1.     Solomina, O. N.,Bradley, R. S., Jomelli, V., Geirsdottir, A., Kaufman, D. S., Koch, J., ...& Nicolussi, K. (2016). Glacier fluctuations during the past 2000 years.Quaternary Science Reviews, 149, 61-90.

A global compilation of glacier advances andretreats for the past two millennia grouped by 17 regions (excludingAntarctica) highlights the nature of glacier fluctuations during the lateHolocene. The dataset includes 275 time series of glacier fluctuations based onhistorical, tree ring, lake sediment, radiocarbon and terrestrial cosmogenicnuclide data. The most detailed and reliable series for individual glaciers andregional compilations are compared with summer temperature and, when available,winter precipitation reconstructions, the most important parameters for glaciermass balance. In many cases major glacier advances correlate with multi-decadalperiods of decreased summer temperature. In a few cases, such as in ArcticAlaska and western Canada, some glacier advances occurred during relativelywarm wet times. The timing and scale of glacier fluctuations over the past twomillennia varies greatly from region to region. However, the number of glacieradvances shows a clear pattern for the high, mid and low latitudes and, hence,points to common forcing factors acting at the global scale. Globally, duringthe first millennium CE glaciers were smaller than between the advances in 13thto early 20th centuries CE. The precise extent of glacier retreat in the firstmillennium is not well defined; however, the most conservative estimatesindicate that during the 1st and 2nd centuries in some regions glaciers weresmaller than at the end of 20th/early 21st centuries. Other periods of glacierretreat are identified regionally during the 5th and 8th centuries in theEuropean Alps, in the 3rd–6th and 9th centuries in Norway, during the 10th–13thcenturies in southern Alaska, and in the 18th century in Spitsbergen. However,no single period of common global glacier retreat of centennial duration,except for the past century, has yet been identified. In contrast, the view thatthe Little Ice Age was a period of global glacier expansion beginning in the13th century (or earlier) and reaching a maximum in 17th–19th centuries issupported by our data. The pattern of glacier variations in the past twomillennia corresponds with cooling in reconstructed temperature records at thecontinental and hemispheric scales. The number of glacier advances also broadlymatches periods showing high volcanic activity and low solar irradiance overthe past two millennia, although the resolution of most glacier chronologies isnot enough for robust statistical correlations. Glacier retreat in the past100–150 years corresponds to the anthropogenic global temperature increase.Many questions concerning the relative strength of forcing factors that droveglacier variations in the past 2 ka still remain.

http://www.sciencedirect.com/science/article/pii/S0277379116301196

2.     Wu, Y., Wang,X., Ouyang, S., Xu, K., Hawkins, B. A., & Sun, O. J. (2016). A test ofBIOME-BGC with dendrochronology for forests along the altitudinal gradient ofMt. Changbai in northeast China. Journal of Plant Ecology.

Aims Process-based models are basic tools forpredicting the response of forest carbon to future climate change. The modelshave commonly been tested for their predictions of spatial variation in forestproductivity, but much less for their ability to predict temporal variation.Here we explored methods to test the models with tree-rings, using BIOME-BGC asan example.

Methods We used net primary productivity (NPP)data and tree rings collected from five major forest types along thealtitudinal gradient of Mt. Changbai, northeast China, to testlocal-parameterized BIOME-BGC model. We first test the model’s predictions ofboth spatial (Test 1) and temporal changes (Test 2) in productivity. Then wetest if the model can detect the climatic factors limiting forest productivityduring historical climate change, as revealed by dendroclimatic analyses (Test3).

Important Findings Our results showed thatBIOME-BGC could well simulate NPP of five forest types on Mt. Changbai, with anr2 of 0.69 between modeled and observed NPP for 17 plots along the altitudinalgradient (Test 1). Meanwhile, modeled NPP and ring-width indices werecorrelated and showed similar temporal trends for each forest type (Test 2).While these tests suggest that the model’s predictions on spatial and temporalvariation of NPP were acceptable, a further test that relate the correlationsof modeled NPP with climate variables to the correlations of ring widths withclimate (Test 3) showed that the model did not well identify the climaticfactors limiting historical productivity dynamics for some forest types, andthus cannot reliably predict their future. Both dendrochronology and BIOME-BGCshowed that forest types differed markedly in the climate factors limitingproductivity because of differences in tree species and climate condition, andthus differed in responses to climate change. Our results showed that asuccessful prediction of spatial NPP patterns cannot assure that BIOME-BGC canwell simulate historical NPP dynamics. Further, a correlation between modeledNPP and tree-ring series cannot assure that the limiting climatic factors forproductivity have been correctly identified by the model. Our results suggestthe necessity to test the temporal predictions of process-based models in amore robust way, and further integration of dendrochronology andbiogeochemistry modeling may be helpful for this purpose.

http://jpe.oxfordjournals.org/content/early/2016/07/29/jpe.rtw076.abstract

3.     Churakova, O.V., Saurer, M., Bryukhanova, M. V., Siegwolf, R. T., & Bigler, C. (2016).Site-specific water-use strategies of mountain pine and larch to cope withrecent climate change. Tree Physiology.

