Prototype App for Green Infrastructure managment in Norway

WORKFLOW

Identifying and protecting Green Infrastructures, GI, for biodiversity is a big challenge from a SCIENTIFIC, MANAGEMENT and SOCIAL perspective. It requires coordination in land planning and decision making among a wide range of academic, administrative, societal and business actors locally, regionally and nationally. GI maps and land-planning support tools are essential to anchor dialogue processes to the reality of ecosystem dynamics and support the co-creation of sustaianble solutions for nature and society

Green Infrastructure Maps

Green Infrastructures Maps need to identify both funcional core areas and corridors for several species, and need to be robust, standardized, avaialble at high-resolution for every administrative scale, and scalable. To be useful in guiding sustainable land planning, these maps need to incorporate information on CUMULATIVE EFFECTS OF HUMAN ACTIVITIES & INFRASTRUCTURES on each species. Only in this way the expected impact of changes in land use can be assessed. To date very few such maps are avaialble. Consequently, land planning processes rarely explicitly accounts for habitat functionality and GI

Land-Planning Support Tools

Decision-Support Tools can guide the synthesis, interpretation, and use of GI maps to help solving concrete land-planning challenges (Land prioritization for Conservation or Restoration, Impact Assessment). These need to be user-friendly, robust, flexible, and thus based on high scientific standards. The App presents prototype tools for visualizing maps (MODULE 1), comparing them (MODULE 2), and performing Land Prioritization for coservation and restoration [prototype feature], for single and multiple species (MODULE 3). Tools to perform scenario analysys are developed, and can be used on demad to estimate the impact of planned changes in land use (e.g. new infrastructures such as roads, cabins, renewable energy etc) or climate change scenario. 

 WORKFLOW

We illustrate the workflow to produce GI maps and land-lanning support tools, using three test-species 

(moose, forest insects associated to old-growth forest, and pollinators), in Ski Municipality in south Norway (3). The workflow and methodological developments were done using reindeer as case study [0; see reindeer web app)

 WORKFLOW - STEP BY STEP

STEP 1: HABITAT QUALITY & PERMEABILITY

Avaialble data on species' occurrence and habitat are analysed to quantify, for each pixel (irrespective from neighbouring pixels): 

STEP 2: ECOLOGICAL CONNECTIVITY

(Green Infrastructure maps)

The software ConScape (Connected Landscapes [7]), uses network models [4,5,6] to produce two maps illustrating two different aspects of Green Infrastructures: [0,3,,8,9]

These maps will initiate the Norwegian Ecological Network Database in support to sustainable land planning

STEP 3: PRIORITY AREAS 

FOR CONSERVATION OR FOR RESTORATION (zonation - single species)

Maps from Step 2 are integrated using sensitivity analyses [6] to identify areas that are most sensitive to perturbations (their perturbation would alter disproportionately the species' ecological network). 

These areas can be prioritized the species' conservation (if they are in good conditions), or for habitat restoration (if in poor conditions).  [prototype feature]

STEP 4: MULTISPECIES ZONATION

for conservation or restoration

Sensitivity maps for single species (step 3) can be integrated to identify priority areas for conservation or restoration for multiple species. This requires defining the importance for management of each species with respect to other species (attribute weights). If a categorical zonation is preferred (high vs low priority, as compared to continuous values), the cut-off threshold for the amount of land to be conserved needs also to be decided.  [prototype feature]

STEP 5: SCENARIO ANALYSES 

for Impact Assessment, Mitigation Measures, Climate change

It is possible to test for the effect of scenarios of changes in land use (e.g. building cabins and/or removing/closing roads, restoring degraded habitat, building wildlife passages..), and/or changes in climatet. This can be use for Environmental Impact Assessment, for guiding the identificaiton of the most efficient Mitigation Measures or Offset Measures, or for forecasting future climate change scenarios (example). [8,9,10,11]

DISCLAIMER

Maps presented here are to be regarded as test-maps produced as described here. Current App functionalities are to be used as mockups, for testing purposes.

In particular, the sensitivity maps and related app funcionalities are under active development in GreenPlan. 

