Constructing a Nature Relationship Indicator by Latent Spatio-Temporal Process Modelling of Citizen Science Data
(2026) In Master's Theses in Mathematical Sciences BERM01 20261Mathematics (Faculty of Sciences)
- Abstract
- This thesis explores the use of birding citizen science data and statistical modelling methods to support the construction of indicators for human-nature relationships. Motivated by the broader aspirational framework of the Nature Relationship Index, the study investigates how voluntary bird observation records can be processed into spatial and temporal measures suitable for statistical analysis, from which a human-nature relationship indicator can potentially be derived. Observation events in Sweden from 2019 to 2025 are collected, filtered, spatially joined to a regular grid, and aggregated into yearly event counts, while accounting for administrative land boundaries and lake coverage. The resulting event-count dataset is then used to... (More)
- This thesis explores the use of birding citizen science data and statistical modelling methods to support the construction of indicators for human-nature relationships. Motivated by the broader aspirational framework of the Nature Relationship Index, the study investigates how voluntary bird observation records can be processed into spatial and temporal measures suitable for statistical analysis, from which a human-nature relationship indicator can potentially be derived. Observation events in Sweden from 2019 to 2025 are collected, filtered, spatially joined to a regular grid, and aggregated into yearly event counts, while accounting for administrative land boundaries and lake coverage. The resulting event-count dataset is then used to examine spatial and temporal patterns and to fit Bayesian spatio-temporal models with different combinations of covariates to adjust for biases in reporting frequencies. Using the R package inlabru, which applies Integrated Nested Laplace Approximation (INLA) to efficiently approximate marginal posterior distributions, several Bayesian spatio-temporal models are fitted and compared across different likelihood families, including Poisson, negative binomial, and zero-inflated negative binomial, and across different covariate combinations. Model comparison and checking are conducted using information criteria and posterior predictive diagnostics. The results from two models suggest areas of lower and higher level of human-nature relationship in Sweden. It also shows an increasing trend in the human-nature relationship indicator after 2020. Overall, the study provides a methodological basis for transforming the frequency of species reporting events from citizen science projects into a structured modelling workflow suitable for indicator development. (Less)
- Popular Abstract
- What can birdwatching data tell us about people's relationship with nature?
The relationship between people and nature is receiving increasing attention. Understanding this relationship may help open a path towards a more sustainable and mutually beneficial future. Bird observations from citizen science data can offer one possible window into how people interact with nature.
The thesis investigates whether birding citizen science data and statistical models can be combined together and help show how people's relationship with nature changes across Sweden during 2019-2025. Here, the frequency of birding records are suggested as a way to derive a quantitative measure of human nature relationship, but before that is possible several... (More) - What can birdwatching data tell us about people's relationship with nature?
The relationship between people and nature is receiving increasing attention. Understanding this relationship may help open a path towards a more sustainable and mutually beneficial future. Bird observations from citizen science data can offer one possible window into how people interact with nature.
The thesis investigates whether birding citizen science data and statistical models can be combined together and help show how people's relationship with nature changes across Sweden during 2019-2025. Here, the frequency of birding records are suggested as a way to derive a quantitative measure of human nature relationship, but before that is possible several things must be done. Birding records are influenced not only by people's interest in nature, but also by factors such as the amount of people in an area and accessibility to areas for bird watching. Statistical modelling is therefore used to make comparisons between places and years more fair after accounting for these biases. Several models are fitted and compared. The best-performing models are then used to derive spatio-temporal human-nature relationship indicators defined in this study at both grid and regional levels. The resulting indicator suggests variation in human-nature relationship between different areas and a potential increasing trend after 2020.
This study shows how citizen science data can be transformed into a comparable spatio-temporal indicator through statistical modelling. It also provides a methodological exploration for broader aspirational frameworks such as the Nature Relationship Index (NRI), which focuses on how societies may develop towards healthier relationships with nature. The latter must be investigated over a longer time period. (Less) - Popular Abstract (Swedish)
- Vad kan fågelskådningsdata berätta om människors relation till naturen?
Relationen mellan människor och natur får allt större uppmärksamhet. Förståelse för denna relation kan bidra till att öppna en väg mot en mer hållbar och ömsesidigt gynnsam framtid. Fågelobservationer från medborgarforskningsdata kan erbjuda en möjlighet för att studera hur människor samspelar med naturen.
