determined pika persistence. Additionally, these 4 sites were among the driest pika habitats in the region; they lacked a sub-talus water source and experienced a smaller mean annual precipitation in comparison to other pika sites. These results suggest that water, in the form of precipitation and sub-surface moisture, was the primary driver of pika distribution patterns in the study region. Therefore, increased drying trends could put American Pika populations at risk to climate change-induced extinction.—Megan Smith
Erb, L.P., Ray, C., Guralnick, R., 2011. On the generality of a climate-mediated shift in the distribution of the American pika (Ochotona princeps). Ecology 92:9, 1730-1735.

The authors conducted their research at 69 sites historically occupied by pikas in the Southern Rocky Mountains of southern Wyoming, Colorado, and New Mexico. The sites were defined as those with recorded pika presence before 1980—the year when climate change became prominent in datasets. The dates of the historical records varied from 1872 to 1979, and the sites were also chosen based on geographic accuracy. The data were collected from 800 historical records of pika presence found in museum records, literature sources, and georeferenced museum specimens. Climate data for each site was accumulated between 1908 and 2007. Site elevation varied from 2703 to 4340 m and the most common vegetation at the sites consisted of alpine forbs, grasses, willow, conifers, and aspen.
The authors sent out crews to each of the 69 sites to assess current pika occupancy. The crews searched for signs of pika presence by detecting individual organisms through sight and sound and by identifying fresh pika food stores (haypiles). If signs of pika occupancy were not found, crews returned 3–5 months later and searched the sites extensively within a 3 kilometer (km) radius. A minimum of 0.5 hours was spent per hectare searching talus for signs of pika presence. While at each site, the crews collected data on microhabitat features. A map of the 69 sites historically occupied by the American pika, differentiated by recent occupancy status, was constructed.
Erb et al. then compared models of pika persistence that incorporated elevation, maximum summer temperature, annual precipitation, and site characteristics with potential climate buttering effects (rock type, talus depth, porosity of individual rocks, and evidence of persistent soil moisture beneath the talus) to assess landscape, microhabitat, and climate characteristics as possible drivers of pika population extirpation. The authors’ model comparisons were guided by pika persistence hypotheses and results from previous studies. The models represented the following hypotheses: 1) pikas persist in locations where the least change in climate (temperature and precipitation) has occurred; 2) pikas persist in areas where the climate has predominantly been wet and cool; 3) pikas persist in sites where they have been exposed to the least climatic variability; 4) pikas persist in locations with the deepest talus, most porous and insulating rock, and where water or ice persist under the talus; 5) pikas persist at higher elevation locations. A table displaying the hypotheses and the candidate model covariates was constructed.
The authors found that only 4 of the 69 pika population sites in the Southern Rockies lacked recent signs of O. princeps in 2008. However, the pattern of these extirpation sites reveal that pika persistence was best explained by water, in the form of mean precipitation and the persistence of moisture under the talus. These four sites were the driest of the 69 sites within the Southern Rockies. The mean annual precipitation across all sites between 1908 and 2007 was 884 mm and the mean annual precipitation across extirpation sites was 593 mm. The four sites also lacked a sub-talus water source. Overall, these results support the authors’ second and fourth hypotheses. A graph displaying observed and predicted pika occupancy as a function of local mean precipitation, change in precipitation, and presence of sub-talus water was constructed, as was a figure comparing observed pika occupancy with mean annual precipitation between 1908 and 2007.
The extirpation locations did not experience significant climate variability. There was very little change in precipitation levels at the extirpation locations since 1980. Therefore, summer maximum temperatures, change in summer maximum temperatures, and variation in both summer maximum and annual precipitation did not support pika persistence. Additionally, elevation, talus depth, and rock porosity did not predict pika persistence. A figure comparing observed pika occupancy with change in mean annual precipitation between the years of 1908 and 1979 and 1980 and 2007 was constructed.
In contrast, Erb et al. found that since 1980, maximum summer temperatures across all sites have averaged 0.48°C warmer than they were from 1908 to 1979. Changes in maximum temperature varied among sites (–1.2°C to +2.5°C), as did changes in annual precipitation (–80 mm to +203 mm, –8.0% to +24.1%). The overall trend in the study region demonstrated an increase in annual precipitation across all sites (+46 mm, +5.6%). These results demonstrate that the overall pika population sites experienced climatic change even though the 4 extirpation sites did not.
Although low precipitation and sub-talus moisture drove pika extinction in the Southern Rockies, pika population sites experiencing a decrease in annual precipitation were not more vulnerable to extirpation. This may seem contradictory with the authors’ previous findings; however, the sites that experienced a decrease in precipitation since 1980 were previously among the wettest locations within the study region. Although these 13 drying sites did not significantly differ in mean post 1980 precipitation levels from the other 56 sites, it would nevertheless be important to monitor their moisture levels since continued drying trends could place these pika populations at risk to extirpation in the near future.
Additionally, though the four extirpation sites were the driest within the study region, pika occupancy was detected at these locations within the past century. Erb et al. proposed that these sites may have been marginal habitats that required immigration from adjacent populations to maintain their own populations. Therefore, these locations only supported pika populations when climatic conditions facilitated their re-colonization by individuals from nearby sites. Each extinction site experienced a year in which annual precipitation was above the site’s upper 99% Confidence Interval 1–4 years before the site’s recorded pika presence. This suggests that variable high precipitation conditions facilitated pika dispersal.
The authors also suggested that the dry extirpation sites were unable to support pika populations because they lacked snow cover. The low precipitation levels recorded at these sites resulted in the low accumulation of snow cover. Since snow cover insulates pika populations from extreme cold weather events, the low levels of snow were inefficient to protect the pika populations from low alpine temperatures. Therefore, projected declines in snowpack throughout the western United States indicate that pika habitats in regions like the Southern Rockies may soon experience drier conditions, placing further pika populations at risk to climate change induced extinction. 

