Adaptive Management Research Articles

Northeast Atlantic fish stock productivity hindcasts and forecasts from a Bayesian framework reveal pronounced climate‐induced dynamics

AbstractClimate change continues to exert pressure on ocean ecosystems. The fisheries‐related responses, such as altered body growth, recruitment and spatial distribution of the targeted stock(s), have generally been reasonably well investigated. Nevertheless, there are still important knowledge gaps in how biophysical drivers impact stock productivity and thereby sustainable harvest levels. Considering this, we investigated 26 fish stocks in the Northeast Atlantic, a region characterized by accelerated climate change effects and a diverse set of fisheries. A novel, stepwise, Bayesian framework to quantify stock productivity was established to identify shared trends and project future patterns, aiming at determining essential baselines for adaptive fishery management in the face of climate change. Despite variation among large marine ecosystems and stocks, an overall declining trend in productivity over the past four decades was observed, especially in high‐latitude areas. These hindcast results were mainly attributed to higher temperatures posing negative effects on productivity, which was dependent on the stock's thermal preference. Contrastingly, the proxy for food availability – gross secondary production – exhibited less consistent impacts. In the forecast, the applied Shared Socio‐economic Pathways (SSPs) indicated that most stocks are likely to encounter adverse effects, with the worst cases expected to occur under SSP2‐4.5 in the 2050s, and under SSP5‐8.5 in the 2090s. Thus, this study generally not only supports earlier climate vulnerability assessments (‘scorings’) of experts but also provides evidence for revised directional effects under climate change, underlining the complexity of processes affecting stock productivity.

What is happening with frequency and occurrence of the maximum river discharges in Bosnia and Herzegovina?

In this study, we explored the frequency and occurrence rate of maximum river discharges in the Una and Sana rivers, to understand hydrological variations amidst climate change. We categorized maximum discharges into severe (Una River M1 > 98.2 m3/s; Sana River M1 > 118.2 m3/s) and extreme (Una River, M2, > 123.4 m3/s; Sana River M2 > 246.4 m3/s) events, and identified trends in these events, crucial for assessing environmental impacts. Our findings reveal a nuanced pattern: both rivers experience an increase in severe events from 58 to 55 and 56 to 54 days return period respectively, indicating complex hydrological dynamics. The trends underscore the significant shifts in annual event occurrences, the evolving nature of river systems and underscore the necessity for adaptive management strategies.

Assessing ecosystem services of mountain lakes

From global to local scales, human-induced environmental changes can impact mountain lakes by, for example, altering species composition, trophic state, and thermal dynamics, thereby affecting ecosystem functions and processes. However, the consequences of these changes on ecosystem services (ES) of mountain lakes are unclear due to a lack of integrative assessments. Therefore, this dissertation adopts an interdisciplinary ES perspective to improve insight into human interactions with mountain lakes and the potential social and ecological impacts of anthropogenic pressures on them. Stakeholder consultations highlighted the importance of regulating, cultural, and provisioning ES of natural mountain lakes, emphasizing habitat, aesthetics, recreation, education and research, and surface water, with nature-based experiences as being a key aspect of human interaction with mountain lakes. Multiple indicators were proposed to quantify potential supply of these ES, revealing variations among case study lakes in the European Alps. These results informed an integrative valuation approach and exposure assessment to anthropogenic pressures, suggesting that ES by mountain lakes are sensitive to climate change-related and human use pressures. Overall, the findings advance a social-ecological understanding of mountain lakes and indicate towards the need for adaptive lake management to maintain ES under potential anthropogenic pressure.

Adaptive grazing enhances plant species richness and density in the soil seed bank in a semi-arid grassland

The soil seed bank plays a key role in vegetation resilience under environmental disturbances, and is especially important for the restoration of degraded vegetation. However, the responsive dynamics of the soil seed bank to animal grazing and its potential in the restoration of grazing degraded steppe grassland remain unclear. Here we examined the changes in plant species diversity and density in both the soil seed bank and the aboveground vegetation of a natural grassland along an experimental gradient of four grazing intensities (nil, light, moderate and heavy grazing) in an adaptive grazing management system that ensures grassland residual cover was always above a certain criteria. The grassland is a typical steppe dominated by Leymus chinensis, Stipa grandis, and Cleistogenes squarrosa in central Inner Mongolia, China. We found that (i) plant species richness and density of the seed bank in the top 10 cm soil layer increased with grazing intensity, though the density of the seed bank in the top 5 cm soil layer showed an decrease. (ii) Moderate and heavy grazing significantly decreased the density of perennial but increased annual and biennial plants in the top 5 cm soil layer, which dominate the changes in the top 10 cm soil layer. (iii) Plant species richness and density in the aboveground vegetation also increased with grazing intensity, so did the similarity between the species composition of the soil seed bank and aboveground vegetation in the top 10 cm. The increase in the richness and density of annual and biennial species dominated the responsive changes to grazing of the soil seed bank and aboveground vegetation in the studied grassland. Our results provide a reference basis for grazing management in the region from the perspective of the soil seed bank, and suggest that the adaptive grazing system with grassland residual height controlled above a criterion benefits to the soil seed bank thus the re-generation of vegetation.

