|Variable Component Type||Environmental Common|
|Theme||Knowledge and uncertainty (learn about themes)|
|Question||How predictable is the availability or prevalence of this commons within years?|
|Select Options||1 Low, 2 Moderate, 3 High|
|Importance||Intra-annual predictability affects the extent to which resource users and/or managers can have an understanding of biophysical dynamics and thus plan for their management within a year. Greater certainty (or more predictability) increases the likelihood that actors manage their resources sustainably.|
"The extent to which it is possible to predict the availability of a resource within a given year. Generally forms an inverse relationship with the level of uncertainty across months and/or seasons. Low: Within year variation does not follow a discernible pattern High: Within year variation is low or follows a known pattern"
|Uncertainty and depletion of natural resources||Low|
|Common property quotas||Low|
|Western Atlantic Bluefin Tuna||High (3)||There is little seasonal variation in resource availability.|
|Galapagos Sea Cucumber||High (3)||With no fishing, little variation in numbers within a given year Density-dependent for reproduction - and density required is unknown.|
|Forests in Indonesia||High (3)||Like most forests, there is little intrannual change in the prevalence of the forest, although some specific non-timber forest products are seasonal. As with inter-annual predictability, forest fires, which are not fully predictable, may affect the availability of this commons unexpectedly.|
|Eastern Atlantic Bluefin Tuna||High (3)||Very little variation in resource numbers within a given year.|
|Ozone Depleting Substances||High (3)|
|Rhine Point source pollutants||Moderate (2)||Pollution by the chemical industry can be moderately predicted in the mid-term by the economic activity of the industry and the nation in general.|
|Rhine Non-point source pollutants||Moderate (2)||Pollution by the agricultural sector (main source of diffuse pollution) can be moderately predicted in the mid-term by the economic activity of the sector and the nation in general.|
|GBR coral cover||High (3)|
|GBR target fish|
|GBR target fish||Moderate (2)|
|Patagonian Toothfish||Low (1)||Note that most toothfish fisheries operate in a limited window of time (usually over the course of a few months), thus the scientific information on toothfish is largely based on an annual snapshot with very little information gathered about toothfish during the rest of the year. As a result, there are still major gaps in the life history knowledge of toothfish. For example, for many populations, their reproductive and spawning cycle (which usually happens in the winter between June and September, while some fisheries only operate in the summer) is not well understood. For some populations of toothfish, their reproductive cycle involves spawning migrations and there is increasing evidence that mature individuals may not spawn every year (i.e. exhibiting skip spawning). Despite these gaps in their intrannual cycle, tag-recapture studies suggest that most toothfish stay close by to where they were caught (e.g., in the HIMI fishery 99% of recaptured tagged fish were caught within 30km of where they were first caught and tagged 1-3 years prior), some individual fish travel great distances (e.g., in the HIMI fishery, some fish traveled up to 1850 km from where they were caught; see Collins et al. 2010 and references therein).|
|NWHI Lobster Fishery||Moderate (2)|
|Macquarie Island Royal Penguin||High (3)||There is little variation in population within years.|
|Light Mantled Albatross||Missing||Not enough information to assess intra annual predictability.|
|Wakatobi coral cover||High (3)|
|Wakatobi Green Turtle||Moderate (2)||Availability varies according to season, but these patterns can be predicted. Also population sizes don't fluctuate too much in relation environmental factors.|
|Wakatobi fish spawning||Moderate (2)|
|Galapagos Green Turtle||Moderate (2)||Availability varies according to season, but these patterns can be predicted. Also population sizes don't fluctuate too much in relation environmental factors.|
|NWHI Trophic Density||Moderate (2)|
|Raja Ampat Reef Fish||Moderate (2)|
|Raja Ampat Coral Cover||High (3)|
|Galapagos Sharks||Moderate (2)||Similar intra-annual patterns between hammerheads, whale, and Galapagos sharks in northern bioregion: greater abundance in cooler months of the year (May-October). In warmers months abundance is greatly reduced.|
|Raja Ampat Green Turtle||Moderate (2)||Availability varies according to season, but these patterns can be predicted. Also population sizes don't fluctuate too much in relation environmental factors.|
|NWHI Green Turtle||Moderate (2)|
|California Rocky Shores Ecosystem Health||High (3)||Fairly constant populations in a well studied ecosystem. Physical habitat always there (rocks along shore), difference is population composition. Seasonality has been observed in species population trends in the rocky shore habitats, leading to more predictability (Horn et. al 1983; Foster et al. 1988, 1991).|
|California Humpback Whale||Moderate (2)||The time of year for humpbacks to exist in Sanctuary waters is expected (April to December), but sometimes migration is a little later or early (as was in 2014).|
|California Groundfish Habitat||Low (1)||Forecasts for stock size and catch are completed for future years, instead of within years. However, seasonality of fish allows for some predictability. For example, Pacific whiting is not expected in January, but would be expected in April through June (PFMC 2015). Other species such as petrel sole and other flatfish migrate seasonally from spending the winter spawning in deep water (November–February) to spending the summer in shallow water while they feed summer (March–October) (Fishwatch, 2015). However, within a year, the size of the population is not as well forecasted as for future years, but quotas are measured throughout the year to assess fishing pressure.|
|Svalbard Polar Bear||High (3)||The seasonal patterns of the polar bear are reasonably predictable, although may vary according to the weather and sea-ice conditions. Bears hibernate during the polar winter and emerge in the spring. Lønø (1970) observes that females generally enter their dens in November/December, and emerge in April.|
|Seaflower coral reefs||High (3)||Once established, coral reefs are quite stable and predictable within years|
|Seaflower groupers||Moderate (2)||Groupers are long lived species and have relatively high site fidelity.|
|Svalbard Beluga||Low (1)||Apart from one telemetry study (Lyderson et al 2001), which indicates that belugas remain close to the coasts, it is difficult to predict where pods will be observed at any particular time.|