Disproportional Risk for Habitat Loss of High-Altitude Endemic Species Under Climate Change

Scientists project that climate change will alter the distributions and range shifts of biota, ultimately causing an increase in terrestrial species’ extinction rates. In many mountainous areas, warming temperatures have already generated an upward shift of tree lines. Therefore, range-restricted, high-altitude, endemic species inhabiting mountain ranges are particularly at risk since the upward shift of the tree line may significantly reduce these endemic species’ habitat areas. Using a Potential Climate Tree Line (PCT) model and statistical analyses, Dirnbock et al. (2011) analyzed the loss of available habitats for high-altitude endemics of five Austrian Alps taxonomic groups (vascular plants, snails, spiders, butterflies, and beetles). Habitat loss was attributed to the upward shift of forest species. Additionally, the authors investigated whether hotspots of endemics would be disproportionally affected by habitat loss. Dirnbock et al.found that even under the weakest climate change scenario (+1.8 °C by 2100), above tree line area was reduced by 77%. The results also demonstrated that areas with high endemic species richness showed the largest losses of suitable habitat. Therefore, endemic species richness was positively related to above tree line area loss. These results suggest that endemic hotspots in the Alps will be disproportionally affected by habitat loss caused by climate change induced forest expansion. Combined with these species’ range restrictions, their ability to persist in the face of climate change may be greatly reduced.—Megan Smith.
Dirnbock, T., Essl, F., Rabitsch, W., 2011. Disproportional risk for habitat loss of high-altitude endemic species under climate change. Global Change Biology, 990–996, doi: 10.1111/j.1365-2486.2010.02266.x

