Geology topics

Lucas Berio Fortini

Publications and source records attributed to Lucas Berio Fortini.

At least 19 recordsLinked to original sources

USGS2026

Experimental translocation of a rare Hawaiian tree reveals disparity between remnant and potential habitat

Translocation is implemented worldwide as a conservation strategy for rare and endangered plant species, yet the factors that influence long-term success remain poorly understood. Remnant wild populations are often used as indicators to model habitat preference and select translocation sites, but such populations may be refugia from past biological or anthropogenic stressors and represent sub-optimal habitat conditions for focal taxa. To test assumptions about habitat preferences of rare species, we conducted a four-year experimental translocation of the Critically Endangered Hawaiian tree, ‘ohe mauka, Polyscias bisattenuata (Araliaceae), planting 3,700 saplings across eleven sites spanning diverse environmental conditions both within and beyond the species’ extant range. We measured seventeen predictor variables at the site and individual plant level in categories of climate, surrounding vegetation, soil chemistry, and genetic provenance. We used linear mixed effects models to assess relative effects of predictors on translocated plant survival, growth, and vigor. The factors which influenced plant performance shifted across ontogeny. The height of surrounding vegetation showed an initial negative relationship with two-year survival, but later showed a positive relationship with four-year growth. Four-year growth demonstrated a strong positive relationship with site annual mean temperature. Successful translocation sites were lower in elevation and warmer in temperature than conditions represented by remnant wild populations. Results demonstrate that basing translocation sites solely on limited extant wild occurrences can lead to suboptimal restoration practices, and experimental outplanting across broad conditions may help identify rare species' contemporary habitat preferences.

Hawaii↗

USGS2025

Getting ahead of the crises: Developing an avian malaria disease management plan for Hawaiian forest birds

Avian malaria is an existential threat to a majority of native Hawaiian forest birds. Climate change is facilitating the spread of malaria to historically disease-free areas, and despite the risk of native Hawaiian forest bird extinctions from malaria outbreaks, no comprehensive disease management plans exist for forest bird conservation areas. Hakalau Forest National Wildlife Refuge, Hawai‘i, supports a thriving bird community in a historically disease-free area that is now vulnerable to malaria incursion. Drawing on the expertise of land managers and research scientists, we developed an approach that could be used to proactively address the risk of expanding malaria into the Refuge. The plan lays out a multi-level approach that includes options for monitoring and management actions depending on defined threat levels: Vigilant, High Alert, Disease Outbreak, and Crisis levels. Initial Vigilant and High Alert levels monitor bird populations, climate conditions, and mosquito occurrence for signs of possible disease outbreaks, with higher levels shifting toward more direct management responses. While specific actions will change as new tools become available, the proactive approach can help Refuge managers better respond to changing malaria levels in the future and provide a model for managing disease here in Hawai‘i and elsewhere.

Hawaii↗

USGS2025

Quantifying landscape-level biodiversity change in an island ecosystem: A 50-year assessment of shifts in the Hawaiian avian community

Hawaii has experienced profound declines in native avifauna alongside the introduction of numerous bird species. While site-specific population studies are common, landscape-level analyses of avian population dynamics are rare, particularly in island ecosystems. To address this gap, we used a density surface model to create a spatio-temporal projection of population densities and distributions across the Island of Hawai‘i, spanning nearly five decades (1976–2023). We incorporated environmental covariates of habitat, precipitation, and elevation, to further refine our projections. Our analysis encompassed nine native and six non-native bird species, inhabiting a range of ecological niches. We found five out of nine native species have declined in density and range size while four were stable. For non-native species, two were stable, one was decreasing, and three were increasing in density and range size. Our landscape projections can inform management by suggesting areas critical for habitat preservation and land acquisition for conservation, identifying where range fragmentation is occurring, and pinpointing locations of multi-species declines that are likely driven by a common cause. Our study demonstrates how long-term, landscape-level monitoring and analyses can advance understanding and addressing biodiversity loss, particularly in vulnerable tropical island ecosystems.

