Marine reserves are used to protect fish populations threatened by intensive fishing. Theoretically, the conservation benefits of protected areas can be predicted by estimating the reduction in fishing mortality attributable to the presence of protected areas and assessing how this affects resident fish populations and dynamics. The reduction in fish mortality depends mainly on the area of ​​the protected area, movement and migration of fish populations, duration of protection, and the ratio of protected areas to surroundings. The response of fish populations to reduced mortality depends on life history features that influence intrinsic population growth rates. Indeed, the models needed to assess the conservation effectiveness of marine protected areas are often as complex as those used for traditional fisheries analysis, with many fish populations threatened by fisheries. It cannot be applied in practice. In fact, one of the benefits of reserves is that it simplifies management and reduces implementation costs for fish populations for which little biological information is available. This is one of the reasons why it is often preferred as a conservation target in developing countries. Overfishing is rampant in developing countries, and intensive fishing is leading to rapid declines in many fish populations. Conservation of these areas is particularly important because many coastal inhabitants depend on fishing for employment, food and income, and the data needed to implement population-based management are often insufficient or non-existent. It Is difficult. Furthermore, it is impractical to delay protective measures until better data are collected. For example, a simple survey to estimate fish populations in coastal areas across Indonesia could take 400 person-years, even though some species are already endangered. If we are to act now, we will have to find the best conservation measures based on fairly limited data and how to do them effectively. The 'simple' fishing model described here is one in which only catch and effort data need to be fitted. In the model described, the biomass yield curve is considered equivalent to the population growth curve. The Fox model is more realistic with respect to fish populations than the Schaefer model and removes the constraint of symmetric yield curves. The Pella-Tomlinson model is the general model and the others are included as special cases. Tests using data from laboratory populations of guppies support the validity of the Fox and Pella-Tomlinson models. The Fox model he is the easier of the two models to customize (due to fewer parameters) and has proven suitable for a wide variety of commercial fisheries. Advantages of models include minimal base data requirements and relatively easy customization. Limitations include the lack of regulation governing reproductive rights and the waste of biological information outside of capture and effort. However, species communities are not the only factor that mitigates the impact of disturbances on fish populations. Diversity of biologically relevant traits in populations of fish of the same species has also been shown to improve resilience to disturbance. For example, the temporal patterns seen in migration timings of salmon species in southeastern Alaska Pacific. These diverse and resilient inland ecosystems provide a reliable source of food when disaster strikes, and become even more important when exacerbated by climate change. It responds directly to environmental stressors such as changes in climate and climate change. Fish also indirectly respond to stressors that affect their environment. For example, the mass mortality of mothers and females introduced to Lake Michigan in the 1960s caused major changes in the Laurentian Great Lakes ecosystem and attracted social and political attention. Worldwide, freshwater fish populations and species assemblages often exhibit nutrient shifts to watersheds.