The authors conducted their study in Austria, a landlocked country in Central Europe. The mountains of the eastern Alps cover two-thirds of Austria, and during the Pleistocene, approximately 70% of them were glaciated. These glaciations led to the widespread migrations, range restrictions, and survival of species in isolated refugia located in non-glaciated, flat, low, peripheral mountains. This process led to the evolution and speciation of different lineages and taxa. Many endemics are currently restricted to the northeast peripheral mountains of the Alps due to their limited migration ability.
Dirnbock et al. used data from an Austrian endemic species inventory that reported each species’ distribution (presence/absence) in grid cells encompassing a 35-km2 area. They selected taxonomic groups containing a high number of endemic species with ranges primarily in Austria and whose habitats were restricted to areas above the current tree line suitable for forest growth. Species were excluded if they were restricted to habitats incapable of forest colonization, either due to the absence of topsoil or the presence of high levels of disturbance (rock habitats, screes). Of the 177 high altitude endemics, 134 species occupied habitat above the tree line that was suitable for forest growth and these 134 species were used in the study. This group was composed of 45% beetles, 32% vascular plants, 10% spiders, 9% butterflies, and 4% snails.  
Since both climate and land use changes trigger the upward shift of the tree line, the authors used a potential climate tree line (PCT) Model to isolate climate as the contributing factor driving forest expansion. Dirnbock et al. derived the current regional tree line by overlaying Austrian forest distribution on a digital elevation model (DEM) in geographic information systems (GIS) computer program. Since different tree species respond individually to climatic variables, the authors divided Austria into nine forest regions based on species. The precipitation sum and monthly mean temperature from April to September were sampled randomly in each region along the tree line. These variables acted as drivers of tree line location within the model. Edaphic traits and ecosystem disturbances were excluded from the model.
Once constructed, the authors used the PCT model to test five climate scenarios to determine how climate change will drive loss of area above the tree line. These standard IPCC scenarios included B1 (an increase of 1.8°C, the minimum expected projected temperature for 2100), A1T and B2 (an increase in 2.4°C), A1B (an increase of 2.8° C), A2 (an increase of 3.4°C), and A1FI (an increase of 4°C). Dirnbock et al. next calculated the proportional loss of area above the tree line by assigning the current area under the PCT model a value of 100%. Therefore, if the model computed a value of 1, the region experienced a complete loss of area above the tree line. A value of 0 indicated no change in area above the tree line.
A statistical test was used to determine if loss of area above the tree line was higher in cells that contained at least one endemic species compared to those that contained none. Dirnbock et al. used an alternative statistical test to assess if endemic species richness and altitude predicted loss of area above the tree line.
They found that with minimum expected climate change (an increase in 1.8°C) a 77% loss of above tree line area due to tree line expansion resulted. Under maximum expected climate change (an increase in 4°C), the hotspots of high altitude endemism were restricted to a few fragmented mountaintops. Interestingly, the results also suggest that areas containing endemic species will not loose more above tree line terrain than areas lacking endemic species. Maps comparing the number of endemic species, the proportional loss of area above the tree line by 2100, and the proportional loss of area above the tree line under two other climate scenarios were constructed.
Additionally, Dirnbock et al. determined that grid cells with low to intermediate endemic species richness (1–8 endemic species) showed small losses in above tree line area. In contrast, grid cells with high endemic species richness (9–30 endemic species) showed the largest losses in above tree line area. When the authors pooled endemic species richness across all five taxonomic groups, they found that species richness was positively related to the loss of above tree line area. The same results were found for species richness within three of the five taxonomic groups (vascular plants, beetles, and snails). Although an increase in altitude resulted in a decrease in species richness, Dirnbock et al. established that endemic species richness was related to loss of above tree line area independent of altitude. Individual analyses of each taxonomic group revealed that beetles’ and snails’ habitat showed a disproportionate above tree line area loss while spiders and butterflies demonstrated the opposite results. A figure comparing the number of endemic species to the proportional loss of above tree line area for each climate scenario was constructed, as was a separate table recording the loss of area above the tree line for each climate scenario and for different groups of endemic species.
Dirnbock et al.’s results suggest that endemic species’ hotspots in the Alps will be affected by habitat loss generated by climate change-driven forest expansion. In particular, these hotspots will be affected by forest expansion more so than regions with low species richness. Hotspots of endemism within the Alps are located predominately on flat mountain plateaus that rise slightly above the tree line. Therefore, endemic species’ suitable habitats are limited to begin with, ultimately leaving little to no available habitat when forests expand slightly into their territory.
Forest expansion did not affect spiders’ and butterflies’ habitats because these species’ also inhabit the higher, central mountain ranges of the Alps, thus alleviating their climate induced extinction risk from habitat loss. Spiders and butterflies also have a higher dispersal capability due to the presence of mobile adults (butterflies, ballooning spiders). Therefore, these species could have re-colonized several larger regions in the Alps after the glacial period ended.
Overall, a species’ risk of extinction in future climate change scenarios corresponds with its ability to shift with its suitable habitats. Yet, as climate change drives the upward expansion of the tree line on mountainsides, non-forested mountaintops will become increasingly fragmented. This fragmentation will not only reduce endemic high-altitude species’ available habitat, but it will also obstruct the lateral movement of these species. Since many endemics are poor dispersers and habitat specialists, the migration capacity of these species’ will be greatly reduced. 

Climate Change and the Invasion of California by Grasses

Abiotic conditions—such as temperature and precipitation—determine local plant community membership by favoring groups with specific functional traits. However, climate change will alter abiotic factors, causing the composition of plant communities to shift by selecting for different functional traits. In some ecosystems, exotic, invasive species may possess functional traits favored by the new climate regime. Therefore, climate change may exacerbate native biodiversity loss by facilitating the spread of invasive species. To determine if climate change will alter the course of invasion of California’s already heavily invaded grass flora community, Sandel and Dangremond (2011) evaluated the differences in trait composition of native and exotic species groups and evaluated the contemporary trait-climate relationships across the state. The authors mapped the distributions of all grass species within California and then calculated the mean trait characteristics, mean climate values, and human influence indexes across 800 discrete zones within the state. They found that exotic species were more likely to be annual, taller, with larger leaves, larger seeds, a higher specific leaf area, and a higher leaf nitrogen percentage than native species. These traits were associated with higher temperatures across the entire state, indicating that increasing temperatures caused by climate change will favor traits possessed by exotic species. Ultimately, this may lead to the dominance of exotic species within California’s grassland communities.—Megan Smith
Sandel, B., and Dangremond, E.M., 2011. Climate change and the invasion of California by grasses. Global Change Biology, doi: 10.1111/j.1365-2486.2011.02480.x