Hawaii↗

USGS2025

The structural and functional impacts of invasive Psidium cattleianum in forests on the Island of Hawai’i

During the past century, the proliferation of invasive species has contributed to loss of biodiversity and ecosystem degradation. In forests, invasive tree species can alter ecosystem function, but the underlying mechanisms of these changes are not fully understood. We use the ongoing invasion of P. cattleianum on the Island of Hawai’i to test the hypotheses that invasive structural changes drive changes to forest evapotranspiration (ET). The aim of our study is first to quantify the structural changes to native ‘ōhi‘a -dominated forest impacted by a gradient of P. cattleianum invasion. Our results suggest that invasive P. cattleianum causes significant changes to the vegetation density and structure of native forest on the Island of Hawai’i, including increased vegetation area index, decreased mean leaf height, and decreased structural heterogeneity. Second, we strove to understand the functional implications of structural changes through a biophysical modeling simulation, testing the sensitivity of ET to canopy structure under contrasting scenarios. Modeling the functional impact of structural change, we found that plots with P. cattleianum invasion importance value (IV inv ) above 0.35 have a higher likelihood to increase ET compared to plots with P. cattleianum invasion less than 0.35 IV inv . Modeled increases in ET due to invasion ranged from 19 and 123% relative to native transects. The large variation in ET increases is caused by structural variation because the modeling scenarios did not include potential species differences in leaf physiology. Diagnostic scenario modeling shows the effect size of increased leaf area on modeled ET is constrained by the structural arrangement, that is vertical distribution, of the increased vegetation. Thus, invasion structure that increases vegetation density in taller, more sunlit forest strata will lead to a greater increase in ET compared to invasion structure that increases vegetation density in the shaded forest understory. Overall, we conclude the vertical distribution of vegetation is an important factor shaping the impact of invasive P. cattleianum on the forest water balance.

Hawaii↗

USGS2025

Breaking down Palila decline: Assessing the role of drought and vegetation health in the population loss of an endangered Hawaiian honeycreeper

The Palila ( Loxioides bailleui ), the last member of the once speciose finch-billed Hawaiian honeycreeper clade (Drepanidinae) in the main Hawaiian Islands, faces critical conservation challenges as an endangered species. Understanding the drivers of its decline is essential for effective management. We used additive decomposition models to examine temporal trends in climatic variables (temperature, precipitation, drought) and Normalized Difference Vegetation Index (NDVI), a vegetation health metric hypothesized to be associated with long-term trends in Palila abundance at landscape (250 m) scales on the Island of Hawai'i. A breakpoint analysis identified 2005–2009 as critical years of Palila decline. Vegetation health metrics at the 250 m scale lined up well both spatially and temporally with trends in Palila declines, with a significant browning from January 2004 to January 2014. Given the strong correlation between vegetation health and drought metrics at the landscape scale (r = 0.75, p < 0.001), NDVI changes appeared driven by drought. To enable the future projection of habitat quality in this area, we explored a stepwise linear regression to explain the variation in MODIS NDVI in recent years. We found that 87 % of the variability in NDVI can be explained by wet season precipitation and vapor pressure deficit from the previous dry season. The model is largely driven by a strong positive correlation between wet season precipitation and NDVI (r = 0.72, adjusted p < 0.001). Areas that maintained a low likelihood of NDVI decline throughout the time series and experienced increases in predicted Palila count represent potential drought microrefugia for the species. This higher elevation microrefugia is likely resilient against decreases in wet season precipitation through supplemental water retention from fog drip. While NDVI rebounded after 2014, Palila have not recovered. Our analysis highlights the importance of trend decomposition for monitoring endangered species with limited rebound potential due to small population dynamics and indicate continued warm, dry conditions may prevent Palila recovery without intervention.

