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Abstract Background Coral reefs are rapidly changing in response to local and global stressors. Research to better understand and inform the management of these stressors is burgeoning. However, in situ studies of coral reef ecology are constrained by complex logistics and limited resources. Many reef studies are also hampered by the scale-dependent nature of ecological patterns, and inferences made on causal relationships within coral reef systems are limited by the scales of observation. This is because most socio-ecological studies are conducted at scales relevant to the phenomenon of interest. However, management often occurs across a significantly broader, often geopolitical, range of scales. While there is a critical need for incisive coral reef management actions at relevant spatial and temporal scales, it remains unclear to what extent the scales of empirical study overlap with the scales at which management inferences and recommendations are made. This systematic map protocol will evaluate this potential scale mismatch with the goal of raising awareness about the significance of effectively addressing and reporting the scales at which researchers collect data and make assumptions. Methods We will use the Collaboration for Environmental Evidence (CEE) systematic mapping guidelines to identify relevant studies using a framework-based synthesis to summarise the spatial and temporal scales of coral reef fish ecology research and the scales at which management inferences or recommendations are made. Using tested predefined terms, we will search for relevant published academic and grey literature, including bibliographic databases, web-based search engines, and organisational websites. Inclusion criteria for the evidence map are empirical studies that focus on coral reef fish ecological organisation and processes, those informing management interventions and policy decisions, and management documents that cite coral reef research for management decision-making. Study results will be displayed graphically using data matrices and heat maps. This is the first attempt to systematically assess and compare the scales of socio-ecological research conducted on coral reef systems with their management.

Background: Coral reefs are rapidly changing in response to local and global stressors. Research to better understand and inform the management of these stressors is burgeoning. However, in situ studies of coral reef ecology are constrained by complex logistics and limited resources. Many reef studies are also hampered by the scale-dependent nature of ecological patterns, and inferences made on causal relationships within coral reef systems are limited by the scales of observation. This is because most socio-ecological studies are conducted at scales relevant to the phenomenon of interest. However, management often occurs across a significantly broader, often geopolitical, range of scales. While there is a critical need for incisive coral reef management actions at relevant spatial and temporal scales, it remains unclear to what extent the scales of empirical study overlap with the scales at which management inferences and recommendations are made. This systematic map protocol will evaluate this potential scale mismatch with the goal of raising awareness about the significance of effectively addressing and reporting the scales at which researchers collect data and make assumptions. Methods: We will use the Collaboration for Environmental Evidence (CEE) systematic mapping guidelines to identify relevant studies using a framework-based synthesis to summarise the spatial and temporal scales of coral reef fish ecology research and the scales at which management inferences or recommendations are made. Using tested predefined terms, we will search for relevant published academic and grey literature, including bibliographic databases, web-based search engines, and organisational websites. Inclusion criteria for the evidence map are empirical studies that focus on coral reef fish ecological organisation and processes, those informing management interventions and policy decisions, and management documents that cite coral reef research for management decision-making. Study results will be displayed graphically using data matrices and heat maps. This is the first attempt to systematically assess and compare the scales of socio-ecological research conducted on coral reef systems with their management. [ABSTRACT FROM AUTHOR]

Coastal habitats have experienced significant degradation and fragmentation in recent decades under the strain of interacting ecosystem stressors. To maintain biodiversity and ecosystem functioning, coastal managers and restoration practitioners face the urgent tasks of identifying priority areas for protection and developing innovative, scalable approaches to habitat restoration. Facilitating these efforts are models of seascape connectivity, which represent ecological linkages across heterogeneous marine environments by predicting species-specific dispersal between suitable habitat patches. However, defining the suitable habitat patches and migratory pathways required to construct ecologically realistic connectivity models remains challenging. Focusing on two reef-associated fish species of the Florida Keys, United States of America (USA), we compared two methods for constructing species- and life stage-specific spatial models of habitat suitability—penalized logistic regression and maximum entropy (MaxEnt). The goal of the model comparison was to identify the modeling algorithm that produced the most realistic and detailed products for use in subsequent connectivity assessments. Regardless of species, MaxEnt's ability to distinguish between suitable and unsuitable locations exceeded that of the penalized regressions. Furthermore, MaxEnt's habitat suitability predictions more closely aligned with the known ecology of the study species, revealing the environmental conditions and spatial patterns that best support each species across the seascape, with implications for predicting connectivity pathways and the distribution of key ecological processes. Our research demonstrates MaxEnt's promise as a scalable, species-specific, and spatially explicit tool for informing models of seascape connectivity and guiding coastal conservation efforts. [ABSTRACT FROM AUTHOR]