Denna uppsats undersöker om fågelskådningsdata från medborgarforskning och statistiska modeller kan kombineras för att visa hur människors relation till naturen har förändrats i Sverige under perioden 2019–2025. Här använder vi frekvenser av rapporterade fågelskådarobservationer för att konstruera en kvantitativ indikator på människors förhållande till naturen,... (More) - Vad kan fågelskådningsdata berätta om människors relation till naturen?
Relationen mellan människor och natur får allt större uppmärksamhet. Förståelse för denna relation kan bidra till att öppna en väg mot en mer hållbar och ömsesidigt gynnsam framtid. Fågelobservationer från medborgarforskningsdata kan erbjuda en möjlighet för att studera hur människor samspelar med naturen.
Denna uppsats undersöker om fågelskådningsdata från medborgarforskning och statistiska modeller kan kombineras för att visa hur människors relation till naturen har förändrats i Sverige under perioden 2019–2025. Här använder vi frekvenser av rapporterade fågelskådarobservationer för att konstruera en kvantitativ indikator på människors förhållande till naturen, men för att detta ska vara möjligt behöver man vidta vissa åtgärder. Fågelobservationer påverkas inte bara av människors intresse för naturen, utan också av mängd människor på en plats och tillgänglighet till områden för fågelskådning. Statistisk modellering används därför för att göra jämförelser mellan platser och år mer rättvisa efter att hänsyn tagits till sådana skevheter. Flera modeller anpassas och jämförs. De modeller som fungerar bäst används sedan för att ta fram rumsliga och tidsmässiga indikatorer för relationen mellan människa och natur, definierade i denna studie, både på lokal och regional nivå. De framtagna indikatorerna tyder på rumsliga skillnader i relationen mellan människa och natur i Sverige, samt en potentiellt ökande trend efter 2020.
Studien visar hur medborgarforskningsdata kan omvandlas till en jämförbar rumslig och tidsmässig indikator genom statistisk modellering. Den ger också en metodologisk utforskning för bredare, framtidsinriktade ramverk såsom Nature Relationship Index (NRI), som fokuserar på hur samhällen kan utvecklas mot hälsosammare relationer till naturen. Den senare behöver undersökas med data över en längre tid. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/student-papers/record/9234376
- author
- Wang, Luhao LU
- supervisor
- organization
- course
- BERM01 20261
- year
- 2026
- type
- H2 - Master's Degree (Two Years)
- subject
- keywords
- Human-nature relationships, Citizen science data, Bayesian spatio-temporal modelling, Integrated Nested Laplace Approximation, Indicators
- publication/series
- Master's Theses in Mathematical Sciences
- report number
- LUNFBV-3010-2026
- ISSN
- 1404-6342
- other publication id
- 2026:E51
- language
- English
- id
- 9234376
- date added to LUP
- 2026-07-27 10:24:40
- date last changed
- 2026-07-27 10:24:40
@misc{9234376,
abstract = {{This thesis explores the use of birding citizen science data and statistical modelling methods to support the construction of indicators for human-nature relationships. Motivated by the broader aspirational framework of the Nature Relationship Index, the study investigates how voluntary bird observation records can be processed into spatial and temporal measures suitable for statistical analysis, from which a human-nature relationship indicator can potentially be derived. Observation events in Sweden from 2019 to 2025 are collected, filtered, spatially joined to a regular grid, and aggregated into yearly event counts, while accounting for administrative land boundaries and lake coverage. The resulting event-count dataset is then used to examine spatial and temporal patterns and to fit Bayesian spatio-temporal models with different combinations of covariates to adjust for biases in reporting frequencies. Using the R package inlabru, which applies Integrated Nested Laplace Approximation (INLA) to efficiently approximate marginal posterior distributions, several Bayesian spatio-temporal models are fitted and compared across different likelihood families, including Poisson, negative binomial, and zero-inflated negative binomial, and across different covariate combinations. Model comparison and checking are conducted using information criteria and posterior predictive diagnostics. The results from two models suggest areas of lower and higher level of human-nature relationship in Sweden. It also shows an increasing trend in the human-nature relationship indicator after 2020. Overall, the study provides a methodological basis for transforming the frequency of species reporting events from citizen science projects into a structured modelling workflow suitable for indicator development.}},
author = {{Wang, Luhao}},
issn = {{1404-6342}},
language = {{eng}},
note = {{Student Paper}},
series = {{Master's Theses in Mathematical Sciences}},
title = {{Constructing a Nature Relationship Indicator by Latent Spatio-Temporal Process Modelling of Citizen Science Data}},
year = {{2026}},
}