A rapid monitoring protocol to estimate unharvested corn biomass in waterfowl impoundments

AbstractConservation planners use bioenergetic models to develop habitat objectives that satisfy energetic demands of waterfowl during nonbreeding periods. In turn, natural resource managers should estimate yield and availability of natural and cultivated waterfowl forage to monitor contributions to objectives and support adaptive resource management. Because bioenergetic models are particularly sensitive to unharvested flooded croplands, we developed a rapid methodology to estimate biomass of unharvested flooded corn (Zea mays) and tested our methodology in impounded corn fields planted and flooded in western Tennessee during autumn and winter of 2019–2021. We evaluated accuracy of our rapid assessment method and conducted simulations to assess variance‐bias trade‐offs relative to sample size. Rapid assessments lasted 20 min ± 10 minutes per field. Our rapid assessment method underestimated number of kernels per ear by 2.6% ± 0.5%. After adjusting for underestimation bias, corn biomass across all surveys was 5,500 kg/ha ± 250 kg/ha, which is similar yield to previous literature from waterfowl impoundment fields. Sampling 15 ears per field allowed field biomass to be estimated within acceptable accuracy (i.e., variance [SE] of mean percent error <1.8%). We recommend our rapid yield assessment method be incorporated into habitat monitoring protocols to efficiently and precisely estimate corn biomass for improved conservation planning initiatives. Additionally, our rapid assessment method allows managers to monitor field yield rapidly, enabling estimates of corn depletion and availability throughout the nonbreeding season for waterfowl to support management decisions.

AI-powered Leadership in Moroccan Organizations: An Integrative Literature Review

This integrative literature review (ILR) examines how we can exploit AI to enhance organizational leadership in Morocco, where there is a notable lack of awareness among leaders and IT policymakers about the revolutionary potential of AI-powered leadership. This ILR aims to address this knowledge gap by looking at the application and impact of strategic analytics and adaptive machine learning management in critical industries such as banking, healthcare, tourism, manufacturing, and logistics. These AI-driven techniques get value for their ability to alter leadership by improving Moroccan decision-makers capacities in driving competitiveness and organizational sustainability. The review thoroughly illuminates the power of AI-driven leadership, which Strategic Analytics and Adaptive Machine Learning Management trigger. The study's conceptual framework revolves around four key pillars: AI, strategic analytics, leadership, and adaptive machine learning management. This ILR employs inclusion and exclusion criteria, data extraction, data analysis and synthesis, and conceptual mapping to ensure the rigor and comprehensiveness of the research material. The findings of this ILR highlight the significance of implementing strategic analytics and adaptive machine learning management into Morocco's leadership practices. They illuminate the need to develop a strong leadership pipeline, conduct collaborative research, establish policy frameworks, safeguard data, foster innovation in management, and train the workforce. This review offers suggestions for forthcoming policies and practices, emphasizing the application of adaptive machine learning management and strategic analytics. These recommendations can significantly influence the practice of AI-powered leadership in Moroccan organizations and offer valuable insights for future research.

Declining geomorphic diversity and potential adaptive management opportunities on a highly regulated reach of the Bighorn River, Montana

ABSTRACT Rivers downstream from dams often experience decreased flow variability and disrupted sediment transport. We investigated a highly regulated 35.5-kilometre reach of the Bighorn River, downstream from Yellowtail Dam, emplaced in 1965. This dam created a thriving trout fishery, but more recently, side channel networks and habitat diminished. We document how the Bighorn River's anabranching morphology responded to flow regulation and a near cessation of sediment supply. Geomorphic diversity drastically decreased since 1939 and the Bighorn River abandoned numerous side channels. By 1980, geomorphic loss slowed, and the river became laterally static. The 1980 river and side channel network could represent the maximum areal extent of a downscaled morphology, maintained through restoration and adaptive management. However, side channel restoration alone will not return natural alluvial processes to this river reach. The Bighorn River needs sediment to reinstate dynamic lateral movement, even within a downscaled morphology. Sediment augmentation is an option, but more complex to implement on rivers where potential downstream impacts and landowners must be considered. The decline of geomorphic diversity and potential adaptive management solutions on the Bighorn River has wide applicability to numerous dammed rivers, where similar changes to the flow and sediment transport regime are common.