Hawaii↗

USGS2024

First records distribution models to guide biosurveillance for non-native species

Quickly locating new populations of non-native species can reduce the ecological and economic costs of species invasions. However, the difficulty of predicting which new non-native species will establish, and where, has limited active post-border biosurveillance efforts. Because pathways of introduction underlie spatial patterns of establishment risk, an intuitive approach is to search for new non-native species in areas where many non-native species have first been detected in the past. We formalize this intuition via first records distribution models (FRDMs), which apply species distribution modeling methods to the collection of first occurrence records across species (i.e. one record per species). We define FRDMs as statistical models that quantify environmental conditions associated with species' first naturalized records to predict spatial patterns of establishment risk. We model the first records of non-native plants in the conterminous USA as a proof-of-concept. The novelty of FRDMs is that their inferences apply not just to the species that contributed data; they provide a rigorous framework for predicting hotspots of invasion for new non-native taxa that share a pathway of introduction with the modeled species. FRDMs can guide survey efforts for new non-native taxa at multiple scales and across ecosystems.

conterminous United States↗

USGS2024

Advancing at-risk species recovery planning in an era of rapid ecological change with a transparent, flexible, and expert-engaged approach

In the face of unprecedented ecological changes, the conservation community needs strategies to recover species at risk of extinction. On the Island of Maui, we collaborated with species experts and managers to assist with climate-resilient recovery planning for 36 at-risk native plant species by identifying priority areas for the management of recovery populations. To do this, we developed a tailored spatial conservation prioritization (SCP) approach distinguished by its emphasis on transparency, flexibility, and expert (TFE) engagement. Our TFE SCP approach consisted of 2 iterative steps: first, the generation of multiple candidate conservation footprints (i.e., prioritization solutions) with a flexible greedy algorithm that reflects conservation practitioners’ priorities and, second, the selection of an optimal conservation footprint based on the consideration of trade-offs in expert-agreed criteria among footprints. This process maximized buy-in by involving conservation practitioners and experts throughout, from setting goals to reviewing optimization data, defining optimization rules, and designating planning units meaningful to practitioners. We minimized the conservation footprint area necessary to meet recovery goals while incorporating species-specific measures of habitat suitability and climate resilience and retaining species-specific information for guiding recovery efforts. Our approach reduced the overall necessary conservation area by 36%, compared with selecting optimal recovery habitats for each species separately, and still identified high-quality habitat for individual species. Compared with prioritizr (an existing SCP tool), our approach identified a conservation area of equal size but with higher quality habitat. By integrating the strengths of existing techniques in a flexible and transparent design, our approach can address natural resource management constraints and provide outputs suitable for local recovery planning, consequently enhancing engagement and buy-in from conservation practitioners and experts. It demonstrates a step forward in making conservation planning more responsive to real-world complexities and helps reduce barriers to implementation for local conservation practitioners.

Hawaii↗

USGS2024

Using systematic conservation planning to recover climate resilient habitat for threatened and endangered species while retaining areas of cultural importance

The effective management of at-risk species often requires fine-scale actions by natural resource managers. However, balancing these actions with concurrent land uses is challenging, particularly when compounded by the interplay of climate shifts, and escalating wildland–urban interface conflicts. We used spatial prioritization tools designed for biodiversity conservation to help resource managers on the Island of Lānaʻi prioritize mutually exclusive land use objectives: endangered species recovery and subsistence and recreational hunting. We weighed the current and anticipated future distributions of threatened and endangered plant species against the distribution of non-native game mammals to plan for species recovery more effectively. Prioritization results identified multiple footprints that could support recovery of all endangered species targets in climate resilient areas while retaining the majority of existing hunting areas. However, very little native vegetation was retained in conservation footprints without deliberate inclusion, which increased footprint area by 268%. Scenarios which prioritized contiguous conservation areas also dramatically increased conservation footprint area, although these scenarios may reduce associated fencing costs. This work demonstrates how spatial prioritization may guide localized species recovery efforts by supporting long-term conservation planning that addresses anticipated climate-driven increases in conflict between conservation and other land uses, with clear applicability beyond Lānaʻi.