Sandel and Dangremond mapped the distributions of all grass species within California. The study’s maps were based on a map of California that divided the state into 35 floristically defined sub-regions. These sub-regions were divided into 100 m elevation bands using a digital elevation map of California. These divisions resulted in 800 discrete zones across the state. The authors used a flora of California, the Jepson Manual, to determine where grass species occur in each zone. The Jepson Manual was also used to determine whether each species was native or exotic. Exotic species were defined as those that were least naturalized and could be invasive. Particular attention was paid to the species listed by the USDA as invasive and noxious weeds.
The authors collected trait information on the grass species in California. These traits included maximum height, plant lifespan, leaf lifespan, seed mass, month of first flowering, length of flowering period, specific leaf area, leaf length and width, leaf N concentration per mass and per area, and photosynthetic pathway. The data were collected from the Jepson Manual species accounts, published sources such as the Glopnet database, genus-level information, and garden seed information databases. When multiple trait values were available for a species, the authors used the mean of all values. Trait information for species varied from complete to very incomplete. The means for each trait were calculated across all species present in each of the 800 zones. A figure demonstrating trait-based filtering on community membership imposed by climate was constructed, as was a table comparing trait geometric means of exotic and native grass species of California.
The time of introduction for each exotic species was obtained from the California Consortium of Herbaria records, which recorded plant species introductions based on the species first date of collection. The number of exotic species known in a particular year was divided by the percentage of native species that were known for that year to estimate the number of exotic grass species in the state through time.
The authors combined PRISM and Daymet climate data for California to calculate climate variable means for each of the 800 zones. The final set of climate variables obtained were mean annual temperature, seasonality of temperature (annual maximum minus annual minimum temperatures), annual precipitation, potential evapotranspiration, water balance (total precipitation minus PET), months of water deficit (the number of months of the year with PET > precipitation), and cumulative water deficit (summed water deficit in all months of deficit, expressed as negative numbers).
Human impacts on California’s ecosystems included increasing the rate of species introductions or producing disturbances that favor exotic species. These possibilities were examined using the Human Influence Index (HII), which measures human impacts by incorporating population density, land cover changes, accessibility, and electrical power infrastructure. The mean HII value was calculated within each of the 800 zones. Both HII and climate variables were treated equally within the study’s analysis.
After collecting data, Sandel and Dangremond statistically assessed whether native and exotic species differed in their trait states. The richness of native and exotic species were calculated and then the species richness of each group, as well as the proportion of species in each zone that were exotic, were compared to mean annual temperature and mean annual precipitation. Next, the authors determined how the traits of the grass flora as a whole related to climate by plotting climate variables against zone mean trait values across all 800 zones.
A quantitative prediction for the prevalence of exotic species per zone was calculated based on the relationship between temperature and zone mean trait values for native species, as well as the relationship between species’ trait value and the probability that species was native. The authors only used zone mean trait values of native species to avoid predicting the proportion of exotic species from trait means that included exotic species. A loess regression was used to fit a curve to the temperature-trait relationship for native species. Then, a logistic regression was used to estimate the probability that a species with a given trait value was native. When combined, these two regressions allowed the authors to start with a temperature, obtain the predicted zone mean trait value of a zone at that temperature, and to convert this into a prediction of the fraction of the community in that zone that was native. This approach was demonstrated using leaf width in Figure 2. 
Since mean zone traits were less variable than individual species traits, the range of predictions for proportion of natives was smaller than the observed range. Therefore, the predicted proportion provided an index of relative susceptibility to exotic species, rather than a 1:1 prediction for the proportion of native species. This index was easily rescaled by using information of the actual proportion of native species within just a few sites. The authors then used further statistical methods to relate the predicted proportion and the actual proportion of native species for five randomly selected sites. They rescaled all predicted proportions according to these results to obtain a properly scaled prediction of the proportion of native species.
Finally, the authors assessed spatial structure in climate and species-level data by separating two sources of climate variation: moving up an elevational gradient within a sub-region, and moving across sub-regions at a constant elevation. Relationships were calculated across all 800 zones, along elevation gradients within each zone, and across sub-regions at a constant elevation.
 Sandel and Dangremond found that grass species richness varied across the state, with a maximum of 163 and minimum of 3 species in a zone. The proportion of exotic grass species within a zone varied between 0% and 66% within zones. Native species richness showed a hump-shaped relationship with temperature while the proportion of species that were exotic increased strongly with temperature. Mean annual precipitation was not strongly related to the richness or the proportion of exotic species. A map displaying the patterns of species richness of grass in California was constructed, as was a map displaying the proportion of species within a zone that were exotic. Additionally, figures displaying the relationship of species richness and climate were constructed.
There was a total of 258 native and 177 exotic grass species in California. These two groups differed significantly in their traits. Exotic species were more likely to be annual, taller, have longer and wider leaves, a higher specific leaf area, a higher leaf N percentage, and a higher seed mass. Noxious invasive weeds had the most extreme trait values, while most exotic species were intermediate between weeds and native species. Many of these traits were strongly related to mean annual temperature. At warmer sites, species were larger (taller and larger-leaved), with a higher specific leaf area, a greater leaf N percentage and mass, shorter-lived leaves, larger seeds, earlier flowering times, and longer flowering seasons. The proportion of grass perennial species decreased with increasing temperatures as well. Figures displaying the relationship of temperature and grass traits were constructed, as was a table displaying the statistical results of comparisons of climate variables and zone mean traits.
The authors also found that with increasing cumulative water deficits, decreasing water balances, and increasing months at water deficit, grasses became longer-leaved with a higher specific leaf area, a higher N leaf percentage and mass, and with larger leaves. As human impacts increased, zones became exotic-like in their trait composition, revealing the increased richness of exotic species in heavily used areas.
Additionally, the results showed that an increase in elevational gradients within sub-regions led to reductions in grass mean height. However, there was little relationship between height and temperature when elevation was constant. Seed mass showed both positive and negative relationships to temperature within sub-regions. At low elevations (across sub-regions) seed mass increased with temperature, while at high elevation, it decreased.  Figures displaying the relationships between mean annual temperature and these two traits were constructed.
Sandel and Dangremond predicted the proportion of species in each zone that were native using only zone mean annual temperature, trait-temperature relationships for native species, and trait differences between native and exotic species groups. Using leaf width patterns, they found that the proportion of native species was strongly correlated with the observed proportion. However, the relationship was nonlinear and the predicted proportions covered a smaller range of values than the observed proportions, causing a poor fit to the 1:1 line. The authors rescaled the predicated proportions based on five randomly sampled sites where the proportion of native species was known. This led to quantitative and accurate predictions of the proportion of native species. A figure displaying the corrected prediction for the proportion of species that were native was constructed.
Finally, the authors found that prior to 1860, there were 20–30 exotic species established in California. This number increased sharply through the 1900s. The continued arrival of exotic species into California significantly changed the composition of the exotic flora. California’s exotic flora became more perennial, more C4, and larger-seeded over time. Figures displaying the changes in the exotic grass flora of California over time were constructed.
Overall, two conditions must be met for climate change to favor one species group (exotic grass) over another (native grasses). The changing climate (an increase in California’s mean annual temperature) must alter filters that act on plant functional traits, leading to communities with altered trait compositions. The two groups must also differ along trait axes. Both these conditions were met in California.
The present distribution of grass species richness within California already show that the proportion of species within a zone that were exotic and the proportion that were noxious weeds were strongly and positively related to mean annual temperature. However, since exotic species were taller and had more light-capturing ability than native species, they may outcompete natives for light. The larger seeds of exotic species also could give them a competitive advantage at the seedling stage. Additionally, increasing temperatures favored traits for which exotics had higher mean values than natives. Therefore, exotic and invasive species may come to dominate California’s grassland community since current noninvasive exotics could become invasive as temperatures increase within the state over time.  