The capacity of sentinel species to detect changes in environmental conditions and ecosystem structure

Abstract A major obstacle to preventing and reversing biodiversity loss in the Anthropocene lies in the scarcity of tools and data for monitoring the health and trajectory of ecosystems. Sentinel species can provide insight into unobserved ecosystem change, but it is unclear how effective sentinels are due to the local, context‐dependent nature of past research. Here, we present the first global evaluation on the effectiveness of sentinel species as indicators of ecosystem change. We conducted a meta‐analysis on 372 case studies to identify the ecological and methodological factors that correlate with the most effective sentinel species. Sentinel performance did not vary consistently across taxa or system; instead, sentinels that were more directly linked to ecosystem change due to their trophic role as predators were more effective. In addition, sentinel responses that were measured on a shorter timescale were more effective at indicating ecosystem change. Policy Implications. These results contribute to the longstanding debate on “what makes a good sentinel” and demonstrate the importance of both ecological and methodological factors when selecting sentinels to detect ecosystem change. For example, sentinel species which are trophically linked and measured on short timescales may be more effective for managers seeking to monitor ecosystem change than other species. By identifying effective traits for the use of sentinel species, scientists and policymakers will be able to develop rapid and adaptable management plans in response to global change.

Climate change shocks and crop production: The foodgrain bowl of India as an example

Global warming is causing climate change (CC) characterized by increased frequency of heatwaves, droughts, erratic rains, hailstorms, cloudbursts, floods, landslides etc. The CC has already adversely affected ecosystems. In spite of efforts to mitigate greenhouse gas (GHG) emissions, which lead to warming, the global temperature during 2011–20 was 1.1°C above that during pre-industrial era. The projections are that warming will continue to increase and adverse effects will intensify particularly in developing countries like India. In India a number of studies have recorded wide spatial variability in rainfall, though, many reported a general overall negative trend since mid-20th century. Further, varying pattern of rainfall has been recorded in three agroclimatic regions of Punjab state, the granary of India. Unseasonal rains followed by spiked temperature during winter (rabi) season of 2021–22 reduced wheat (Triticum aestivum L.) yield in Punjab by 651 kg/ha and by 301 kg/ha in Haryana compared to 2020–21. Further, the grain was of lower quality. During rainy (kharif) season of 2022, Southern Rice Black-streaked Dwarf Virus (SRBSDV), appeared for the first time in Punjab and Haryana. Some farmers ploughed the affected fields. Adverse weather during rabi 2022–23 also, reduced the wheat yield (143–150 kg/ha) in these states. At the national level, erratic weather during rabi 2021–22 and kharif 2022 caused losses of about 3 mt of grain of each of wheat and rice (Oryza sativa L.). The projected increased adverse effects due to intensified CC include food insecurity. Thus, there is an emergent need to accelerate implementation of adaptation and mitigation strategies in agriculture. The adaptation options include cultivar improvement, conservation agriculture altering growing seasons, crop diversification and sustainable soil, and water resource management. In the process of adaptive management of crop production, adjusting sowing dates and breeding cultivars having varying duration in consonance with CC has been one of the central aspects. Shifting sowing dates to find appropriate crop cultivation season is a low-cost measure. However, cultivar development is time and resource consuming. Novel biotechnological tools enable fast cultivar development with precision, and facilitate mobilization of genes from wild-weedy relatives, which are rich in genes conferring resistance/tolerance to biotic and biotic stresses, required to combat CC challenge. In view of CC stress on water resources, improving water-use efficiency (WUE) has gained importance. Sensor-based micro-irrigation/fertigation has great potential to enhance water and fertilizer-use efficiency. Similarly, the application of other smart technologies like nanotechnology, sensor-based pesticide application, bio-fertilizers and bio-pesticides, need to be mobilised. In view of agro-ecological diversity in India, right-sized regionspecific technology packages have to be developed implying that crop research will expand exponentially. This needs strengthening of human resources and institutional infrastructure, expanding and linking basic and applied researches, and fortifying inter-disciplinary/inter-institutional collaborations to develop and diffuse technology innovations. Enabling factors include enhanced funding and international cooperation. All-out efforts are needed to have more climate-resilient agriculture.

