Landscape Dynamics: Natural Range of Variability

Transcription

1 Landscape Dynamics: Natural Range of Variability

2 Origins of Natural Range of Variability The backdrop Shifting ecological paradigms: from the equilibrium to dynamic view Disturbance and succession processes drive natural variability in ecosystem/ landscape structure, composition, and function! Variability is a better descriptor of ecosystem/ landscape dynamics than the central tendency or the climax condition!

3 Origins of Natural Range of Variability The backdrop Emergence of ecosystem management and the shift from T&E species to ecosystem integrity Ecosystem integrity T&E species Fine filter Biodiversity Conservation Coarse filter Ecosystem management required a baseline or reference and historical ecology appeared to be the best reference

4 Origins of Natural Range of Variability First attempts Designed target stand conditions from historical evidence: Recreated historical stand structures Selected an appropriate stand structure Designed a silvicultural or Rx burn treatment Implemented treatment to create contemporary stand

5 Origins of Natural Range of Variability First attempts problems Target stand approach encountered many problems: Wrong scale for effective management Selected condition mostly arbitrary Difficult and inappropriate to treat entire landscape with one treatment Did not recognize inherent variability

6 Origins of Natural Range of Variability First attempts revelations Incorporating ecological variability into management is key to maintaining ecosystem integrity: Ensures optimal biodiversity Recognizes the roles of disturbance Widens the options for management Maintains ecosystem resilience

7 Origins of Natural Range of Variability First attempts revelations Incorporating ecological variability into management is key to maintaining ecosystem integrity Use variability to set acceptable thresholds State variable (landscape attribute) Don t use the average Time

8 Foundations of NRV The seminal publication Landres et al (1999): Collection of papers that serve as the foundation of the NRV concept None of the papers dealt with application Many papers have been written since Concept is still in a state of flux NRV still has many problems in implementation Is it still viable with rapid climate change?

9 Foundations of NRV Premises Ecosystems are naturally dynamic and native species have adapted to disturbance-driven fluctuations in their habitats. Therefore, the potential for survival of any given species may diminish if temporal and spatial patterns of species habitats shift outside their natural range of variation.

10 Foundations of NRV Premises Approximating historical conditions provides a coarse-filter management strategy that is likely to sustain the viability of diverse species, even those for which we know little about. Similarly, because of limited understanding about ecosystems, approximating past conditions offers one of the best means for predicting and reducing impacts to presentday ecosystems.

11 Foundations of NRV Premises Managing within the constraints of site variability and history is easier, requires fewer external subsidies, and is more cost effective than trying to achieve management goals that are outside the bounds of the system. 6 million dollars/mile/decade

12 Foundations of NRV Premises Natural variability is a useful reference for evaluating the influence of anthropogenic change in ecological systems, including lakes, commodity production lands, and protected areas such as wilderness.

13 Foundations of NRV Premises Analysis of an ecological system at different sites and over long time frames provides the context that is important in understanding the driving variables, constraints, and behavior of a system. Such analysis yields essential understanding about the dynamic ecological processes that drive both spatial and temporal variation in ecological systems...

14 Foundations of NRV Premises Spatial (and temporal) heterogeneity per se is an important component of ecological systems. Reducing spatial (and temporal) variability typically results in declining biological diversity, increased vulnerability to insects, pathogens, or other disturbances, and decreased resiliency to subsequent disturbances.

15 Natural Range of Variability Definition The ecological conditions, and the spatial and temporal variation in these conditions, that are relatively unaffected by people, within a period of time and geographical area appropriate to an expressed goal. (Landres et al. 1999) Key attributes: Any ecological attribute Spatial or temporal variability Defined reference period Defined geographic area Goal oriented

16 Natural Range of Variability Variations on a theme Natural Range of Variability (NRV) = variability unaffected by people Social Range of Variability (SRV) = variability that society finds acceptable Historical Range of Variability (HRV) = natural variability in the past Future Range of Variability (SRV) = variability in the future determined by natural and human forcings

