All subgroups identified monitoring climate conditions as fundamental variables of interest. This highlights a widely shared need for improved downscaled climate projection products, informed by a network of observation stations sufficient to capture the spatial variation in regional temperature, precipitation, and wind fields. Water-related topics appeared most frequently in the reports of the sub-groups. Often, the topics incorporated aspects of hydrology and other disciplines (e.g., surface storage and active layer thaw, stream discharge and sediment transport/deposition). Hydrologic-related topics identified by the fish and bird sub-groups were most similar, reflecting overlap in the habitat requirements of fish and the large proportion of arctic-breeding bird species dependent on aquatic systems. In contrast, the hydrologic topics most relevant to terrestrial mammals were related to snow conditions and indirect effects of water on vegetation phenology and plant community composition. Unlike most bird species, mammals and many fish live year-round in arctic environments where the snow season prevails for most of the year. and fish sub-groups also identified coastal processes and aquatic invertebrate phenology and abundance as being important, whereas the mammal group did not. Changing seasonality (phenology) was identified as a separate category because the general was of interest to all sub-groups, even though the specific indicators varied. With the exception of insect emergence, the identified indicators can be monitored via remote sensing, and the required activities are mostly in the realm of image processing, image interpretation, and trend analysis. Correlating changing phenology with changing climate, however, requires an adequate weather monitoring network and availability of reliable interpolated gridded climate data products. In summary, despite the complexity with which climate interacts with all components and processes of the arctic terrestrial ecosystem, the working group was able to identify a limited list of cross-cutting themes. Recommendations regarding field measurements and modeled data products most needed by biologists to address those themes are contained in the individual summaries for each sub-group. These are contained in the tables and accompanying narratives that follow.
Kivalina 50 Point Hope 77 Point Lay 72 Noatak 18 Nuiqsut 32 Wainwright 69 *small but important part of the diet Table 3. Most frequently harvested terrestrial and freshwater species (or species groups) by subsistence users in northern Alaska, listed by community. (ADF&G 2001, Bacon 2009, Fuller and George 1997). Community Mammals Birds Fish Caribou Arctic Fox Arctic Ground Squirrel Dall’s Sheep Ptarmigan spp. Gr. White-fronted Goose Canada Goose Eider spp. Black Brant Murre spp. Grayling Dolly Varden/Char Broad Whitefish Humpback Whitefish Arctic Cisco Least Cisco Rainbow Smelt Coastal Kivalina X X X Point Hope X X X X X X Point Lay X X X X X X X X X X Wainwright X X X X X X X X Barrow X X X X X X Nuiqsut X X X X X X X X X X Kaktovik X X X X X X X X X X Inland Noatak X X X X Atqasuk X X X X X X X X Anaktuvuk Pass X X X X X X X Arctic Village X X X X X X
Biological Processes Monitoring Accurate predictions of climate change effects on fish cannot be made without sufficient information about the underlying biological processes that drive aquatic ecosystem functions. Monitoring changes in physical parameters will be most useful if conducted in conjunction with field-based observations and focused studies to clarify the mechanisms by which environmental variables influence populations. Baseline information on presence, abundance, life history traits, and genetic diversity of fish populations in representative watersheds must be collected and analyzed over time. While studies of arctic fish populations have been conducted in the past, a more complete body of knowledge is required before the true effects of climate change on habitat use and population success can be assessed. Future work with invertebrate productivity and shifts in the aquatic invertebrate community, measuring fish productivity, age and length at maturity, timing and extent of seasonal migrations and population status, as well as primary productivity within drainage systems would allow for evaluating the effects of habitat change on biological processes. Information on spatial variation (population-level adaptive variation) would be useful in assessing adaptive potential and whether or not some populations may be more successful in responding to change. For example, fish may be able to distribute more widely and exploit more available habitat during longer summer migratory periods, but this will go unnoticed if appropriate reference baseline information is unavailable. Increased competitive interactions with species expanding their range northward may occur, if species share habitat and have similar life history, foraging and spawning behavior, although the timeline and degree of competition is highly uncertain. Understanding the response to climate-associated habitat change may be difficult if baseline distribution, habitat use, feeding strategies, or life history traits are not sufficiently documented before these changes occur. Group members acknowledged that interspecific interactions are important, but recognized that understanding these as a function of climate change adds a level of complexity requiring understanding of physical process change, as well as biotic responses, which may be highly individualistic.
Changes in water chemistry and quality, including but not limited to: pH, dissolved oxygen, dissolved carbon and nitrogen, light levels, turbidity, alkalinity, chlorophyll-a levels, and zooplankton abundance. Potential negative outcomes: direct physiological stresses such as increased parasite load, increased metabolic demands, and increased rate of contaminant uptake indirect physiological stresses such as restriction of movement and migration, especially when coupled with changes in temperature regimes and prey availability All freshwater species Monitor chemistry in representative watersheds throughout seasons. Maintain existing long term datasets of water quality and characteristics, including timing and intensity of breakup, any drying events, and timing of freeze-up (Kuparuk River, Hulahula River, Judy/Fish Creek, Chipp/Ikpikpuk rivers/Teshepuk Lake) for time series analysis. Monitor changes in level productivity, including aquatic invertebrates. Coastal Processes and Change in Sea Level Increased coastal erosion: Potential positive outcomes: increased ease of anadromous migration and coastal migrations between feeding and overwintering habitat Potential negative outcomes: loss of terrestrial habitat, increased lake drainage, conversion of freshwater to saline habitat, restriction of movement/migration of freshwater adults and juveniles Salmon species, whitefish species including ciscos, Dolly Varden, freshwater species esp. in early spring Remote sensing of coastal habitat Monitoring of lagoon water chemistry. Measure and monitor total river discharge to assess freshwater and sediment delivery to estuarine areas. BIOPHYSICAL PROCESSES – FISH What Species or Species Groups May Be Affected? What biophysical parameters to measure/model? Change in Glacial
Longer Growing Season Earlier ungulates, lemmings + voles, squirrels, hares, porcupines, grizzly bears, weasels, foxes + wolves Assemble retrospective NDVI data with date-stamped values at finest spatial and temporal scale practical for the entire LCC domain. Develop retrospective datasets of greenness and progression at finest spatial and temporal scales practical. Ongoing updates and dissemination of gridded NDVI data. Establish calibration algorithms among AVHRR platforms and MODIS at 1-km resolution to facilitate transition to the newer MODIS technology. Review literature and extract, or explicitly project, future changes in growing season length and validate with ongoing data collections. Develop/compile a uniform Arctic LCC wide landcover class map with quantitatively estimated accuracy; Establish relationships among existing landcover maps (i.e. pixel-level correspondence and proportional composition of land blocks of relevant size. Develop/evaluate the ability to upscale 30m landcover class pixels to larger remote sensing pixels. Establish relationships between landcover classes and NDVI dynamics at finest spatial and temporal scales practical. Prolonged plant senescence Vegetation Change Increased Vegetation Biomass ungulates, lemmings +voles, squirrels, hares, porcupines, grizzly bears, weasels, foxes + wolves All items in Section III relevant to this issue. Test for trends in date of maximum NDVI at the finest spatial and temporal scales practical, by landcover class.
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