TECHNICAL WORKFLOW

First, focal species (umbrella/indicator species), covariates and areas are identified (ex.: moose, beetles, pollinators modelled in Ski Municipality [3]). Step 1: Map Habitat Quality/Loss & Permeability/Friction to movements using niche modelling or Machine Learning [1,2,]. Step 2: Integrate these maps using Network modes [3,4,5,6,7] to produce maps quantifying Functional Habitat (high quality & well-connected) and Functional Corridors (highest probability of movements), at 100 m resolution, for Norway. These represent key aspects of Green Infrastructures, quantify cumulative impacts/footprint of anthropogenic activities, and will be used to initialize the Norwegian Ecological Network database. Step 3: Integrate these maps using sensitivity analyses to identify, for each species, areas /features to be prioritized conservation or restoration. Step 4: Produce multispecies land prioritization maps, calibrated based upon species’ weight, area protection goals and uncertainty estimates; this map can be categorized to facilitate zonation. Step 5: Simulate the impact of climate or land-use changes to guide Impact Assessment of new infrastructures (ex.: building a specific tourist resort, trail and road reduces functional habitat of ca. 20% [8,9,10,11]), the identification of efficient mitigation/off-set measures, and the estimation compensation costs. Land-planning support tools will be freely available.

REFERENCES

[0] Panzacchi, M., van Moorter, B., Tveraa, T., Rolandsen, C. M., Gundersen, V., Lelotte, L., Dos Santos, B. B. N., Bøthun, S. W., Andersen, R., Strand, O. (2022). Statistisk modellering av samlet belastning av menneskelig aktivitet på villreinområder. Identifisering av viktige leveområder og scenarioanalyser for konsekvensutredning og arealplanlegging. NINA Report 2189. Norwegian Institute for Nature Research (in Norwegian with english summary) 

[1] Panzacchi M, van Moorter B Strand O, Loe LE, Reimers E (2015) Searching for the fundamental niche using individual-based habitat selection modelling across populations. Ecography 38: 659-669

[2] Panzacchi, M, van Moorter B, Strand B, Saerens M, Kivimäki I, St. Clair CC, Herfindal I, Boitani L (2016) Predicting the continuum between corridors and barriers to animal movements using Step Selection Functions and Randomized Shortest Paths. J Anim Ecol 85: 32-42

[3] Stange E, Panzacchi M, van Moorter B (2019) Modelling green infrastructure for conservation and land planning – a pilot study. NINA Report 1625. See also: Modellerer grønn infrastruktur for å støtte bærekraftig arealplanlegging (nina.no) 

[4] Kivimäki I, Shimbo M, Særens M (2014) Developments in the theory of randomized shortest paths with a comparison of graph node distances. Physica A: Statistical

Mechanics and its Applications 393: 600-616

[5] Kivimäki I, van Moorter B, Panzacchi M, Jari Saramäki, Marco Saerens. (2020) Maximum likelihood estimation for randomized shortest paths with trajectory data. Journal of Complex Networks (8),4

[6] Van Moorter B, Kivimäki I, Panzacchi M, Særens M (2021). Review & Synthesis: defining and quantifying Effective Connectivity. Ecography44, 6: 870-884

[7] Van Moorter M, Kivimaki I, Noack A, Devooght R, Panzacchi M, Hall K, Leleux P, Saerens M. (2022 ) Accelerating advances in landscape connectivity modeling with the ConScape library. Methods in Ecology and Evolution

[8] Van Moorter B, Kivimäki I, Panzacchi M, Saura S, Niebuhr B.B., Strand O, Saerens M. (2023) Habitat Functionality: integrating environmental and geographic space in niche modelling for conservation planning. Ecology 104(7): e4105

[9] Van Moorter M, Kivimaki I, Noack A, Devooght R, Panzacchi M, Hall K, Leleux P, Saerens M. (2023) Accelerating advances in landscape connectivity modeling with the ConScape library. Methods in Ecology and Evolution, 14, 133– 145. https://doi.org/10.1111/2041-210X.13850 

[10] Villrein-ferdselsanalyser på Hardangervidda. Anbefalinger og tiltak. Gundersen, V., van Moorter, B. Panzacchi, M., Rauset, G.R. & Strand, O. 2021. Villrein-ferdselsanalyser på Hardangervidda - Anbefalinger og tiltak. NINA Rapport 1903. Norsk institutt for naturforskning. [in Norwegian]

[11] M.Panzacchi, Fornybar energi og reinsdyr: nye metoder for å simulere effekten av inngrep, forstyrrelser og kompenserende tiltak Energi Norge - Produksjonsteknisk konferanse 2021 (here)

[12] Unikt verktøy beregner hvordan mennesker påvirker naturen. Panzacchi M, Landrø J. NINA nyhettsak. 2020 (here) 

[13] Dorber, M., Panzacchi, M., Strand, O. et al. New indicator of habitat functionality reveals high risk of underestimating trade-offs among sustainable development goals: The case of wild reindeer and hydropower. Ambio (2023). https://doi.org/10.1007/s13280-022-01824-x 

FURTHER READS


Reports (most in Norwegian)




Manuela.Panzacchi@nina.no Bram.Van.Moorter@nina.no

Contacts


Lucrezia.Gorini@miljodir.no