17 Natural Range of Variability Planning rule 2012 Forest Service Planning Rule: "Plan decisions affecting ecosystem diversity must provide for maintenance or restoration of the characteristics of ecosystem composition and structure within the range of variability that would be expected to occur under natural disturbance regimes of the current climatic period" (36 CFR ) In practice, HRV has been deemed the best approach to meet the planning rule requirement

18 How is NRV/HRV Used? 1. Communicating variability Communicating the dynamic view of the system and the importance of variability to stakeholders builds support for management Change within limits is good Disturbances are natural & necessary Management can emulate disturbances

19 How is NRV/HRV Used? 2. Reference for understanding Understanding system drivers and synthesizing ecological knowledge helps us determine the ingredients of an integral system, and to better forecast future system behavior

20 AI How is NRV/HRV Used? 3. Establishing desired future conditions Providing detailed and specific desired future conditions to guide project-level planning Landscape metric Percentiles of HRV 5 th 50 th 95 th LPI AREA_AM 1, , , GYRATE_AM 2, , , SHAPE_AM DCORE_AM Detailed and specific DFCs are critical to adaptive management CAI_AM TECI ED CWED

21 How is NRV/HRV Used? 3. Establishing desired future conditions Remember, NRV/HRV does not (should not) dictate the desired future condition of any single stand (wrong scale), but rather the desire range of conditions among stands across the entire landscape (right scale)

22 How is NRV/HRV Used? 4. Determining current departure Determining magnitude and nature of current departure and prioritizing treatments to restore NRV/HRV

23 How is NRV/HRV Used? 4. Determining current departure LANDFIRE was initially established to quantify and map current departure in fire regime (Fire Regime Condition Class) as the basis for prioritizing areas for treatment (and allocation of funding) Fire Regime Condition Class Changes in species composition & structure 1 Largely intact Return interval (Increase or Decrease) Little to none Fire Regime Changes Size, intensity, severity, & landscape patterns Little to none 2 Moderately altered One or more Moderate 3 Significantly altered Multiple Dramatic

24 How is NRV/HRV Used? 4. Determining current departure Remember, NRV/HRV does not (should not) dictate whether individual stands are departed (wrong scale), but rather the departure of the entire landscape (right scale)

25 How is NRV/HRV Used? 5. Benchmark for scenario analysis Providing a benchmark to evaluate relative impacts of alternative (future) management scenarios MS7 scenario isn t too bad!

26 Connectors How Quantify NRV/HRV? 1. Define geographic extent Define the landscape extent based on the specific objectives and the scale at which desired future conditions are being established

27 Connectors How Quantify NRV/HRV? 1. Define geographic extent Note, range of variability decreases with landscape extent Sunset Sanfran Peaks San Francisco Peaks, AZ

28 Connectors How Quantify NRV/HRV? 1. Define geographic extent Note, range of variability decreases with landscape extent Coast Range, OR Province (2,25 mil ha) Siuslaw NF (0.3 mil ha) LSOG Reserve (40,000 ha) Wimberly et al. (2000)

29 Connectors How Quantify NRV/HRV? 1. Define geographic extent Why? Asynchrony in disturbances across large landscapes, creating a shifting mosaic and dampening the variability Spruce-fir Stand Initiation Percent of Landscape San Juan NF, CO Doldist Hermosa Piedra Percent Doldist Hermosa Piedra SJNF Time Step (x10 yrs) SJNF

30 Connectors How Quantify NRV/HRV? 1. Define geographic extent What is the optimal landscape size? Composition San Juan NF, CO Districts Watersheds Forest Coefficient of Variation (%) Configuration Landscape extent (ha)

31 Connectors How Quantify NRV/HRV? 1. Define geographic extent What is the optimal landscape size? Karau and Keane (2007) 30m 90m 300m 900m Percent Area Burned (ln(s 2 )) Landscape Size (km 2 ) Flat landscapes Percent Burned Area (ln(s 2 )) Mountainous landscapes Landscape Size (km 2 )

32 Connectors How Quantify NRV/HRV? 1. Define geographic extent What is the optimal landscape size? Fire Size (km 2 ) Fire Freq Mountainous Landscape Flat Landscape Half Karau and Keane (2007) Historical Double Half Historical Double Half Historical Double

