Characterization of Ecological Networks on Wetland Complexes by Dispersal Models

분산 모형에 따른 습지경관의 생태 네트워크 특성 분석

Abstract

Wetlands that provide diverse ecosystem services, such as habitat provision and hydrological control of flora and fauna, constitute ecosystems through interaction between wetlands existing in a wetlandscape. Therefore, to evaluate the wetland functions such as resilience, it is necessary to analyze the ecological connectivity that is formed between wetlands which also show hydrologically dynamic behaviors. In this study, by defining wetlands as ecological nodes, we generated ecological networks through the connection of wetlands according to the dispersal model of wetland species. The characteristics of these networks were then analyzed using various network metrics. In the case of the dispersal based on a threshold distance, while a high local clustering is observed compared to the exponential dispersal kernel and heavy-tailed dispersal model, it showed a low efficiency in the movement between wetlands. On the other hand, in the case of the stochastic dispersion model, a low local clustering with high efficiency in the movement was observed. Our results confirmed that the ecological network characteristics are completely different depending on which dispersal model is chosen, and one should be careful on selecting the appropriate model for identifying network properties which highly affect the interpretation of network structure and function.

동식물의 서식지 제공 및 수문학적 조절 등 다양한 생태계 서비스를 제공하는 습지는 경관 내 습지간의 상호작용을 통해 생태계를 구성한다. 따라서 습지경관에서의 생태계의 리질리언스 등의 기능을 평가하기 위해서는 습지의 동역학적 특성과 더불어 습지간에 형성되는 생태적 연결성 분석이 필요하다. 본 연구에서는 습지를 생태학적 노드로 정의하여 습지 서식종의 분산 모형에 따라 발생하는 습지간 연결을 통해 생태 네트워크를 생성하고 네트워크 분석 방법을 통해 생태 네트워크의 특성을 비교, 분석하였다. 임계거리를 활용한 분산모델 (threshold distance)의 경우 확률적인 분산모델(exponential dispersal kernel, heavy-tailed dispersal model)과 비교하여 국지적인 군집화가 높으나 습지 간의 이동에는 비효율적인 것으로 나타났다. 반면 확률적 분산모델의 경우 국지적인 군집화는 낮게 나타나나 습지 경관 내에서의 이동은 효율적인 것으로 나타남에 따라 분산 모델에 따른 생태 네트워크 특성에 차이가 발생함을 확인하였다. 본 연구는 향후 습지경관 리질리언스 분석을 위한 생태 네트워크 구축의 기초자료로 활용될 수 있을 것으로 사료된다.

Fig. 1. Map of study area with wetlands in prairie pothole region, Deuel county (dotted line) and Big Sioux Basin of ecoregion (red solid line), South Dakota (solid line). Polygon indicates geographically isolated wetlands.

Fig. 2. Calculating distances between a pair of wetlands. Polygons are the shape of real wetlands while circles are transformed wetlands

Fig. 3. Generating ecological networks using threshold distance model (a: 1 km, b: 2 km, c: 3 km)

Fig. 4. Generating ecological networks using exponential dispersal kernel(a: 0.6 km, b: 1.2 km, c: 1.8 km mean distance)

Fig. 5. Generating ecological networks using heavy-tailed dispersal model(a: β = 2, b: β = 3, c: β = 3)

Fig. 6. Spatial distribution of node degrees in the ecological network generated by threshold distance model (a: 1km, b: 2km, c: 3km)

Fig. 7. Spatial distribution of node degrees in the ecological network generated by exponential dispersal kernel (a: 0.6km, b: 1.2km, c: 1.8km mean distance)

Fig. 8. Spatial distribution of node degrees in the ecological network generated by heavy-tailed dispersal model (a: β =2, b: β = 2.5, c: β = 3)

Table 1. Metric values of ecological networks by dispersal models

Table 2. Correlation coefficients of the degrees between ecological network models