The Source-to-Sea Landscape: A hybrid integrative territory management approach

Whether fresh or salty, water is a unique resource, a continuum interlinked by the hydrological cycle. It forms a complex system connected to the landscape. When the landscape is altered, water flows and their benefits are impacted. Degraded land compromises water resources. The governance and management of landscape and water resources are handled in a fragmented manner and in separate contexts. The Source-to-Sea approach offers an integrative vision based on systems thinking that focuses its concerns on the interaction among parts, flows, and processes. It proposes a framework for the governance and management of freshwater and marine water but does not bring the landscape into the context of the approach. This research used an analytical-deductive method to explore the interactions and connections between the Source-to-sea approach, landscape concepts and approaches, and the guidelines of the European Landscape Convention. The main objective was to identify and assess the feasibility of integrating these elements. The integration resulted in a governance and management approach termed the S2S Landscape approach. It is grounded in systems thinking, practical learning, active participation, and adaptive governance and management, providing an integrated vision between landscape and water. The approach includes four essential steps (Comprehension, Involvement, Planning, and Execution and Monitoring) that address the complex connections that freshwater and marine water maintain in the landscape, considering physical, biological, socio-environmental, and economic aspects across all segments, from the land to the open sea. This S2S Landscape approach may be the path to address the challenges of governance and sustainable management of resources in an interconnected and constantly changing world.

Construction and Analysis of Automated Human Resource Management System

The issues of constructing and developing an automated system that is adaptive to external internal factors of personnel management are important for improvement of personal management of modern enterprises. Due to these issues there is a need in the  automation the process of approving both strategic and operational plans at the enterprise. To reach this goal the adaptive personnel management system under consideration is built on the basis of an automated dynamic model, taking into account decision support in the personnel management process for each employee, which makes it possible to reduce the significance of the discrepancy between strategic and operational tasks. The results of a study of local sustainability for the constructed automated personnel management system make it possible to draw a conclusion about possibilities to increase the efficiency of using human resources in the enterprise with the use of the system. The proposed automated personnel management system is presented in the form of cross-links, which helps prevent duplication of employee tasks.

Effects of Grazing Regulations on Pasture Health in New Zealand

Purpose: The aim of the study was to analyze the effects of grazing regulations on pasture health in New Zealand. Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: Grazing regulations in New Zealand have both positive and negative effects on pasture health. While well-managed regulations can enhance grass growth and prevent overgrazing, stringent rules may lead to underutilization and reduced biodiversity. Effective enforcement and farmer compliance are crucial for maximizing the benefits of grazing regulations, highlighting the need for a balanced approach that considers ecological sustainability and livestock management needs. Unique Contribution to Theory, Practice and Policy: Environmental determinism, resource dependence theory & ecological modernization theory may be used to anchor future studies on analyze the effects of grazing regulations on pasture health in New Zealand. Tragedy of the commons, ecological resilience theory & adaptive management theory

A framework for studying the effects of offshore wind energy development on birds and bats in the Eastern United States

Offshore wind energy development (OWED), while a key strategy for reducing carbon emissions, has potential negative effects to wildlife that should be examined to inform decision making and adaptive management as the industry expands. We present a conceptual framework to guide the long-term study of potential effects to birds and bats from OWED. This framework includes a focus on exposure and vulnerability as key determinants of risk. For birds and bats that are exposed to OWED, there are three main effects of interest that may impact survival and productivity: 1) collision mortality, 2) behavioral responses, including avoidance, displacement, and attraction, and 3) habitat-mediated effects to prey populations. If these OWED effects cause changes in survival and/or breeding success (e.g., fitness), they have the potential for population-level consequences, including changes in population size and structure. Understanding the influence of ecological drivers on exposure and effect parameters can help to disentangle the potential impacts of OWED from other stressors. We use this theoretical framework to summarize existing relevant knowledge and identify current priority research questions (n=22) for the eastern United States, where large-scale development of OWED is primarily in the planning and early construction phase. We also identify recommendations for study design and further prioritization of research topics.