Ecological Correlates of Distribution Change and Range Shift in Butterflies

Increasing evidence suggests that the worldwide biodiversity loss should be attributed to anthropogenic disturbance, particularly habitat loss and climate change. To conserve biodiversity, scientists must identify the factors driving population decline. The ecological traits of a focal species and the traits of species they interact with have previously been correlated with species’ extinction risks and distribution changes. Mattila et al. (2011) analyzed the distribution declines (area of occupancy) and range shifts (extent and direction) of 95 threatened and non-threatened butterfly species in Finland to identify ecological traits that influence species’ distribution changes and range shifts. These traits included larval specificity, resource distribution, dispersal ability, adult habitat breadth, flight period length, body size, and overwintering stage. The results show that the distribution of Finnish butterflies has declined substantially, with the distribution of threatened species’ declining more so than non-threatened species. Additionally, the authors found that the ranges of butterfly species have shifted in both direction and degree, with non-threatened species shifting more so than threatened species. Ecological specialization at the larval or adult stage, as well as poor dispersal ability and large body size, affect both distribution declines and range shifts. These results suggest that highly dispersive generalists will eventually dominate biological communities as result of climate change and habitat fragmentation. However, both non-threatened and threatened species are prone to extinction since both groups possess traits that make them vulnerable to range shifts and distribution declines.—Megan Smith
Mattila, N., Kaitala, V., Komonen, A., Paivinen, J. Kotiaho, J.S., 2011. Ecological Correlates of Distribution Change and Range Shift in Butterflies. Insect Conservation and Diversity. DOI: 10.1111/j.1752-4598.2011.00141.x

