Remote sensing, through satellite image analysis has become an integral and invaluable tool to inform biodiversity conservation and monitoring of habitat degradation and restoration over time. Despite the disproportionately high levels of biodiversity loss in freshwater ecosystems worldwide, ichthyofauna are commonly overlooked in favor of other keystone species.Freshwater fish, as indicators of overall aquatic ecosystem health can also be indicators of larger scale problems within an ecosystem. If endemic and specialized fishes are at risk, the forest and landscape around their habitat is also undergoing change. As a case study demonstrating the utility of multi-temporal, multi-resolution satellite imagery, we examined deforestation and forest fragmentation around the Atewa Forest Reserve, south eastern Ghana. Within small creeks, Limbochromis robertsi, a unique freshwater cichlid with an extremely limited distribution range can be found. Historically, the land cover in the area has undergone substantial deforestation for agriculture and artisanal small-scale mining, primarily for gold. We found deforestation accelerated along with increased forest fragmentation in the 2014 -2017 period with the majority of the forest loss along the river and creek banks due to small-scale mining operations and increased agriculture. Field visits indicate a decrease in the total population by approximately 90% from the early 1990s to 2018. We illustrate the benefits of determining landscape metrics from local scale remote sensing studies as proxies to assess the decline of endemic species with restricted ranges, whose habitat characteristics and the subsequent pressures they face require detailed analysis at fine temporal and spatial scales not captured by global or continental scale datasets.

Hyperspectral remote sensing across multiple spatio-temporal scales allows for mapping and monitoring mangrove habitats to support urgent conservation efforts. The use of hyperspectral imagery for assessing mangroves is less common than for terrestrial forest ecosystems. In this study, two well-known measures in statistical physics, Mean Information Gain (MIG) and Marginal Entropy (ME), have been adapted to high spatial resolution (2.5 m) full range (Visible-Shortwave-Infrared) airborne hyperspectral imagery. These two spectral complexity metrics describe the spatial heterogeneity and the aspatial heterogeneity of the reflectance. In this study, we compare MIG and ME with surface reflectance for mapping mangrove extent and species composition in the Sierpe mangroves in Costa Rica. The highest accuracy for separating mangroves from forest was achieved with visible-near infrared (VNIR) reflectance (98.8% overall accuracy), following by shortwave infrared (SWIR) MIG and ME (98%). Our results also show that MIG and ME can discriminate dominant mangrove species with higher accuracy than surface reflectance alone (e.g., MIG–VNIR = 93.6% vs. VNIR Reflectance = 89.7%).

Remote sensing has become an integral and invaluable tool to inform biodiversity conservation and monitoring of habitat degradation and restoration over time. Despite the disproportionately high levels of biodiversity loss in freshwater ecosystems worldwide, ichthyofauna are commonly overlooked in favor of other keystone species. Freshwater fish, as indicators of overall aquatic ecosystem health, can also be indicators of larger scale problems within an ecosystem. As a case study with multi-temporal, multi-resolution satellite imagery, we examined deforestation and forest fragmentation around the Atewa Forest Reserve, Ghana. Within small creeks, Limbochromis robertsi, a unique freshwater cichlid with an extremely limited distribution range, can be found. Historically, the land cover in the area has undergone substantial deforestation for agriculture and artisanal small-scale mining. In the 1389-km 2 study area, we found deforestation accelerated along with increased forest fragmentation in the 2014-2017 period (167.4 km 2 of deforestation) with the majority of the forest loss along the river and creek banks due to small-scale mining operations and increased agriculture. Field visits indicated a decrease in the total L. robertsi population by approximately 90% from the early 1990s to 2018. Its distribution has been reduced to higher elevations by anthropogenic habitat barriers at low elevations and the presence of predatory species. Loss of riparian forest through land use and cover change to mining and agriculture contributes to the habitat degradation for this endemic species. Fine spatial-and temporal-scale studies are required to assess habitat characteristics are not captured by global-or continental-scale datasets. K E Y W O R D S agricultural expansion, deforestation, freshwater fish, gold mining, land use/land cover change, remote sensing, satellite imagery 1 | INTRODUC TI ON Remote sensing in the form of satellite image Earth observation plays an increasingly important role in species conservation (Rose et al., 2015). Since the early pioneering studies illustrating its utility for quantifying and mapping deforestation (e.g., Skole &

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