Broadly, recovery of threatened and endangered species requires specific management actions by natural resource managers at a fine scale. We used a systematic conservation planning framework to outline conservation goals across multiple land-uses, including native habitat protection and identifying endangered species-specific recovery areas while minimizing intrusion on existing hunting areas on the island of Lanai. We used spatial prioritization tools to generate multiple scenarios where both conservation and hunting areas (deemed zones for analysis purposes) were delineated to meet land-use goals. These delineated areas will help land managers to minimize conflicts between uses for populations of non-native game animals and the conservation and restoration of native plant species in climate resilient areas. This dataset includes 3 data tables (.csv). These three tables contain identical column names and descriptions including: input name, the proportion of area for each input to conserve, and which zone (conservation or hunting) to allocate the input to in the spatial prioritization analysis. What varies between these three tables is the amount of AA_CGMA and AA_PL (both are hunting areas) and native_habitat to be conserved during scenario analyses.

This data release includes data and metadata on all native plant species, native habitat, and hunting areas included in the spatial prioritization analyses. Broadly, recovery of threatened and endangered species requires specific management actions by natural resource managers at a fine scale. We used a systematic conservation planning framework to outline conservation goals across multiple land-uses, including native habitat protection and identifying endangered species-specific recovery areas while minimizing intrusion on existing hunting areas on the island of Lanai. We used spatial prioritization tools to generate multiple scenarios where both conservation and hunting areas (deemed zones for analysis purposes) were delineated to meet land-use goals. These delineated areas will help land managers to minimize conflicts between uses for populations of non-native game animals and the conservation and restoration of native plant species in climate resilient areas.

This data release includes data and metadata on all native plant species, native habitat, and hunting areas included in the spatial prioritization analyses. Broadly, recovery of threatened and endangered species requires specific management actions by natural resource managers at a fine scale. We used a systematic conservation planning framework to outline conservation goals across multiple land-uses, including native habitat protection and identifying endangered species-specific recovery areas while minimizing intrusion on existing hunting areas on the island of Lanai. We used spatial prioritization tools to generate multiple scenarios where both conservation and hunting areas (deemed zones for analysis purposes) were delineated to meet land-use goals. These delineated areas will help land managers to minimize conflicts between uses for populations of non-native game animals and the conservation and restoration of native plant species in climate resilient areas.

Broadly, recovery of threatened and endangered species requires specific management actions by natural resource managers at a fine scale. We used a systematic conservation planning framework to outline conservation goals across multiple land-uses, including native habitat protection and identifying endangered species-specific recovery areas while minimizing intrusion on existing hunting areas on the island of Lanai. We used spatial prioritization tools to generate multiple scenarios where both conservation and hunting areas (deemed zones for analysis purposes) were delineated to meet land-use goals. These delineated areas will help land managers to minimize conflicts between uses for populations of non-native game animals and the conservation and restoration of native plant species in climate resilient areas. This dataset includes one data table (.csv): a list of the plant species included in the analysis, and their listed federal status.

Broadly, recovery of threatened and endangered species requires specific management actions by natural resource managers at a fine scale. We used a systematic conservation planning framework to outline conservation goals across multiple land-uses, including native habitat protection and identifying endangered species-specific recovery areas while minimizing intrusion on existing hunting areas on the island of Lanai. We used spatial prioritization tools to generate multiple scenarios where both conservation and hunting areas (deemed zones for analysis purposes) were delineated to meet land-use goals. These delineated areas will help land managers to minimize conflicts between uses for populations of non-native game animals and the conservation and restoration of native plant species in climate resilient areas. This dataset includes one data table (.csv): a list of the plant species included in the analysis, and their listed federal status.

Multi-species recovery planning can be a challenging natural resource management task. In collaboration with state and federal agencies, and botanical and technical experts, we developed and tested a multi-step optimization process to assist in identifying the minimum climate resilient habitat for the recovery of multiple threatened, endangered, and at-risk plant species across east Maui. Data include the underlying land-use configuration file, predictive climate models, list of plant species and number of populations to recover/protect, habitat and forest bird distribution information, presence of fencing, land management status, and naming protocol file. We identified a suite of potential conservation footprints that are constrained by ecological and resource management selection criteria based input and co-production with botanical experts and resource managers. These solutions include recovery habitat for all species of interest. The optimization process also identified priority recovery planning units, equal to the number of populations required for recovery, to inform find-scale recovery efforts. Data include: 1) underlying land-use configuration and input metrics used for optimization, input_metrics.gpkg; 2) species list, species_list.csv; 3) and output metrics from an example solution, pu_solution_example.gpkg.

Multi-species recovery planning can be a challenging natural resource management task. In collaboration with state and federal agencies, and botanical and technical experts, we developed and tested a multi-step optimization process to assist in identifying the minimum climate resilient habitat for the recovery of multiple threatened, endangered, and at-risk plant species across east Maui, Hawaiʻi. Data include the underlying land-use configuration file, predictive climate models, list of plant species and number of populations to recover/protect, habitat and forest bird distribution information, presence of fencing, land management status, and naming protocol file. We identified a suite of potential conservation footprints that are constrained by ecological and resource management selection criteria based input and co-production with botanical experts and resource managers. We present an example solution that includes sufficient recovery habitat for all species of interest and identify priority recovery planning units for population-level recovery planning. The dataset is presented at the planning unit level and indicates which species can be recovered within a given unit.

Multi-species recovery planning can be a challenging natural resource management task. In collaboration with state and federal agencies, and botanical and technical experts, we developed and tested a multi-step optimization process to assist in identifying the minimum climate resilient habitat for the recovery of multiple threatened, endangered, and at-risk plant species across east Maui. The list of plant species used during this project, and number of planning units required to recover each species, are included.

This dataset contains the point-transect distance sampling records of Hawaii Akepa collected at Hakalau Forest National Wildlife Refuge in 2002, including survey point locations, distance to detected birds, number of detected birds, elevation, and alliance-level habitat classification. This data release consists of two tabular datasets, one that contains distances and the other that contains locations, elevation, habitat and counts.

This raster integrates the species-specific and community classifications using a hierarchical approach based on classification certainty. A 0.66 probability threshold was applied, with pixels assigned the finest species-specific class as long as the probability exceeded the threshold. Pixels below the threshold were assigned to the broader community class meeting the threshold. This approach displays the most detailed class possible given a minimum confidence, providing a map that balances specificity and certainty. Please note that to reduce the inherent 'salt and pepper' noise in the final land cover classification map, we applied a 3x3 pixel moving window majority filter to the final classification results.