Projected habitat preferences of commercial fish under different scenarios of climate change

The challenges of commercial species with the threats of climate change make it necessary to predict the changes in the distributional shifts and habitat preferences of the species under possible future scenarios. We aim to demonstrate how future climatic changes will affect the habitat suitability of three species of commercial fish using the predictive technique MaxEnt. The dataset used to extract geographical records included OBIS (54%), GBIF (1%), and literature (45%). The output of the model indicated accurate projections of MaxEnt (AUC above 0.9). Temperature was the main descriptor responsible for the main effects on the distribution of commercial fish. With increasing RCP from 2.5 to 8.5, the species would prefer saltier, higher temperatures and deeper waters in the future. We observed different percentages of suitable habitats between species during RCPs showing distinct sensitivity of each fish in facing climate changes. Negative effects from climate change on the distribution patterns of commercial fish were predicted to lead to varying degrees of reduction and changes of suitable habitats and movement of species towards higher latitudes. The finding emphasizes to implement adaptive management measures to preserve the stocks of these commercial fish considering that the intensification of the effects of climate change on subtropical areas and overexploited species is predicted.

The past and future of ecosystem restoration in China

For decades, China has implemented restoration programs on a large scale, thanks to its capacity to set policy and mobilize funding resources. An understanding of China's restoration achievements and remaining challenges will help to guide future efforts to restore 30% of its diverse ecosystems under the Kunming-Montreal Global Biodiversity Framework. Here we summarize the major transitions in China's approach to ecosystem restoration since the 1970s, with a focus on the underlying motivations for restoration, approaches to ecosystem management, and financing mechanisms. Whereas China's restoration efforts were predominantly guided by the delivery of certain ecosystem functions and services in earlier decades, more recently it has come to emphasize the restoration of biodiversity and ecosystem integrity. Accordingly, the focal ecosystems, approaches, and financing mechanisms of restoration have also been considerably diversified. This evolution is largely guided by the accumulation of scientific evidence and past experiences. We highlight the key challenges facing China's restoration efforts and propose future directions to improve restoration effectiveness, with regard to goal setting, monitoring, stakeholder involvement, adaptive management, resilience under climate change, and financing.

OATracker: Object-aware anti-occlusion 3D multiobject tracking for autonomous driving

Efficient and accurate 3D multiobject tracking (MOT) is essential for autonomous driving. However, existing methods still struggle with multiobject occlusion, in which interruptions or even loss of crucial tracked objects is likely. Therefore, a more intelligent object-aware anti-occlusion 3D MOT for autonomous driving, named OATracker, is developed in this paper. First, an updated 3D cascaded detection (3DCD) is adopted as the detection backbone, with incorporation of an updatable component based on the OpenPCDet framework to increase the longevity. Second, a reliable object state-constrained affinity (OSA) metric is designed that adaptively combines 3D geometric and motion metrics to dynamically measure objects’ size and distance in both spatial and temporal dimensions. Third, an object-aware trajectory management (OTM) module is developed for trajectory management and status updating. Specifically, the object identity-aware adaptive tracking life manager (ATLM) allows the tracker to adaptively manage the trajectories of captured objects through a confidence metric for each objects, and the ghost-aware trajectory postoptimizer (GTP) associates the historical and detected motion states, further overcoming id-switch and fragmentation problems. Finally, experiments on the KITTI-Car tracking benchmark and practical autonomous driving car application platform show that the OATracker can achieve competitive and robust tracking performance even in occlusion conditions.

Urbanization impact assessment on environment and transportation perspectives: Remote sensing-based approach application

Environmental impact assessment of urbanization and road network analysis are more essential for city’s health measurement. Road contraction due to high urbanization is more impactful for the ecology and traffic congestion-related phenomena. Remote sensing (RS) is a highly applied approach for analyzing the environmental and road cities network-related activities. Landsat 5 TM and 8 OLI/TIRS databased and recent time road network information were used and aimed for assessment of different cities (i.e., Baghdad “Iraq” and Los Vegas “United States”). The Land use and land cover (LULC) and road network are related to each other’s due to the high urbanization and population pressure. Based on modeling results, built-up zones of the selected cities were increased by 249.84 km2 (Baghdad) and 728.47 km2 (Los Vegas) while barren land fluctuated 396.85 km2 (Baghdad) and -712.58 km2 (Los Vegas). Based on the studied period, land surface temperature (LST) increased by 8.68 °C (Baghdad) and 10.06 °C (Los Vegas), which indicates the urbanization effects. Road density observed to be high in the central part of the Baghdad city, while Los Vegas have road density in the entire region. Both cities showed low content of water bodies and vegetation due to urbanization and population pressure. In general, both cities need proper adaptation strategies, urban planning, novel approaches, and management that can help for reduction of the environmental impact. In addition, cities road network-related issues could be substantially increased due to unplanned traffic congestion, accident, environmental degradations in which is triggering the urban vulnerability in near future.

