Use of historical data to improve conservation of the black grouse (Lyrurus tetrix) in Northeast China

Abstract

Biological conservation requires sufficient basic data, like knowledge of the biogeographic characteristics and spatiotemporal dynamics of endangered species. Reconstructing range dynamics through time and detecting their underlying causes can be helpful for present and future conservation actions. Black grouse (Lyrurus tetrix) populations have declined during the late 20th century in Northeast China, but the mechanisms are still unclear. We integrated species distribution models with long-term historical ecological records to reconstruct historical distributions of black grouse in Northeast China (1950s-2000s). Then, we prioritized the landscape for species protection based on the long-term historical potential distribution to improve the conservation management of this species. The area of potential distribution was 27.01% of the total study area in the 1950s, but the potential distribution in the 2000s was 16.39% of the study area. The range loss from the 1950s to the 2000s was 160,567 km 2 , representing a 39.30% reduction. Within the study area, the species' potential distribution in the Changbai Mountains has gradually disappeared since the 1980s. Based on conservation prioritization analysis, the priority conservation area is 151,276 km 2 , which is mainly distributed in the Greater and Lesser Khingan Mountains. National nature reserves only included 6.35% of the potential distribution of the black grouse in the 2000s. Several conservation actions should be implemented to rejuvenate black grouse populations in Northeast China.

Identification of Conservation Priority Areas and a Protection Network for the Siberian Musk Deer (Moschus moschiferus L.) in Northeast China

“…We modeled the potential distribution of M. moschiferus in Northeast China using ensemble forecasting approaches via the R package BIOMOD2 Version 3.3-7 [35,36]. BIOMOD2 includes ten modeling algorithms and is considered a suitable platform for the ensemble forecasting of species distributions [35,37,38]. Presence-absence models tend to perform better than presence-only models [39].…”

“…Presence-absence models tend to perform better than presence-only models [39]. In this study, we created 2000 random points for pseudo-absence data using geoprocessing tools in ArcGIS Version 10.2.2 [38,40]. To reduce model uncertainty, we first tested all ten modeling algorithms in BIOMOD2 to determine the optimal algorithm, as evaluated by the true skill statistic (TSS) and the area under the curve of the receiver operating characteristic curve [41,42].…”

Suitable Habitats of Chrysolophus spp. Need Urgent Protection from Habitat Fragmentation in China: Especially Suitable Habitats in Non-Nature Reserve Areas

“…MaxEnt is an algorithm model with a remarkable prediction capability that preserves constraints on environmental data information but has no restrictions on unknown distribution data and missing environmental variables [ 8 ]. This model has been identified as useful for determining the distribution changes of wildlife [ 9 , 10 ], and it has been used to demonstrate the dynamic habitat suitability of wild populations under the influence of environmental and human factors [ 11 , 12 ]. It should be noted that this model only requires two sources of data of the target-species occurrences (longitude and latitude) and accommodates a variety of climatic, geographic, interferential, and biological variables [ 13 , 14 ].…”

Evaluation of Spatio-Temporal Patterns of Predation Risk to Forest Grouse Nests in the Central European Mountain Regions

“…Ground-nesting bird species populations have dramatically decreased during recent decades in Europe [ 1 , 2 , 3 ] with most dramatic declines reported for larger species such as waders and bustards inhabiting agricultural landscape [ 2 , 4 , 5 , 6 ] or forest grouses ( Tetraonidae ) [ 7 , 8 , 9 , 10 , 11 , 12 ]. For example, the long-term population decline and range contraction of black grouse ( Lyrurus tetrix ) has been recorded in the majority of its distribution area, including the British Isles, continental Europe, and Fennoscandia [ 7 , 8 , 12 , 13 , 14 , 15 , 16 ].…”