Conservation↗

USGS2024

Exploring and integrating differences in niche characteristics across regional and global scales to better understand plant invasions in Hawaiʻi

The spread of ecosystem modifying invasive plant (EMIP) species is one of the largest threats to native ecosystems in Hawaiʻi. However, differences in niche characteristics between Hawaiʻi’s isolated insular environment and the wider global distribution of these species have not been carefully examined. We used species distribution modeling (SDM) methods to assess similarities and differences in niche characteristics between global and regional scales for 17 EMIPs present in Hawaiʻi. With a clearer understanding of the global context of regional plant invasion, we combined two SDM methods to better understand the potential future regional spread: (1) a nested modeling approach to integrate global and regional invasive species distribution projections; and (2) integrating all available agency and citizen science data to minimize the effect of monitoring gaps and biases. Our results show there are multiple similarities in niche characteristics across regional and global scales for most species, such as similar sets of climatic determinants of distribution, similar responses along environmental gradients, and moderate to high niche overlap between global and regional models. However, some differences were apparent and likely due to several factors including incomplete regional spread, community assembly or diversity effects. Invaders that established earlier showed a higher degree of niche overlap and similar environmental gradient responses when comparing global and regional models. This pattern, coupled with the tendency for regionally-based projections to predict narrower distributions than global projections, indicates a potential for continued spread of several invasive species across the Hawaiian landscape. Our study has broader implications for understanding the distribution and spread of invasive species in other regions, as similar analyses and models, including a novel way to characterize environmental gradient response differences across regions or scales, can likely provide valuable information for conservation and management efforts.

Hawaii↗

USGS2024

Fine-resolution land cover mapping over large and mountainous areas for Lāna‘i, Hawaii using posterior probabilities, and expert knowledge

The task of accurately mapping species-specific vegetation cover in remote and topographically complex regions like those found in Hawaiʻi presents unique challenges. This study leverages a machine learning approach to accurately classify vegetation into fine species-specific classes across the island of Lāna‘i, Hawaii, offering a novel methodology for tackling such challenges. Utilizing high-resolution WordView-2 satellite imagery, a neural network classifier and a custom lidar-based geometric correction, we introduced two new approaches to refine our high-resolution land cover classifications. This included the implementation of prior-based adjustments to class posterior probabilities to enhance land cover classification accuracy. Moreover, we developed mixed hierarchical classification maps that use class posterior probabilities to identify, at the pixel level, the finest land cover class that meets a user-defined confidence threshold. The resulting high-resolution land cover map for Lāna‘i captures the rich diversity and distribution of native and invasive plant species with high overall accuracy, generally exceeding 95%, based on independent ground control data. The capacity to produce wall-to-wall species-level vegetation maps provides a new window into monitoring vegetation dynamics on Lāna‘i and similarly remote and topographically complex regions, and contributes to our broader understanding of ecosystem responses to invasive species, climatic changes, and land management practices such as erosion and sediment control planning. Our approach offers a blueprint for similar efforts in other complex and remote ecosystems.

Hawaii↗

USGS2024

Identifying conservation introduction sites for endangered birds through the integration of lidar-based habitat suitability models and population viability analyses

Similar to other single-island endemic Hawaiian honeycreepers, the critically endangered ‘ākohekohe ( Palmeria dolei ) is threatened by climate-driven disease spread. To avert the imminent risk of extinction, managers are considering novel measures, including the conservation introduction (CI) of ‘ākohekohe from Maui to higher elevation habitats on the Island of Hawai’i. This study integrated lidar-based habitat suitability models (LHSMs) and population viability analyses (PVAs) to assess five candidate sites currently considered by managers for CI. We first developed an LHSM for the species’ native range on Maui. We then projected habitat suitability across candidate CI sites, using forest structure and topography metrics standardized across sensor types. Given the structural variability observed within the five candidate sites, we identified clusters of contiguous, highly suitable habitat as potential release sites. We then determined how many adult individuals could be supported by each cluster based on adult home range estimates. To determine which clusters could house the minimum number of ‘ākohekohe birds necessary for a stable or increasing future population, we conducted PVAs under multiple scenarios of bird releases. We found that canopy height and relative height 90 had the greatest effects on model performance, possibly reflecting ‘ākohekohe’s preference for taller canopies. We found that a small release of at least nine pairs of equal sex ratios were sufficient for an 80% chance of success and a <1% chance of extirpation in 20 years, resulting in a minimum release area of 4.5 ha in size. We integrated the results of the LHSM and PVA into an interactive web application that allowed managers to consider the caveats and uncertainties associated with both LHSMs and PVAs in their decision-making process. As climate change continues to threaten species worldwide, this research demonstrates the value of lidar remote sensing combined with species-specific models to enable rapid, quantitative assessments that can inform the increasing consideration of time-sensitive conservation introductions.