We aim to achieve a mechanistic understandingof the eco-physiological processes in Larix decidua and Pinus mugo var.uncinata growing on north- and south-facing aspects in the Swiss National Parkin order to distinguish the short- and long-term effects of a changing climate.To strengthen the interpretation of the δ18O signal in tree rings and itscoherence with the main factors and processes driving evaporative δ18O needlewater enrichment, we analyzed the δ18O in needle, xylem and soil water over thegrowing season in 2013 and applied the mechanistic Craig–Gordon model (1965)for the short-term responses. We found that δ18O needle water stronglyreflected the variability of relative humidity mainly for larch, while onlyδ18O in pine xylem water showed a strong link to δ18O in precipitation. Largerdifferences in offsets between modeled and measured δ18O needle water for bothspecies from the south-facing aspects were detected, which could be explainedby the high transpiration rates. Different soil water and needle waterresponses for the two species indicate different water-use strategies, furthermodulated by the site conditions. To reveal the long-term physiologicalresponse of the studied trees to recent and past climate changes, we analyzedδ13C and δ18O in wood chronologies from 1900 to 2013. Summer temperatures aswell as summer and annual amount of precipitations are important factors forgrowth of both studied species from both aspects. However, mountain pine treesreduced sensitivity to temperature changes, while precipitation changes come toplay an important role for the period from 1980 to 2013. Intrinsic water-useefficiency (WUEi) calculated for larch trees since the 1990s reached asaturation point at elevated CO2. Divergent trends between pine WUEi and δ18Oare most likely indicative of a decline of mountain pine trees and are alsoreflected in decoupling mechanisms in the isotope signals between needles andtree-rings.

http://treephys.oxfordjournals.org/content/early/2016/07/28/treephys.tpw060.abstract

4.     Chhetri, P. K., Bista,R., & Cairns, D. M. (2016). Population structure and dynamics of Abiesspectabilis at treeline ecotone of Barun Valley, Makalu Barun National Park,Nepal. Acta Ecologica Sinica, 36(4), 269-274.

The population structure and dynamics of highaltitude, long-lived treeline species can be utilized as an indicator forclimate change. This study was conducted in the treeline ecotone of the BarunValley, eastern Nepal in order to understand the population dynamics of Abiesspectabilis. The A. spectabilis population showed the reverse J-shaped size andage distribution curves indicative of undisturbed old growth forest. The agestructure is mostly dominated by the young individuals, however, theirmortality was found to be very high. Positive relationships between recruitmentand high temperatures during winter months (January, February and December) andone summer month (August) were discovered. No significant relationship wasfound between precipitation and climate of the region. If warming conditionprevails in summer and winter seasons in the near future, then there is chancethat more individuals will be established above the treeline area, triggeringthe treeline advance.

http://www.sciencedirect.com/science/article/pii/S1872203215300263?np=y

5.     Rodríguez‐Catón, M., Villalba, R., Morales, M., & Srur, A. (2016).Influence of droughts on Nothofagus pumilio forest decline across northernPatagonia, Argentina. Ecosphere, 7(7).

Understanding the influence of climaticvariations on forest decline is a major challenge for scientists investigatingglobal changes. Although reductions in tree growth have previously beenassociated with forest decline, comprehensive efforts to understand theserelationships are rare. Based on ring-width variations, we determine the influenceof climatic fluctuations on the onset and temporal evolution of Nothofaguspumilio forest decline in the Patagonian Andes. Basal area increment (BAI) datafrom 294 Nothofagus trees at 11 stands in a 500-km latitudinal transect alongthe forest–steppe ecotone were used to identify the dominant patterns ofregional growth. Three Regional dominant patterns, showing common variations inBAI, were derived. Two BAI patterns show high rates of growth from early tomid-20th century, followed by sustained negative trends over the last 3–6decades, whereas the third pattern is characterized by a positive trend sincethe 1960s. Tipping points in growth trends of the first two patterns areassociated with two extreme dry–warm climate events in spring–summer of 1942–1943/1943–1944/1944–1945and 1978–1979. Both severe droughts were preceded by up to 10 yr of wet periodsthat promoted above-average tree growth. We concluded that severe droughtsoccurring after wet periods trigger the decline of large, dominant N. pumiliotrees with high rates of growth. The coincidence between major changes inregional growth with two of the most severe droughts in the instrumentalrecords shows that climatic variations over northern Patagonia synchronize thebeginning of forest decline at a regional scale. As these dry–mesic N. pumiliosites will face more severe droughts in the 21st century, as suggested byfuture climate scenarios, the areas affected by forest decline would increasesubstantially.

http://onlinelibrary.wiley.com/doi/10.1002/ecs2.1390/full

6.     Tomscha, S. A.,Sutherland, I. J., Renard, D., Gergel, S. E., Rhemtulla, J. M., Bennett, E. M.,... & Clark, E. E. (2016). A Guide to Historical Data Sets forReconstructing Ecosystem Service Change over Time. BioScience.

Ecosystem services (ES) span the interface ofsocial and ecological systems, which makes them inherently challenging tomeasure. Tracking ES patterns over long time frames is crucial forunderstanding slow variables and complex interactions, but long-term studies ofES are rare. Historical records can play an important role in revealingtemporal patterns of ES, but because they rarely measure ES directly,historical ES reconstruction presents new practical challenges. Furthermore,long-term data are limited in availability, quality, and structure. We reviewthe utility, strengths, and challenges of some unconventional historical datasets with the potential for long-term ES tracking (e.g., aerial photography,oral history, tree rings.). We link each type of data to a simple ES frameworkthat distinguishes ES capacity, ES flows, and ES demand. Using multiplehistorical data sets in parallel may enhance our understanding of ESsustainability and ES interactions.

http://bioscience.oxfordjournals.org/content/early/2016/07/19/biosci.biw086.abstract