Accurate assessment of postfire vegetation recovery is important for forest management and the conservation of species diversity. Topography is an important factor affecting vegetation recovery but whether species composition varies with different recovery stages and between valleys and slopes is unclear. Using field data and a space-for-time substitution method, we quantified species richness and diversity to obtain the successional trajectories of valleys and slopes. We surveyed the species of 10 burned areas from 1986 to 2010 in the Greater Khingan Mountains in northeastern China, and found that with increasing postfire recovery time, species richness in both valleys and slopes gradually decreased. However, species richness in valleys was relatively higher. Shrubs recovered rapidly in the valleys, and species diversity maximized approximately 11 years after fire. However, it maximized 17–18 years after fire on the slopes. Numerous shade-tolerant species were present in the valleys 11 years after fire but not until after 18 years on slopes. Larch appeared earlier than 11 years after fire and its recovery was slow in the valleys but appeared quickly on slopes and established dominance early. Our study provides some new insights into vegetation succession after fire at local scales. After fire, the vegetation recovery processes differ with topography and it affects the initial rate of recovery and species composition at different successional stages.

Solar-induced chlorophyll fluorescence (SIF), when used as a proxy for plant photosynthesis, can provide an indication of the photosynthesis rate and has the potential to improve our understanding of carbon exchange mechanisms within an ecosystem. However, the relationships between SIF and vegetation indices (VIs) operating within different ecological contexts and the effect of other environmental factors on SIF remain unclear. This study focused on three ecosystems (cropland, forest, and grassland), with different ecological characteristics, located in Northeast China. These areas provide case studies where numerous relationships can be explored, including the correlations between the Orbiting Carbon Observatory-2 (OCO-2) SIF and MODIS products, meteorological factors, and the differences in the relationships between the three different ecosystems. Some interesting results and conclusions were obtained. First, in different ecosystems, the relationships between SIF and MODIS products show different correlations, whereby the enhanced vegetation index (EVI) has a close relationship with SIF in all the three ecosystems of forest, cropland, and grassland. Second, forest-type ecosystems appear to be sensitive to changes in daily temperature, whereas cropland and grassland areas respond more closely to changes in previous 16-day daily minimum temperature. Compared with forest and cropland areas, grasslands were more sensitive to precipitation (although the R2 value was small). Third, different ecosystems have different mechanisms of photosynthesis. Hence, we suggest that it is better to use SIF in areas exhibiting different ecological characteristics, and different models should be employed while simulating SIF.