An indicator-based evolutionary algorithm with adaptive archive update cycle for multi-objective multi-robot task allocation

The multi-robot task allocation problem has garnered significant attention in research and development. This paper addresses the multi-robot task allocation problem by introducing a unified model that seamlessly transforms into four popular mathematical models through simple parameter adjustments. We propose an efficient indicator-based multi-objective evolutionary algorithm with a hybrid encoding scheme for task execution order and robot starting point information. The algorithm employs the hypervolume indicator for environmental selection to enhance convergence and the modified crowding distance for archive updates to promote diversity. Additionally, an adaptive archive update mechanism is designed for time efficiency. In experiments comparing our proposed algorithm with 8 state-of-the-art algorithms on 18 randomly generated instances of various sizes, along with 4 real-world problems from the TSPLIB benchmark, our algorithm consistently outperformed the comparison algorithms in five key indicators. These results underscore the effectiveness of our approach in addressing real-world multi-robot task allocation problems.

Enhancing sustainability: Exploring the evolution and dynamics of the grassland social-ecological system in Inner Mongolia over the past 260a

Understanding the intricate relationship between social-ecological systems (SES) coupling and long-term regional sustainable development is critical for effective management strategies. While recent research has predominantly focused on human-earth coupling, there is a dearth of knowledge concerning the transition of grassland SES from one regime to another and the underlying drivers. This study employs a comprehensive SES framework to identify and analyze interactions within typical pastoral areas of Inner Mongolia, aiming to shed light on the evolution of the grassland SES over the past centuries. Our research defines five distinct evolutionary phases in the grassland SES since the mid-Qing Dynasty. Each phase is characterized by unique social and ecological features, providing a nuanced understanding of the system's dynamics. We establish empirical links between the phases and their driving forces and impacts by assessing the main changes between these periods. Specifically, our findings reveal instances of negative cross-scale effects emerging during the evolution process. We observe that unreasonable resource utilization and an inability to curb ecological degradation may lead to unsustainable traps, posing challenges to long-term sustainability. To illustrate, during the transition from Phase 3 to Phase 4 in the late 19th century, a shift towards sedentary pastoralism led to increased land degradation due to intensified grazing practices. This unsustainable trajectory highlights the importance of adaptive management strategies to mitigate such negative consequences. This study contributes insights into the social and ecological management of grassland pastoral areas in China and for global analogous regions. By addressing the identified phases and their associated challenges, our research provides a foundation for crafting sustainable policies and practices to ensure the resilience of grassland SES in diverse geographical contexts.

Modeling attenuation of photosynthetically active radiation across the optical gradient in the Laurentian Great Lakes with application to Lake Erie

Representation of subsurface photosynthetically active radiation (PAR) in biophysical models of the Laurentian Great Lakes (LGL) is imperative to their utility as tools for research and management. Here we consolidated measured vertical profiles of subsurface PAR with concurrent water quality (WQ) data from four LGL. We estimated the diffuse attenuation coefficient of PAR (Kd(PAR)) by fitting an exponential function to measured PAR over depth, and evaluated 68 regressions predicting Kd(PAR) as a function of water quality variables (Kd-WQ regressions). We compare four of the top cross-lake calibrated regressions against two published regressions trained on western Lake Erie (WLE) data. Then, as a case study, we demonstrate the utility of our cross-lake calibrated Kd-WQ regressions with a simplified biophysical model of Lake Erie consisting of the Finite Volume Community Ocean Model with submodules for simulating suspended sediment and dissolved organic carbon (FVCOM-SS-DOC). Twenty-five Kd-WQ regressions were identified as candidates for use in biophysical models based on their skill determined via cross-validation. WLE-trained Kd-WQ regressions were less able to simulate Kd(PAR) and PAR in more transparent waters compared to cross-lake calibrated Kd-WQ regressions, which translated to considerable differences in primary production estimates for the central and eastern basins when using WQ data simulated by FVCOM-SS-DOC. A cross-lake calibrated Kd-WQ regression was installed into FVCOM-SS-DOC, which then simulated spatial patterns of suspended sediments and Kd(PAR). These calibrated Kd-WQ regressions can be used in a variety of biophysical models across optically-distinct waters of the LGL to support adaptive management of nutrient inputs and fisheries