33 Connectors How Quantify NRV/HRV? 1. Define geographic extent What is the optimal landscape size? Not too small: Variability too great Ecologically meaningless Not too large: Cross ecoregion boundaries Ecologically meaningless Treatments undetectable ln(s 2 ) Landscape Extent Sweet spot is probably several times larger than largest disturbance events

34 Connectors How Quantify NRV/HRV? 1. Define geographic extent Be cautious extrapolating results to different landscapes given idiosyncracies of landscape context Sanfran Sunset Peaks Vertical shift in the ROV is due to unique landscape characteristics

35 Connectors How Quantify NRV/HRV? 2. Define reference period Natural variability should be assessed over relatively consistent climatic, edaphic, topographic, and biogeographic conditions (Morgan 1994). Period of relative climate stability (not to be confused with lack of variability) Minimal human influence (usually interpreted to mean Euro-Americans) Sufficient data record (quality and length, ideally over multiple disturbance cycles)

36 Connectors How Quantify NRV/HRV? 2. Define reference period Note, range of variability increases with length of reference period British Columbia Spruce-fir Larch/Doug-fir Hallett et al. (2003)

37 Connectors How Quantify NRV/HRV? 2. Define reference period Why? Climate variability, which largely drives disturbance regimes, increases with length of time due to longer term climate changes Mann et al. (2008)

38 Connectors How Quantify NRV/HRV? 2. Define reference period Not too recent or short: Human influence too great Not enough variability Ecologically meaningless Not too distant or long: Biogeographic instabilities Not enough data What is the optimal reference period and length? Ecologically meaningless ln(s 2 ) Poor data Pre-settle, stable climate, good data Time bp Settlement Sweet spot is probably pre-euro-american settlement and several times length of disturbance cycles

39 Connectors How Quantify NRV/HRV? 3. Select state variables Select state variables to characterize patterns and/or processes that are measurable and relevant to the specified objective Typical state variables: Landscape composition proportion of cover types, seral stages, etc. Landscape configuration spatial arrangement of composition Ecological process flow of energy (e.g., organisms, disturbances)

40 Connectors How Quantify NRV/HRV? 4. Quantify variability Quantify variability in the state variables Alternative approaches: Chronological sequence... multiple records over time of an attribute in one place Spatial sequence... multiple records of an attribute across space at one point in time Simulation sequence multiple records of an attribute across all places at all points in time

41 Connectors How Quantify NRV/HRV? Simulation approach Why use simulation (landscape disturbance-succession model, LDSM) to quantify variability in the state variables Ensures spatial consistency Includes spatial effects Derives long time series Expands spatially and temporally inconsistent data Integrates processes Includes other factors (e.g., land use, exotics)

42 Connectors How Quantify NRV/HRV? Simulation modeling Landscape disturbance-succession models (LDSMs) are simplified abstract representations of reality Typically include only dominant disturbance processes (fire) Interactions among processes poorly represented, if at all More complex models aren t necessarily better!

43 Connectors How Quantify NRV/HRV? Simulation modeling Not prognostic or predictive Not well suited for individual events Simulate statistical properties of regimes Data and computer intensive LDSMs are stochastic, requiring long and/or many replicate simulations to generate the intended statistical properties of the outputs

44 Connectors How Quantify NRV/HRV? Simulation modeling Model parameter uncertainty induces uncertainty in the model outcomes Just how accurate is that HRV? Guestimation Local empirical data Science Local expertise

45 Connectors How Quantify NRV/HRV? Simulation modeling Landscape boundary (depending on openness) and spatial context can effect results if not dealt with properly Must account for immigration and emigration of disturbances Include buffer around landscape (e.g., 2-10 km wide depending on disturbance regime) Keane (2013)

46 Connectors How Quantify NRV/HRV? Simulation modeling Model calibration should focus on the independent variables (disturbance regime drivers), not the dependent variables (vegetation response) Independent variable Dependent variable Disturbance Vegetation patterns Controlled by design Response/outcome