Hawaii↗

USGS2024

Environmental and geographical factors influence the occurrence and abundance of the southern house mosquito, Culex quinquefasciatus, in Hawai‘i

Hawaiian honeycreepers, a group of endemic Hawaiian forest birds, are being threatened by avian malaria, a non-native disease that is driving honeycreepers populations to extinction. Avian malaria is caused by the parasite Plasmodium relictum , which is transmitted by the invasive mosquito Culex quinquefasciatus . Environmental and geographical factors play an important role in shaping mosquito-borne disease transmission dynamics through their influence on the distribution and abundance of mosquitoes. We assessed the effects of environmental (temperature, precipitation), geographic (site, elevation, distance to anthropogenic features), and trap type (CDC light trap, CDC gravid trap) factors on mosquito occurrence and abundance. Occurrence was analyzed using classification and regression tree models (CART) and generalized linear models (GLM); abundance (count data) was analyzed using generalized linear mixed models (GLMMs). Models predicted highest mosquito occurrence at mid-elevation sites and between July and November. Occurrence increased with temperature and precipitation up to 580 mm. For abundance, the best model was a zero-inflated negative-binomial model that indicated higher abundance of mosquitoes at mid-elevation sites and peak abundance between August and October. Estimation of occurrence and abundance as well as understanding the factors that influence them are key for mosquito control, which may reduce the risk of forest bird extinction.

Hawaii↗

USGS2024

Ohi'a lehua (Metrosideros polymorpha): A most resilient and persistent foundation species in Hawaiian forests

Metrosideros polymorpha (‘ōhi‘a, ‘ōhi‘a lehua) is an important foundation species in Hawaiian forest habitats. The genus originated in New Zealand and was dispersed to the Hawaiian archipelago approximately 3.9 million years ago. It evolved into five distinct endemic species and one of these, Metrosideros polymorpha , further differentiated into eight varieties across what are now the main Hawaiian Islands. ‘Ōhi‘a is a tree that has great significance in indigenous Hawaiian culture. It is considered a physical manifestation of several principal Hawaiian deities, and serves a broad range of uses in Hawaiian material culture. It occupies a wide diversity of habitats, extending from sea level to over 2,200 m elevation, occupying habitats that range from extremely wet to dry rainfall zones. It is the dominant or co-dominant tree species in wet and mesic forests and is also one of the first woody species to become established on young lava flows. Although ‘ōhi‘a is a dominant forest tree it also exhibits many characteristics of a pioneer species. ‘Ōhi‘a provides the matrix for a wide diversity of endemic plants and animals found in these habitats and functions as the primary vegetation cover on native Hawaiian watersheds, facilitating groundwater recharge and regulating surface runoff. ‘Ōhi‘a has shown remarkable resilience by recolonizing forests that were opened up by disturbance, such as the widespread ‘ōhi‘a canopy dieback that occurred on East Maui in the 1900s and on the east side of the Island of Hawai‘i in the 1970s. Several human-related conditions threaten the continued stability of Hawaii’s native ecosystems, including invasive plants, plant diseases, introduced animals, and changing climate. The research and conservation legacy of Dr. Dieter Mueller-Dombois helped to expand our knowledge of the ecology and importance of ‘ōhi‘a forests, and to increase awareness and appreciation of the remarkable Hawaiian ecosystems that are unique to the world.

