Optimizing landscape-scale coastal monitoring and reporting through predicted versus observed animal abundance models DOI Creative Commons
Ben L. Gilby, Lucy A. Goodridge Gaines, Christopher J. Henderson

и другие.

ICES Journal of Marine Science, Год журнала: 2024, Номер unknown

Опубликована: Окт. 10, 2024

Abstract Effective environmental management hinges on monitoring drivers of change and effectively communicating results to stakeholders. While animals are valuable for engagement, few programs successfully integrate metrics quantifying their assemblages. We studied fish responses factors (including landscape context water quality) in a 3-year survey across six ecosystems 13 estuaries eastern Australia (for >1800 surveys), developed novel predicted versus observed approach monitoring, grading, reporting animal populations. Fish species richness the abundance five indicator were explained significantly by at least one spatial attribute sites (e.g. connectivity with mangroves ocean), quality metric reflecting annual median conditions (especially turbidity, dissolved oxygen (DO), chlorophyll concentration). For our grading approaches, values calculated each replicate using best-fit models indicator, thereby accounting natural spatiotemporal variation standardizing site-to-site comparisons. Evaluating methods translating into graded scores estuary, we recommend simple metric: percentage above predictions. discuss this as useful complementary predominantly physical parameter challenges establishing ongoing protocols.

Язык: Английский

Optimizing landscape-scale coastal monitoring and reporting through predicted versus observed animal abundance models DOI Creative Commons
Ben L. Gilby, Lucy A. Goodridge Gaines, Christopher J. Henderson

и другие.

ICES Journal of Marine Science, Год журнала: 2024, Номер unknown

Опубликована: Окт. 10, 2024

Abstract Effective environmental management hinges on monitoring drivers of change and effectively communicating results to stakeholders. While animals are valuable for engagement, few programs successfully integrate metrics quantifying their assemblages. We studied fish responses factors (including landscape context water quality) in a 3-year survey across six ecosystems 13 estuaries eastern Australia (for >1800 surveys), developed novel predicted versus observed approach monitoring, grading, reporting animal populations. Fish species richness the abundance five indicator were explained significantly by at least one spatial attribute sites (e.g. connectivity with mangroves ocean), quality metric reflecting annual median conditions (especially turbidity, dissolved oxygen (DO), chlorophyll concentration). For our grading approaches, values calculated each replicate using best-fit models indicator, thereby accounting natural spatiotemporal variation standardizing site-to-site comparisons. Evaluating methods translating into graded scores estuary, we recommend simple metric: percentage above predictions. discuss this as useful complementary predominantly physical parameter challenges establishing ongoing protocols.

Язык: Английский

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