47 Connectors How Quantify NRV/HRV? Simulation modeling Model calibration should focus on the independent variables (disturbance regime drivers), not the dependent variables (vegetation response) Fire Rotation Period (FRP) Cover type Area (ha) Simulated Target Delta Sierran Mixed Conifer - Mesic 57, % Sierran Mixed Conifer - Xeric 52, % Oak-Conifer Forest & Woodland 23, % Red Fir - Mesic 8, % Red Fir - Xeric 7, % Mixed Evergreen - Mesic 7, % Mixed Evergreen - Xeric 6, % Sierran Mixed Conifer - Ultramafic 4, % Grassland 1, % Meadow 1, % Oak-Conifer For. & Wdl - Ultramafic 1, % Total 174, %

48 Connectors How Quantify NRV/HRV? Simulation modeling Verify that behavior is within empirically known bounds Verify that modeled behavior is consistent with known ecological system behavior Validate process components Model validation requires tests against independent data not used in building the model; difficult to validate predictions made over large areas and long time scales

49 Connectors How Quantify NRV/HRV? Simulation modeling NRV/HRV can only be meaningfully described if a stable range of variability is defined and realized in the outputs What range to use? Is it stable; i.e., unchanging for long enough to be meaningful? Usually 3 or more disturbance cycles

50 How to Quantify Current Departure? What is departure? Current departure is an estimate of the magnitude of deviation between the current value of the state variable and its NRV/HRV

51 How to Quantify Current Departure? Interpretation challenges How to measure the deviation between the current and RNV/HRV? What standard to use? Percentiles of RNV/HRV 0 % 0 % 5 % 10 % 25 % 50 % 75 % 95 % 100 % Current (z c ) Raw values of RNV/HRV (z c % = current value expressed as percentile; D1 is bounded -1, 1) (z q = raw values at q th percentile; D2 is unbounded)

52 How to Quantify Current Departure? Simulation challenges Model equilibration is the process of bringing the current state variable into the NRV/HRV maintained by the simulated disturbance & succession processes Magnitude and duration of equilibration departure How much is due to true departure versus other causes??

53 How to Quantify Current Departure? Simulation challenges One cause of apparent departure is inconsistency between model input GIS data resolution and model outputs Model input Model output Partial solutions: Coarsen model output to match input? Limit departure to composition and/or area-weighted metrics?

54 How to Quantify Current Departure? Simulation challenges How to interpret apparent departure from NRV/HRV?? True departure in landscape condition! NRV/HRV? Inconsistent spatial resolution between input and output layers? Departure?? Misspecification of model parameters? Current

55 Challenges to NRV/HRV Practical issues 1. Site-specific data may be lacking, requiring extrapolation from other areas and a great deal of expert opinion to fill the knowledge gaps True, but its better than nothing Guestimation Local empirical data Science Local expertise

56 Challenges to NRV/HRV Empirical issues 2. There may be insufficient temporal depth of data, precluding a reconstruction of historical conditions for a sufficiently long reference period, and the estimates become more uncertain further back in time, making the analysis of long-term trends difficult OK, but can we assume the observed record is representative of the reference period?

57 Challenges to NRV/HRV Empirical issues 3. The spatial patterns of disturbances are poorly described with confidence from historical data, resulting in weak information about the spatial variation of past conditions OK, but we can verify that simulated disturbance patterns are consistent with contemporary observations

58 Challenges to NRV/HRV Conceptual issues 1. Native and contemporary people have so altered natural systems that there are no pristine natural areas left, making information derived from the past difficult to interpret or irrelevant 1600s Present This may be true in some areas like the eastern US

59 Challenges to NRV/HRV Conceptual issues 2. Each point in time and space is unique, and dominant climate patterns are rapidly changing, therefore a description of past patterns and processes is largely irrelevant today or in the future But what s the alternative?

60 Challenges to NRV/HRV My prognosis NRV/HRV is the best approach we have today and will likely remain so for quite a while! At the very least, it provides an informative benchmark to help us better understand the current landscape However, it provides a guide for desired future conditions that probably has the best change of achieving the goal of ecological integrity and biodiversity conservation