Hawaii↗

USGS2023

Examining current bias and future projection consistency of globally downscaled climate projections commonly used in climate impact studies

The associated uncertainties of future climate projections are one of the biggest obstacles to overcome in studies exploring the potential regional impacts of future climate shifts. In remote and climatically complex regions, the limited number of available downscaled projections may not provide an accurate representation of the underlying uncertainty in future climate or the possible range of potential scenarios. Consequently, global downscaled projections are now some of the most widely used climate datasets in the world. However, they are rarely examined for representativeness of local climate or the plausibility of their projected changes. Here we explore the utility of two such global datasets (CHELSA and WorldClim2) in providing plausible future climate scenarios for regional climate change impact studies. Our analysis was based on three steps: (1) standardizing a baseline period to compare available global downscaled projections with regional observation-based datasets and regional downscaled datasets; (2) bias correcting projections using a single observation-based baseline; and (3) having controlled differences in baselines between datasets, exploring the patterns and magnitude of projected climate shifts from these datasets to determine their plausibility as future climate scenarios, using Hawaiʻi as an example region. Focusing on mean annual temperature and precipitation, we show projected climate shifts from these commonly used global datasets not only may vary significantly from one another but may also fall well outside the range of future scenarios derived from regional downscaling efforts. As species distribution models are commonly created from these datasets, we further illustrate how a substantial portion of variability in future species distribution shifts can arise from the choice of global dataset used. Hence, projected shifts between baseline and future scenarios from these global downscaled projections warrant careful evaluation before use in climate impact studies, something rarely done in the existing literature.

Hawaii↗

USGS2023

Empirical estimation of habitat suitability for rare plant restoration in an era of ongoing climatic shifts

Accurate estimates of current and future habitat suitability are needed for species that may require assistance in tracking a shifting climate. Standard species distribution models (SDMs) based on occurrence data are the most common approach for evaluating climatic suitability, but these may suffer from inaccuracies stemming from disequilibrium dynamics and/or an inability to identify suitable climate regions that have no analogues within the current range. An alternative approach is to test performance with experimental introductions, and model suitability from the empirical results. We used this method with the Haleakalā silversword ( Argyroxiphium sandwicense subsp. macrocephalum ), using a network of out-plant plots across the top of Haleakalā volcano, Hawaiʻi. Over a ~ 5-year period, survival varied strongly across this network and was effectively explained by a simple model including mean rainfall and air temperature. We then applied this model to estimate current climatic suitability for restoration or translocation activities, to define trends in suitability over the past three decades, and to project future suitability through 2051. This empirical approach indicated that much of the current range has low suitability for long-term successful restoration, but also identified areas of high climatic suitability in a region where plants do not currently occur. These patterns contrast strongly with projections obtained with a standard SDM, which predicted continued suitability throughout the current range. Under continued climatic shifts, these results caution against the common SDM presumption of equilibrium between species’ distributions and their environment, even for long-established native species.

Hawaii↗

USGS2023

Citizen science can complement professional invasive plant surveys and improve estimates of suitable habitat

Aim Citizen science is a cost-effective potential source of invasive species occurrence data. However, data quality issues due to unstructured sampling approaches may discourage the use of these observations by science and conservation professionals. This study explored the utility of low-structure iNaturalist citizen science data in invasive plant monitoring. We first examined the prevalence of invasive taxa in iNaturalist plant observations and sampling biases associated with these data. Using four invasive species as examples, we then compared iNaturalist and professional agency observations and used the two datasets to model suitable habitat for each species. Location Hawai'i, USA. Methods To estimate the prevalence of invasive plant data, we compared the number of species and observations recorded in iNaturalist to botanical checklists for Hawai'i. Sampling bias was quantified along gradients of site accessibility, protective status and vegetation disturbance using a bias index. Habitat suitability for four invasive species was modelled in Maxent, using observations from iNaturalist, professional agencies and stratified subsets of iNaturalist data. Results iNaturalist plant observations were biased towards invasive species, which were frequently recorded in areas with higher road/trail density and vegetation disturbance. Professional observations of four example invasive species tended to occur in less accessible, native-dominated sites. Habitat suitability models based on iNaturalist versus professional data showed moderate overlap and different distributions of suitable habitat across vegetation disturbance classes. Stratifying iNaturalist observations had little effect on how suitable habitat was distributed for the species modelled in this study. Main Conclusions Opportunistic iNaturalist observations have the potential to complement and expand professional invasive plant monitoring, which we found was often affected by inverse sampling biases. Invasive species represented a high proportion of iNaturalist plant observations, and were recorded in environments that were not captured by professional surveys. Combining the datasets thus led to more comprehensive estimates of suitable habitat.

