Protected areas and conservation planning

Protected areas are the cornerstone of most national conservation strategies. National parks, wildlife refuges, ecological reserves and marine protected areas set aside places where the destruction and exploitation that drive biodiversity loss are limited by law or agreement. But protected areas vary enormously in what they protect, how well they are managed and how they relate to the people who live in and around them. This lesson examines the types of protected areas, the long debate over how they should be designed, the methods of systematic conservation planning used to choose them, and the global and national targets that now drive their expansion, including the commitment to conserve 30 percent of land and sea by 2030.

What counts as a protected area

The IUCN defines a protected area as a clearly defined geographical space, recognized, dedicated and managed, through legal or other effective means, to achieve the long-term conservation of nature with associated ecosystem services and cultural values. The definition emphasizes that conservation of nature must be the primary purpose. The IUCN recognizes six management categories, which describe what a protected area is managed for rather than how strictly it is protected.

Since 2018 the Convention on Biological Diversity has also recognized other effective area-based conservation measures (OECMs): areas that are not designated as protected areas but are governed and managed in ways that achieve positive long-term outcomes for biodiversity, such as some military lands, watershed protection areas, sacred sites or fishery closures that protect sensitive seabed habitats. OECMs can count toward national targets if they meet agreed criteria.

Do protected areas work?

A protected area can fail in several ways. Paper parks exist in law but receive little management, enforcement or funding, so poaching, logging and encroachment continue. Protected areas are often located where land is cheap and unproductive, at high elevations or far from roads, rather than where biodiversity is most threatened, so they may protect places that would not have been developed anyway. Evaluating protected areas therefore requires a counterfactual: what would have happened without protection? Studies using matching methods, which compare protected sites with similar unprotected sites, have found that protected areas do reduce deforestation on average, though by less than simple comparisons suggest, and that their effects are largest where pressure is high. Effectiveness also depends on management capacity, funding and the support of local people.

SLOSS: single large or several small?

In the 1970s, ecologists began applying the theory of island biogeography to reserve design. Jared Diamond proposed in 1975 a set of geometric principles: a large reserve is better than a small one; a single large reserve is better than several small ones of the same total area; reserves close together are better than reserves far apart; reserves clustered together are better than reserves in a line; reserves connected by corridors are better than unconnected ones; and round reserves are better than elongated ones, because they have less edge. Daniel Simberloff and Lawrence Abele challenged the second principle in 1976, arguing that island biogeography theory did not imply that one large reserve would hold more species than several small ones of the same total area. The resulting debate, known as SLOSS, for single large or several small, ran through the late 1970s and 1980s.

The debate was not resolved in favor of either side, but it clarified the trade-offs. A single large reserve supports larger populations, which are less vulnerable to the small-population processes of lesson 6, holds species that need large areas such as wolves and grizzly bears, and has less edge. Several small reserves may include a greater variety of habitats, spread the risk of catastrophes such as fire or disease, and, if species composition differs among them, contain more species in total. Which matters more depends on the species and the landscape. A 2020 review by Lenore Fahrig reported that in most empirical comparisons, several small patches held at least as many species as a single large patch of the same total area, a result that strengthens the case for protecting small remnants in heavily converted landscapes. The practical consensus is that both large core areas and networks of smaller sites are needed.

Other design principles have been added since. Buffer zones around core protected areas can reduce edge effects and pressure from surrounding land use. The UNESCO biosphere reserve model, used in places such as the Southwest Nova Biosphere Reserve in Nova Scotia and the Everglades and Dry Tortugas in Florida, combines a strictly protected core, a buffer zone where compatible activities occur, and a transition zone of sustainable development. Protected areas must also be large enough to contain natural disturbance regimes; a forest reserve smaller than the area typically burned by a single large fire may be entirely reset by one event, so reserves in fire-prone ecosystems should be several times larger than the largest expected fire, an idea called the minimum dynamic area.

Systematic conservation planning

Historically, many protected areas were chosen opportunistically, for their scenery, their recreation value or because land happened to be available. In 2000 Chris Margules and Bob Pressey published an influential framework for systematic conservation planning, which approaches the problem as a sequence of explicit steps: compile data on biodiversity in the region; set explicit conservation goals and quantitative targets, such as protecting at least 30 percent of the range of each species; review how well existing reserves already meet the targets, a step called gap analysis; select additional areas to meet the targets efficiently; implement conservation actions; and maintain and monitor the results.

Three principles guide the selection of areas. Complementarity means choosing each new site for what it adds to those already chosen, not for its own richness alone; a species-poor site that holds species missing from the network can be more valuable than a rich site whose species are already protected. Irreplaceability measures how essential a site is to meeting the targets: a site containing the only population of an endemic species is completely irreplaceable. Efficiency means meeting the targets at the lowest cost, in area, money or forgone economic opportunity. Because thousands of candidate sites are usually involved, the selection is carried out by computer algorithms. The most widely used program, Marxan, developed by Ian Ball and Hugh Possingham in Australia around 2000, uses simulated annealing, an optimization method, to find networks of sites that meet all targets while minimizing a combination of cost and boundary length, so that the selected sites are compact rather than scattered. Marxan has been used in hundreds of planning exercises, including the rezoning of Australia's Great Barrier Reef Marine Park in 2004 and marine planning on Canada's Pacific coast.