Mattila et al. collected Finnish butterfly species data from several scientific papers to assess if threatened and non-threatened species differ in their distribution and range shifts. The authors first categorized the 95 Finland butterfly species as threatened or non-threatened using The Finnish Red List of Species. Butterfly species that were classified as near-threatened, vulnerable, endangered, or critically endangered in the Finnish Red List of Species were classified as by the authors as threatened. The other species were classified as non-threatened.
The authors then determined the distributions, distribution changes, and range shifts of each butterfly species. The distributions were based on the Atlas of Finnish Macrolepidoptera. The distributions are given as the number of occupied 10 km X 10 km grid cells found in the Finnish national coordinate system. The distribution data in the Atlas is categorized into old (before 1988) and new (1988–1997) observations. The authors calculated the distribution changes per butterfly species by finding the difference between the old and new occupied cells, and dividing by the number of old cells. These values were reported as a negative or positive percent, depending on the direction of the distribution change. Range shifts (the movement of the center of the distribution for each species) were measured by taking the difference between the centers of the distributions between the two timescales (old and new). The range shifts were reported in distance (km) and direction (degrees). A figure displaying the direction of range shifts for non-threatened and threatened species and a table reporting the direction of range shifts for all species were constructed. 
Mattila et al. then extracted data from previous scientific papers to determine if the ecological characteristics of Finnish butterflies affect distribution changes and range shifts. First, the authors categorized larval host-plant specificity in Finland into three classes: monophages (feed on a single plant species), oligophages (restricted to one genus of food plants), and polyphages (feed on more than one genus). Monophage data were exclusively used to analyze the effects of resource distribution since their food supply is limited. Plant distribution data were collected from the Atlas of the Distribution of Vascular Plants in Finland and was reported as the number of occupied 10-km grid squares in the Finnish national coordinate system.
Butterfly dispersal information was obtained using a previous paper’s data. Experienced lepidopterists in Finland received questionnaires and were asked to report the dispersal ability index (on a scale from 0 – 10) for each butterfly species. The 0 value represented an extremely immobile species, while the 10 value represented an extremely mobile species. The questionnaires were averaged to obtain the average dispersal ability for each butterfly species.
Additionally, the authors categorized Finnish butterfly habitats into types: uncultivable lands (edge zones next to industrial areas, harbor and storage areas, loading places, un-cropped fields, and other areas that have been impacted by humans), meadows (non-cultivated grasslands), forest edges (roadsides), and bogs. Using these habitat types, Mattila et al. formed an index of adult habitat breadth. This index reports the number of habitat types in which adult butterflies were found. An index value of 1 represents specialist species. Specialist species were confined to one habitat type. An index value of 2 represents intermediate species (those that can inhabit two habitat types), and an index value of 3 represents generalist species. Generalists could occupy three or four habitat types.
The average length of the flight period (days) for each butterfly species was extracted from a previous scientific paper. Wingspan (mm) acted as a measure of butterfly body size because wingspan correlates with body size. Finally, the authors did not include phylogenetic corrections because the information was unavailable, and earlier analyses using preliminary phylogeny showed no change in the results. Two graphs displaying the percent distribution change of species exhibiting larval resource specificity and variation in adult habitat breadth were constructed. Two other graphs demonstrating the effect of body size and dispersal ability on distribution change were also constructed.
Mattila et al. analyzed butterfly distribution changes using standard statistical analyses. They conducted two separate analyses for testing the effects of ecological characteristics (larval specificity and habitat breadth) and life history traits (dispersal ability, body size, length of flight period) on distribution changes since data concerning larval specificity and habitat breadth for 14 northern butterfly species could not be found. The authors analyzed range shifts using circular statistics.
The authors found that the distribution of Finnish butterflies declined on average by 35%. Threatened butterfly species’ distributions declined by 63%, while non-threatened butterfly species’ distributions declined by 26%. The ecological traits driving the distribution declines were larval specificity and adult habitat breadth. In particular, Monophagous butterfly species’ distributions declined more than the distributions of Oligophages and Polyphages. Additionally, the habitat specialists’ and intermediate species’ distributions declined more than the distributions of habitat generalist species, with the largest decline seen in the habitat specialists. Within the habitat specialists, the distributions of species inhabiting semi-natural meadows and bogs declined more than edge specialists. Life history traits that contributed to distribution declines were dispersal ability and body size.
Mattila et al. also found that all butterfly species shifted an average of 22.6 km to the northeast (74.2°). Non-threatened species shifted an average of 30.3 km to the northeast (73.7°), while threatened species only shifted an average of 7.9 km in no consistent direction. The authors asserted that these shifts were caused by changes in climate because Finland’s climatic isotherms move to the northeast, near to where the butterfly species seem to be moving. The directions of the range shifts were not influenced by larval specificity or adult habitat breadth. However, they were influenced by dispersal ability, body size, and flight period length. Species that had better dispersal ability, a smaller body size, and a longer flight period experienced larger range shifts in the direction of the overall, average range shift for the butterfly species.
These results indicate that ecological specialization, whether at the larval or adult stage, contributed to Finnish butterfly species’ distribution declines and range shifts. Specialist species may be incapable of following changes in the environment (i.e. changes in climate), because these species were isolated and confined to small habitat patches. For example, half of the habitat specialist species lived in semi-natural grasslands or natural bogs. These habitats had consistently declined in area since the 1950s-1960s. Therefore, habitat specialization, combined with poor dispersal ability, contributed to the inability of specialists to shift their ranges. Additionally, most specialist species were categorized as threatened species, which may explain why the threatened species did not shift their ranges to the same degree as non-threatened species. Overall, the results suggest that future biological communities will be dominated by generalist species that are efficient dispersers.
Mattila et al.’s findings demonstrate that the ecological traits of Finnish butterfly species influence the distribution changes and range shifts of these species. However, it is imperative to recognize that both threatened and non-threatened species share traits that make them vulnerable to extinction. Therefore, scientists should focus on protecting current, threatened species, as well as species that may be at risk to extinction in the future.  

Rapid Range Shifts of Species Associated with High Levels of Climate Warming

Changes in climate are impacting biodiversity on a global scale. Recent evidence has suggested that numerous terrestrial species are shifting their geographic ranges to higher elevations and latitudes in response to warming temperatures. However, previous studies have yet to demonstrate a direct link between the warming climate and species’ range shifts. Using a combination of data from several studies, Chen et al. (2011) analyzed the mean latitude range shifts across species of 23 taxonomic groups per region and the mean elevation range shifts across species of 31 taxonomic groups per region. The authors then compared these observed range shifts to expected range shifts necessary for taxonomic groups to remain in the same average temperature zone. The results suggest that the rates of terrestrial range shifts in latitude and elevation are two to three times faster than previously described. Additionally, the authors found that the observed latitudinal and elevation range shifts were correlated with the expected range shifts, suggesting a causal relationship between warming temperatures and terrestrial species’ range shifts. Despite these results, there was variation in the directional range shifts among species, indicating that other internal and external factors influence terrestrial species distributions.—Megan Smith
Chen, I., Hill, J.K., Ohlemuiler, R., Roy, D.B., Thomas, C.D., 2011. Rapid Range Shifts of Species Associated with High Levels of Climate Warming. Science 333, 1024 – 1026.