Hawaii↗

USGS2023

High resolution lidar data shed light on inter-island translocation of endangered bird species in the Hawaiian Islands

Translocation, often a management solution reserved for at-risk species, is a highly time-sensitive intervention in the face of a rapidly changing climate. The definition of abiotic and biotic habitat requirements is essential to the selection of appropriate release sites in novel environments. However, field-based approaches to gathering this information are often too time intensive, especially in areas of complex topography where common, coarse-scale climate models lack essential details. We apply a fine-scale remote sensing-based approach to study the 'akikiki ( Oreomystis bairdi ) and 'akeke'e ( Loxops caeruleirostris ), Hawaiian honeycreepers endemic to Kaua'i that are experiencing large-scale population declines due to warming-induced spread of invasive disease. We use habitat suitability modeling based on fine-scale light detection and ranging (lidar)-derived habitat structure metrics to refine coarse climate ranges for these species in candidate translocation areas on Maui. We found that canopy density was consistently the most important variable in defining habitat suitability for the two Kaua'i species. Our models also corroborated known habitat preferences and behavioral information for these species that are essential for informing translocation. We estimated a nesting habitat that will persist under future climate conditions on east Maui of 23.43 km 2 for 'akikiki, compared to the current Kaua'i range of 13.09 km 2 . In contrast, the novel nesting range for 'akeke'e in east Maui was smaller than its current range on Kaua'i (26.29 vs. 38.48 km 2 , respectively). We were also able to assess detailed novel competitive interactions at a fine scale using models of three endemic Maui species of conservation concern: 'ākohekohe ( Palmeria dolei ), Maui 'alauahio ( Paroreomyza montana ), and kiwikiu ( Pseudonestor xanthophrys ). Weighted overlap areas between the species from both islands were moderate (<12 km 2 ), and correlations between Maui and Kaua'i bird habitat were generally low, indicating limited potential for competition. Results indicate that translocation to east Maui could be a viable option for 'akikiki but would be more uncertain for 'akeke'e. Our novel multifaceted approach allows for the timely analysis of both climate and vegetation structure at informative scales for the effective selection of appropriate translocation sites for at-risk species.

Hawaii↗

USGS2023

Estimating the impact of climate and vegetation changes on runoff risk across the Hawaiian landscape

In Hawai’i, ecosystem conservation practitioners are increasingly considering the potential ecohydrological benefits from applied conservation action to mitigate the degrading impacts of runoff on native and restored ecosystems. One determinant of runoff is excess rainfall events where rainfall rates exceed the infiltration capacity of soils. To help understand runoff risks, we calculated the probability of excess rainfall events across the Hawaiian landscape by comparing the probability distributions of projected rainfall frequency and land-cover-specific infiltration capacity. We characterized soil infiltration capacity based on different land cover types (bare soil, grasses, and woody vegetation) and compared them to the frequency of large rainfall events under current and future climate scenarios. We then mapped the potential risk of excess rainfall across the main Hawaiian Islands. Our results show that land cover type has a very large effect on runoff risk as excess rainfall conditions are 234% more likely in bare soil and 75% more likely in grasslands compared to woody forests and shrublands. In contrast, projected shifts in rainfall intensity by end-of-century show little impact on these probabilities and thus, the risk of runoff. This indicates that the probability of excess rainfall is primarily driven by differences in land cover and not by current or potential shifts in rainfall patterns across the Hawaiian landscape. The ability to estimate the risk of potentially ecologically and economically costly runoff based on changes of land cover is useful for managers focused on invasive species control and restoration planning, especially for native and endemic ecosystems unique to the State of Hawai’i.

Hawaii↗