Climate change will ultimately result in higher surface temperature and more variable precipitation, negatively affecting agricultural productivity. To sustain the agricultural production in the face of climate change, adaptive agricultural management or best management practices (BMPs) are needed. The currently practiced BMPs include crop rotation, early planting, conservation tillage, cover crops, effective fertilizer use, and so on. This research investigated the agricultural production of BMPs in response to climate change for a Hydrologic Unit Code12 sub-watershed of Choctawhatchee Watershed in Alabama, USA. The dominating soil type of this region was sandy loam and loamy sand soil. Agricultural Production Systems sIMulator and Cropping Systems Simulation Model were used to estimate the agricultural production. Representative Concentration Pathway (RCP) 4.5 and RCP8.5 that projected a temperature increase of 2.3℃ and 4.7℃ were used as climate scenarios. The research demonstrated that crop rotation had positive response to climate change. With peanuts in the rotation, a production increase of 105% was observed for cotton. There was no consistent impact on crop yields by early planting. With selected peanut-cotton rotations, 50% reduced nitrogen fertilizer use was observed to achieve comparable crop yields. In response to climate change, crop rotation with legume incorporation is thus suggested, which increased crop production and reduced fertilizer use.

As the human population increases, the landscape is altered to provide housing, food, and industry. Human activity poses a risk to the health of natural habitats that, in turn, affect biodiversity. Biodiversity is necessary for a functioning ecosystem, as species work synergistically to create a livable environment. It is, therefore, important to know how human practices and natural events threaten these habitats and the species living in them. A universal method of modeling habitat threats does not exist. This paper details the use of a literature review to formulate a new framework called Define–Investigate–Estimate–Map (DIEM). This framework is a process of defining threats, investigating an area to discover what threats are present, estimating the severity of those threats, and mapping the threats. Analysis of 62 studies was conducted to determine how different authors define and characterize threats in various contexts. The results of this analysis were then applied to a case study to evaluate the Choctawhatchee River and Bay Watershed. Results suggest that the most abundant threat in the watershed is agricultural development, and the most destructive threat is urban development. These two threats have the greatest impact on the total threat level of the watershed. Applying the DIEM framework demonstrates its helpfulness in regional analysis, watershed modeling, and land development planning.

Habitat suitability (HS) describes the ability of the habitat to support living organisms. There are several approaches to estimate habitat suitability. These approaches are specific to a species or habitat or estimate general HS broadly across multiple species or habitats. The objectives of the study were to compare the approaches for estimating HS and to provide guidelines for choosing an appropriate HS method for conservation. Three HS estimation methods were used. Method 1 scores the suitability based on the naturality of the habitat. Method 2 uses the average of HS values found in the literature. Method 3 uses the species richness as an indicator for HS. The methods were applied to a case study in the Choctawhatchee River Watershed. GIS applications were used to model the suitability of the watershed. The advantages and disadvantages of the HS methods were then summarized. The multiple HS maps created using the three methods display the suitability of the watershed. The highest suitability occurred in the southern parts of the region. Finally, a decision support tool was developed to help determine which approach to select based on the available data and research goals.

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