In this map, all the wetlands at greatest risk of degradation are selected and overlaid with the poverty level in the surrounding subcounties. It displays the location of these wetland sample points and the poverty rate for the neighboring 60 rural subcounties.

如图所示，高影响力的湿地在乌干达各地广泛传播，属于农村贫困线以下的子县人口的比例包括所有贫困水平。使用较高影响的湿地位于该国西南部的贫困水平较低（绿色阴影）的子县。但是，受影响很高的湿地也位于较差的子县，大多数位于里拉，阿米里亚，杜科洛和阿莫拉塔尔地区（棕色和黄色的阴影）的北湖以北，也位于金贾地区，农民在湿地种植米饭。

This means that based on the existing data from the National Wetlands Information System and the most recent poverty map, there is no straightforward relationship between poverty levels and potential wetland degradation. High impact from wetland use occurs in both poor and better-off subcounties.

Nevertheless, the map can be useful to flag certain subcounties where close coordination between wetlands management and poverty reduction efforts could be beneficial for both wetlands and human well-being. For example, in subcounties with high poverty rates of 40-60 percent (shaded in light brown) and a great number of highly impacted wetlands, additional or more intensive use could threaten the future supply of benefits. This in turn could negatively impact poor families who depend on wetlands for their livelihoods or fall back on these resources in emergencies.

Improved wetlands management that results in a more optimal combination of products and services (one that lowers the overall impact on the wetland system while maximizing the revenue) could reduce the risk of resource degradation and negative well-being impacts for poor households. Conversely, creating new economic opportunities outside of the wetland sector may permit some families to reduce dependence on resource extraction with low returns and high impacts, resulting in both improvements in well-being and lower resource pressure on wetlands.

在湿地受影响很大但贫困率低的子县中，替代收入的活动和生计策略的存在更有可能。这表明，任何改变和优化湿地用途或恢复湿地的策略都可以基于这些子县的家庭资产和能力的更多。

This map represents just one example that analyzes the relationship between wetland use impacts and poverty. Other useful analyses are also possible. For example, a different map overlay could pinpoint where wetlands exposed to no or low impacts coincide with high poverty levels and could lead to further investigation of the reasons behind this pattern.

资料来源：国际边界（NIMA，1997年），地区行政边界（UBOS，2006a），子县行政边界（Ubos，2002a），水体（NFA，1996; Nima，1997; Brakenridge et al。，2006），从all wetland uses (authors’ calculation based on WID, 2006), and rural poverty rate (UBOS and ILRI, 2008).