Coexisting with Whales | Norwegian and surrounding waters

Vessel strikes are one of the leading anthropogenic causes of large whale mortality. The Norwegian Sea, Barents Sea and surrounding waters host fin, blue, sperm, humpback and minke whales alongside some of Europe's busiest shipping lanes. This tool overlays cetacean observation density with gridded vessel density and translates the result into a transparent strike-risk score per port and per sea region.

Why this exists

The Mesh Oslo "What else can you build" prompt highlighted whale incident tracking as an open problem. Hubocean.earth and the One Ocean Expedition show how rich open ocean data has become; this app uses a small, public slice of that for a single, pragmatic question: where do whales and ships overlap, and how does cutting vessel speed change strike lethality.

A sister project, Coexisting with Birds, answers the same question for wind farms and birdlife.

Conservation status

The map shows two parallel categorisations. The Norwegian Red List 2021 (Artsdatabanken) covers national populations; the global IUCN Red List covers the species worldwide. We display the stricter of the two, and call out the divergence where it matters (e.g. the fin whale is VU globally and LC nationally because the Norwegian feeding population is recovering).

CR	Critically endangered Extremely high risk of extinction.
EN	Endangered Very high risk of extinction.
VU	Vulnerable High risk of extinction.
NT	Near threatened Close to qualifying for a threatened category.

Strike vulnerability per species

Risk scales with body size, surface time and overlap with shipping routes. We use the species accounts in , and to classify each cetacean as high, medium or low vulnerability.

▲	High vulnerability Large slow surface dwellers. Includes blue, fin, sei, humpback, sperm whale and the North Atlantic right whale (functionally absent from NE Atlantic but listed for completeness).
●	Moderate vulnerability Common minke whale, killer whale, long-finned and short-finned pilot whales.
no icon	Lower vulnerability Agile small cetaceans (porpoises, dolphins) and deep divers (beaked whales). Bycatch and acoustic disturbance dominate over direct strikes for these species.

Heatmap and points

The heatmap uses a 10K stratified sample from GBIF (taxonKey 733) covering the bounding box lat 56-82, lon -10 to 70 across all twelve months. Counts reflect where people record whales, not absolute abundance. Coastal and tourist viewpoints (Andoya, Lofoten, Tromso) are overrepresented. Points view shows individual records colored by species; click a point for details.

	Low to high cetacean observation density
	Major Norwegian port (icon size scales with annual cargo throughput)

Per port strike risk

Each major port is colored from green (low) through yellow to red (very high) based on a composite weighted score of nearby observations.

Step 1. Find nearby observations

For each port, all cetacean observations within a 30 km radius are collected. Distance is computed using a flat earth approximation (sufficient at sub-100 km scales).

dx = (obs.lon - port.lon) × 111 × cos(port.lat) dy = (obs.lat - port.lat) × 111 distance = sqrt(dx² + dy²) // in km

Step 2. Weight each observation

Each observation starts with weight 1. Three multipliers are applied: red list weight, strike vulnerability and a relative speed factor.

Red list weight
CR	× 8
EN	× 5
VU	× 3
NT	× 1.5
Least concern (LC) / Data deficient (DD)	× 1
Strike vulnerability
High	× 3
Medium	× 1.5
Low	× 1

A speed factor scales the score by P_lethal(v) / P_lethal(default), where P_lethal is the Vanderlaan and Taggart 2007 logistic curve (). The default speed is 14 knots.

Step 3. Normalise and color

The raw score is divided by 300 (empirical threshold for a 10K sample) and clamped to [0, 1]. Color interpolates green to red.

normalized = min(1, score / 300) Color mapping: 0.0 - 0.2 → green (low strike risk) 0.2 - 0.5 → yellow (moderate) 0.5 - 0.75 → orange (high) 0.75 - 1.0 → red (very high)

Vessel speed and lethality

The probability that a struck large whale dies or is severely injured rises sharply with vessel speed. The single best published curve is the Vanderlaan and Taggart 2007 logistic :

P_lethal(v) = 1 / (1 + exp(-(β₀ + β₁ · v))) β₀ = -4.89, β₁ = 0.41 v in knots P=0.21 at v= 8.6 kn (NOAA slow zone target) P=0.50 at v=11.8 kn P=0.79 at v=15.0 kn (typical merchant cruising) P→1.0 above ~18 kn

The 10 knot threshold underpinning NOAA's Seasonal Management Areas () and IMO MEPC.1/Circ.674 () is set at the value where P_lethal drops below ~27%. Conn and Silber 2013 () re-fit the same form with a gentler slope and is the curve NOAA cites for North Atlantic right whales today.

Encounter rate (advanced)

For per cell mortality, Rockwood et al. 2017 () factor the rate of encounters out of the strike physics:

λ_e = 2 r_c (v_b + v_w) · I(v_b, v_w) / S r_c = (L_whale + W_ship) / 2 M = encounters · P_strike_depth · (1 - P_avoidance) · P_lethal(v_b)

I(v_b, v_w) is the Gerritsen-Strickler velocity correction term; for v_b ≫ v_w it approaches 1. P_strike_depth is the fraction of time the whale is in the hull-swept depth band (typically 0.4 to 0.6 from tag data). P_avoidance is the chance of last second evasion (0 by default, conservative).

Williams and O'Hara 2010 () take the simpler co-occurrence approach: relative risk per cell is whale_density × ship_density. Redfern et al. 2013 () integrate this along candidate shipping routes, the canonical marine spatial planning citation.

Region density layer

When toggled on, each sea region is colored by observation count. Empty regions appear in grey, indicating low data confidence rather than absence of whales. With a 10K sample over four large IHO sea areas, expect at most a few thousand records per region.

Data sources

Limitations

This is a screening tool, not an environmental impact assessment. Cetacean records reflect observer effort, not true density. EMODnet's vessel density grid is a 2017 to 2024 average. Norwegian-waters specific strike-risk modelling is sparse in the literature; we apply global physics and global species accounts. For real planning, use site specific surveys, Kystverket / BarentsWatch live AIS and modelled species distributions from Havforskningsinstituttet ().

Project

Built by Almaz Ermilov in Oslo, April 2026. MIT licensed, free to fork.

GitHub repository · Coexisting with Birds (sister project) · HUB Ocean (inspiration)

All data from open sources. Code is open source under MIT.