          Chen et al. collected data from previous studies to analyze the current rates of elevation and latitudinal range shifts of terrestrial taxonomic groups. Though other studies investigated the range shifts of individual species, the authors averaged the response of a taxonomic group in a specific region and used this mean as a single observation (i.e. plants in Switzerland). These authors determined range shifts by comparing the differences between two temporally separated recordings of a taxonomic group’s range margins (the average of a group’s upper/cold and lower/warm temperature range). The latitudinal shift of taxonomic groups was categorized as poleward, stable, or Equatorward while the elevation shift was categorized as up, stable, or down. A figure showing the observed latitudinal shifts of the northern range boundaries of species of four taxonomic groups in Britain was constructed.
          The authors extracted regional temperature increases from previous studies or identified the time periods and locations of the regions using CRU_TS2.0 data at 0.5° resolution. They gridded each region and then averaged the temperature across the grid cells to obtain a mean yearly temperature for the area in question. The regional temperature increase over each time period was then obtained by measuring the change in temperature between two temporally separate recordings. 
          The authors then derived the expected range shifts of the study’s taxonomic groups to assess the possible link between the changing climate and terrestrial species’ range shifts. Chen et al. calculated the expected elevation range shift by first computing the lapse rate, which is the decrease in degrees Celsius per increase in meters. For each region, Chen et al. divided the regional temperature increase by the lapse rate to calculate an estimate of the elevation increase or decrease a taxonomic group would have to make to remain within the same temperature range.
          Latitudinal range shifts were estimated by first calculating the temperature-distance transfer rate, which is the decrease in degrees Celsius per increase in kilometer of latitude, using CRU_CL2.0 data on a global 10’ grid. After gridding each region, the authors identified the nearest cell that was 0.5°C cooler than an original cell. The transfer rate was computed by dividing the temperature difference between the two cells by the latitudinal distance in kilometers between the cells. Then, Chen et al. averaged these measurements across every cell in the region to obtain the final transfer rate. The expected latitudinal shifts were determined by dividing the regional temperature increase by its corresponding transfer rate. These shifts represent an estimate of the latitude increase or decrease that a species would need to make to remain in the same temperature range. A figure comparing the observed and expected elevation and latitudinal range shifts for the taxonomic groups was constructed.
          The authors found that taxonomic groups shifted their boundaries north of the Equator at a median rate of 16.9 kilometers per decade and that species shifted to higher elevations by a median rate of 11.0 meters per decade. A previous meta-analysis study, which looked at individual species rather than taxonomic groups per region, reported that species’ shifts were increasing north of the Equator at a rate of 6.1 kilometers per decade and to higher elevations at a rate of 6.1 meters per decade. Chen et al.’s new rates suggests that species’ range shifts are moving at a much faster rate, indicating that terrestrial species are responding to climate change more rapidly than previously proposed.
          Most significantly, Chen et al. found a correlation between the observed range shifts of the taxonomic groups and their expected range shifts. Although other studies suggest that species lag in their response to warming temperatures, nearly equal amounts of taxonomic groups have exceeded expected range shifts as have fallen below in response to climate change. In contrast, the observed distances moved in elevation by species are much shorter than those proposed by the expected range shifts. This may be due to a variety of factors that include difficulty of movement at higher elevations and directional climate complexities found on mountainsides.
          Interestingly, although 75% of species moved north, 22% of species shifted southwards in latitude against expectations. Similarly, 25% of species shifted to lower elevations instead of following expected range shifts to higher elevations. Chen et al. identified three processes that could account for the diversity of species’ range shifts. These processes include time delays in species’ responses to climate change, physiological limits, and other interacting drivers of change. For example, some species may lag behind in response to climate change if they specialize in a certain habitat or if they are immobile. Other species may exhibit different responses to increasing temperatures at different stages in their life cycles. Species’ ranges may also be determined by non-climatic driving factors such as competition with other species and habitat loss.
          Although further studies investigating the physiological, ecological, and environmental drivers of species boundaries are needed to assess the variation in range shifts found in this study, Chen et al.’s findings overall suggest that species’ ranges are shifting faster than reported and that these range shifts are connected to rising temperatures worldwide. 