# Reserve selection on an invented matrix of 8 candidate sites x 10 species (1 = present).
sites = {
    "S1": [1, 1, 1, 1, 1, 1, 0, 0, 0, 0],
    "S2": [1, 1, 1, 1, 1, 0, 0, 0, 0, 0],
    "S3": [1, 1, 1, 1, 0, 1, 0, 0, 0, 0],
    "S4": [0, 0, 0, 0, 0, 0, 1, 1, 0, 0],
    "S5": [0, 0, 0, 0, 0, 0, 0, 0, 1, 0],
    "S6": [0, 0, 0, 0, 0, 0, 0, 0, 0, 1],
    "S7": [1, 0, 0, 0, 0, 0, 1, 0, 0, 1],
    "S8": [0, 1, 1, 0, 0, 0, 0, 1, 0, 0],
}
cost = {"S1": 5, "S2": 4, "S3": 4, "S4": 2, "S5": 1, "S6": 1, "S7": 3, "S8": 2}
n_sp = 10
def covered(chosen):
    return {j for s in chosen for j in range(n_sp) if sites[s][j]}
# Approach 1: pick the richest sites first (scoring), until all species are covered
by_richness = sorted(sites, key=lambda s: -sum(sites[s]))
chosen = []
for s in by_richness:
    if len(covered(chosen)) == n_sp: break
    chosen.append(s)
print("richness ranking:", chosen, "cost", sum(cost[s] for s in chosen))
# Approach 2: greedy complementarity, choosing the site adding most new species per unit cost
chosen = []
while len(covered(chosen)) < n_sp:
    best = max((s for s in sites if s not in chosen),
               key=lambda s: len(covered(chosen + [s]) - covered(chosen)) / cost[s])
    chosen.append(best)
print("complementarity:  ", chosen, "cost", sum(cost[s] for s in chosen))
# Irreplaceability: species found at only one site make that site essential
for j in range(n_sp):
    holders = [s for s in sites if sites[s][j]]
    if len(holders) == 1:
        print(f"species {j + 1} occurs only at {holders[0]}")

richness ranking: ['S1', 'S2', 'S3', 'S7', 'S8', 'S4', 'S5'] cost 21
complementarity:   ['S8', 'S5', 'S6', 'S1', 'S4'] cost 11
species 9 occurs only at S5

Ranking sites by richness picks the three richest sites first, but they hold largely the same widespread species, so the network must keep adding sites until the rare species are covered, at higher total cost. Complementarity picks sites for the new species each adds per unit of cost and covers all ten species for about half the cost. Species 9 occurs only at site S5, so S5 is irreplaceable: every solution that meets the targets must include it, however poor it looks on its own. The example is tiny, but the same logic scales up: in real planning problems, complementarity-based selection typically meets targets with far less area than ranking by richness or choosing hotspots alone.

Global targets: from Aichi to 30 by 30

In 2010 the parties to the Convention on Biological Diversity (CBD) adopted the Aichi Biodiversity Targets, including Target 11, to conserve at least 17 percent of land and inland waters and 10 percent of coastal and marine areas by 2020 through well-connected, effectively managed and representative protected areas. The area targets were nearly met on land and partly met at sea, but most of the qualitative elements, such as effective management and representativeness, were not, and none of the twenty Aichi targets was fully achieved. In December 2022, at the CBD's fifteenth Conference of the Parties, held in Montreal under the presidency of China, 196 parties adopted the Kunming–Montreal Global Biodiversity Framework, with four goals for 2050 and 23 targets for 2030. Target 3, widely called 30 by 30, commits parties to ensure that by 2030 at least 30 percent of terrestrial and inland water areas and of marine and coastal areas are effectively conserved and managed through ecologically representative, well-connected and equitably governed systems of protected areas and OECMs, recognizing Indigenous and traditional territories. The framework also includes Target 2, to have at least 30 percent of degraded ecosystems under effective restoration by 2030.

According to the Protected Planet Report 2024, about 17.6 percent of land and inland waters and about 8.4 percent of the ocean were covered by protected areas and OECMs, so reaching 30 percent requires a large expansion, especially at sea. The sixteenth Conference of the Parties met in Cali, Colombia, in 2024, and the seventeenth was under way in Yerevan, Armenia, in late October 2026 as this lesson was written, with progress toward the 2030 targets on its agenda. Critics of 30 by 30 caution that area targets can encourage protecting cheap, remote places rather than the most important ones, and that expansion must respect the rights of Indigenous peoples and local communities; supporters respond that the framework explicitly addresses both concerns.

In January 2021 an executive order set a goal of conserving 30 percent of US lands and waters by 2030, and the resulting America the Beautiful initiative supported locally led conservation, including voluntary easements on working lands, tribal conservation and new national monuments. In January 2025 a new executive order revoked the 2021 order, ending the federal 30 by 30 goal, and the administration has since emphasized energy development and access on federal lands. The United States is not a party to the Convention on Biological Diversity, so the Kunming–Montreal targets do not formally apply to it. The US Geological Survey's Protected Areas Database (PAD-US) tracks lands managed primarily for biodiversity; depending on how strictly protection is defined, roughly an eighth of US land is in the most protective categories. Several states, including California, have adopted their own 30 by 30 goals, and national wildlife refuges, national parks, wilderness areas and marine national monuments remain the core of the federal system.

Marine protected areas

Marine protected areas (MPAs) range from no-take reserves, where all extraction is banned, to multiple-use areas where some fishing continues. A global analysis led by Graham Edgar in 2014 found that MPAs deliver their largest benefits when they have five features: no take, good enforcement, age of more than ten years, large size of more than 100 square kilometers, and isolation by deep water or sand. Effective no-take reserves typically contain much higher biomass of fish than surrounding fished areas, and larger fish produce disproportionately more eggs, so reserves can export larvae and adult fish to surrounding fisheries. Large MPAs have been established in remote waters, such as the Papahānaumokuākea Marine National Monument in Hawaii, but critics note that many large MPAs protect areas with little fishing pressure. In Canada, minimum protection standards adopted in 2019 prohibit oil and gas activities, mining, dumping and bottom trawling in new federal MPAs.