SHC attempts to bridge the chronic gap between management and science by incorporating both facets of science, that is, science as (1) a body of knowledge and science as (2) a method of discovery.
SHC is an iterative cycle of planning, doing, learning, and planning anew:
1. Biological planning
From the pool of priority species, select a small subset of focal species that may be used to represent the status and trend of the full array.
Establish unambiguous objectives for focal species populations (the conservation of populations is our mission. Habitat management is a tool).
Make assumptions about factors limiting populations below objective levels and identify available management actions to remediate limiting factors.
Develop mechanistic models that describe the relationship between the limiting factor (management action) and the population size or change (or other measurable population attribute described in the population objective).
Apply model for each focal species/management action to spatial data to determine where a population response for that focal species can be most efficiently achieved. The outcome is a called a spatially-explicit model (SEM). Obviously these same models can often be used to assess potential policy impacts.
2. Conservation Design
When there is more than one focal species (more than one resource management priority), combine SEMs for focal species with similar management to determine potential aggregate benefit. You may also combine species which respond very differently to management to identify high priority conflict areas.
Assign every part of the ecoregion to a management action (including no management) based on it’s potential to affect focal species. This is a landscape design.
Using landscape design, estimate the minimal amount of habitat of each type needed to attain your population objectives (habitat objectives). Deviating from the landscape design (which is optimal or nearly so) will require larger amounts of habitat to attain the same population response.
Market the landscape design to other government agencies, corporate entities, policy makers and the public.
3. Conservation Delivery – the implementation of the landscape design by your own and other agencies (the result of effective marketing of an efficient strategy).
4. Assumption-driven Research:
Document explicit assumptions in the Biological Planning and Conservation Design processes. Consider each assumption in terms of its uncertainty and importance to the management strategy (formal or informal sensitivity analysis).
Conduct research on the most important and most uncertain assumptions.
5. Outcome-based monitoring:
Compare model predictions for management actions to actual outcomes at the tract scale to determine if the habitat response was as predicted and if focal species populations responded to habitat changes. Adjust models accordingly over time.
Monitor habitat changes at ecoregional scales and apply models to predict population trends. If predicted and observed trends do not match and tract-level monitoring generally supports model assumptions, look for other limiting factors.
Apply models to actual habitat actions to report accomplishments in terms of estimated population response (mission-oriented terms).
6. Using results of assumption-driven research and tract-scale monitoring, revise biological planning and conservation design tools and continue the cycle.