Rapid Range Shifts of Species Associated with High Levels of Climate Warming

Changes in climate are impacting biodiversity on a global scale. Recent evidence has suggested that numerous terrestrial species are shifting their geographic ranges to higher elevations and latitudes in response to warming temperatures. However, previous studies have yet to demonstrate a direct link between the warming climate and species’ range shifts. Using a combination of data from several studies, Chen et al. (2011) analyzed the mean latitude range shifts across species of 23 taxonomic groups per region and the mean elevation range shifts across species of 31 taxonomic groups per region. The authors then compared these observed range shifts to expected range shifts necessary for taxonomic groups to remain in the same average temperature zone. The results suggest that the rates of terrestrial range shifts in latitude and elevation are two to three times faster than previously described. Additionally, the authors found that the observed latitudinal and elevation range shifts were correlated with the expected range shifts, suggesting a causal relationship between warming temperatures and terrestrial species’ range shifts. Despite these results, there was variation in the directional range shifts among species, indicating that other internal and external factors influence terrestrial species distributions.—Megan Smith
Chen, I., Hill, J.K., Ohlemuiler, R., Roy, D.B., Thomas, C.D., 2011. Rapid Range Shifts of Species Associated with High Levels of Climate Warming. Science 333, 1024-1026.

          Chen et al. collected data from previous studies to analyze the current rates of elevation and latitudinal range shifts of terrestrial taxonomic groups. Though other studies investigated the range shifts of individual species, the authors averaged the response of a taxonomic group in a specific region and used this mean as a single observation (i.e. plants in Switzerland). These authors determined range shifts by comparing the differences between two temporally separated recordings of a taxonomic group’s range margins (the average of a group’s upper/cold and lower/warm temperature range). The latitudinal shift of taxonomic groups was categorized as poleward, stable, or Equatorward while the elevation shift was categorized as up, stable, or down. A figure showing the observed latitudinal shifts of the northern range boundaries of species of four taxonomic groups in Britain was constructed.
          The authors extracted regional temperature increases from previous studies or identified the time periods and locations of the regions using CRU_TS2.0 data at 0.5° resolution. They gridded each region and then averaged the temperature across the grid cells to obtain a mean yearly temperature for the area in question. The regional temperature increase over each time period was then obtained by measuring the change in temperature between two temporally separate recordings. 
          The authors then derived the expected range shifts of the study’s taxonomic groups to assess the possible link between the changing climate and terrestrial species’ range shifts. Chen et al.calculated the expected elevation range shift by first computing the lapse rate, which is the decrease in degrees Celsius per increase in meters. For each region, Chen et al. divided the regional temperature increase by the lapse rate to calculate an estimate of the elevation increase or decrease a taxonomic group would have to make to remain within the same temperature range.
          Latitudinal range shifts were estimated by first calculating the temperature-distance transfer rate, which is the decrease in degrees Celsius per increase in kilometer of latitude, using CRU_CL2.0 data on a global 10’ grid. After gridding each region, the authors identified the nearest cell that was 0.5°C cooler than an original cell. The transfer rate was computed by dividing the temperature difference between the two cells by the latitudinal distance in kilometers between the cells. Then, Chenet al. averaged these measurements across every cell in the region to obtain the final transfer rate. The expected latitudinal shifts were determined by dividing the regional temperature increase by its corresponding transfer rate. These shifts represent an estimate of the latitude increase or decrease that a species would need to make to remain in the same temperature range. A figure comparing the observed and expected elevation and latitudinal range shifts for the taxonomic groups was constructed.
          The authors found that taxonomic groups shifted their boundaries north of the Equator at a median rate of 16.9 kilometers per decade and that species shifted to higher elevations by a median rate of 11.0 meters per decade. A previous meta-analysis study, which looked at individual species rather than taxonomic groups per region, reported that species’ shifts were increasing north of the Equator at a rate of 6.1 kilometers per decade and to higher elevations at a rate of 6.1 meters per decade. Chen et al.’s new rates suggests that species’ range shifts are moving at a much faster rate, indicating that terrestrial species are responding to climate change more rapidly than previously proposed.
          Most significantly, Chen et al. found a correlation between the observed range shifts of the taxonomic groups and their expected range shifts. Although other studies suggest that species lag in their response to warming temperatures, nearly equal amounts of taxonomic groups have exceeded expected range shifts as have fallen below in response to climate change. In contrast, the observed distances moved in elevation by species are much shorter than those proposed by the expected range shifts. This may be due to a variety of factors that include difficulty of movement at higher elevations and directional climate complexities found on mountainsides.
          Interestingly, although 75% of species moved north, 22% of species shifted southwards in latitude against expectations. Similarly, 25% of species shifted to lower elevations instead of following expected range shifts to higher elevations. Chen et al. identified three processes that could account for the diversity of species’ range shifts. These processes include time delays in species’ responses to climate change, physiological limits, and other interacting drivers of change. For example, some species may lag behind in response to climate change if they specialize in a certain habitat or if they are immobile. Other species may exhibit different responses to increasing temperatures at different stages in their life cycles. Species’ ranges may also be determined by non-climatic driving factors such as competition with other species and habitat loss.

          Although further studies investigating the physiological, ecological, and environmental drivers of species boundaries are needed to assess the variation in range shifts found in this study, Chen et al.’s findings overall suggest that species’ ranges are shifting faster than reported and that these range shifts are connected to rising temperatures worldwide.