|Svalbard Shrimp||High (3)|
|GABMP (Commonwealth Waters) Southern Right Whale||Moderate (2)||Southern right whales are a migratory species and the movements of males, non-breeding females and sub-adults are less understood than breeding females. Finding a southern right whale at any one point during the summer months when whale migration is occurring is not guaranteed. However, female whales and their calves are observed frequently from the cliffs at the Head of Bight in the near shore waters of southern Australian during the winter months.|
|GABMP (Commonwealth Waters) Benthos||Missing|
|GABMP (Commonwealth Waters) Southern Bluefin Tuna||High (3)||The availability or prevalence of this commons is predictable within years - there is little seasonal variation in commons availability.|
|King Penguin||High (3)||Colony location and breeding life cycle is well known for King Penguins. Their foraging ecology has been extensively studied and is strongly dependent on the frontal zone features, especially the Antarctic Polar Front. Because of their unusual breeding life cycle (the longest of all seabirds, lasting more than a year), there are always penguins at the colony, even though the laying period is asynchronous and has considerable variation between breeding sites and years (Bost et al. 2013 and references therein).|
|GBR Green Turtle||Moderate (2)||Turtles typically arrive at nesting grounds around the same time each year, and show strong site fidelity by returning to the same beach to nest (Limpus et al 2003). Predictability of turtle locations during the rest of the year is less predictable.|
|Cenderwasih green turtle||Moderate (2)|
|GABMP (Commonwealth Waters) Sea Lion||Moderate (2)||Duration of pupping season varies between colonies (from 5 - 8 months) - complicate assessing abundance (Shaughnessy et al. 2011)|
|Svalbard Kittiwake||High (3)||Little variation within years http://www.mosj.no/en/fauna/marine/black-legged-kittiwake.html|
|Cenderwasih target fish||Moderate (2)|
|Patagonian squid (Loligo gahi)||Moderate (2)||The fishery is managed according to real time assessment of stock size. Data is collected from fishery participants. While not perfect, a number of models and environmental monitoring have been successful in maintaing spawner escapement. In-season monitoring continues because environmental conditions and other factors (e.g. new predators) changes availability.|
|Arrow Squid (Nototodarus spp.)||Low (1)||Weak assessment, but generally can tell early on if going to be a good year. There are models for such prediction, but they are fairly new and have not been proven successful.|
|California market squid (Loligo opalescens)||Moderate (2)||Recruitment surveys help inform, but not always accurate.|
|New Zealand Sea Lion|
|Mangrove forest in Bragança, Brazil||Moderate (2)|
|Coral reefs, coast and small-island on and surrounding Gili Trawangan, Indonesia||High (3)|
|Gulf of Nicoya fisheries||Missing|
|Lombok aquaculture irrigation canals||High (3)||Seasonality (wet vs dry season) plays a strong role in the amount of water availability in the canals.|
|Cenderwasih coral cover||High (3)|
Basic:A basic variable describes essential and basic background information for a component.
Biophysical:Biophysical variables describe just that: important biophysical properties, largely of environmental commons, that are not captured by a more specific theme.
Causation:A variable with this theme describes issues of causality, which is a complex subject. Most basically this theme is associated with variables that describe different types of causation and different types of causes of environmental problems.
Context:contextual variable relates the component with which it associated to the social and/or ecological setting of a particular interaction and/or case.
Ecosystem services:Variables associated with this theme describe factors that affect or describe the provision of important ecosystem services by a natural resource.
Enforcement:Enforcement involves several different processes, including monitoring for violations of rules, sanctioning violators, and conflict resolution mechanisms involved in this process. Variables that relate to any of these processes should be attached to this theme.
External:Variables with this theme relate a component to processes external to the case with which the component is associated.
Heterogeneity:Variables with this theme describe important ways in which the member of an actor group differ from each other.
Incentives: This theme is associated with variables that are not directly related to institutions and rules, but which still play a role in affecting the incentives that commons users have to ameliorate or exacerbate the commons they use.
Institutional-biophysical linkage:This is a sub-theme of the institutions theme, and describes those variables that ask about the relationship between a set of institutions and a biophysical aspect of a commons.
Institutions:Variables with this theme describe the social institutions (rules, property rights) that are used to organize and direct human behavior. It does not include monitoring and enforcement of these institutions, as these are associated with the Enforcement theme.
Knowledge and uncertainty:Variables with this theme describe levels of knowledge that actor groups have regarding a commons, as well as factors that affect how much uncertainty there is in the status and dynamics of that commons.
Leadership:Leaders play an important role in commons management, most traditionally by providing for public goods needed to organize commons users. But there are other possible roles, and variables associated with this theme can relate to any role that a leader might play in an interaction.
Outcomes:This theme is attached to variables that deal with any outcomes that are produced by the actions of relevant actors in an interaction.
Resource renewability:Variables associated with this theme deal with the ability of a natural resource to be highly productive and renewable.
Social capital:Social capital captures the processes that enable the members of an actor group to work effectively together. Variables associated with this theme describe factors that affect or in some way express the level of social capital among members of a group.
Spatial:Variables associated with the Spatial theme describe important spatial patterns or dynamics, such as the spatial heterogeneity of a commons, or whether or not a user group resides within a particular commons.
Technology:This theme is attached to variables that consider the role that technology and infrastructure have in affecting commons outcomes.